Download TEMG_plan_draft_semifinal_2013_02_15

1
CAFF Monitoring Series Report nr. xx
2
April 2013
3
4
5
Arctic Terrestrial Biodiversity
Monitoring Plan
6
7
8
Terrestrial Expert Monitoring Group
Circumpolar Biodiversity Monitoring Program
9
10
DRAFT – FOR REVIEW
11
Updated for February 13th, 2012
12
13
Authors:
14
15
16
Christensen, T.; Payne, J.; Gill, M. J.; Svoboda, M.; Doyle, M.; Aronsson, M.; Behe, C.; Buddle, C.; Cuyler,
C.; Heidmarsson, S.; Ibarguchi, G.; Kenning Krogh, P.; Madsen, J.; McLennan, D.; Nymand, J.; Pääko, E.;
Rosa, C.; Salmela, J.; Schmidt, N. M.; Shuchman, R.; Soloviev, M.; Taylor, J.; and Wedege, M.
17
18
Editing:
19
Barry, T. and Fannar, K.
20
(CAFF International Secretariat, Akureyri, Iceland)
1
21
Table of Contents
22
ARCTIC TERRESTRIAL BIODIVERSITY MONITORING PLAN ....................................................................................... 1
23
AUTHORS: .............................................................................................................................................................. 1
24
EDITING: ................................................................................................................................................................ 1
25
EXECUTIVE SUMMARY ........................................................................................................................................... 5
26
ACKNOWLEDGEMENTS .......................................................................................................................................... 5
27
1
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
1.1
BENEFITS OF CONTRIBUTING TO A CIRCUMPOLAR, COORDINATED EFFORT....................................................................7
1.2
GOALS AND OBJECTIVES OF THE ARCTIC TERRESTRIAL BIODIVERSITY MONITORING PLAN.................................................8
1.3
SCOPE OF THE CBMP-TERRESTRIAL PLAN ..............................................................................................................9
1.4
INTEGRATED, ECOSYSTEM-BASED APPROACH TO ARCTIC BIODIVERSITY MONITORING.....................................................9
1.5
DEFINITIONS OF BIODIVERSITY, FOCAL ECOSYSTEM COMPONENTS, ATTRIBUTES AND PARAMETERS .................................10
1.6
CONSIDERATIONS FOR MONITORING ARCTIC TERRESTRIAL BIODIVERSITY ...................................................................11
1.6.0
Species and Ecosystems included in the CBMP-Terrestrial Plan ........................................................11
1.6.1
Heterogeneity of Arctic terrestrial ecosystems ..................................................................................11
1.6.2
Drivers ...............................................................................................................................................12
1.6.3 Brief Overview of Monitoring and Limitations in the CBMP-Terrestrial Plan ........................................14
1.7
COMMUNITY BASED MONITORING (CBM), TRADITIONAL KNOWLEDGE (TK), CITIZEN SCIENCE, AND HISTORICAL DATA .....16
1.8
LINKS AND RELEVANCE TO OTHER PROGRAMS AND ACTIVITIES.................................................................................18
1.8.1
Arctic Council Working Groups and Activities: ..................................................................................19
1.8.2
Other Programs ..............................................................................................................................21
2
43
44
TEMG FOCAL AREAS: GEOGRAPHIC BOUNDARIES AND DEFINITIONS .......................................................... 24
2.1
3
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
INTRODUCTION AND BACKGROUND ............................................................................................................. 6
GEOGRAPHIC BOUNDARIES AND DEFINITIONS .......................................................................................................24
MONITORING APPROACH, OBJECTIVES AND METHODS .............................................................................. 27
3.1
OVERALL MONITORING APPROACH ....................................................................................................................27
3.2
CENTRAL QUESTIONS TO BE ADDRESSED IN THE MONITORING ..................................................................................28
3.3
SCALE OF MONITORING AND REPORTING .............................................................................................................29
3.4
DATA AND MODELING .....................................................................................................................................30
3.4.1
Standardization and harmonization of protocols and data ..............................................................30
3.4.2
Modeling ...........................................................................................................................................30
3.5
KEY CONCEPTS OF THE CBMP-TERRESTRIAL PLAN.................................................................................................30
3.5.1
Monitoring supported by conceptual models ....................................................................................30
3.5.2 Linkage to system drivers .......................................................................................................................31
3.5.3 The CBMP TEMG Conceptual Model ......................................................................................................32
3.5.4 Identification of Focal Ecosystem Components, Attributes and Parameters .........................................34
3.6
ESTABLISHING REFERENCE (BASELINE) CONDITIONS ...............................................................................................35
3.7
ESTABLISHING THRESHOLDS OF CONCERN ............................................................................................................35
3.8
LINKAGES BETWEEN THE CBMP-TERRESTRIAL PLAN AND THE CBMP INDICES AND INDICATORS .....................................37
4
SAMPLING DESIGN ...................................................................................................................................... 42
2
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
4.1
SAMPLING DESIGN OVERVIEW ...........................................................................................................................42
4.1.1
Introduction to CBMP-Terrestrial Plan sampling design .......................................................................42
4.1.2
Interpreting the sampling design tables ............................................................................................43
4.1.3 Sampling Metadata ...............................................................................................................................43
4.2
VEGETATION ..................................................................................................................................................44
4.2.0
Introduction .......................................................................................................................................44
4.2.1
Vegetation sampling approach and design issues ................................................................................44
4.2.2
Sampling protocols ............................................................................................................................49
4.2.3 Site establishment data .........................................................................................................................50
4.2.4
Vegetation sample processing, archiving and DNA analysis ................................................................50
4.2.5 DNA analysis of fungi from soil samples at the vegetation plots...........................................................51
4.3
BIRDS ...........................................................................................................................................................62
4.3.1 Avian monitoring questions and design issues ......................................................................................64
4.3.2 Potential contributors to the avian monitoring scheme ........................................................................66
4.3.3 Avian conceptual model in relation to monitoring ................................................................................67
4.3.4 Terrestrial avian monitoring design principles and components ...........................................................68
4.3.5 Monitoring on non-breeding grounds ....................................................................................................70
4.3.6 Existing Capacity and future needs to deliver the CBMP-Terrestrial Plan .............................................71
4.3.7 Sampling protocols ................................................................................................................................72
4.4
MAMMALS ....................................................................................................................................................92
4.4.1 Mammal monitoring questions .............................................................................................................92
4.4.2 Potential contributors to the mammal monitoring scheme...................................................................93
4.4.3 Mammal conceptual model in relation to monitoring ...........................................................................93
4.4.4 Terrestrial mammal monitoring design principles and components .....................................................94
4.4.5 Existing monitoring capacity ..................................................................................................................96
4.4.6 Mammal sampling protocols .................................................................................................................96
4.4.7 Sampling protocols ................................................................................................................................97
4.5
ARTHROPODS AND INVERTEBRATES ..................................................................................................................105
4.5.0
Introduction and scope ....................................................................................................................105
4.5.1
Pan-Arctic sampling approach.........................................................................................................105
4.5.2
Sampling protocols and design ........................................................................................................107
4.5.3
Site establishment data ......................................................................................................................111
4.5.4
Sampling sorting, long-term storage, and DNA barcoding .................................................................111
5
94
95
96
97
98
99
100
101
102
DATA MANAGEMENT FRAMEWORK FOR THE ARCTIC TERRESTRIAL MONITORING PLAN .......................... 121
5.1
5.2
5.3
5.4
6
DATA MANAGEMENT OBJECTIVES FOR THE CBMP ..............................................................................................121
PURPOSE OF DATA MANAGEMENT ...................................................................................................................122
COORDINATED DATA MANAGEMENT AND ACCESS: THE CBMP WEB-BASED DATA PORTAL ........................................122
DATA STORAGE, POLICY AND STANDARDS ..........................................................................................................124
DATA, SAMPLES AND INFORMATION ANALYSIS ........................................................................................ 127
6.1
BASIS FOR ANALYSIS ......................................................................................................................................127
6.1.1 Start-up phase......................................................................................................................................127
6.1.2 Implementation phase .............................................................................................................................128
6.2
DATA SAMPLES .............................................................................................................................................129
3
103
104
105
106
107
6.2.1 Sample processing ...............................................................................................................................129
6.2.2 Sample archiving ..................................................................................................................................129
6.2.3 Tools, samples, and baselines to complement monitoring and future surveillance efforts .................129
6.3
DATA ANALYSIS STRATEGY ...............................................................................................................................132
7
108
109
110
111
112
113
114
115
116
117
REPORTING ............................................................................................................................................... 133
7.1
AUDIENCES ..................................................................................................................................................133
7.2
TYPES AND TIMING OF REPORTING ...................................................................................................................133
7.3
REPORTING RESULTS......................................................................................................................................134
7.3.1
State of Arctic Terrestrial Biodiversity Report .................................................................................134
7.3.2
Status of indicators .............................................................................................................................134
7.3.3
Program review ...................................................................................................................................134
7.3.4
Scientific publications ......................................................................................................................135
7.3.5
Performance reports and work plans ..............................................................................................135
7.3.6
Summaries and other communications material ................................................................................135
8
118
119
120
ADMINISTRATION AND IMPLEMENTATION OF THE MONITORING PROGRAM .......................................... 138
8.1
8.2
8.3
GOVERNING STRUCTURE ................................................................................................................................138
PROGRAM REVIEW ........................................................................................................................................140
IMPLEMENTATION SCHEDULE AND BUDGET ........................................................................................................141
121
9
LITERATURE CITED ..................................................................................................................................... 147
122
10
GLOSSARY ................................................................................................................................................. 163
123
11
APPENDICES .............................................................................................................................................. 172
124
125
126
127
128
129
130
131
132
133
134
135
A
APPENDIX: METADATA AND SAMPLING COVERAGE MAPS BY FOCAL ECOSYSTEM ELEMENTS - ONGOING .........................172
i. Introduction and Description..........................................................................................................................172
ii. MAPS .............................................................................................................................................................172
B
APPENDIX: WHAT CAN WE MONITOR WITH SATELLITE DATA IN THE ARCTIC? ...............................................................172
i. Remote Sensing ..............................................................................................................................................172
ii. Satellite Imaging of Pan-Arctic Research Stations ........................................................................................177
C
APPENDIX: WORKSHOP PARTICIPANTS...................................................................................................................179
i. Workshop 1 (October 11-13, 2011, Hvalsø, Denmark) - Designing an Arctic Terrestrial Biodiversity
Monitoring Plan ................................................................................................................................................179
ii. Workshop 2 (May 15-17, 2012, Anchorage, Alaska, USA) - Designing an Integrated Arctic Terrestrial
Biodiversity Monitoring Plan .............................................................................................................................180
136
4
137
Executive Summary
138
To be finalised.
139
140
141
Acknowledgements
142
143
144
To be completed. The Terrestrial Expert Monitoring Group gratefully acknowledges the invaluable
contributions of international collaborators, managers, experts, institutions, governments, and
Aboriginal community members during the planning and development of the CBMP-Terrestrial Plan.
145
In particular we wish to thank:
146
147
METADATA – Anna Maria Fosaa (Botanical Department at Natural History Museum Faroe Islands); Hallur
Gunnarsson (CAFF - Data management)
148
CAFF OFFICE – Courtney Price
149
Workshop I and II organisers and participants (see Appendix C)
150
151
152
153
SWEDEN - Anders Dahlberg, Swedish Species Information Centre (valuable input on fungi and fungi
monitoring); Wenche Eide, Swedish Species Information Centre (ongoing monitoring and monitoring
design); Hand Gardfjell, Department of Forest Resources Management, SLU (vegetation monitoring
design, ongoing monitoring); Lars Petterson, Lunds University (invertebrate monitoring)
154
155
156
157
158
NOTE FOR REVIEWERS: The TEMG Team wishes to thank you for your time and contributions to improve
the working draft of the Terrestrial Plan. We would be pleased to acknowledge your contributions.
Please write your NAME here if you wish to be named; otherwise we will only thank you as ‘Anonymous
Reviewer’.
159
REVIEWERS:
160
161
5
162
163
1
164
165
166
167
168
169
170
Healthy Arctic ecosystems are of fundamental economic, cultural, and spiritual importance to Northern
residents. Furthermore, the size and nature of Arctic ecosystems make them critically important to the
biological, chemical, and physical balance of the globe. Dramatic changes in regional climates, and
increasing industrial development and other activities, now underway, are threatening Arctic
biodiversity, the resilience of species, the potential for human use, and the overall integrity of northern
ecosystems (CAFF-ABBA 2013 ). Moreover, continued rapid change in the Arctic will have repercussions
for the ecosystems and biodiversity of the entire planet.
171
172
173
174
175
176
177
178
Currently, monitoring of Arctic biodiversity lacks the coordination needed to provide an integrated, panArctic picture of status and trends related to key species, habitats, and ecological processes and
services. Enhanced coordination would improve our ability to detect important trends, link these trends
to their underlying causes, assess the effects of increasing anthropogenic activities, and provide critical
information to decision makers. Information on how the Arctic is responding to pressures such as
climatic change and human activity is urgently needed to allow decision makers, whether in local Arctic
communities, regional or national governments, or international venues, to make timely and effective
decisions regarding resource management, conservation actions, and adaptive management.
179
180
181
182
183
184
185
186
187
188
189
In response to these critical needs, the Conservation of Arctic Flora and Fauna (CAFF)1 Working Group of
the Arctic Council created the Circumpolar Biodiversity Monitoring Program (CBMP). CAFF’s CBMP is
working with scientists, Traditional Knowledge (TK) holders, and local resource users from around the
Arctic to harmonize and enhance long-term Arctic biodiversity monitoring efforts (Fig. 1.1). The
Terrestrial Expert Monitoring Group (TEMG) is one of four Expert Monitoring Groups (EMGs) created
by the CBMP to develop integrated, ecosystem-based monitoring plans for the Arctic’s major biomes.
Each of the groups (Marine, Coastal, Freshwater, and Terrestrial)2 functions as a forum for scientists,
community experts, and managers to promote, share, and coordinate research and monitoring
activities, and to use existing data and knowledge to facilitate improved, cost-effective monitoring that
can detect and provide insight into emerging trends in Arctic biodiversity. These efforts will be
coordinated through the implementation of integrated, pan-Arctic biodiversity monitoring plans.
190
191
192
193
The development of the Arctic Terrestrial Biodiversity Monitoring Plan (CBMP-Terrestrial Plan) comes at
a critical time. The Secretariat of the Convention on Biological Diversity, having recognized that its 2010
goal to reduce the rate of loss of global biodiversity has failed, has established new 2020 targets (Aichi
Biodiversity Targets) to reduce the rate of loss of biodiversity by focusing efforts on the underlying
1
Introduction and Background
Acronyms and key terms used throughout the Terrestrial Plan are defined in Chapter 10 (Glossary).
2
Visit http://www.caff.is/about-the-cbmp for more information on the Circumpolar Biodiversity Monitoring Plan,
the Monitoring Expert Groups and the completed CBMP Monitoring Plans for each biome.
6
194
195
196
197
198
199
200
201
causes driving these losses. In most cases, the rate of loss has not been adequately measured yet. The
recent report, Global Biodiversity Outlook 3 (SCBD 2010), noted the need for increased mobilization of
resources for the research and monitoring of biodiversity. At the same time, while efforts to reach an
international agreement on global climate change continue, there is broad acknowledgement that the
polar regions are experiencing and are expected to experience rapid and dramatic impacts (see review
by Anisimov and Fitzharris 2001). The Intergovernmental Panel on Climate Change (IPCC) has concluded
that climate change related to increased greenhouse gas concentrations will result in major physical,
ecological, social, and economic impacts (Pachauri and Reisinger 2007).
202
203
204
205
206
207
208
209
210
A number of Arctic Council assessments and reports have called for improved biodiversity information
to support effective management of the Arctic environment. The Arctic Climate Impact Assessment
(ACIA 2005, 2004) recommended that long-term Arctic biodiversity monitoring be expanded and
enhanced in the face of a rapidly changing Arctic. A key finding of Arctic Biodiversity Trends 2010:
Selected Indicators of Change (CAFF-ABT 2010) was that “long-term observations based on the best
available traditional and scientific knowledge are required to identify changes in biodiversity, assess the
implications of observed changes, and develop adaptation strategies.” Similarly, the Oil and Gas
Assessment (Skjoldal, et al. 2010) called for “…improved mapping of vulnerable species, populations and
habitats in the Arctic…”.
211
212
213
214
215
216
217
218
219
220
All of these recommendations highlight the increasingly urgent need for improved Arctic biodiversity
monitoring to support effective management of the Arctic environment. In addition, Arctic states have
commitments through various regulatory regimes and associated legislation to protect their Arctic
ecosystems and the biodiversity they support. Sub-national governments, including Aboriginal
governments in some countries, also have mandates to ensure the maintenance of healthy Arctic
ecosystems and wildlife. This CBMP-Terrestrial Plan for monitoring, a key component of the
Conservation of Arctic Flora and Fauna (CAFF) Working Group’s Circumpolar Biodiversity Monitoring
Program, will result in improved information on the status and trends of the Arctic’s terrestrial living
resources, thereby directly supporting national and sub-national needs as well as international reporting
mandates.
221
222
223
1.1
Benefits of Contributing to a Circumpolar, Coordinated Effort
224
225
226
227
228
229
230
The CBMP-Terrestrial Plan will facilitate more powerful and cost-effective assessments of Arctic
terrestrial ecosystems through the generation of and access to improved, pan-Arctic data sets. This will,
in turn, contribute directly to more informed, timely, and effective conservation and management of the
Arctic terrestrial environment. While most Arctic biodiversity monitoring networks are—and will
remain—national or sub-national in scope, there is considerable value in establishing circumpolar
connections among monitoring networks. The development of the CBMP-Terrestrial Plan is designed to
facilitate these connections and encourage harmonization amongst national and sub-national research
7
231
232
233
234
235
and monitoring networks, including scientific and community-based knowledge networks, increasing
their power to detect and attribute change. In addition, the increased power will come at a reduced
cost, compared to the cost of multiple uncoordinated approaches. Metadata generated from the
integrated monitoring approaches will provide insight on the status of Arctic biodiversity from a
scientific perspective, and including awareness on the changing state of Arctic communities also.
236
237
238
1.2
Goals and Objectives of the Arctic Terrestrial Biodiversity Monitoring Plan
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
The overall goal of the CBMP Arctic Terrestrial Biodiversity Monitoring Plan (CBMP-Terrestrial Plan) is to
improve the collective ability of Arctic Traditional Knowledge holders, northern communities, and
scientists to detect, understand and report on long-term change in Arctic terrestrial ecosystems and
biodiversity. Through coordination and harmonization of Arctic terrestrial biodiversity monitoring we
aim to generate better quality long-term data to inform decision-making, to help plan and monitor
industrial activities, to contribute toward understanding of ecosystem changes and underlying
processes, underpin authoritative assessments of status and trends, and enhance the overall efficiency
and effectiveness of Arctic terrestrial biodiversity monitoring. To meet these goals, the CBMP-Terrestrial
Plan has a number of key objectives:
269
270
More specifically, the CBMP-Terrestrial Plan has been designed to answer a number of ‘key monitoring
questions’ that were identified for each biotic group (refer to Chapter 4 for a list of these questions).









Identify key agency, industrial, community, and traditional knowledge management needs for
terrestrial biodiversity information and key ecological relationships.
Identify a common suite of biological focal ecosystem components (FECs, see below), attributes,
parameters and harmonizable methods to coordinate the monitoring of change across Arctic
terrestrial ecosystems.
Identify key abiotic drivers, relevant to terrestrial biodiversity, which should be monitored and
integrated with biological parameters.
Identify existing monitoring capacity and data that can be aggregated to establish baselines and
form the backbone of a monitoring scheme.
Identify new partners in government, industry, communities, and academia that could
contribute to an evolving terrestrial monitoring effort.
Identify a sampling strategy to meet identified monitoring objectives, making efficient use of
existing monitoring capacity and planning for the future.
Identify priority gaps (taxa, spatial, and/or temporal) in coverage and opportunities to address
gaps where feasible
Identify key monitoring methodologies and ways to incorporate traditional knowledge expertise
and to build and extend collaborative initiatives and partnerships to identify priorities, needs,
and knowledge gaps
Facilitate communication and coordination among Arctic terrestrial biodiversity researchers and
monitoring groups.
271
8
272
273
1.3
Scope of the CBMP-Terrestrial Plan
274
275
276
277
278
279
280
281
The boundaries of the CBMP-Terrestrial Plan are consistent with the geographic boundaries, species and
ecosystem coverage as defined by the CAFF Arctic Biodiversity Assessment (CAFF-ABBA 2013 ). The
geographic scope is the High and Low Arctic (see Fig. 2.1, CAVM Map), and alpine Subarctic regions in
proximity of the Arctic proper, consistent with the Circumpolar Arctic Vegetation Map’s subzones A-E
(CAVM Team 2003); further detail and definitions are explained in Chapter 2 by Christensen and
colleagues (2011). The CBMP-Terrestrial Plan is aimed at responding to questions and information needs
at the circumpolar scale, but includes a scaled approach applicable at smaller spatial scales and thus, is
designed to provide relevant information to serve decision-making at multiple scales.
282
283
284
285
286
287
The CBMP-Terrestrial Plan includes all ecosystems and species within them from the marine high-water
mark and inland. The intertidal zone is considered part of the CBMP-Marine Plan (Gill, et al. 2011). Fens
and marshes are considered terrestrial while tarns, ponds, lakes and rivers are considered freshwater
and are included in the CBMP-Freshwater Plan (Culp, et al. 2012). All species that reproduce in the
Arctic proper and/or have genuine populations in the Arctic proper are included in the CBMP-Terrestrial
Plan scope.
288
289
290
291
292
293
294
295
296
297
298
The CBMP-Terrestrial Plan aims at identifying focal ecosystem components (FECs), indicators that are
considered critical to the functioning and resiliency of Arctic ecosystems, that are representative of
biodiversity, and also of ecosystem function and integrity. While the plan focuses on biological elements
and develops sampling designs for biological components only, the plan also identifies critical abiotic
parameters which affect and drive biological change which should be monitored as part of an integrated
ecosystem approach. Where those abiotic parameters are appropriately layered with biological
monitoring sites and stations they will be included in the CBMP-Terrestrial Plan, otherwise, developing a
sampling strategy for these abiotic factors is outside the scope of the current plan. In those instances,
the TEMG will rely on and communicate with other relevant organizations and programs that are
responsible for abiotic Arctic monitoring (see below: Links and Relevance to Other Programs and
Activities).
299
300
301
1.4
Integrated, Ecosystem-based Approach to Arctic Biodiversity Monitoring
302
303
304
305
306
307
The CBMP is adopting an integrated ecosystem-based approach to monitoring in its program design,
organization, and operation (Fig. 1.1). The ecosystem-based approach integrates information on land,
water, and living resources, and lends itself to monitoring many aspects of an ecosystem within a
geographic region. This approach considers the integrity of entire ecosystems and their interaction with
other ecosystems. Although the complexity and data/analysis requirements far exceed those of the
species approach, the rewards of the ecosystem-based approach are significant. It identifies important
9
308
309
310
311
312
313
relationships, bridging ecosystems, habitats, and species and the impacts of stressors and drivers on
ecological function. The resulting information contributes directly to adaptive management, enabling
effective conservation, mitigation, and adaptive actions appropriate to the Arctic. Lastly, by connecting
biodiversity to its supporting abiotic drivers, it will be possible also to model future changes in biota as a
result of anticipated changes in key drivers, thus providing decision makers with critical information to
support proactive management approaches for the Arctic.
314
315
316
317
1.5 Definitions of Biodiversity, Focal Ecosystem Components, Attributes and
Parameters
318
319
320
321
322
323
The Convention on Biological Diversity defines biological diversity, often shortened to biodiversity, as
“the variability among living organisms from all sources including, inter alia, terrestrial, marine and
other aquatic ecosystems and the ecological complexes of which they are a part; this includes diversity
within species, between species and of ecosystems”(SCBD 1992). Biodiversity, therefore, must be
viewed at the level of the gene, the species, and the ecosystem, ranging in scope from local to regional
and, even, global systems.
324
325
326
327
328
329
330
331
In the context of Arctic biodiversity, CAFF’s CBMP recognizes the integral nature of global and human
processes in the Arctic ecosystem. Arctic biodiversity depends, to a large extent, on conditions outside
the Arctic, due to a high proportion of migratory species and the interconnections of Earth’s systems
(e.g., global ocean circulation, contaminant pathways). In addition, humans and their cultural diversity
are components of Arctic ecosystems, as well as beneficiaries of essential goods provided by Arctic
biodiversity. Monitoring all elements of ecosystems—including species, habitats, ecosystem structure,
processes, functions, and drivers to the ecosystems—is necessary to gain meaningful insight into the
state of biodiversity in the Arctic, and to predict what may happen in the future.
332
333
334
335
336
337
338
339
340
341
342
343
344
The monitoring programme outlined here is based on a three-level hierarchical approach: Focal
ecosystem components (FECs, and also known as indicators), attributes, and parameters, as exemplified
in Table 1.1 below. Focal ecosystem components are critical to the functioning and resiliency of Arctic
ecosystems and/or reflect the vital importance to the subsistence and economies of northern
communities. The TEMG identified FECs on the basis of (a) consensus expert opinion which was
described in conceptual ecological models that were used to clarify and communicate the ecological
theory and critical system components and interactions supporting their selection, and (b) information
needs of communities and managers/decision-makers. Key element selection followed the guidelines
developed by CBMP (five-year implementation plan, strategy for developing indices and indicators, etc.)
and which, as much as possible, can be scaled.
Each FEC then has a number of attributes, which describe various aspects or characteristics of the
component. Lastly, each attribute has a number of potential parameters that are the actual metrics
10
345
346
347
348
349
350
351
352
353
354
355
measured in the field. Working in concert, the hierarchical components (FECs, attributes, and
parameters) build on one-another; that is, individual parameters inform the status of the attributes, and
in turn, the attributes collectively inform the status of the FECs (e.g. Table 1.1).
356
Table 1.1. Structure of the monitoring program, here exemplified with caribou.
To facilitate effective and consistent reporting, the CBMP has chosen a suite of FECs and related
attributes that provide a comprehensive picture of the state of Arctic biodiversity—from species, to
habitats, to ecosystem processes, to ecological services. The FECs have been chosen to represent key
ecological species or functions, and have been identified via conceptual ecological modelling that
reflects existing monitoring capacity and expertise, and through an expert-opinion consultation process.
A full description of the FEC, attribute and parameter selection process is provided in Chapter 3.
FEC
ATTRIBUTE
Caribou
Abundance
Demographics
Health
PARAMETER
FREQ.
Number
Calf percentage
Age composition
…
Prevalence
…
Annually
Annually
LIKELY
DRIVER
Forage; snow
Forage; snow
PROGRAM
CARMA
357
358
359
360
1.6
Considerations for Monitoring Arctic Terrestrial Biodiversity
361
362
1.6.0
Species and Ecosystems included in the CBMP-Terrestrial Plan
363
364
365
366
367
Since there is no strict definition of the Arctic or Arctic species, we considered all ecosystems of the
Arctic-proper (defined below, and see Chapter 2) and species that reproduce in the Arctic-proper and/or
have genuine populations in the Arctic-proper, except for species with accidental or clearly insignificant
appearance within the Arctic. Subarctic species and ecosystems are dealt with as described below.
368
369
1.6.1
370
371
372
373
Although Arctic biodiversity is low compared to other regions of the world, the Arctic hosts a varied
array of ecosystems and highly specialized and endemic species. Given this, and the large geographic
extent of the circumpolar Arctic, the climatic, geological, and geophysical variability involved, it is not
realistic to fully represent all Arctic terrestrial ecosystems and ecosystem components in a biodiversity
Heterogeneity of Arctic terrestrial ecosystems
11
374
375
376
377
378
379
380
381
382
383
384
monitoring program. A major task for the design phase of a monitoring program is to define the priority
ecosystems and ecosystem components to be included, from plot to landscape scales, within each of the
regions in the Arctic, and the feasibility of monitoring these components. Trade-offs exist between a
scientifically ideal design, political and cultural interests, and available resources. However, with remote
sensing techniques becoming more readily available, we can now look beyond the site level and use
remotely-sensed information to better integrate and harmonize monitoring data across multiple scales
of inquiry. In addition, complementing scientifically-designed monitoring with community-based
monitoring and Traditional Knowledge (see below), which often include from local to regional scales, can
greatly enhance the coverage of monitoring including direct observations, measuring, and datagathering at finer temporal and spatial scales.
385
386
1.6.2
387
388
389
390
391
392
393
394
395
396
397
398
399
400
The Arctic is currently undergoing rapid changes: cultural, political and socioeconomic transitions
resulting in exploitation of natural and non-renewable resources, as well as physical development,
changes in climate, and changes in pollution—both local and trans-boundary. These changes can
interact and accelerate in the future, and in various ways, place increased pressure on biodiversity
within the Arctic.
401
402
403
404
405
406
407
408
409
410
411
412
Effects may be successional changes, such as the northward movement of the treeline which will affect
not only Arctic biodiversity through shifting habitats and species, but also reduce albedo (surface
reflectivity), further enhancing warming of the atmosphere. Similarly, the composition and distribution
of plant communities is likely to change throughout the Arctic. To date, an increase in productivity over
much of the Arctic has been reported (CAFF-ABT 2010; Gensuo, et al. 2009), as well as an increase in the
length of the growing season. While the number of plant species inhabiting the current Arctic may
actually increase over the long-term, plants unique to the Arctic could decrease in abundance and
diversity (e.g., high Arctic mosses and lichens are expected to suffer). Retreat of permafrost and
changing soil moisture conditions will also affect plant communities. For example, mires, an important
habitat, and alpine habitats, are at risk of drying out, leading to possible losses of associated arthropod
and bird fauna. For estuarine and other lowland flora and fauna, sea level rise may cause substantial
habitat loss. In addition, changing conditions may result in altered habitat structure (vegetation height,
Drivers
Generally, there is a strong correlation between biodiversity and temperature, directly in the form of
freezing tolerance or productivity, but also indirectly through effects of thawing of permafrost, earlier
snowmelt, drought, fires, and changes in trophic interactions, invasive species pest outbreaks and
disease transmission. Therefore, it is expected that future warming will have a large and widespread
impact on biodiversity throughout the Arctic. For some species currently limited by the short Arctic
summer, longer growing seasons may be an advantage in terms of reproduction and growth; however,
for specialized Arctic flora and fauna, the combined drivers may result in mainly negative effects (Bale,
et al. 2002; Descamps, et al. 2009; Ma, et al. 2011; Post, et al. 2009; Rouse, et al. 1997).
12
413
414
density, and openness), with important implications for animal communities including nesting birds
(Ballantyne and Nol 2011; Walpole, et al. 2008).
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
Effects may also be abrupt which are more difficult to predict. Increased risk of extreme events, such as
icing and severe wind and storms, and their cascading effects will contribute to more unstable and
unpredictable conditions (Mallory, et al. 2009; Pisaric, et al. 2011; Vermaire, et al. 2013). An example is
the fading-out of rodent cycles due to unstable winter conditions which has a cascading effect on the
guild of mammalian and avian predators depending on these prey (Reid, et al. 2012; Schmidt, et al.
2012). Decreasing winter ice may be limiting the dispersal ability of large carnivores (e.g. polar bears)
and other mammals (Durner, et al. 2011; Stirling and Derocher 2012). Indirectly, inability to disperse
may be forcing the exploitation of novel prey and niche shifts by large carnivores and herbivores, which
may have unpredictable long-term impacts on the predators themselves, prey species, vegetation, or
foodwebs which may already be under stress (Descamps, et al. 2011; Mallory, et al. 2009; Smith, et al.
2010). Other unpredictable and quick changes may include large-scale outbreaks in Arctic populations
not previously exposed at the same levels to pathogens and parasites from southern climates, or at the
same levels (Descamps, et al. 2011; Descamps, et al. 2009; Gaston, et al. 2002; Verocai, et al. 2012).
Migratory Arctic species constitute a special case since they will not only be affected by changing
conditions on their Arctic breeding grounds but also by global change effects operating on their staging
and wintering grounds outside the Arctic. Arctic-breeding shorebirds are at particular risk from
pressures on their intertidal habitats in their staging and wintering areas (Baker, et al. 2004).
432
433
434
435
436
437
438
439
Human use of living resources in terms of harvesting, reindeer husbandry, and small-scale farming,
harvesting of roots and greens, and collection of mushrooms and berries, affect certain species and
ecosystems. Patterns and intensity of use will change with on-going cultural and technological
transitions and warmer climate. Many Arctic communities are already changing their harvest strategies
in respose to multiple drivers. For example, as Caribou migrations change due to warmer temperatures,
interest in Caribou-hunting from outside users increases, and changes in vegetation and water levels
occur, Arctic hunters now may travel further and longer to harvest Caribou (Kendrick, et al. 2005;
Nancarrow and Chan 2010).
440
441
442
443
444
445
446
447
448
449
450
451
With increasing global demands for resources, the Arctic is becoming a focal area for hydrocarbon and
mineral development. Increasing industrial development to extract hydrocarbon, mineral and
hydropower resources in the Arctic affect biodiversity directly due to physical development of
infrastructures, transportation and traffic, disturbance, on-site and downstream pollution and/or,
indirectly, via behavioural disturbances (via human activity in wildlife-use areas) , alteration of ground
surfaces including vegetation and permafrost, or by opening up access to adjacent, previously remote
areas (Prowse, et al. 2009). For example, reindeer herding in Siberia is impacted by increased resource
development (Forbes, et al. 2009), and in northern regions, hydrocarbon development, resource
extraction, and human disturbance have been shown to affect Rangifer populations (Anttonen, et al.
2011; Boulanger, et al. 2012; Vistnes and Nellemann 2008). Large-scale mining proposals in Arctic
Canada for metals including zinc, copper, gold, uranium, diamonds and other resources, are already
undergoing evaluation, and some would require both on-land infrastructure and extensive road
13
452
453
454
expansion, as well as include infrastructure for shipping (ports and fuelling), waste disposal, and for
supporting communities employed by these larger industries in ecologically sensitive areas, or near
calving ground for example (e.g. http://nunalogistics.com/services/bathurst.html).
455
456
457
458
459
460
461
462
463
464
465
466
Increasing industrialisation within and outside the Arctic releases contaminants which are being
revealed in Arctic foodwebs and ecosystems (See http://www.amap.no/ for more information). While
some volatile compounds are released in warmer regions around the globe where they evaporate, these
contaminants travel via atmospheric transport into cold regions including the Arctic where they
condense and are deposited into the environment, and may enter foodwebs through bioaccumulation
(e.g. organochlorines in fish and seabirds; Blais, et al. 1998; Choy, et al. 2010; Krummel, et al. 2003). In
addition, metal contaminants may be transported into terrestrial Arctic ecosystems via migratory
species themselves (Blais, et al. 2007; Foster, et al. 2011), and include recent inputs from increasing
industrialisation (e.g. mercury, cadmium, and other metals). Contaminants have been detected in
species from polar bears to soil arthropods (Dietz, et al. 2009; Fisk, et al. 2005; Hargreaves, et al. 2011),
and while the long-term effects of exposure are unknown in some taxa, negative effects such as eggshell
thinning in endangered ivory gulls have been linked to contaminants (Miljeteig, et al. 2012).
467
468
469
470
471
472
In addition to the industrialization of the Arctic and climate change, tourism is increasing throughout the
Arctic. On–shore activities from cruise ship tourists, self-funded explorers and individual-based hiking,
are placing increased disturbance pressure on terrestrial flora and fauna in some places. Lessons from
Antarctica demonstrate that, concurrent with warming temperatures and increasing traffic and tourism,
the risk of colonisation and establishment of non-native species can increase (Barnes, et al. 2006; Chown
and Convey 2007; Chown, et al. 2008).
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
1.6.3
Brief Overview of Monitoring and Limitations in the CBMP-Terrestrial Plan
Standardising protocols and sampling, knowledge-sharing through existing networks, and the
integration of existing monitoring capacity where possible will greatly extend the reach and coverage of
ecosystem components and ecological integrity that can be considered. Focal ecosystem components
(that can be used as indicators), their characteristics of interest (attributes), and some ecosystem drivers
that have been carefully selected by the TEMG as part of the CBMP-Terrestrial Plan are described in
more detail in Chapter 3 (Monitoring Approach, Objectives and Methods), Chapter 4 (Sampling Design),
and Chapter 6 (Data, Samples and Information Analyses). Briefly, indicators include biotic groups
(vegetation including fungi, birds, mammals, and terrestrial invertebrates), some of their key attributes
(e.g. abundance, diversity, spatial and temporal patterns, demographics, phenology, and health), and
some drivers (e.g. abiotic such as climate, biotic such as nutrients, and anthropogenic such as land use).
Suggested methods and analyses for monitoring range from direct sampling and observation from a
local level following standard ecological protocols (e.g. direct measurement, capture-mark-recapture
methods, analytics, etc.), scientific experimental design, and community-based monitoring, to pan-Arctic
scales using remote sensing, data modelling, and conducting metadata analyses.
14
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
Currently, the CBMP-Terrestrial Plan does not include comprehensive coverage of some important
functional groups or ecosystem indicators due to limited monitoring capacity, costs, logistics, or
feasibility. For example, the TEMG acknowledges the crucial role of microorganisms in ecosystem
processes including nutrient cycling (e.g. bacteria), functioning as primary producers in some harsh
terrestrial environments (e.g. snow algae), and influencing the population dynamics of other species (as
symbionts or pathogens). However, due to current limitations, microorganisms are only included for
monitoring indirectly at this time (e.g. measurements of decomposition rates and nutrient cycling), or
under particular key components (e.g. monitoring health and outbreaks in some cases). Through some
limited sampling that can serve as a baseline (e.g. soil samples as part of the current CBMP-Terrestrial
Plan; see Chapter 4), microorganisms can be included in future surveys using DNA-based identification
and quantification methods. However, when opportunities exist to include microorganisms through
collaboration or future surveys and expansion of monitoring capacity, it is strongly recommended that
this functional group is included. Climate change is already influencing microbe-driven ecological
processes, resulting in important positive and negative implications for food webs, disease transmission,
nutrient cycling, and even Arctic greenhouse gas emissions (Descamps, et al. 2011; Vincent 2010).
Complementing field-based surveys, behavioural observations, and population monitoring (see Chapters
3, 4, and 6), genetic analyses can provide insight into population connectivity, reproductive success,
systematics, population health, evolutionary history of lineages, and colonisation routes. Recent
improvements in wildlife forensic protocols, ancient DNA methodology, sample processing and
genotyping (e.g. third-generation sequencing), and bioinformatics (e.g. including DNA barcoding) are
greatly expanding our ability to collect data using less intrusive methods for wildlife, and to obtain
opportunistic samples for detecting the presence of taxa (and even the sex and genetic identity of
individuals; see Chapter 6, Section 6.2.3). In addition, incorporating analyses of stable isotope and trace
element signatures in conjunction or in addition to genetic analyses or other studies can provide insight
into migratory patterns and diet preferences of species (e.g Chabot, et al. 2012; Kristensen, et al. 2011;
Rolshausen, et al. 2009), and even how these may be affected by climate change (Hirons, et al. 2001). At
the present time, the CBMP-Terrestrial Plan does include some use of these tools (see Chapters 4 and 6);
however, limitations exist with respect to long-term sample storage and archiving, laboratory
infrastructure, specialised equipment, and costs. Currently, contaminants could be monitored where
capacity and infrastructure exist, but at this time stable isotope and trace element analyses are limited
under the CBMP-Terrestrial Plan (see Chapter 4 and 6). Much contaminant monitoring is already
coordinated under the auspices of the Arctic Council Arctic Monitoring & Assessment Program working
group (AMAP: http://www.amap.no/). Advances in satellite tracking technology (data loggers), stable
isotope signature and trace element analyses, and genetics show excellent potential to facilitate and
complement future monitoring activities, and inclusion of such tools in current initiatives through
collaborations is recommended where sampling and sample storage can be accommodated as a
minimum.
15
530
531
532
1.7 Community Based Monitoring (CBM), Traditional Knowledge (TK), Citizen
Science, and Historical Data
533
534
535
536
537
The Peoples inhabiting the various regions of the Arctic spend vast amounts of time on the land and at
sea. Drawing on personal experience, information shared with others, knowledge handed down through
generations, and their traditional knowledge (TK), residents of the Arctic are able to recognize subtle
environmental changes and offer insights into their causes. They are community-based monitors by
virtue of their day-to-day activities.
538
539
540
541
In addition to gaining a holistic understanding through information based on both traditional knowledge
and science (see the following sections), Arctic residents have the ability to employ standard scientific
monitoring procedures in the practice of citizen science, thereby extending the reach and effectiveness
of programs which tend to rely solely on a limited number of trained scientists to carry out monitoring.
542
543
544
545
546
While endeavoring to understanding changes occurring within the Arctic, many challenges arise
stemming from the remoteness of areas, cost of conducting scientific monitoring, incomplete data,
complex systems, uncertainties about the effects of management actions and identifying what
monitoring objectives should be according to both community based and scientific groups. Some of
these concerns may be addressed through community based monitoring (CBM).
547
548
549
550
551
552
CBM refers to a range of observation and measurement activities involving participation by community
members and designed to learn about ecological and social factors affecting a community. While CBM
has gained attention in the last decade as its value is increasingly recognized (Berkes, et al. 2007; Conrad
and Hilchey 2011), it is not a new concept. Throughout history, amateur scientists, or naturalists, and
Aboriginal groups have taken in observations of change within their environment and addressed
concerns as they arise (see below).
553
554
555
556
557
558
559
Many types of CBM approaches exist (e.g. Danielsen, et al. 2009), with distinct plan goals, such as those
that aim to gain baseline data, or those designed to monitor for ongoing changes. To better grasp
changes occurring within the Arctic there is a need for obtaining information at many different spatial
and temporal scales. Various types of monitoring techniques and tools may be employed to address
these needs. Technology including satellite imagery may be used to determine species abundance and
distribution patterns, or on the ground climatologically tools may be used to determine snow depth and
coverage to better understand changes occurring in weather patterns.
560
561
562
563
564
Due to the high cost of research conducted within the Arctic and the remote locations, CBM plans are
ideal for monitoring schemes which employ standardized scientific monitoring techniques. Citizen
science may be utilized to man such monitoring techniques. Yet, another important source of
understanding this unique environment comes from traditional knowledge of Arctic Aboriginal Peoples.
Effective CBM plans employ both citizen science and traditional knowledge.
565
566
567
Citizen science is the collection of observations on the natural world often conducted by nonprofessional community members following recommended protocols. This technique has been used for
some time (Heiman 1997; Noss 2002), including in climatology, where members of the general public
16
568
569
570
571
572
573
574
575
576
577
578
579
580
and trained volunteers keep records of measured precipitation rates, temperatures, or changes in
weather as early as the 19th century. Citizen science has contributed valuable knowledge for over a
century in remote areas, and in other fields including ornithology, where volunteers have recorded
species observed during migration or at other times (e.g. the Audubon annual Christmas Bird Count,
started in 1900: http://birds.audubon.org/about-christmas-bird-count ), and in surveys of other
species such as wildflowers (e.g. http://www.thewildflowersociety.com/) and butterflies (e.g.
http://www.butterfly-conservation.org/). Today many projects based on citizen science exist and there
are a growing number of volunteer-based programs engaging local citizens in everything from
monitoring water quality to community health (Danielsen, et al. 2009; Heiman 1997). In addition to
lowering costs of monitoring and research, and accessing remote areas, recruiting and training willing
volunteers to use scientific monitoring techniques offers additional benefits, such as strengthening
partnerships between communities and scientists, improving knowledge exchange, and building
community awareness.
581
582
583
584
585
586
587
588
589
590
591
592
593
Traditional knowledge includes skills, knowledge and values which have been acquired through
experience, observation, from the land or from spiritual teachings, and taught through generations.
Children are taught from an early age about the world around them through epistemology, based on
knowledge and trained with skill and keen senses. TK is a systematic way of knowing, transmitted
through generations, and informs on physical and biological phenomena, and ethnic and cultural
heritage. It tends to be collectively owned and takes the form of stories, songs, folklore, proverbs,
cultural values, beliefs, rituals, community laws, and local language. Modern day observations can
benefit from TK, and holders of this knowledge can observe anomalies within their environment. The
participation of TK holders in field monitoring should not be viewed as a cost saving method. The
usability of data generated from TK should not be viewed as observations made simply to further inform
science. The objective within establishing CBM plans within the Arctic is to better understand changes
that are occurring. Observations based on both TK and scientific understanding will be required to gain
this understanding.
594
595
596
597
598
599
Effective CBM plans are collaboratively designed, flexible, adaptable and implemented to address locally
determined information needs, and to provide contextual data for more informed decision-making;
CBM is therefore most effective when it adopts a bottom-up approach. This scheme involves a holistic
perspective and encourages an interdisciplinary approach. Applying a CBM plan within the Arctic can
generate high quality data of both qualitative and quantitative observations and based on both scientific
and traditional knowledge techniques.
600
601
602
603
604
605
606
The CBMP believes that community-based monitoring (CBM) and TK can make significant contributions
to circumpolar monitoring efforts. Maximizing the contributions of circumpolar Peoples to the CBMP will
help ensure that the program is relevant and responsive to local concerns. The participation and
collaboration of community members in the collection of research and monitoring data leads to a
greater investment in the effort itself and a greater understanding of the results. The CBMP-Terrestrial
Plan includes varying levels of complexity for data collection methods (see Chapter 4) to engage
participation in Arctic terrestrial biodiversity monitoring across a range of capacity levels. The CBMP
17
607
608
609
TEMG will make use of the best available information on ecosystem and biodiversity states and changes.
To this end, community based knowledge and TK will be incorporated into CBMP TEMG analysis and
reporting products.
610
611
612
613
614
615
616
617
A wealth of historical data on various aspects of the Arctic terrestrial system, including biological
measurements, exists in various forms, including scientific publications, gray literature (unpublished
manuscripts, reports, technical papers, white papers, etc.), databases, photo libraries, archived records,
field books, etc. Museum data collections exist for some Arctic terrestrial species. These data are often
not readily accessible, but they represent, in many instances, cost-effective opportunities for
establishing retrospective, long-term datasets. The potential use of these historical data repositories is
described in more detail in Chapter 6.
618
619
1.8
620
621
622
623
624
625
626
A coordinated monitoring approach for Arctic terrestrial ecosystems serves a variety of mandates at
several scales. The Arctic Council will be a direct beneficiary. The outputs of the CBMP-Terrestrial Plan
will help populate Arctic Council assessments and identify issues that require a coordinated, pan-Arctic,
or even global response. The CBMP-Terrestrial Plan will also benefit scientists directly, by improving
cross-disciplinary collaboration and providing greater access to long-term and pan-Arctic data sets. This,
in turn, will facilitate advanced research and publications on the mechanisms that drive environmental
trends.
627
628
629
630
631
632
633
634
635
CBMP-Terrestrial Plan outputs will also be of direct value to national and sub-national governments and
organizations charged with monitoring and reporting on the status of Arctic terrestrial ecosystems
within their jurisdictions. In many Arctic countries, this responsibility is shared across a number of
government agencies. Developing optimal sampling schemes and harmonized and integrated
approaches to monitoring at a pan-Arctic scale will: (1) improve sub-national and national governments’
ability to understand trends and the mechanisms driving these trends; (2) support planning and
monitoring activities around industrial and other developments; and (3) increase the capacity of
individual agencies to respond effectively. Integration with international monitoring schemes will allow
monitoring programs a multiple scales of effort to contextualize observed changes.
636
637
638
639
To the greatest extent possible, information developed under the CBMP-Terrestrial Plan will be provided
at the local scale to serve local decision-making. This will be achieved partly through local-scale,
community-based monitoring, but also through interpolation and modeling techniques to provide
information that Arctic residents can use to make effective adaptation decisions.
640
641
642
643
644
The successful implementation of the CBMP-Terrestrial Plan depends upon effective links to a number
of biotic and abiotic monitoring programs and initiatives, including those that are concerned with
anthropogenic drivers. However, critical information could also be garnered from other monitoring
efforts including other national, umbrella and extra-Arctic programs (see below). In turn, these
programs can use the information generated by the CBMP-Terrestrial Plan and might provide
Links and Relevance to Other Programs and Activities
18
645
646
647
opportunities for coordinated monitoring (e.g. shared sampling sites). Examples of potentially related
abiotic, umbrella, and extra-Arctic monitoring programs, assessments, and initiatives include the
following3:
648

Arctic Breeding Bird Conditions Survey
649

International Tundra & Taiga Experiment (ITEX)
650

CircumArctic Rangifer Monitoring Network (CARMA)
651

PPS Arctic
652

Program for Regional and International Shorebird Monitoring (PRISM)
653

SCANNET/INTERACT
654

Breeding Bird Survey (BBS)
655

CALM (Circumarctic Active Layer Monitoring) Network
656

Arctic Palaeoclimate and its Extremes (APEX)
657
658

Global Observation Research Initiative in Alpine Environments (GLORIA)
659
660
661
662
663
1.8.1
664
665
666
667
668
669
670
671
The ABA, led by the CAFF Working Group of the Arctic Council, is a three-phase assessment of the status
of the Arctic’s biodiversity. The first phase, the Selected Indicators of Change report (CAFF-ABT 2010),
was based on the suite of CBMP indicators and indices. The CBMP-Terrestrial Plan will benefit from the
ABA’s full scientific assessment report. This assessment involves gathering and analyzing existing data on
Arctic terrestrial biodiversity. The development of the ABA terrestrial chapters will provide useful
baseline information from which the CBMP-Terrestrial Plan can build. The CBMP-Terrestrial Plan will use
the ABA as the baseline from which it will periodically (every five years) reassess the state of the Arctic’s
terrestrial ecosystems.
672
673
674
675
Other CAFF activities as related to the terrestrial environment including the work of the CAFF Flora
Group. This group will also contribute to and benefit from the CBMP-Terrestrial Plan.
Arctic Council Working Groups and Activities:
Examples of related programs in the Arctic Council include:
Arctic Biodiversity Assessment (ABA)
3
See Chapter 10 (Glossary) for more information and links to these programs
19
676
Arctic Council Arctic Monitoring and Assessment Programme (AMAP) Working Group
677
678
679
680
681
682
683
684
AMAP’s objective is “providing reliable and sufficient information on the status of, and threats to, the
Arctic environment, and providing scientific advice on actions to be taken in order to support Arctic
governments in their efforts to take remedial and preventative actions relating to contaminants.” As
such, AMAP is responsible for “measuring the levels, and assessing the effects of anthropogenic
pollutants in all compartments of the Arctic environment, including humans; documenting trends of
pollution; documenting sources and pathways of pollutants; examining the impact of pollution on Arctic
flora and fauna, especially those used by Aboriginal Peoples; reporting on the state of the Arctic
environment; and giving advice to Ministers on priority actions needed to improve the Arctic condition.”
685
686
687
688
The information generated by AMAP on pollutants and their impacts on Arctic flora and fauna will be an
important data element in interpreting Arctic terrestrial biodiversity trends in some cases. Opportunities
for monitoring efficiencies between AMAP’s monitoring program and the CBMP-Terrestrial Plan should
be investigated and, wherever feasible and desirable, coordinated monitoring should be implemented.
689
690
691
692
693
694
AMAP is also involved in climate assessment and led the Snow, Water, Ice and Permafrost in the Arctic
(SWIPA) project. SWIPA was established by the Arctic Council in April 2008 as a follow-up to the 2004
Arctic Climate Impact Assessment, with the goal of assessing current scientific information about
changes in the Arctic cryosphere, including the impacts of climate change on ice, snow, and permafrost.
Of particular relevance is the assessment of snow cover and permafrost change as these are important
physical elements that can influence many aspects of the Arctic terrestrial ecosystem.
695
696
Arctic Council Sustainable Development Working Group (SDWG) Working Group
697
698
699
700
701
702
703
The objective of the SDWG is to protect and enhance the economies, culture, and health of the
inhabitants of the Arctic in an environmentally sustainable manner. Currently, the SDWG is involved in
projects in the areas of children and youth, health, telemedicine, resource management, cultural and
ecological tourism, and living conditions in the Arctic. The work of SDWG—in particular, development of
indicators related to human-community response to changes in biodiversity—will be useful to the
CBMP-Terrestrial Plan. In turn, it is anticipated that the outputs of the monitoring plan will directly
benefit SDWG’s indicator development.
704
Sustaining Arctic Observing Networks (SAON) – An Arctic Council Initiative
705
706
707
708
709
SAON is composed of representatives of international organizations, agencies, and northern residents
involved in research and operational and local observing. This initiative is developing recommendations
on how to achieve long-term, Arctic-wide observing activities. The goal is to provide free, open, and
timely access to high-quality data that will contribute to pan-Arctic and global value-added services and
provide societal benefits. CAFF’s CBMP is the biodiversity component of SAON. The CBMP-Terrestrial
20
710
711
Plan will both facilitate and benefit from the development of an integrated pan-Arctic observing
network.
712
713
714
1.8.2 Other Programs
715
Group on Earth Observations Biodiversity Observation Network (GEO BON)
716
717
718
719
720
721
722
723
724
725
GEO BON is the biodiversity arm of the Global Earth Observations System of Systems (GEOSS). Some 100
governmental and non-governmental organizations are collaborating through GEO BON to make their
biodiversity data, information, and forecasts more readily accessible to policy makers, managers,
experts, and other users. GEO BON is a voluntary, best-efforts partnership guided by a steering
committee. The Network draws on GEO’s work on data-sharing principles and on technical standards for
making data interoperable. This global initiative is closely aligned with the CBMP, and the CBMP is the
now the Arctic-BON of the global network. The CBMP’s outputs, including the outputs from the CBMPTerrestrial Plan, will feed directly into the GEO BON effort. Correspondingly, pan-Arctic biodiversity
monitoring will benefit from the information generated globally, providing context for the patterns and
trends detected in Arctic ecosystems.
726
Biodiversity Indicators Partnership and the Convention on Biological Diversity
727
728
729
730
731
732
733
734
735
736
The CBD-mandated Biodiversity Indicators Partnership is the global initiative to promote and coordinate
development and delivery of biodiversity indicators in support of the CBD, Multilateral Environmental
Agreements (MEA), the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES),
national and regional governments and a range of other sectors. The Partnership brings together over
forty organizations working internationally on indicator development to provide the most
comprehensive information on biodiversity trends. The CBMP is a partner organization to BIP and the
CBMP has identified a suite of high-level indicators and indices that will be used, in part, to track the
Arctic’s progress towards some of the Aichi 2020 Targets. The data rescued, aggregated and generated
by the CBMP-Terrestrial Plan will be used to directly populate many of these indicators and thus, the
CBMP-Terrestrial Plan will be a direct contributor to the global assessment of trends in biodiversity.
737
The Global Biodiversity Information Facility (GBIF)
738
739
740
741
742
The Global Biodiversity Information Facility (GBIF) was established by governments in 2001 to encourage
free and open access to biodiversity data, via the Internet. Through a global network of countries and
organizations, GBIF promotes and facilitates the mobilization, access, discovery and use of information
about the occurrence of organisms over time and across the planet, and provides a platform to
standardize taxonomy (http://data.gbif.org/welcome.htm ).
743
21
744
Programs and Monitoring Networks in other global cold regions: Antarctica and Mountains
745
746
747
748
749
750
751
752
753
754
755
The Arctic is undergoing rapid change, along with other cold regions of the world including Antarctica
and high alpine regions. Comparative data, monitoring capacity, infrastructure, and expertise already
exist focusing on these cold regions elsewhere and on bipolar settings, and valuable contributions and
knowledge can be exchanged via existing networks. As an illustration, IPY projects often resulted in
Antarctic, Arctic, and bipolar collaborations, and outputs are often accessible, nationally and
internationally (e.g. http://www.ipy.org/ ; even for the earliest IPY in the late 1800’s:
http://www.arctic.noaa.gov/aro/ipy-1/). The Scientific Committee on Antarctic Research (SCAR:
http://scar.org/ ) and the British Antarctic Survey (BAS: http://www.antarctica.ac.uk/) specialize in
Southern regions, but include many bipolar initiatives also. For alpine regions, an international initiative
for research, monitoring and assessment includes Diversitas - Global Mountain Biodiversity Assessment
(http://gmba.unibas.ch/index/index.htm ).
756
22
CAFF Management Board
CBMP Office &
Steering Committee
Arctic Biodiversity
& Assessment
Network of
networks:
Species &
habitat
networks
Site-based
networks
Integrated ecosystembased management
approach
ARCTIC
Marine
Coastal
Freshwater
Terrestrial
Including but
not limited to:
Indicators
Remote sensing
Communitybased
monitoring
Traditional
knowledge
Abiotic,
extra-Arctic &
umbrella
networks
Data Integration
Management & Depiction
Global, National, Regional & Local
Communication, Education & Outreach
Reporting (Indicators & Regular Assessments)
Public, Scientists, Northern Communities, Decision-Makers
757
758
Figure 1.1 Organizational structure of the Circumpolar Biodiversity Monitoring Program (CBMP).
759
23
760
761
2
TEMG Focal Areas: Geographic Boundaries and Definitions
762
763
764
765
766
The TEMG closely follows the definitions, geographic boundaries, species and ecosystem coverage as
outlined by the CAFF Arctic Biodiversity Assessment (CAFF-ABBA 2013 ) (Figure 2.1). The CBMPTerrestrial Plan scope includes High and Low Arctic and alpine Subarctic regions in proximity of the
Arctic proper.
767
768
769
770
771
772
773
774
775
776
777
The CBMP’s mandate is to measure biodiversity within an ecosystem perspective. Spatial integration is
necessary to deliver meaningful information for the terrestrial monitoring program. To facilitate the
development of the terrestrial monitoring program, spatial scales were outlined. ‘Region’ can be defined
in several ways including political borders (territorial or settlements), socioeconomic categories,
geologic regions, watersheds, or biogeography. Different regions will be affected by different drivers to
varying degrees. In some cases, a given region can serve as a reference for another site (e.g., a remote
site could be used as reference site for one to be impacted by development). Monitoring should be
performed in a way to meet a given region’s specific issues or interests, but that allows comparisons
among regions also.
778
779
2.1
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
Arctic proper: From a geophysical point of view, the terrestrial Arctic may be defined as the land north
of the Arctic Circle, where there is midnight sun in the summer and winter darkness. But from an
ecological point of view, it is more meaningful to use the name for the land north of the treeline, which
generally has a mean temperature below 10-12 °C for the warmest month. With this definition, the
Arctic land area comprises about 7.5 million km², or some 5.5% of the land surface on Earth. The Arctic
may be divided into a number of subzones based on floristic types, i.e., subzones A-E on the Circumpolar
Arctic Vegetation Map (CAVM Team 2003). Here, the division between the High Arctic and the Low
Arctic is most relevant, and we use the separation between subzones C and D on the CAVM.
Geographic Boundaries and Definitions
High Arctic: The high Arctic comprises the Arctic land masses in the far north where mean July
temperatures vary from 6°C in the south to only approximately 2°C in the north. Precipitation in the
north is less than 50 mm per year and falls mainly as snow. The high Arctic consists of polar semidesert
vegetation in the south (cryptogam–herb, cushion plant–cryptogam, and wetland communities which do
not cover all of the ground) and polar desert (herb-cryptogam communities which cover only
approximately 5% of the ground) in the far north.
24
796
797
798
799
800
801
802
803
804
805
806
807
Low Arctic: The Low Arctic is characterised by mean July temperatures between 6-12°C, more
precipitation more evenly distributed during the year, both in form of snow and rain. The Low Arctic
tundra has much more productive vegetation than the High Arctic, with shrub tundra, wetlands and, in
the northern end, dwarf shrub–herb communities.
Subarctic (or Sub-Arctic): This is the ecotone between the Arctic and the taiga, i.e., the area between
the timberline and the treeline. Hence, the Subarctic is not part of the Arctic. However, the Subarctic
comprises low alpine and high alpine zones in mountainous areas closely connected to the Arctic,
oceanic tundra (e.g., the Aleutian Islands) and the forest tundra (e.g., the Subarctic). The Subarctic is
addressed because it comprises species of significance to the Arctic tundra and has an influence on this
region, and it serves as a potential corridor for species movement into the current Arctic tundra region
(e.g. due to global change).
25
808
809
810
811
812
813
814
815
Figure 2.1. Boundaries of the geographic area covered by the Arctic Biodiversity Assessment and the
terrestrial CBMP, defined by the division between High Arctic, Low Arctic and Subarctic according to the
Circumpolar Arctic Vegetation Map (CAVM Team, 2003). Mostly the Arctic proper is covered in the
CBMP-Terrestrial Plan, but with the inclusion of Eurasia, alpine regions in close proximity or with
ecological linkages to the Arctic proper, Subarctic regions are included also. Map from: (Hohn and
Jaakkola 2010).
816
26
817
3
Monitoring Approach, Objectives and Methods
818
819
3.1
Overall Monitoring Approach
820
821
822
823
824
825
826
827
The CBMP TEMG will pursue a terrestrial biodiversity monitoring program following an ecosystem-based
approach, which generates a comprehensive, system-based understanding to better inform decisionmaking related to the conservation and management of critical Arctic terrestrial biodiversity. Indicators,
or Focal Ecosystem Components (FECs), which are made up of key biodiversity elements (and related
composition, structure, and function elements), captured via multiple interacting parameters at various
scales will be identified and integrated (via harmonization) to describe and report assessments of
biodiversity and ecosystem status and trends and to diagnose potential drivers, processes at play, and
implications of those trends.
828
829
830
831
832
833
834
835
836
837
838
839
840
841
The CBMP-Terrestrial Plan is focused on Arctic terrestrial biodiversity elements status and trends, but
also on the ability to predict future potential changes in these elements and to facilitate the
identification of the causal mechanisms driving these trends. A solid conceptual understanding of Arctic
ecosystems, and clearly-articulated monitoring questions (see section 3.2 and Chapter 4), are essential
to shape the selection and assessment of FECs and their associated attributes and parameters.
Monitoring to address the priority questions (See 3.2) identified within the CBMP-Terrestrial Plan
initially builds extensively from existing monitoring networks and local capacity to maximize the
efficiency and likelihood of success. However, while much can be accomplished through existing
networks and monitoring efforts, the CBMP-Terrestrial Plan also identifies monitoring needs which
cannot be addressed through current capacities or existing efforts. Existing and new monitoring
initiatives and partners will be considered at different spatial scales (from plots to landscapes, and from
species to communities and/or populations) and temporal scales (from years to decades) and integrated
through modeling. Figure 3.1 illustrates the overall conceptualization of the global TEMG monitoring and
data harmonization scheme.
842
843
844
845
846
847
848
849
850
851
852
853
The CBMP TEMG is pursuing a balance of both (1) targeted, question-oriented, research-based
monitoring (Lindenmayer and Likens 2010) and (2) survey-based, or surveillance, monitoring (Boutin, et
al. 2009; Nichols and Williams 2006). Surveillance monitoring commonly focuses on a broad suite of
ecological indicators to identify impacts of multiple drivers across a range of possible biological
endpoints and ecosystem functions. Because surveillance monitoring is commonly applied at a broad
scale and across multiple indicators, it is more likely to remain relevant over the long-term as ecological
stresses arise and evolve (Boutin, et al. 2009) and as drivers are impacted by climate change.
Surveillance monitoring best supports general status and trend estimations and will likely not address
why a change is occurring, although qualitatively derived cause/effect relationships may be
hypothesized based on conceptual model formulation (and form the basis for future research needs).
Surveillance monitoring, which includes traditional knowledge (TK) methodologies also, recognizes
anomalies and is hypothesis-seeking (descriptive and exploratory, when patterns are first observed)
27
854
855
856
857
858
859
860
861
rather than hypothesis-driven (experimental and systematically designed studies; pre-planned) (see
commentaries on the value of both approaches: Casadevall and Fang 2008; Kell and Oliver 2004).
Question-oriented monitoring, on the other hand, targets specific indicators and their drivers, and is
designed to address a specific set of hypotheses, usually at a finer scale of assessment than surveillance
monitoring, to quantitatively build a mechanistic understanding of cause/effect relationships
(Lindenmayer and Likens 2010). A challenge for the CBMP-Terrestrial Plan is to develop a
harmonization/analytical process that will allow for the integration of both survey and question-based
monitoring to meet Arctic terrestrial biodiversity monitoring goals.
862
863
864
865
The CBMP-Terrestrial Plan development follows steps required to establish an effective, efficient,
adaptive monitoring program (Boutin, et al. 2009; Elzinga, et al. 1998; Fancy, et al. 2009; Gross 2003;
Lindenmayer and Likens 2010; Mulder, et al. 1999; Taylor, et al. 2012; Toevs, et al. 2011). The key
activities are outlined in Table 3.1.
866
867
Table 3.1. Key activities of the CBMP-Terrestrial Plan development processes, timelines, and chapter
references.
Activity
Clearly define monitoring goals and objectives.
Compile and summarize existing information (TEMG
Monitoring inventory)
Develop conceptual models to elucidate and
communicate understanding and interrelationships of
key ecological components and interactions
Identify and select indicators meaningful to
management objectives and ecosystem priorities
Identify and select monitoring parameters, methods,
and develop overall sampling design
Establish data management, analysis and reporting
procedures
Field test; analyze data
Modify and adapt as required
When completed
TEMG Workshop 1, 2, & 3
Background Paper; on-going
Plan reference
Chapter 4
Appendix
TEMG Workshop 1 & 2
Chapter 4
TEMG Workshop 1 & 2
Chapter 4
TEMG Workshop 2 & 3
Chapter 4
CBMP Data Management
Strategy
Implementation
Implementation
Chapter 6, 7
Chapter 6, 8
Chapter 6, 8
868
869
870
871
872
873
874
875
876
877
878
3.2
Central Questions to be addressed in the Monitoring
The CBMP-Terrestrial Plan aims to address the following overarching key monitoring questions:
1. What are the status, distribution, and conditions (including thresholds of concern) of terrestrial
focal species, populations, communities, and landscapes/ecosystems and key
processes/functions occurring in the Arctic?
2. How and where are these terrestrial focal species, populations, communities, and
landscapes/ecosystems and key processes/functions changing?
3. What and how are the primary environmental and anthropogenic drivers influencing changes in
biodiversity and ecosystem function?
28
879
880
881
882
4. Where are the areas of high ecological importance including, for example, resilient and
vulnerable areas (related to the focal ecosystem components) and where are drivers having the
greatest impact?
883
3.3
Scale of Monitoring and Reporting
884
Biological diversity operates at different scales and is generally understood to include species diversity,
885
genetic diversity and ecosystem diversity (see Chapter 1). Correspondingly, the CBMP Terrestrial Plan
886
aims to measure and report changes in biodiversity, as well as relevant structures, processes, and
887
functions affecting diversity, at scales from local to landscape, to regions, and the circumpolar Arctic, as
888
appropriate and feasible. Data collection and analytical methods and reporting will be multi-scale and
889
will include plot-based ground measures, remotely-sensed products, and sampling of species,
890
populations, and communities. At the local (plot or site) scale, data will be collected on individual
891
species, life forms, or functional guilds as appropriate; at landscape scales, the composition, structure
892
and diversity of populations, communities, or ecosystems will be measured; and finally, at the regional
893
or pan-Arctic scale, measures will focus on landscapes and/or regions and relevant features therein.
894
895
896
897
898
Methods that detect change at scales from local to landscape and provide complementary information
are essential. The various approaches can be designed as layers and combined during data collection,
analysis, and/or reporting. Multi-scale integration between and among the monitoring efforts will
increase the probability of detecting change, will support up- and down-scaling of identified effects, and
will hence create a more effective monitoring scheme.
899
900
901
902
903
904
905
906
907
908
Monitoring Arctic biodiversity with ground-based sampling and a number of remote sensing platforms in
an integrated manner offers an opportunity to complete a pan-Arctic assessment for a number of
priority focal ecosystem components. Ground-based monitoring data will be used to derive local
estimates of status, trend, and condition where robust data exist. These ground data can also be used to
validate remote sensing products where applicable, which can then be used to extrapolate groundbased resource estimates to broader areas (especially for vegetation characteristics) which are
logistically or financial difficult to access or completely inaccessible. Combining ground sampling with
remote sensing observations will provide a regional context for detailed ground measurements. Fine
spatial resolution remote sensing data and ground sampling can also be combined to better interpret
coarse resolution (1km) satellite data so that pan-Arctic classifications are possible.
909
910
911
CBMP TEMG aims to identify and assess trends at the appropriate scale relative to the monitoring
question, but attention will be given to scales from landscape to pan-Arctic, versus site-specific
reporting (see Chapter 7).
912
29
913
3.4
Data and Modeling
914
915
3.4.1
Standardization and harmonization of protocols and data
916
917
918
919
920
921
922
923
924
The TEMG supports standardization of biodiversity monitoring methods, where appropriate (e.g., for
new measures and for existing measures that are already close to standardized in their application). The
adoption of robust monitoring protocols will ensure the validity and consistency of the data and
demonstrate to end users that results are reliable. In some cases, however, the opportunity to
standardize monitoring protocols will be limited due to natural heterogeneity of desired monitored
parameters among regions or the existence of long-term data sets following differing protocols. In such
cases where standardization is not possible or practical, harmonization of monitoring methodologies will
facilitate integration and assessment of data across regions and scales. The TEMG also supports
standardization of taxonomy and robust synonymy.
925
926
927
3.4.2
Modeling
928
929
930
931
932
933
Modeling will be used, where possible, to integrate and upscale/downscale identified trends. By
combining local information, including traditional knowledge, on changes in biodiversity indicators and
abiotic drivers with the geographic extrapolation abilities of remote sensing, modeling will serve to
extend local results to broad areas of the circumpolar Arctic where direct monitoring information is
lacking. Models are also useful to predict and test potential future scenarios and will further elucidate
possible changes and inform proactive adaptive management.
934
935
936
3.5
Key Concepts of the CBMP-Terrestrial Plan
937
938
939
940
941
942
943
944
945
946
947
3.5.1
Monitoring supported by conceptual models
An integrated monitoring approach needs to reach across programs, jurisdictions, stakeholders, and
agencies to manage for ecosystem sustainability. One way to achieve this goal is to identify both
essential management questions, and key ecosystem elements (i.e. focal ecosystem components, FECs)
and associated attributes and drivers, leading to the selection of priority monitoring parameters and
methods. Of primary importance is that final parameter selection is based on key ecological functions or
essential species demonstrated within common, accepted conceptual ecological models.
A conceptual model represents a working hypothesis about key system relationships, functions and
organization (Beever and Woodward 2011). Developing a monitoring program based on a structured,
30
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
discussed (amongst multiple experts and/or stakeholders), and well thought-out ecosystem-based
conceptual model approach can generate a comprehensive, system-based understanding that provides
the foundation to identify and assess a suite of key biodiversity elements and related, priority
ecosystem components, structure, functions, and processes (Gross 2003; Lindenmayer and Likens 2010;
Taylor, et al. 2012). Conceptual ecological models for the Arctic based on science and other expert input,
are tools that can provide a “common language” that addresses to elucidate and communicate the
critical components and processes of ecosystem sustainability within and across resource disciplines.
Conceptual models allow for the identification and selection of priority monitoring elements that will
meaningfully describe the status of many parts of the ecosystem with the least effort possible. This is
especially critical when monitoring remote, difficult to access locations like much of the Arctic, where a
program cannot monitor everything, everywhere, and all of the time. Once established and fully vetted,
the conceptual models provide a basis for resource-use decisions predicated on maintaining or restoring
ecosystem capacities through monitoring FECs, and functions, processes, and their associated attributes
and parameters.
970
971
3.5.2
972
973
974
975
976
977
Increasing cumulative pressures induced by, for instance, climate change and human activities are
contributing to rapid changes in natural ecosystems in the Arctic and elsewhere. Hence, it is necessary
to identify natural and anthropogenic drivers in the terrestrial monitoring program. An appropriate
balance between monitoring of ecosystem FECs and system drivers must be developed to not only
document change, but also to establish the causal relationships between changes in biodiversity and
these pressures.
978
979
980
981
982
983
984
985
986
Understanding linkages between the drivers (non-biological as well biological) of the system and the
potential FECs is critical to development of a successful, efficient monitoring program. Differential driver
impacts, or strength of impacts, have direct relevance on what to monitor, where to monitor, and how
often to monitor. Understanding what biodiversity elements are likely to be affected by a given
drivers(s), may prioritize the element or driver(s) for monitoring. Understanding where priority elements
exist (geographically), or which potential sampling strata are likely to be influenced first (or most
heavily) by any given driver(s), may prioritize the sampling strata driver(s) for monitoring, or call for an
intensive or extensive sampling approach to best understand the effects. Similarly, understanding that
any driver may influence an element or location first or more heavily (compared to other elements or
31
Resource scientists/specialists commonly will be able to employ expert knowledge to determine the
most critical components and processes essential to their field of study, which was also true for
members of the TEMG. The CBMP TEMG used both ecological theory based in conceptual models
(section 3.5.3 and Chapter 4) as well as needs of management, industry, and communities (Chapter 4) to
identify and rank the parameters and indicators of the focal ecosystem component in the CBMPTerrestrial Plan.
Linkage to system drivers
987
988
989
990
991
locations), may prioritize this element for more frequent monitoring compared to other elements that
are likely to change more slowly through time. For these reasons, the CBMP TEMG clearly identified the
drivers in the development of a global conceptual model (Fig 3.2; Table3.2) and biotic models (Chapter
4). Table 3.2 below illustrates the high priority drivers identified and how they will be monitored
through the CBMP-Terrestrial Plan.
992
993
994
3.5.3
The CBMP TEMG Conceptual Model
995
996
997
998
999
1000
1001
Consensus opinion amongst TEMG members and associated experts was used to create a
comprehensive conceptual model of the entire ecosystem, including key relationships and drivers
affecting the ecosystem (Figure 3.2). Furthermore, ecosystem-based conceptual models for the broad
focal ecosystem components (i.e., birds, mammals, vegetation, and invertebrates) at the broadest
thematic scale (see Chapter 4) were developed by consensus at two expert workshops. The conceptual
models integrate both key biological (biotic) and non-biological (abiotic) drivers affecting diversity as
well as ecosystem function characteristics.
1002
1003
1004
The conceptual models are generic enough to be applied across the entire Arctic landscape through a
process of localization, where the general conceptual model is adapted to the local food web structure,
local drivers, and other relevant local phenomena (see Case studies in Chapter 4; e.g. Box 4A-D).
1005
1006
32
Table 3.2. Monitoring high priority drivers as outlined in the CBMP-Terrestrial Plan and recommended
additional drivers for monitoring as capacity permits (or where data exist from other networks).
TYPE OF DRIVER
HOW DRIVER WILL BE MONITORED
ABIOTIC DRIVERS (may be influenced by anthropogenic influences)
·
Climate: Length of growing season
·
Climate: temperature air and soil
Phenology monitoring: (Chapter 4: vegetation)
Collection of site data (Chapter 4); linkage with other
networks
· Climate: precipitation (rain/snow, snow
cover duration and extent; icing events)
Collection of site data (Chapter 4); remote sensing; linkage
with other networks
· Site characteristics (soils, permafrost,
soil moisture, topography)
Collection of site data (Chapter 4); remote sensing; linkage
with other networks
·
Collection of site data (Chapter 4); remote sensing; linkage
with Freshwater plan
Hydrology
Other recommended abiotic drivers: cloud cover, solar radiation, treelines, storms, wind.
Climate change (rates of change) can be monitored indirectly from climate data
BIOTIC DRIVERS (may be influenced by abiotic and anthropogenic drivers)
· Competition from southern species and
other interspecies processes
·
·
·
·
Species/community monitoring (Chapter 4)
Invasive and non-native species
Shrubification
Grazing/foraging
Pollination
Species/community monitoring (Chapter 4)
Species/community monitoring (Chapter 4)
Species/community monitoring (Chapter 4)
Species/community monitoring (Chapter 4: arthropods)
Species/community monitoring (Chapter 4: mammals,
· Pathogens and parasites
birds)
· Habitat quality (connectivity, natural
Collection of site data and species/community
disturbance, nesting/breeding habitat,
monitoring(Chapter 4); remote sensing; for water resources
water resources)
see CBMP - Freshwater Plan
Other recommended biotic drivers: health of soil biota (rates of nutrient cycling, decomposition); drivers
as required for species of special interest (e.g. affecting reproductive effort, rates of herbivory, etc.).
Changing species distributions due to climate change can be monitored indirectly through data-collection
on species diversity, abundance and other from ecological data as above (and see Chapter 4)
ANTHROPOGENIC DRIVERS
· Harvesting, hunting, trapping, fishing
(fish prey important for terrestrial species)
TK, CBM, data available from other networks (e.g.
governments, migratory bird data from other regions, etc.)
· Anthropogenic disturbance (noise,
trampling, increased visitors and traffic)
· Land use and habitat conversion within
Arctic (including fragmentation,
infrastructure, resource extraction, roads)
· Habitat conversion outside Arctic
Land use monitoring (Chapter 4: vegetation); remote
sensing; collection of site data; data from other networks
Land use monitoring (Chapter 4: vegetation) ; other drivers
outside study scope: remote sensing; collection of site data;
data from other networks
Outside study scope; linkage with other networks
· Contaminants and pollution
Outside study scope; other networks (e.g. AMAP)
Other recommended anthropogenic drivers: Nutrification and enrichment (chemical analyses; vegetation
C stock; CANTTEX manual); domestication; tourism (disturbance; non-native species movement)
33
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
3.5.4
1018
1019
A process based on expert-opinion was then completed to rank and prioritize potential monitoring FECs
and their attributes. Rankings were based on a simple sum of scores for several factors, including:
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
Identification of Focal Ecosystem Components, Attributes and Parameters
The list of potential FECs was generated based on a combination of the conceptual models and
management and community needs. During the first expert workshop, TEMG teams developed base
conceptual models for each biotic group. In addition, TEMG teams identified key audiences for Arctic
terrestrial biodiversity monitoring information, including resource managers and community members,
and their needs for biodiversity information to answer key questions and manage/adapt to the
environment. During the second expert workshop, these models and biodiversity information needs
were refined and tables generated to identify (in list form) potential Focal Ecosystem Components
(FECs). To each FEC a number of describing attributes were assigned, and to each attribute a number of
parameters and attributes were assigned (e.g. Figure 3.3).
a)
b)
c)
d)
Ecological Relevance
Relevance to ecosystem services
Relevance to Arctic Peoples
Relevance to management and legislation
Highly-ranked FECs (greater than 75% of the potential score) plus several additional FECs, based on
agreed management and/or community needs, were carried forward as priorities for the CBMPTerrestrial Plan. Expert teams identified parameters to be measured in the field related to each
identified attribute. At a minimum, the parameters were SMART (specific, measurable, achievable,
results oriented and temporally defined). In addition, the following additional criteria refined the
parameter selection:







sensitivity to natural or anthropogenic drivers;
relevance to Traditional Ecological Knowledge-based management
validity;
ecological relevance;
availability and sustainability of monitoring capacity and expertise;
relevance to targets and thresholds; and
practicality.
A multi-scale sample and reporting design for the priority FECs, attributes and parameters was
developed (see Chapter 4). The CBMP-Terrestrial Plan affords flexibility in the selection of locally
relevant focal ecosystem components which best typify biodiversity and ecosystem integrity by focusing
on functional ecosystem components, rather than specific species, as appropriate. In this manner, the
plan aims to balance the need for standardized data collection for assessment and reporting with
requirements for the adoption and use of locally relevant indicators.
34
1047
1048
1049
3.6
Establishing Reference (Baseline) Conditions
1050
1051
1052
Points of reference against which the status of populations, species, or ecosystems can be compared are
required to assess change (and condition) in a meaningful way. Baselines provide a starting point for
analysis of change (Dunster and Dunster 1996). The baselines for trend analysis are parameter-specific.
1053
1054
1055
1056
1057
1058
1059
1060
1061
Nielsen et al. (2007) identify four potential sources for establishing baselines or reference points: (1)
protected areas or other spatial benchmarks (i.e., comparisons of areas unaffected by a given driver,
such as a control site, to areas affected by the driver); (2) time-zero (arbitrary date or level); (3) desired
goals or targets (management goals); and (4) modeled reference conditions using empirical estimates.
Baselines may also be strengthened by incorporating knowledge from TK holders. For example, audio
recordings from traditional knowledge holders, which describe changes over a period of time, can be a
useful source of information for time-zero analysis. Other data sources include natural archives from
pollen records and genetic material in sediment, and historical museum records and early published
data and reports can also provide information to help develop baselines for time-zero analysis.
1062
1063
1064
1065
The Arctic is impacted by some drivers affecting the entire region including climate change and
contaminants, for which a spatial baseline or “control” cannot be fully derived. Other drivers, such as
anthropogenic footprint, are spatially differentiated so that spatial benchmarks can be used to assess
changes between impacted and non-impacted sites.
1066
1067
1068
1069
1070
1071
1072
1073
1074
In the absence of global management goals or targets for Arctic biodiversity, focal ecosystem attributes,
and detailed empirical data on historical biodiversity trends from which modeled reference conditions
could be derived, the CBMP TEMG is recommending baseline conditions be established using a
combination of (1) current and historical data for analysis over time and (2) spatial benchmarks, as
appropriate for a given attribute. Protected areas and appropriately situated field stations conducting
integrative monitoring (e.g. SCANNET/INTERACT sites) could act as suitable spatial reference sites. The
TEMG recommends seeking out and integrating the best available historical and current data as the
basis for reporting indicator changes, and hence, changes in biodiversity and ecosystem integrity into
the future (see Chapter 6 for more information).
1075
1076
1077
3.7
Establishing Thresholds of Concern
1078
1079
1080
1081
In order to establish ecological relevant thresholds of concern, one must understand how resilient a
system is and where the system’s ecological tipping points reside. Ecological tipping points are locations
along a gradient of change where a small change in external conditions can result in a drastic change in
the structure and composition of a system (Groffman, et al. 2006). Such changes are often abrupt and
35
1082
1083
1084
1085
1086
may be irreversible. In some cases, multiple stable steady states exist and systems may fluctuate
between the two states without loss in ecosystem function. Changes between states may be driven by
both anthropogenic and natural disturbance (Van der Wal 2006). Change in ecosystems is natural, but
the pace, magnitude and cumulative impact of biodiversity drivers may push ecosystems beyond normal
system variation.
1087
1088
1089
1090
1091
1092
1093
Tipping points are scale-dependent. For example, the minimum number of individuals to maintain a
viable population of a particular species is a biological tipping point. It is possible that a species could go
locally or regionally extinct, without loss of overall ecosystem function and structure, if other species
can perform a similar function or if other system compensation mechanisms exist. In the Arctic, there is
little functional redundancy in avian and mammalian biota, so the likelihood of other species assuming
similar functional roles of a vulnerable species is reduced. This may render Arctic systems more
vulnerable to drastic ecosystem shifts.
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
Tipping points are difficult to identify, because ecological relationships are often non-linear and
characterized by uncertainty. Some Arctic vegetation communities, for example, are resistant to change
and it may not be possible to detect ecosystem level responses until after a threshold is crossed (Hudson
and Henry 2010). An additional complication for determining tipping points is that many populations of
species and species relationships follow a cyclical pattern of depending on, for example, interactions of
weather factors, the abundance of the forage available, and the density of predator species (e.g.
lemmings). Establishing the natural range of variation for ecosystems, their communities, and other key
components is essential to identify and understand biologically relevant tipping points, and
subsequently, to derive biologically relevant thresholds of management concern. Determining natural
range of variation necessarily involves analysis of long-term information.
1104
1105
1106
1107
Thresholds can also be assigned based on management goals or targets. These targets may be made
based on best available scientific knowledge for the appropriate management of a given ecosystem, as
well as the values and trade-offs considered by ecosystem managers and society. Common goals and
targets for Arctic biodiversity have not yet been well-defined.
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
The CBMP TEMG implementation plan will strive to understand the normal range of variation for each
FEC-attribute parameter. For some parameters, sufficient information may already exist, while for
others, establishing this variation will necessarily involve collection of data over a period of years,
particularly through focused monitoring at the integrative research monitoring sites (see Chapter 4).
Where biological thresholds are unknown, statistical thresholds may be identified as interim thresholds
until sufficient data is collected to understand variability. Ecosystems are subject to a range of local
pressures and drivers which may have a cumulative impact on biologically identified thresholds. A clear
understanding of the range of historical variation will allow managers to identify, as best as possible,
biological and ecological thresholds in their particular context and assist Arctic managers and
communities with evidence-based decision-making.
1118
36
1119
1120
1121
1122
1123
1124
3.8 Linkages between the CBMP-Terrestrial Plan and the CBMP Indices and
Indicators
The CBMP has developed a suite of overarching indicators and indices characterizing Arctic ecosystems
(Gill and Zöckler 2008). The CBMP-Terrestrial Plan has tight linkages to the CBMP indicators and indices,
and hence also to indicators outlined in the Convention on Biological Diversity (CBD) (Table 3.3).
1125
37
1126
1127
1128
Table 3.3. Linkages between the CBMP indicators and indices, and the CBMP-Terrestrial Plan and the
CBD indicators. A “√” means that the indicator is supported, while an “X” means that the indicator is not
supported by the CBMP-Terrestrial Plan.
CBMP biodiversity indices and indicators
Linkage to CBMP
TEMG biodiversity
indicators
Linkage to CBD
indicators
Species composition
Arctic Species Trend Index
Trends in indicators of Focal ecosystem Components
√
√
√
√
Trends in abundance of Focal ecosystem Components
√
√
Arctic Red List Index
Change in Status of threatened Species
√
√
√
√
Trends in Total Species Listed at Risk
Ecosystem structure
Arctic Trophic Level Index
Habitat extent and Change in Quality
Arctic Land Cover Change Index
Trends in Extent Biomes, Habitats and Ecosystems
√
√
√
√
√
√
√
√
Arctic Habitat Fragmentation Index
Trends in Patch Size Distribution of Habitats
√
√
√
√
Ecosystem Function and Services
Trends in Extent, Frequency, Intensity and Distribution
of Natural Disturbances
√
√
Trends in Phenology
Trends in Decomposition Rates
Human-health and Well-being
Arctic Human Well-being Index
Trends in Availability of Biodiversity of Traditional Food
and Medicine
√
X
X
X
X
√
X
√
Trends in Use of Traditional Knowledge in Research,
Monitoring and Management
√
√
Trends in Incidence of Pathogens and Parasites in
Wildlife
√
√
1129
38
1130
1131
1132
1133
1134
1135
Figure 3.1. Conceptual visualisation of the TEMG monitoring scheme. Monitoring efforts at the various levels (unbroken frames) are integrated
through modeling (blue arrows), and complemented with experimental research and monitoring efforts conducted outside the TEMG
monitoring scheme. Causal linkages (red arrows) can be established through experimental work, and on the larger scale inferred from detailed
data on the smaller scale. Monitoring outputs (green arrows) can be extracted on all levels, and feed into the assessment and decision-making
processes, ultimately also feeding back into the TEMG monitoring scheme (black arrows).
39
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
Figure 3.2. Overall conceptual model of the terrestrial biota showing the various compartments and their primary interactions.
40
1155
1156
1157
1158
1159
FOCAL
ECOSYSTEM
COMPONENT
ATTRIBUTE
PARAMETER
Number
1160
1161
1162
Abundance
Density
Spatial use
Distribution of
migratory herds
1163
1164
1165
1166
1167
Large
herbivores
Sex and age
structure
Demographics
1168
Mortality
1169
1170
1171
Health
1172
Disease
prevalence
Body fat
1173
1174
Genetics
Heterozygosity
1175
1176
1177
1178
Figure 3.3. The nested structure of the TEMG monitoring scheme, here exemplified by a large herbivore.
1179
1180
41
1181
4
Sampling Design
1182
4.1
Sampling Design Overview
1183
1184
4.1.1
Introduction to CBMP-Terrestrial Plan sampling design
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
The sampling domain for developing a cost effective experimental design for the CBMP-Terrestrial Plan
includes all of the area covered by the CAVM Team (2003) map (Figure 2.1) as described in Chapters 1
and 2. Across the vast CAVM area, tundra ecosystems change locally (with topography, soil conditions,
disturbance history, and local-scale, abiotic driving processes such as riverine or estuarine flooding and
slope seepage, ground ice processes, and snow effects), across watersheds and landscapes (with aspect,
elevation, exposure, snow phenology, distribution, condition and depth, hydrology, mineralogy of
bedrock and soil parent material), and across the circumpolar Arctic where vegetation physiognomy
(low shrub, dwarf shrub, herb) changes along climatically-defined bioclimatic zones (south to north, east
to west, and with elevation). Other factors that impact tundra vegetation composition, structure and
productivity include biogeographic histories, dominant bedrock, and unique interactions with drivers
such as rates and kinds of herbivory, pests and diseases, and various anthropogenic effects.
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
Capturing all of this variability in a randomized experimental design in an attempt to answer the
questions outlined in Chapter 3 is clearly impossible given the vast areas under consideration, poor
access, and limited resources. The TEMG conducted an inventory of long-term Arctic terrestrial
biodiversity monitoring assessment to understand current monitoring capacity. As a matter of
practicality, we have designed the sampling for the CBMP-Terrestrial Plan to take advantage of available
resources (existing research stations, mandated and regulatory monitoring conducted by many
government agencies and industry, community monitoring), and to reach out more broadly through
modeling and remote sensing techniques to achieve some degree of randomization of reported results.
Using this approach, the aim is to report valid and defensible assessments of terrestrial ecosystem
change in the circumpolar Arctic, by implementing a practical and sustainable system that optimizes the
use of all available resources and builds toward future harmonization of data collection.
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
The approach taken within the TEMG is ecosystemic at a range of scales from local to circumpolar
(Figure 4.1). To this end, question-based monitoring conducted at research stations will anchor the
program, and will be designed to link measured changes in FECs, attributes, parameters and indicators
to measured changes in ecosystem drivers and processes to establish causal relationships for the
changes observed. Such long term installations can also be used to integrate the key components of the
CBMP-Terrestrial Plan (vegetation, mammals, birds, and arthropods) and to draw functional connections
among these components and the physical environment by, as much as possible, co-locating monitoring
measurements of all components at integrated, long term monitoring sites. These local scale results at
research stations can be combined with broader scale monitoring (wide-ranging mammals, migratory
birds and remote sensing) to develop a coherent picture of Arctic biodiversity change, and an
understanding of the reasons for the changes reported (e.g. the presence of drivers including climate
42
1218
1219
change, sifts in species ranges including changes in pathogens and more southern species, land use
changes, and others).
1220
1221
1222
4.1.2
Interpreting the sampling design tables
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
Although there is a clear need to integrate monitoring across terrestrial components, this chapter lists
specific monitoring questions and sample design issues for each of the four main components of the
CBMP-Terrestrial Plan – tundra vegetation, mammals, birds and arthropods. For each component, we
recommend a series of essential and recommended attributes that should be monitored to contribute
to the program. Essential attributes are those components of the FECs that we recommend should be
measured at any given monitoring location to capture a minimum set of biodiversity information
relative to the focal ecosystem component under study. Recommended attributes may be measured at
some sites with additional capacity and intensity of design in order to provide more comprehensive
information on the nature of the observed changes and to better understand processes driving
biological change. We also distinguish between basic and advanced protocols – where basic protocols
are simple methods that could be used by sites with minimum monitoring capacity to provide
scientifically robust results, and advanced protocols are those that require a higher level of scientific
expertise and oversight for proper application.
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
Some additional methods have generally insufficient power to provide scientifically robust answers to
management question, due to low accuracy, biases, or lack of systematic sampling. However, they can
provide useful supporting information to conclusions based on data derived using basic and advanced
methods. Simplified methods will be common in opportunistic data collection, TK data, community
based monitoring, short-term surveys and check-list based surveys. In some cases, opportunistic data
collection may be outside the scope of the CBMP-Terrestrial Plan, but may provide valuable information
where knowledge gaps exist, or where future monitoring is required. For example, monitoring
immigrating non-native species at initial low densities may be effort-intensive, but opportunistic data
collection within or just beyond Arctic boundaries may be helpful in identifying sites that may be
affected or at greater risk in the near future.
1246
1247
1248
4.1.3
1249
1250
1251
Metadata collected at the site should be consistent with metadata collection standards. Along with the
target data suggested in the tables in Chapter 4 and the site establishment metadata, this metadata
should be recorded with each monitoring event.
1252

Sampling Metadata
Date of monitoring event
43





1253
1254
1255
1256
1257
1258
Location name
Name(s) of monitors
Experience/capacity of monitors and impact on data quality (e.g. taxonomic expertise)
Time of day
Weather
Description of the handling, sharing and archiving of data and metadata is described in Chapter 5.
1259
1260
4.2
Vegetation
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
4.2.0 Introduction
The vegetation component of the CBMP-Terrestrial Plan has, as a fundamental goal, to monitor and
report on important changes in Arctic/tundra vegetation. Vegetation is essential to the terrestrial
component of tundra ecosystems in that it forms the habitat structures and resources that support the
other elements of tundra ecosystems considered under the CBMP-Terrestrial Plan – namely mammals,
birds and arthropods. In turn, the composition, structure and composition of the tundra vegetation that
makes up these habitat attributes is largely determined by the direct and indirect influences of key
biotic and abiotic drivers. From a monitoring design perspective then, question-based monitoring at long
term sites should be established to enable spatial and temporal integration of monitoring results so that
causative relationships among abiotic and biotic components can be established, measured and
reported. These relationships may also help inform changes reported from other types of mammal, bird
and arthropod monitoring.
1273
1274
4.2.1
Vegetation sampling approach and design issues
1275
4.2.1.1 Vegetation monitoring questions
1276
1277
1278
1279
1280
Development of the CBMP-Terrestrial Plan is guided by the broad set of priority management
questions/issues presented in Chapter 3, and a conceptual understanding of key vegetation attributes
(Figure 4.1) including specific examples of vegetation composition, structure, function, and drivers which
were selected through an ecosystem-based conceptual modeling process. Priority vegetation-based
monitoring questions that guided the vegetation monitoring scheme are:
1281
1282
1283
1284
1285
1286
1287
1. How are the diversity, abundance, productivity, composition, location and pattern of vegetation
species and communities changing across the circumpolar Arctic? Specifically;
a. How is vegetation changing along major physiognomic ecotones, e.g., treeline,
shrubline?
b. How and where are the productivity, local abundance, and distribution of Arctic shrubs
changing, and how is this affecting ecosystem function and biodiversity?
44
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
2. How are important foods and forage vegetation species/communities changing?
a. How is quality and availability of forage changing in key areas?
b. How are plant-based subsistence foods changing?
3. Where are the locations of high native plant species richness and other important habitats and
how are these changing?
a. What is the pattern of native plant species richness across the landscape?
b. How are the composition, structure, distribution and extent of landscapes changing?
4. Where and how abundant are non-native plant species on the landscape and how are they
changing?
5. How are the distribution, status and extent of plant species of conservation concern changing?
a. How is plant productivity changing across the Arctic? Are there hot spots of plant
productivity?
6. How is vegetation phenology changing across the Arctic?
7. How are soil fungal (mycorrhiza and decomposers) composition and relative abundance
changing and what is the impact on soil ecosystem function, structure and stability?
1309
4.2.1.2 Vegetation Conceptual Model in relation to monitoring
1310
1311
1312
1313
1314
The vegetation conceptual model (Fig 4.1) was developed by the vegetation expert teams as described
in Chapter 3. The model illustrates the scaled conceptualization of vegetation biodiversity from species
and life form diversity operating at local scales, to changes in communities and focal species operating
at landscape scales, to changes in vegetation types or landscapes operating at regional scales, to
changes in regions operating at the scale of the entire Arctic.
1315
4.2.1.3 Potential contributors to the vegetation monitoring scheme
1316
1317
A partial list of stations, networks and monitoring groups that could contribute to the CBMP-Terrestrial
Plan vegetation component includes:
1318
1319
 the network of Arctic field stations (SCANNET/INTERACT) and other seasonal or permanently
1320
 the International Tundra and Taiga Experiment (ITEX) network;
1321
1322
 industry/agency local and regional cumulative effects monitoring associated with resource
1323
 national parks and other protected areas;
manned research and monitoring installations;
development;
45
1324
 PPS Arctic network;
1325
1326
 on-going vegetation research and monitoring conducted by governments, academia, non-
1327
 historical vegetation research, monitoring or inventory sites and data;
1328
 other on-going research and monitoring where vegetation monitoring could be co-located, and;
1329
1330
 Arctic community members, including TK holders, who could contribute to existing or new
governmental organizations, and community groups;
community-based monitoring schemes;
1331
1332
1333
1334
These sources represent a wide variety of potentially-useful monitoring information that ranges from
repeated, protocol-based monitoring, to station-based research and monitoring, to industry and
community monitoring. It will be a major challenge to organize all of this potential information to create
a coherent and repeatable assessment of Arctic vegetation change.
1335
4.2.1.4 Vegetation design principles and components
1336
1337
1338
1339
The CBMP-Terrestrial Plan will utilize an initial stratification of the circumpolar Arctic into the highArctic, low-Arctic, and alpine areas of the Subarctic (see Definitions). Vegetation based sampling,
analyses, and reporting will be stratified by Bioclimatic Subzones as delineated by the Circumpolar Arctic
Vegetation Map (CAVM; Figure 2.1).
1340
1341
The CBMP-Terrestrial Plan will maximize the use of existing monitoring investments through efficient,
effective designs integrated across multiple scales by applying the following approaches:
1342
1343
1344
i)
establish intensive monitoring of both essential and recommended field monitoring
attributes at a core network of long-term, integrated monitoring sites including both basic
and advanced protocols;
1345
1346
1347
ii)
for the essential attributes, establish a core set of basic field monitoring protocols to be
implemented as broadly as possible through engagement and collaboration with the
monitoring schemes listed above
1348
1349
1350
iii)
conduct spatial up-scaling from local to broader geographic scales through (a) modeling, and
(b) integration of field or high resolution spatial data with broader scale, coarser-resolution
remote sensing.
1352
i)
Ground-based (or remote-sensing), question/cause-and-effect, intensive sampling
1353
1354
1355
What: The CBMP-Terrestrial Plan recommends intensive monitoring of both essential and
recommended attributes at a core network of long-term, integrated monitoring stations and other
sites as capacity allows. Monitoring will include both the core set of basic parameters as well
1351
46
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
advanced parameters that can help to elucidate cause and effect relationships. Ideally there should
be a minimum of three intensive monitoring stations within each CAVM bioclimatic subzone (Fig.
2.1) to allow for spatial variability in tundra change. Monitoring study design should include the
range of tundra ecosystems, and be statistically valid with sufficient power at the site level. The
design should include, for example, stratified, randomly placed long-term plots and transects as
capacity allows. It is understood that all ground stations will not meet these specifications through
current monitoring although some will, and these can stand as a reference sites as monitoring
capacity expands (see Box 4A), and as existing stations re-implement their monitoring programs.
Monitoring related to other terrestrial biotic groups (mammals, birds, arthropods) as well as
relevant abiotic factors/physical drivers necessary for improving understanding of processes driving
biodiversity change should be conducted at these stations in an integrated fashion. The CBMPTerrestrial Plan also recommends deploying high resolution, remote sensing tools to address
detailed or targeted questions, where appropriate and required. Specific sampling parameters are
listed in section 4.2. Intensive monitoring will serve many purposes including:
1370

understand cause-and-effect relationships and specific process-based monitoring questions
1371

training and validation of multi-scale remote sensing
1372

contribute to status and trend (surveillance), extensive sampling
1373

modeling observed changes and relationships from local to broader geographic scales
1374
1375
Who: Research facilities including participating INTERACT/SCANNET sites, ITEX sites, GLORIA sites,
PPS sites, protected areas and other partners as capacity allows
1376
1377
Scale of analysis: local to watershed. Locally derived results can be extended to broader geographic
regions through integration with remote sensing and with extensive monitoring (see Box 4A).
1378
Where: An inventory showing the locations of potential contributors is shown in Figure A1.
1379
1380
ii)
Ground-based, status and trend , extensive sampling
1381
1382
1383
1384
1385
What: Extensive monitoring generally employs a less rigorous set of monitoring methods and
sample sites are not organized to answer questions around key drivers and identifying the reasons
for change in the FECs. Extensive sampling conducted by a range of collaborating partners greatly
increases the geographic range over which the CBMP-Terrestrial Plan can detect changes. Extensive
monitoring recommended by the CBMP-Terrestrial Plan includes:
1386

Implementation of an essential set of basic monitoring attributes
1387

Targeted sampling for rare and invasive species and vegetation phenology,
47
1388
1389

Use and expansion of community based monitoring networks (e.g., invasive species,
phenology, red-listed species, and other targeted monitoring)
1390

Validation of pan-Arctic remote sensing models
1391
Specific sampling parameters are listed in section 4.2.
1392
1393
1394
Who: Current and potential Arctic vegetation monitoring contributors including governments at
various scales, industry partners, academia, protected area monitoring practitioners, and
communities.
1395
Scale of Analysis: Regional to Pan-Arctic.
1396
1397
1398
1399
Where: Use remote sensing to understand representativeness of all sample locations within each
stratum. Compare these sites/facilities and their geographic and thematic distributions and propose
new sample locations to fill critical gaps in relation to bioclimatic subzone/strata and national
boundaries.
1400
iii)
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
What: Monitoring Arctic vegetation with ground-based sampling and a number of remote sensing
platforms collected at a variety of spatial (cm-km) and temporal scales (Figure A1) in an integrated
manner offers an opportunity to expand the results of ground based sampling to the complete panArctic area for a number of focal ecosystem attributes and related drivers. Using these data,
functional relationships between abiotic drivers and biotic response measures developed at
experimental sites can be extrapolated to broader areas using the range of available remote sensing
platforms. Fine spatial resolution remote sensing data and ground sampling can also be combined to
better interpret coarse resolution (1km) satellite data so that pan-Arctic classifications are possible.
Remote sensing derived information on weather, climate, sea ice, and the coastal marine
environment can also support terrestrial biodiversity monitoring modeling activities. Remote
sensing technologies continue to rapidly evolve and the CBMP-Terrestrial Plan aims to take
advantages of these emerging technologies when possible and where appropriate
1413
1414
1415
1416
1417
1418
1419
1420
Synoptic, time series mapping of measurable attributes and abiotic drivers will be used to
understand both broad-scale cause and effect relationships and to detect general trends. We aim to
collect boundary information (explanatory variables) to initialize models. As much as possible, the
CBMP-Terrestrial Plan has recommended the use of free or nearly free imagery to facilitate
sustainable remote sensing product creation. We recommend the use and development of Digital
Elevation Models (DEMs) as critical to interpretation of remote sensing products and other data.
The CBMP-Terrestrial Plan recommends taking advantage of evolving technologies in remote
sensing through an adaptive approach. Specific sampling parameters are listed in section 4.2.
1421
1422
Who: Current and potential Arctic vegetation monitoring contributors with appropriate expertise.
This may involve teams of sub-national, national and international remote sensing specialists
Remote-sensing, mid- to low-resolution, status and trend extensive sampling
48
1423
1424
working together to develop analyses that support different jurisdictions and taken together can
represent the whole Arctic area.
1425
Scale of Analysis: Regional to Pan-Arctic.
1426
1427
Where: Remote sensing approaches can be applied across the entire circumpolar Arctic, or sampled
using stratified random approaches.
1428
4.2.1.5 Existing capacity to deliver the CBMP-Terrestrial Plan
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
In addition to opportunities that may arise to conduct sampling and observations, collect data, and
conduct monitoring as part of collaborations with international governments, academic institutions,
museums and herbaria, Aboriginal partners, and Arctic communities, monitoring capacity already exists
in the form of long-term programs, infrastructure, and international initiatives (see Appendix A:
Metadata and Sampling Coverage Maps). The TEMG is compiling a database of facilities and long-term
monitoring programs based out of all of nine circumpolar regions (Norway, Finland, Sweden, Russia,
Iceland, Greenland and the Faroe Islands [Denmark], Canada and the United States [Alaska]), and
including monitoring sites from more southern alpine regions in the Subarctic, to Svalbard and the High
Arctic (Appendix A). The comprehensive database includes information on the type of program, location,
and on the components that are monitored or the type of data that is collected (including contaminants,
soils, fauna, flora, and data such as observations of components of importance to Arctic communities
and traditional knowledge). The data will become part of the Polar Data Catalogue
(http://www.polardata.ca/). Integrated monitoring as part of the CBMP-Terrestrial Plan can build on
existing capacity as part of these programs.
1443
1444
1445
1446
1447
1448
Other types of contributions that can facilitate and complement long-term monitoring already exist
through programs that use remote sensing (see Appendix B: What can we monitor with satellite data in
the Arctic?). Data obtained through such programs can provide invaluable information on land cover,
climate, and how the landscape is changing, and will be indispensable to complement and extend the
coverage of data-collection through monitoring as proposed in the CBMP-Terrestrial Plan for vegetation
and other biotic groups.
1449
1450
4.2.2
Sampling protocols
1451
4.2.2.1 FECs, Essential Attributes, and Parameter summary
1452
1453
1454
1455
1456
1457
A summary list of FECs, essential and recommend attributes and monitoring parameters that were
developed through the TEMG workshop process are listed in Tables 4.1 (Essential Attributes) and 4.2
(Recommended Attributes). Each FEC may have one or more attributes, and attributes may have a
number of monitoring parameters. Both plot scale and remotely sensed parameters are listed. The
tables also suggest a sampling methodology, classify the attribute as advanced or basic, and provide a
temporal frequency for the sampling. The attributes listed in the tables are the heart of the CBMP49
1458
1459
1460
1461
Terrestrial Plan, and their implementation according to the design principles outlined in this chapter
would provide a comprehensive assessment of tundra vegetation change in a given sample area. The
proposed protocols can be applied to answer a number of different monitoring questions, depending on
the study design, yet generate standardized information that can be integrated at broader scales.
1462
1463
4.2.3
1464
1465
The following plot level information should be collected when establishing a monitoring site (when
relevant and where possible):
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483










Site establishment data
Site latitude and longitude
Description of topographic setting
Elevation
Aspect
Slope angle at plot locations
Local hydrology (proximity to streams, rivers, lakes and ocean)
Soil parent material, slope, aspect
Soil description including
o Substrate lithology
o Depth and homogeneity of soils across the study area
o Soil total carbon and nitrogen content (if possible)
o Patterned ground type
o Soil class
Depth of active layer
Plot digital photographs should be taken at every plot, following standardized procedures
The following information landscape and regional-level information is required to effectively interpret
biodiversity information. This information should be derived from existing or new remote sensing
products.
1484
1485
1486


1487
1488
4.2.4
1489
1490
1491
Plot photographs must be accurately labeled and archived so that plot data is associated with the photo.
Where species identification is required, for example to complete a plot species list, identify an
unknown species or document a rare plant species, standardized procedures should be followed.
Hydrology
Topography using Digital Elevation Models (DEMs)
Vegetation sample processing, archiving and DNA analysis
50
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
Collection of representative plot vegetation species samples, also known as vouchers, when first
establishing a plot is recommended where capacity to process and store the monitoring samples is
available. When capacity is not available, collection of vouchers for unknown species is recommended
to facilitate identification. At a minimum, high resolution digital photographs of the species in question
should be taken. To preserve the integrity of the plot, voucher collection should occur outside the plot. .
Careful study of specimens under a dissecting microscope is often required to properly identify an
unknown plant species. To document a rare plant species, voucher specimen could be collected
provided the local rare plant population has more than 100 individuals and the specimen will be
donated to a Herbarium.. Plot establishment data should be shared and integrated into national and
international efforts to establish an international database of vegetation plots to support research and
decision-making, such as the International Arctic Vegetation Database (CAFF 2013).
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
Voucher sample collections should follow best practices and standardized procedures for collecting,
pressing, rapidly drying, storage and shipping, identification, mounting and archiving. Voucher
specimens should be deposited with an appropriate herbarium, such as at a museum or university,
where it will be mounted and archived. For both specimen photographs and voucher samples, it is
essential to ensure the specimen are appropriately labeled with key information which should include
name of the plant, location of collection/monitoring event, habitat, associated species collector,
collection number, collection date, and the name of the person who identified the plant. Specimen
identification should be verified by an expert , as required. These records are then available for future
reference or DNA analysis, as required. Standardized procedures for preparation of vegetation samples
for DNA analysis are available (Saarela 2011). The samples can be integrated into international efforts
to develop a DNA database for polar regions (International Barcode of Life Project, 2011).
1514
1515
1516
1517
1518
1519
1520
1521
1522
Standardized taxonomies should be used for species identification. The TEMG recommends using the
Annotated Checklist of the Panarctic Flora –Vascular Plants (Elven 2011 [onwards]) for describing
taxonomies, in conjunction with available volumes of the Flora of North America series. A project is
currently underway to develop a new Arctic Flora of Canada and Alaska (Gillespie, et al. 2012
[onwards]), which will eventually serve as the standard reference for Arctic plant taxonomy in the
region. The proposed CAFF Arctic Red List species could serve as the basis for identification of rare
species (CAFF, in press). Further, the CAFF Flora Group has recommended development of a
standardized set of protocols for monitoring Red Listed plants throughout the Arctic (Gillespie, et al.
2012).
1523
1524
1525
4.2.5
DNA analysis of fungi from soil samples at the vegetation plots
1526
1527
1528
Collection of soil samples for DNA analysis is essential for tracking changes in soil fungal (mycorrhiza and
decomposers) composition and relative abundance. Collection of the soil samples for DNA-analysis for
fungi should be conducted at the same time as the vegetation is sampled. The analysis will identify and
51
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
be used to assess the abundance of fungal taxa, hence also measure species richness and species
composition. The functional properties of the fungi, hence effects on ecosystem processes, may be
possible to infer from linking identified soil fungi to documented life-forms, such as different mycorrhizal
forms, saprotrophytic and parasitic fungi (e.g. Kubartová, et al. 2012). The sampling may be coordinated
with the collection of soil cores taken for DNA-barcoding of soil animals (4.5.2 and 4.5.3). Sampling
should follow best practice and standardized protocols for sampling, processing and analysis of fungal
DNA, procedures that quickly are developed and improved (Lindahl, et al. 2013). For each site, 10 soil
cores are recommended to provide a measure of the more abundant species and their frequencies
(each with 50 ml soil, minimum sampling is the A-horizon, preferably down to 5 cm) and directly in the
field conserved by being put into 70% ethanol or CTAB, allowing for long-term storage without
breakdown of DNA at storage above zero degrees, or if possible frozen (Timling, et al. 2012). Fungal
DNA-barcoding will be accomplished using high throughput sequencing approaches with fungal-specific
rDNA primers (Ihrmark, et al. 2012; Lindahl, et al. 2013). Even though environmental barcoding will not
presently enable all taxa to be taxonomically identified, all distinguished DNA sequences, irrespective of
whether they have been identified or not, will enable monitoring in space and time. Initially unidentified
sequences can be grouped phylogenetically and will over time increasingly be identified. The analyzed
samples should be integrated into international efforts to develop a DNA database for Polar Regions
(International Barcode of Life Project 2011; Polar Barcode of Life 2010) or used for other kinds of
research.
1548
52
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
BOX 4A. From Local Scale Monitoring to the Circumpolar Arctic – An Example for the Vegetation
Biomass Indicator
A key premise of the CBMP-Terrestrial Plan design is that the results of local scale, question-based
monitoring can be projected broadly across the Arctic, through the development of remote-sensing
based models that extrapolate causative relationships derived locally to a wide area using a similar,
driver-indicator relationship. Vegetation biomass is one attribute in the CBMP-Terrestrial Plan that may
be increasing both locally (Gauthier, et al. 2011; Hudson and Henry 2010), and across broad areas of the
Arctic tundra (CAFF-ABT 2010; Gensuo, et al. 2009). Vegetation biomass has also been used to predict
the quality of habitat factors such as caribou forage during the post-calving period (Chen, et al. 2009b),
and thus links to other CBMP-Terrestrial Plan components.
Vegetation biomass is measured in quadrats of known area, through destructive sampling of above- and
below-ground plant components (species or species group), field-weighed to estimate total fresh
weights of all components, and developing fresh weight-dry weight relationships from sub-samples
dried in a field laboratory (Bean, et al. 2003; Jefferies, et al. 2008). Biomass can also be calculated based
on community composition and height of representative plants. Sample sites are selected to be
relatively uniform in vegetation composition and structure, and vegetation dry weight/m2 is estimated.
Sampling is repeated to account for spatial variability within a site, and estimates are linked to the
imagery through regression analysis with the different radiometric bands and indices in the imagery,
often scaling through high resolution to lower scales of resolution for broader coverage. Sampling is
generally conducted across the range of tundra ecosystems (e.g., tall shrub, low shrub-herb, dwarf shrub
herb, herb, herb-moss lichen, and rock-lichen) to account for variability in vegetation biomass across a
tundra landscape, and to facilitate scaling-up from the destructive ground sampling to high, medium and
low resolution satellite imagery.
The CBMP-Terrestrial Plan proposes that biomass sampling occurs concurrently in areas where abiotic
drivers such as soil and air temperatures, wind, depth of thaw, nutrient availability, and snow
conditions, are monitored. Causative relationships are interpreted between biomass change and these
drivers. Recent work has shown that vegetation biomass change varies across the landscape, and is
greatest in moist or seepage-affected tundra ecosystems where soil moisture and nutrients are
sufficient to support the increased productivity made possible by increasing summer warmth
(Elmendorf, et al. 2012). Models would be parameterized for each ecosystem (or ecosystem groups)
with similar driving ecosystem processes and vegetation biomass production. Remote sensing models
predicting changes in vegetation biomass could be developed that use the same causative drivers and
relationships identified in the local scale modeling, and then applied widely using the imagery. Model
prediction can be refined using non-destructive, photographic methods (Chen, et al. 2009a; Chen, et al.
2010).
Correlating localized ground observations to remote sensing and other regional data can achieve broad
coverage – a critical consideration in the vast and remote Arctic. Options for extrapolation to remote
sensing imagery include a broad census of the circumpolar Arctic, imagery transects along climatic
gradients, or imagery tiles sampled according to a stratified random design. Reliable models can be
extrapolated in time as well as space. Future conditions of vegetation biomass, or other
vegetation/landscape indicators (vegetation functional groups, active layers, and caribou forage
production) can be predicted for a range of climate scenarios – a very useful tool for anticipating change
and
supporting
proactive
management
decision
making.
53
1592
1593
1594
Fig. 4.1. The Arctic vegetation monitoring conceptual model showing key drivers, attributes and geographic scales of biodiversity and analysis.
1595
54
1596
All plants (Species, life form groups and
associations/ communities)
All vegetation components
Composition;
Horizontal &
vertical structure;
abundance
Essential
Percent cover by
life form
Local
Canopy gap
Local
Percent cover by
species
Local
Alpha Diversity
55
Point
intercept/line
point intercept
US Bureau of
Land
Management
Basic
5 years
Advanced
5 years
Point
intercept/line
point intercept
Advanced
5 years
Local
Plot species list
Basic
5 years
Local
DNA soil sampling
Advanced
5 years
Local
Plot photograph
Basic
5 years
COMMENTS
TEMPORAL
RECURRENCE
PROTOCOL
COMPLEXITY
METHOD
SCALE
PARAMETER
PRIORITY
ATTRIBUTE
FOCAL ECOSYSTEM
COMPONENT
Table 4.1. List of focal ecosystem components for vegetation (FECs: major biodiversity elements), their attributes (compositional, structural,
and functional aspects), monitoring priority of attributes, parameters of attributes (individual measures/methods to quantify attributes),
geographic scale, method (monitoring technical approach or reference to methods), protocol complexity (basic or advanced) and temporal
recurrence (how frequently monitoring should be conducted).
Area (amount),
location, spatial
pattern,
composition,
abundance
Productivity
Essential
Essential
Height of
representative life
forms
Local
Mean of 5
representative
plants
Basic
5 years
Beta/gamma
diversity
Regional/
pan-Arctic
Low resolution
remote sensing:
MODIS
Basic
Annual
Beta/gamma
diversity
Landscape/
regional
Med resolution
remote sensing:
Landsat
Basic
10 years
Beta/gamma
diversity
Landscape
High resolution
remote sensing
(e.g. Quickbird)
Advanced
As req.
Landscape/
regional
Remote sensing
Basic
5 years
Remote sensing
Basic
5 years
Remote sensing
Basic
5 years
Remote sensing
Basic
Annual
Local
Harvest sampling;
clip plots
(destructive)
Basic
5 years
Local
Photo digital
photograph
classification
(non-destructive)
Advanced
5 years
Pattern:
fragmentation/
connectivity
Area: total area by
community
Distribution of
communities
NDVI/ FPAR/ LAI/
EVI
Landscape/
regional
Landscape/
regional
Landscape/
regional
Aboveground
Biomass
Aboveground
Biomass
56
Phenology
Essential
Total biomass
Local
Harvest and root
clipping
(destructive)
Advanced
5 years
Biomass
Landscape/
regional
Remote sensing
Advanced
Annual
Basic
As req.
Basic
Annual
Basic
Annual
TK: Harvest
observations
related to food
abundance
Direct
observation
Direct
observation
Direct
observation
Biomass
Local
Date of leaf-out
(species)
Local (plot)
Date of flowering
(species)
Local (plot)
Date of senescence
(species)
Local (plot)
Direct
observation
Basic
Annual
Date of senescence
(species)
Local
TK:
Morphological
observation
Advanced
Annual
Presence/ absence;
number of
individuals
/population size
Local
Direct count
observations
Basic
10 year
Rare species, species
of concern
Species of special interest
Species
abundance/
occurrence/
location
Essential
57
Rare species, species of concern
Genetic diversity;
neutral diversity
Population viability
Health/ Pathogen
load (disease,
parasites, insects)
Location and
spatial pattern
Recommended
Recommended
Recommended
Recommended
Gene flow,
effective
population size,
migration rate and
directionality,
population growth
rates, bottlenecks;
evolutionary
potential
Regional
DNA analysis
Advanced
As req.
How many
populations,
locations (metapopulations)
Landscape
Direct
observation
Basic
As req.
Abundance of
individuals within a
populations over
time
Local
Direct
observation
Basic
As req.
Presence/ absence
of population with
condition
Local
Direct
observation
Basic
As req.
% of population
with condition
Local
Direct
observation
Basic
As req.
Community
observed changes
in plant health
Local
Direct
observation
basic
As req.
Pattern:
fragmentation/
connectivity
Landscape
Remote sensing
Basic
5 years
58
Non-native species
Area: total area by
community
Distribution of
communities
Abundance/
occurrence/
location
Essential
Spatial pattern
Essential
Non-native Species
Health (pathogens
and disease,
Recommended
reduced resilience);
population viability
Phenology
Recommended
Landscape
Remote sensing
Basic
5 years
Landscape
Remote sensing
Basic
5 years
Basic
As req.
Advanced
As req.
Direct count
observations
Direct count
observations
Presence/ absence
Local
Population size
Local
Extent
Landscape
Remote sensing
Advanced
As req.
Presence/ absence
of population with
condition
Local
Direct
observation
Basic
As req.
Basic
As req.
Basic
Annual
% of population
with condition
Date of leaf-out
(species)
Local
Local (plot)
Direct
observation
Direct
observation
Date of leaf-out
Landscape/
regional
Remote sensing
Basic
Annual
Date of flowering
(species)
Local (plot)
Direct
observation
Basic
Annual
Date of senescence
(species)
Local (plot)
Direct
observation
Basic
Annual
Date of senescence
Landscape/
regional
Remote sensing
Basic
Annual
59
Recommended
Gene flow,
effective
population size,
migration rate and
directionality,
population growth
rates, bottlenecks;
evolutionary
potential
Food/ forage
species
composition,
abundance and
occurrence/
location
Essential
See above
Food/ forage
species
productivity/
biomass
Essential
See above
Genetic diversity
Regional
DNA analysis
Advanced
As req.
Species Mix
Local
TK; direct
observation
Basic
As req.
Size-distribution
Local (plot)
TK; direct
observation
Basic
As req.
Local (plot)
Phyto-chemical
analysis
(Laboratory
analysis)
Advanced
As req.
Food/ forage species
Food/ forage species
Food/ forage
species nutrient
content
Essential
Palatability;
secondary
compounds
60
Food/ forage
species phenology
Date of leaf-out
(species)
Local (plot)
Direct
observation
Basic
Annual
Date of leaf-out
Landscape/
regional
Remote sensing
Basic
Annual
Date of flowering
(species)
Local (plot)
Direct
observation
Basic
Annual
Date of senescence
(species)
Local (plot)
Direct
observation
Basic
Annual
Landscape/
regional
Remote sensing
Basic
Annual
Local
TK:
Morphological
observation
Advanced
Annual
Aboveground
Biomass
Local
Harvest sampling;
clip plots
(destructive)
Basic
5 years
Presence/ absence
of species with
condition
Local
Direct
observation
Advanced
As req.
% of pop with
condition
Local
Direct
observation
Advanced
As req.
Community
observed changes
in plant health
Local
Direct
observation
Basic
As req.
Essential
Date of senescence
Food/ forage species
Productivity,
biomass
Health/ Pathogen
load (disease,
parasites, insects)
Recommended
Recommended
61
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
4.3
Birds
The goal for avian monitoring is to track and report on changes in bird abundance and distribution in
relation to biotic and abiotic drivers, and monitor and report how these changes may affect other
functional groups in the ecosystem.
The ecosystem approach design in relation to birds will enable spatial and temporal integration of
monitoring results to establish, measure, and report on causative interrelationships among abiotic and
biotic components. Identifying links among such abiotic and biotic components, and relationships
between these components and changes in avian populations may also provide a basis to understand
changes reported from other components included in the vegetation, mammal and arthropod
monitoring sections.
The CBMP-Terrestrial Plan establishes an important aim from a management perspective: to maintain
the current levels of biological diversity in the Arctic. This includes enhancing the conservation status of
populations showing evidence of declines caused by factors that are preventable. In relation to birds,
establishing baselines and acquiring data on the status of populations can be achieved by compiling
information on flyway population sizes, documenting the temporal changes in flyway populations, and
tracking the drivers implicated in causing the observed changes. These baselines and data may facilitate
the interpretation of trends so that improved management recommendations can be made to reverse
declines.
Avian flight enables migrants to exploit seasonal pulses of food in different parts of the globe to survive
and reproduce. Utilising the brief Arctic summer to raise their young, some of the most extreme longdistance migrants such as the Arctic tern travel to southern polar regions to exploit resources in the
Austral summer. Many (but not all) Arctic birds are long-distance migrants, mere visitors to a feeding
resource made available by the short summer melt. A few, such as the raven and ptarmigan, are
resident throughout the year. Hence, factors affecting the status and well-being of birds may occur on
the breeding areas in the Arctic or many thousands of miles away (in the Antarctic in the case of the
Arctic tern). These contrasting patterns result in great challenges to population monitoring, but also
great potential advantages. Species breeding at very low density in the Arctic (such as the shorebirds)
may aggregate in vast groups on their wintering grounds in temperate or tropical areas, where they can
be counted more effectively to track overall changes in population size rather than trying to track small
changes in highly variable local breeding densities. Species of particular significance for human
communities in the Arctic and elsewhere, such as important harvestable species like ducks and geese,
may be already very well monitored for their abundance and population trends because of their shared
cultural values outside of the Arctic. This may even be to the extent that there is good existing
knowledge over many years, as well as information on factors regulating and limiting those populations,
and their demographics, (e.g. annual survival rates and assessments of annual production of young, for
example based on age assessments amongst shot individuals gathered by hunters through so called
62
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
“wing surveys” or “tail surveys”)4. For non-migrant species, population size and change will have to be
assessed through sampling approaches at some stage during the year. Climate change may not only
affect the overall size of populations, but also their distributions, as the climate template that shapes
their habitat and food resources shift in time and space. It is therefore important to combine flyway
population monitoring with breeding avian community composition studies, an objective that can also
be achieved through sampling on the breeding grounds.
Not all avian species can be covered in a circumpolar monitoring programme at all stages of their life
cycle, so the challenge is to be able to achieve coverage of as many species as possible in relation to
reporting on parameters that will answer specific management questions in the future. This should be
done in a representative, but pragmatic and cost-effective way. Fortunately, there are very many ongoing monitoring mechanisms in existence. For example, the global waterbird monitoring coordinated
by Wetlands International (http://www.wetlands.org/ ) already attempts to make an annual midwinter
count of all species and undertakes a three year cycle of audits of the geographical flyways, size and
population trends of all waterbirds around the world. The quality and quantity of data varies between
regions, but these mechanisms are in place. For other bird groups, such as birds of prey, carnivores,
piscivores and passerines, the data-collection is less systematic, and we need to assess the best methods
of deriving annual indices of their numbers and how we might begin to track changes in their abundance
over time. This is especially important for the status of those bird species that provide insight into
ecosystem process or the functioning of such processes. For example, some species such as the snowy
owl and Pomarine skua, show major annual variations in distribution and abundance in response to prey
cycles. Small passerines, such as Lapland bunting may show similar fluctuations in relation to their
arthropod prey (such as moth larval abundance, which also have impacts on vegetation), which in turn
affect predators of small birds. However, for widespread and common species, such as snow buntings
which winter in remote areas where they are difficult to count, it may be more expedient to sample
breeding densities, abundance and breeding success at a range of different focal areas throughout the
Arctic.
Hence the shaping of a pan-Arctic terrestrial avian monitoring programme needs to identify the
monitoring needs for such a programme, establish the parameters that need to be collected to fulfil
those needs and, to some extent, select the most suitable species for monitoring, accepting that some
species present insurmountable problems with regard to their monitoring. The CBMP-Terrestrial Plan
recognises the potential to coordinate Arctic bird monitoring activities in a way never envisaged before,
combining the efforts of existing mechanisms with innovative means of collecting relevant data, using
4
Wing surveys or tail surveys: Harvested bird species provide opportunities to estimate the numbers and species,
age and sex composition of the harvest. Hunters participating in surveys submit one wing and/or the tail of bird
that they shoot during the hunting season; programs run by governments in collaboration with experts identify the
tissues to gather demographic and abundance data.
63
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
agreed best practices for dissemination at the pan-Arctic, regional and local scales, and via the CAFF
portals to a range of stakeholders and end users of the data.
1693
1694
1695
1696
1697
1698
1699
1700
1701
4.3.1 Avian monitoring questions and design issues
The CBMP-Terrestrial Plan is guided by the broad set of priority management questions/issues
presented in Chapter 3. However Arctic birds constitute a special case with regard to monitoring
populations and causes of change. Firstly, with few exceptions, Arctic-breeding birds are migratory and
causes of change in population sizes are often due to factors outside the Arctic, such as hunting,
development, habitat changes in wintering and staging areas, pollution and disturbance. Secondly, many
species have a patchy, but wide breeding distribution; hence, it is difficult to capture but a few
populations with a site-based approach, particularly given that the CBMP-Terrestrial Plan will be based
primarily on the existing station networks.
1702
1703
1704
1705
1706
1707
1708
Any strategy to monitor avian populations must recognise logistic limitations and prioritise accordingly.
Hence, monitoring effort should be concentrated on species with (i) keystone functions in Arctic
ecosystems, (ii) indicator species of particular value because of correlations with specific variables (e.g.
snowy owl and Pomarine skua in relation to lemming cycles), (iii) rare, threatened or rapidly declining
species, (iv) species of cultural or exploitative value to human communities (e.g. huntable species), (v)
flyway populations for which there are legal obligations (national or international) to monitor and (iv)
non-native species.
1709
1710
Traditional Ecological Knowledge is most relevant to include in this regard since knowledge holders
quickly will be able to assess potential changes within the environment. For instance, assessments can
The primary objectives are:
1. To estimate current size of Arctic bird populations and locate the best available information and
sources of annual data that would enable some assessment of the recent trends in flyway
population sizes.
2. To structure a future monitoring framework that would improve on and continue to provide
better data on overall population sizes for all flyways of all avian populations in the Arctic
3. To gather existing data on changes in annual survival and productivity of as many Arctic
breeding flyway populations as is possible and to begin to coordinate and standardize the
collection and collation of such data following the best available protocols to inform and
understand the reasons behind changes in overall numbers
4. For Arctic keystone species, to integrate the monitoring in a site-based ecosystem monitoring
system to understand how Arctic abiotic and biotic factors affect bird population abundances
and breeding success
5. To integrate the above into abiotic and biotic factors for monitoring that may affect Arctic birds
inside and outside the Arctic to facilitate the interpretation of changes, with particular reference
to providing informed knowledge to management agencies in the appropriate countries that
could effect change to improve the conservation status of species currently in unfavourable
status.
64
1711
1712
be conducted on unusual species spotted in new areas, or reporting can be included on locally-observed
declines on harvested or not harvested populations
1713
1714
1715
1716
The management questions related to birds comprises a two-tier approach. Many of the core questions
are related to a conceptual understanding of key attributes (Figure 4.2) including specific examples of
structure, function, and drivers which were selected via expert opinion through an ecosystem-based
conceptual modeling process.
1717
1718
1719
1720
1721
1722
1723
1724
However questions related to birds can also be connected to specific conservation issues. In this case,
more tailored monitoring follows. Where wild bird populations function in the human food supply chain,
there is a need to secure a long-term sustainable harvest, as well as fulfill information needs related to
reporting required under international (or national) obligations such as the Ramsar Convention,
Convention on Biological Diversity (CBD), Agreement on the Conservation of African-Eurasian Migratory
Waterbirds (AEWA), Migratory Birds Act, etc., as well as reporting on national and internationally redlisted species (partly related to the international obligations). The CBMP-Terrestrial Plan therefore
divides the “bird management questions” into two types:
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1) Questions that are focused on a conceptual understanding of key attributes related to birds.
This is the site-based integrated ecosystem monitoring approach, targeted to understand causal
relationships. Related questions to be addressed are:
- What and how are the primary biotic, abiotic and anthropogenic stressors influencing changes
in avian diversity and ecosystem function (within and outside the Arctic) and how are these
stressors changing?
- What are the implications of changes in stressors for birds and other species? (phenology,
structure, productivity)
- For those bird species of concern, are the factors affecting phenology, distribution and
abundance acting inside or outside of the Arctic?
- How are populations and communities changing?
- What can we do about negative trends (including related to food security)?
1742
1743
1744
1745
1746
1747
2) Questions that lead to a more tailored and species oriented approach. This is the overall
population monitoring approach, including monitoring conducted at staging or wintering sites
where birds congregate and the coverage is generally higher than in the Arctic. Related
questions to be addressed are:
65
1748
1749
1750
- What are the status (in terms of abundance, richness and diversity), trends and distributions of
the priority (as established above) Arctic avian species at the population flyway level?
Specifically:
1751
a. In a global perspective: Conventions like CBD and Ramsar
1752
b. In a Regional/ National perspective: For legislation
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
- Are the protected site networks living up to their intended criteria for bird species
conservation and protection?
- How many birds can be harvested?
- Where and how are populations and communities changing?
The two approaches are interlinked; for example, demographic parameters such as breeding success
collected in the wintering quarters can be related to changes in snow conditions in key breeding areas,
detected by a combination of local snow coverage measurements and remotely sensed data.
1763
1764
1765
4.3.2
Potential contributors to the avian monitoring scheme
1766
1767
In the interests of efficiency and effectiveness, it is essential to recognise the activities of many existing
mechanisms that already collate monitoring data relating to birds that breed in the Arctic.
1768
1769
1770
1771
1772
1773
Some of these sources of information are vital cornerstones to any future CBMP construction, since
many of these already deliver the results of monitoring data or analysis of such data at the flyway
population levels. Pre-eminent amongst these is the Wetlands International Waterbird Monitoring
Programme (http://www.wetlands.org/Whatwedo/tabid/55/Default.aspx), which globally monitors all
waterbird populations and provides a three year reporting cycle of population sizes, trends and the
reliability of the census data.
1774
1775
1776
1777
The Arctic Birds Breeding Conditions Survey (ABBCS: http://www.arcticbirds.net/) is a joint venture of
the International Wader Study Group and Wetlands International's Goose and Swan Specialist Groups,
which collates annual information on environmental conditions on the breeding grounds of Arctic
nesting birds.
1778
1779
1780
1781
For data on changes in abundance of non-waterbird avian species, there are a number of regional
schemes that monitoring winter bird abundance on the winter quarters, as for example the Christmas
Bird Count and Breeding Bird Surveys in Canada and the US, which generates annual abundance indices
for species not otherwise covered by annual surveys (http://birds.audubon.org/data-research).
66
1782
1783
Past and on-going information through subsistence monitoring programs must be used. Thus in some
countries information and reporting systems already exist , including TK monitoring.
1784
1785
1786
1787
1788
A regularly updated database presents syntheses of analyses of data on bird numbers and breeding
performance during the Arctic summer in relation to climatic, predatory and other relevant factors can
give insights into the ecological processes and drivers acting at wide scale, and also provide valuable
information for the conservation of sites and species. Other networks provide guidance on best practice
and monitoring protocols, for example:
1789
1790

The Arctic Shorebird Demographics Network Breeding Protocol
(http://www.manomet.org/arctic-shorebird-demographics-network)
1791

The ArcticWOLVES (http://www.cen.ulaval.ca/arcticwolves/index.html)
1792
1793

Some active field stations (http://www.zackenberg.dk/monitoring/biobasis/), such as the
Zeckenberg Research Station, for example (Box 4B below: http://www.zackenberg.dk/ )
1794
1795

Arctic Program for Regional and International Shorebird Monitoring (Arctic PRISM,
http://www.ec.gc.ca/reom-mbs/default.asp?lang=En&n=FC881C1B-1);
1796
1797
1798

International Waterbird Census (IWC,
http://www.wetlands.org/Whatwedo/Biodiversitywaterbirds/InternationalWaterbirdCensusI
WC/tabid/773/Default.aspx);
1799
1800

Northwest Territories/Nunavut Bird Checklist Survey (http://www.ec.gc.ca/reommbs/default.asp?lang=En&n=60E48D07-1);
1801

International Shorebird Surveys (ISS, http://www.pwrc.usgs.gov/iss/iss.html);
1802

Australasian Wader Studies Group (AWSG, http://www.awsg.org.au/);
1803
1804
1805

U. S. Fish and Wildlife Service and Canadian Wildlife Service Waterfowl and Breeding Bird
surveys (http://www.fws.gov/migratorybirds/NewsPublicationsReports.html;
http://ec.gc.ca/rcom-mbhr/default.asp?lang=En&n=762C28AB-1)
1806

Birdlife International (http://www.birdlife.org/ )
1807
1808

The Ornithological Council (based in the US, but supporting societies and networks in the
Americas and internationally: http://www.nmnh.si.edu/BIRDNET/orncounc/index.html )
1809
1810
1811
4.3.3
Avian conceptual model in relation to monitoring
1812
1813
1814
The avian conceptual model is provided in Figure 4.2. Birds as keystone consumers in Arctic ecosystems
are highly affected by the processes and drivers (biotic, abiotic and anthropogenic) that affect their food
base. For example, in common with mammalian herbivores, grazing herbivores (primarily geese) are
67
1815
1816
1817
1818
1819
1820
1821
1822
greatly influenced by the length of growing season and the climate template for graminoid production
upon which they depend for energy and nutrition (Dickey, et al. 2008; Madsen, et al. 2011). Likewise,
the many birds that consume the flush of invertebrates during the short summer season (such as the
grouse, waders and passerines) are also affected by climatic factors that shape the abundance of such
organisms (Bolduc, et al. 2013) . However, these same species are also affected by top-down control, for
instance through the influence of raptors and mammalian carnivores, which may shift between
alternative prey in response to differential prey availability, or other factors (Giroux, et al. 2012; Smith,
et al. 2010).
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
Human exploitation of populations, both within and outside the Arctic, may also have a major effect on
population trajectories. Furthermore, for many of the long distant migrant species, the major factors
affecting the abundance of avian species may operate outside the part of the annual cycle when the
birds are present in Arctic regions. For this reason, it is absolutely essential that in considering the
functional significance of specific avian species, monitoring of avian attributes is closely integrated into
those of other relevant taxa. Hence, if expansions in geese are causing cascade effects on vegetation,
such as snow geese grubbing of Hudson Bay lowlands (Abraham, et al. 2005; Jefferies, et al. 2006), as a
keystone avian species, it is vital that the botanical monitoring is closely integrated with that of the
geese (e.g. see Box 4C). Likewise if a species monitoring protocol is designed around reflecting changes
in key variables, such as snowy owl abundance, Arctic foxes and lemmings (Giroux, et al. 2012; Roth
2002; Schmidt, et al. 2012), it is essential that these elements are integrated into a cohesive monitoring
programme that includes all facets of the functional ecosystem components.
1835
1836
1837
4.3.4
Terrestrial avian monitoring design principles and components
1838
1839
1840
1841
1842
1843
1844
The terrestrial Arctic bird fauna has been grouped into functional groups consisting of: herbivores
(geese, swans, and ptarmigan), omnivores (ducks, cranes), insectivores (shorebirds, passerines) and
carnivores (raptors, owls, skuas, ravens). The CBMP-Terrestrial Plan specifically does not cover seabirds
and sea ducks, which are covered in the CBMP-Marine Plan. Some overlap may occur between the
CBMP-Terrestrial Plan and the CBMP-Freshwater Plan. The Freshwater plan includes all birds that can
have an effect to the freshwater ecosystem on a site-based level including divers and grebes. The CBMPFreshwater Plan does not divide bird species into functional groups as the Terrestrial Plan does.
1845
1846
1847
1848
1849
1850
1851
For all four functional groups, six common attributes have been selected for monitoring. The parameters
to be monitored, the drivers of change as well as methods and scale are largely the same for all
functional groups; however, with some deviations which are specified in Table 4.2. As mentioned in the
introduction to Chapter 4, the CBMP-Terrestrial Plan recommends a series of essential and
recommended attributes that should be monitored to contribute to the program. Based on criteria
developed from the management questions (e.g. “ecological relevance”, relevance for “ecosystem
services”, importance for “Arctic Peoples”, and relevance for “legislation based information needs”),
68
1852
1853
various experts have assisted the TEMG to categorize avian-related attributes during two Workshops
(Appendix C).
1854
The attributes and their overall priority are:
1855
1856
1857
1858
1859
1860
1861
1) Abundance. From an overall monitoring perspective, the key attribute is abundance from which
trends in population sizes can be inferred; for Arctic resident species, this has to be done on the Arctic
breeding grounds based on networks of monitoring sites, while for migratory species, a combination of
breeding bird monitoring and surveys outside the Arctic can be applied, dependent on the population in
question. For a wide range of species, the most efficient way to monitor trends in population size is by
standardized surveys on the staging or wintering grounds, in some cases supplemented by surveys of
birds on passage at migration hotspot areas. Essential
1862
1863
1864
1865
1866
1867
1868
2) Distribution. Birds are expected to rapidly shift breeding ranges northwards with ongoing climate
change. Due to fragmentary coverage in terms of site-based station networks, it will be difficult to
quantify the rate of change over wide areas. The terrestrial station network can be used to provide data
on detailed rates of settlement and ecosystem consequences. CBMP will promote and use/link to
software such as eBird, geo-referenced information for recording distribution changes which will to a
high degree be applicable for a citizen science approach as well as for expeditions visiting remote areas;
standards for recording will have to be developed. Essential
1869
1870
1871
1872
1873
1874
1875
1876
3) Demography. Monitoring trends in demographic parameters is important to assess causes behind
observed population trends, in order to provide the basis for management actions. Such monitoring for
instance can directly feed into inferences about the impacts of harvest on huntable populations. At local
scale, data on breeding output can be monitored in terms of nest success rates; at population level by
standardized surveys of the proportion of juveniles in the observed flocks on migration or staging or
even on the winter quarters. Survival rates can either be derived from population surveys (e.g. geese) or
by specific mark capture-recapture studies which are, however, in most cases costly in terms of manpower and effort. Essential
1877
1878
1879
1880
1881
1882
1883
1884
1885
4) Community structure. Monitoring the composition and diversity of bird communities can give a first
indication of ecosystem structure and habitat quality, e.g., the density, abundance and composition of
the predatory bird guild will reflect rodent cycle persistence. If collected in a standard way over a variety
of climatic gradients and habitats, the composition of communities can indicate general effects of
climate change. In the CBMP context it is regarded as a supplement to species-specific monitoring as
well as providing a regular measure of local biological diversity and insights into changing trophic
relationships. Community structure can be monitored indirectly from essential attributes such as
abundance and demography; where possible and feasible it can be monitored directly also.
Recommended
1886
1887
1888
5) Health. With climate change, zoonoses are expected to become more prevalent in Arctic birds which
may affect the health of populations; in some species, the combined effects of climate change, zoonoses
and contaminant load may aggravate the impacts. Furthermore, since most species are migratory, birds
69
1889
1890
1891
may increasingly be a pathway for the transmission of vectors to Arctic ecosystem and human
populations. Prevalence and impacts of zoonoses can be investigated at field stations or specific studies
with programs for capturing birds for ringing. Recommended
1892
1893
1894
1895
1896
1897
6) Body condition. Body condition is a measure of the fitness of an organism at a given time and state.
Monitoring trends in body condition of birds in a standardized way can provide useful information that
can be related to the health of a population and can be linked to changes in the environment.
Monitoring of body condition can be carried out at field stations or part of specific studies where
standardized capture of birds or field observations of body condition indexes are performed.
Recommended
1898
1899
1900
4.3.5
Monitoring on non-breeding grounds
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
For many migratory species that breed in the Arctic, particularly those travelling thousands of kilometers
and crossing several international jurisdictions (e.g. many with wintering grounds in southern
continents), monitoring within breeding grounds only provides information on a fraction of the yearly
cycle of these species. Identifying factors that may influence reproduction and survival, recruitment, and
changing abundance and distributions, must include monitoring during migration and overwintering
outside the Arctic. Fortunately, data on many species is collected systematically and/or opportunistically
as part of existing research efforts, international networks, and citizen science initiatives (see above and
Chapter 1). In addition to existing networks already mentioned in Section 4.3.2 above and in Chapter 1,
opportunities exist for knowledge exchange through additional groups already working throughout the
Americas, their partners, and their research and community outreach tools (e.g. MANOMET:
http://www.manomet.org/; Western Hemisphere Shorebird Network: http://www.whsrn.org; Cornell
Laboratory of Ornithology, http://www.birds.cornell.edu, and their tools such as eBird:
http://ebird.org; and Bird Studies Canada: http://www.bsc-eoc.org/). At a global scale, smaller focal
networks include partners conducting research or monitoring at least including some migratory Arctic
species (e.g. Global Raptor Information Network: http://www.globalraptors.org). Additional
information to track avian populations outside their breeding grounds may be obtained through bird
observatories (e.g. migrants) and banding offices (e.g. the Bird Banding Laboratory: http://www.bsceoc.org/; EURING: http://www.euring.org/index.html ).
1919
1920
1921
1922
1923
1924
1925
Monitoring species within and outside the Arctic can be facilitated by incorporating data derived from
technology-based tools that can complement observations and site-based studies (see Chapter 1 and
Chapter 6). Recent advances in satellite tracking technology and data loggers have facilitated the
collection of information including the location and type of activity of individuals (e.g. accelerometers,
temperature and pressure recorders), and coupled with remote sensing (Appendix B), such tools can
provide valuable data on natural history and distributions of species that are difficult to follow. In
addition, improved protocols and a growing body of knowledge to enable comparative studies of
70
1926
1927
1928
1929
1930
1931
genetics, trace elements, and stable isotope signatures, are expanding our knowledge on diet and
trophic levels, population connectivity, migratory routes, contaminant levels and sources, and the
conservation status of species (see Chapter 1 and 6). Together, using these technology-based tools can
greatly extend our potential for monitoring species within and outside the Arctic, complementing
censuses and focal studies on the wintering grounds and stop-over sites, and for providing insight into
some of the emerging threats to Arctic breeders.
1932
1933
1934
1935
4.3.6 Existing Capacity and future needs to deliver the CBMP-Terrestrial Plan
NOTE - To Come: Map with sites of intensive bird monitoring in the Arctic (divide into categories) – wait
for the progress with metadata table (see Appendix A).
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
Future monitoring needs must be related directly to management questions, but this in turn reflects
several different levels of requirements of knowledge and the necessity for a process to secure
adequate coverage. Hence, the first priority for a monitoring programme to cover all flyway populations
of Arctic breeding bird species is to review the existing available extent of monitoring programmes to
see to what extent the flyway populations are sufficiently covered to deliver (i) an assessment of
contemporary population size and (ii) whether this population is increasing, decreasing or stable. This
should be an immediate major priority in coming years, to synthesise the available knowledge on Arctic
breeding birds to produce a clear statement about the number of species that breed in the Arctic, their
current distribution and abundance and their trends in population change, with an assessment of the
reliability of the information upon which this is based. This synthesis will rely entirely on existing
monitoring mechanisms, but will include, in the short-term, an assessment of addition monitoring needs
to fill gaps in our current ability to deliver the necessary data to CAFF on the status of breeding birds in
the Arctic. This will be a particular problem for species which we cannot count on the winter quarters
(e.g. the very common species such as Lapland bunting or those that winter mainly in the Arctic such as
ravens or snowy owl) and these species may require a dispersed sampling approach using coordinated
data collected from monitoring station networks specifically designed for this purpose.
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
Having established current knowledge, sources of information and gaps in coverage, the challenge will
then be to fill those gaps and use the knowledge of keystone, indicator, rare, threatened, protected,
exploited and non-native species as model species to examine the causes of change in abundance. This
will require a further period of assessment to determine the demographic explanations for changes seen
in overall abundance of flyway populations which will enable identification of the phase in the life cycle
where factors affect population size. Hence, where falling reproductive success is found to be
responsible for declines in a population where survival has been stable, causes of the decline can be
sought with confidence on the Arctic breeding grounds. Such an appraisal across species of importance
and those of unfavourable conservation status will provide a road map to better understand the causes
for these declines and also highlight further gaps in the ability of monitoring programmes to deliver
information about populations and their trophic interactions.
71
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
Changes in breeding distribution may constitute an especially challenging area of monitoring – the
prediction is that many species will be expected to shift their distributions northwards and those that
already breed to the northern edge of their continents will have nowhere to go. However, it is difficult
to achieve this through a network of dispersed monitoring stations, most of which were designed for
other purposes, and impossible to achieve with sufficient statistical power to demonstrate effects. For
this reason, it is necessary to promote other innovations to generate extensive data, for example by
encouraging collation of casual visit species lists, preferably through centralised collation of citizen
science observations (for example though e-bird http://ebird.org/content/ebird/ ). Large scale
research based studies could use spatial modelling approaches to predict species distributions based on
biotic and abiotic envelopes, using remote sensing and other data layers, reliant upon field surveys to
validate model predictions.
1974
1975
1976
4.3.7 Sampling protocols
1977
1978
1979
1980
1981
1982
1983
A wide variety of methods have been used for bird monitoring across the Arctic; sometimes different
methods are used to monitor the same parameters in the same functional groups due to regional
differences in bird biology (e.g., density and behaviour). Methods vary in accuracy and precision as well
as in implementation costs. It is difficult to suggest a single unified method to monitor an attribute,
because it can turn out to be prohibitively time-consuming even for the majority of professional
researchers and will be entirely impossible to implement in framework of traditional ecological
knowledge observations, citizen science, etc.
1984
1985
1986
1987
Table 4.2 includes a list of focal ecosystem components for terrestrial birds. The table also describes
attributes, their monitoring priority and references to method designs. As described in section 4.1.2,
two categories (basic or advanced) of methods were defined to address an issue of differences in
resources and expertise between monitors.
1988
72
1989
1990
1991
1992
BOX 4B. Site-based Bird monitoring at Zackenberg Field station
– Part of a bigger picture.
INPUT - ongoing
1993
73
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
BOX 4C. Goose target-oriented monitoring.
Results from breeding/ staging/ wintering regions contribute to overall assessment of
status and trends
Abundance and trends: In the case of Arctic nesting geese, because of their cultural importance as
major huntable species and recent interactions with agriculture, there has been a long term interest in
monitoring the size and conservation status of the different flyway populations. This information is
centrally collated and provided on a three year reporting cycle for all waterbird populations by Wetlands
International, the last tabulation is available on the web (Wetlands International 2012). This synthesis
(see Table BOX 4C) is achieved through inventory work on the wintering areas, which gives rise to an
annual index and a flyway population estimate in the case of the North American populations (US Fish
and Wildlife Service 2012), periodic assessments of Eurasian continental populations and in exceptional
cases total counts (Fox, et al. 2010a; Fox, et al. 2010b; Fox and Glahder 2010).
Distribution: Many of the inventory schemes generate data on local wintering density,
presence/absence and in rarer cases habitat utilisation, both on the wintering grounds and staging
areas, for most flyway populations. Information is less forthcoming from the breeding areas, where
there may be infrequent extensive aerial surveys (e.g. Fox and Glahder 2010; Malecki, et al. 2000).
Demography: Age specific survival rates are available for some populations (e.g. Fox 2003) even to the
extent of understanding the effects of density on emigration/immigration rates (Marchi, et al. 2010).
Breeding success is regularly sampled on an annual basis and published for many flyway populations
(Fox, et al. 2010a; Fox, et al. 2010b; US Fish & Wildlife Service 2010).
Community structure, health and body condition: Attributes under these subjects are of lower priority
and available data varied enormously between flyways. Generally, little is collected or collated on
community structure because the species typically breeds in low densities over large areas of the Arctic,
although such information is available in areas where nesting density is high (e.g. Yukon-Kuskokwim
Delta Alaska). Health is often screened periodically, typically checking for blood, feather and faecal
parasites, but data are rarely collated or centrally reported (Hoye, et al. 2011). Most capture
programmes (such as those associated with capture-mark-recapture studies of population dynamics)
take measurements of mass at capture which can be related to linear body measurements to generate
indices for fat content and to factors affecting fitness (Madsen and Riget 2007).
Table BOX 4C below – CONTINUED
74
1.000.000 STA
albifrons,
Pannonic
European Central
Arctic
Europe
Russia &
NW Siberia
X
X
10,000- DEC
40,000
albifrons,
European SE
Pontic/Anatolian Arctic
Europe,
Russia &
Turkey
NW Siberia
X
X
350,000- STA
700,000
75
(Gilissen, et al. 2002;
Koffijberg 2005?;
Wetlands
International
Specialist Groups)
Notes
X
Increases in 1990s
levelled off in 2000s,
as indicated by lower
breeding success of
birds wintering in W
Europe.
X
(Madsen,
et al.
1999)
Literature sources
European NW
Arctic
Europe
Russia &
NW Siberia
Trend
albifrons, Baltic
- North Sea
(Madsen,
et al.
1999)
Population estimate
North America
Asia
Wintering, or core nonbreeding range
Breeding range
Europe
Greater Whitefronted Goose
Anser albifrons
Subspecies and Population
TABLE BOX 4C. Worked example showing the conservation status of the entire set of circumpolar flyway populations of the Greater Whitefronted Goose Anser albifrons. Results of respective monitoring schemes from around the different breeding/staging/wintering regions
contribute to the overall assessment of abundance and trends, with literature resources provided where appropriate.
English and scientific name
2030
2031
2032
2033
frontalis, Pacific YukonCentral
Kuskokwim Valley,
Delta,
California
Alaska
X
443.900 INC
(US Fish
& Wildlife
Service
2005)
frontalis, MidContinent
X
644.300 STA
(US Fish &
Wildlife Service
2001, 2005)
"Greenland
White-fronted
Goose"
albifrons,
Caspian, Iran,
Iraq (non-bre)
European Caspian,
Arctic
Iran, Iraq
Russia &
NW Siberia
X
flavirostris
W
Ireland,
Greenland Scotland,
Wales
X
frontalis, E Asia
E Siberia
East Asia
C & NW
Louisiana,
Alaska
Texas &
across
Mexico
Arctic
Canada to
Foxe Basin
76
X
X
Numbers peaked at 35,500
in late 1990s, declined to
<27,000 by 2002 .
Production of young in
2003 remained below that
necessary to maintain a
stable population.
Population estimated at
24,000 in spring 2005.
150,000- DEC
200,000
144,917
recorded by
AWC in 1999.
40,000 migrate
through the
Kamchatka
Peninsula in
spring
27.000 DEC
(Fox and Francis 2004)
(Perenno
u, et al.
1994;
Scott and
Rose
1996)
15.000 DEC
(Gerasimov and
Gerasimov
2003;
Kondratyev
1995; Li and
Mundkur 2004)
X
"Tule Whitefronted Goose"
Alaskan
Taiga
California,
USA
X
elgasi
SW Alaska
San
Clemente
Valley,
California
X
77
Recently described;
recognised by AOU
(1998) and Clements
(2000); see online
updates.
(Callaghan
and Green
1993;
Orthmeyer,
et al. 2002)
5.100 INC
(AOU 1983
[onward]; Clements
2007 [onwards])
gambelli
2035
BOX 4D: Lapland bunting - Fluctuations of local density and breeding success can be
linked to trophic relationships
2036
2037
2038
2039
2040
2041
2042
Abundance and trends: By comparison with Arctic nesting geese, data are lacking on the abundance and
trends of Lapland Bunting (or Lapland Longspur, Calcarius lapponicus) populations. This represents the
other end of the spectrum with regard to tracking abundance, distribution and diversity of Arctic
breeding birds. The species has a circumpolar Arctic and Subarctic breeding distribution, wintering in
the temperate zone to Japan, Korea, China, across central Eurasia and around North Sea coasts, and
right across continental North America. Little is known about changes in sub-population abundance and
distribution around the globe on the breeding, staging or wintering areas.
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
Because buntings are not perceived to have equal cultural importance to other species that are
harvested, despite extraordinarily high abundance and ubiquity throughout the Arctic, limited
information about the species abundance is available, but the species has been estimated to include
approx. 150 million individuals (http://rmbo.org/pif_db/laped/PED4.aspx). The relationship between
breeding, staging and wintering areas is poorly known, and few assessments of long term changes in
annual winter distribution and abundance have been conducted. The North American continental
population is estimated to be 70 million (http://rmbo.org/pif_db/laped/PED4.aspx), but the population
trends are not well known. Some winter surveys based on the Christmas Bird Count in the US suggest
declines, but the large mid-continent wintering concentrations show no change. The species can
aggregate into enormous flocks which roam in search of food making censuses extremely challenging.
2053
2054
2055
2056
2057
2058
2059
The Lapland Bunting thus represents a species which presents challenges for developing global or flyway
monitoring programmes that can deliver a simple status report on the instantaneous conservation
status for the species as a whole. However, conducting regular monitoring to obtain key abundance
measures may be possible at a series of sites where sufficiently high breeding densities exist and
monitors with expertise are available. Monitoring can help to generate a useful time series to examine
fluctuations in local density and breeding success, and investigate links to trophic relationships, and
biotic and abiotic factors affecting the populations at local scales.
2060
2061
2062
2063
2064
2065
2066
2067
2068
2069
2070
2071
Distribution: Almost nothing is known about changes in density and distribution on the breeding areas,
apart from results from local studies, which suggest retractions in the southern parts of the range in
Hudson Bay, Canada and parts of Finland, balanced by expansion in Kola Peninsula in Russia (Hussell and
Montgomerie 2002). However, to be able to design a protocol of data collection relating to such an
abundant and widespread species is challenging, since data would need to be collated from a very large
number of sites over many years before the study would have sufficient statistical power needed to
detect changes in abundance at large spatial scales. In contrast, long time series to track local changes
in density, in concert with collations of species lists and casual records over many years and across many
sites may enlighten long term changes, and would therefore merit monitoring actions across many
different Arctic regions. As above, this long term monitoring would illuminate the relationship of the
species with its local environment and help separate any short term noise (driven by food supply or
weather) from long term signals (trends in local population development).
2072
2073
2074
Demography: Annual adult survival rates are available for very few populations (estimated at 43-45%) or
for breeding success at egg, nest and fledging stages (Hussell and Montgomerie 2002). Although
obtaining good measures of survival and reproduction parameters from intensive monitoring effort may
78
2034
2075
2076
2077
2078
2079
2080
2081
2082
be insufficient to generate population models to track changes in abundance, there is great value in
collecting such data on a regular basis at sites where the species is common, and possibilities for large
samples sizes offers very exciting monitoring opportunities to link annual reproductive success to local
environmental conditions to gain deeper insight into factors affecting breeding. It is known from studies
that late snow and prey availability affects the timing of breeding and reproductive success (e.g. Fox, et
al. 1987), so gaining a deeper understanding of these types of processes from regular monitoring would
greatly contribute to our ability to understand factors affecting the distribution and abundance of this
species throughout the Arctic.
2083
2084
2085
2086
2087
2088
2089
2090
2091
2092
2093
2094
2095
Community structure, health and body condition: Attributes under these subjects are currently of
lower priority, until such time that serious declines in abundance signal the need for further
investigation. The species is common throughout the Arctic wherever the habitat is suitable, and so its
disappearance would be evident from key areas, and would likely have ecosystem consequences, both
as a consumer (e.g. of arthropods) and prey (e.g. of generalist predators such as Arctic foxes but also of
specialist predators, such as peregrine falcons, where declines could have local consequences). At least
in other species, disease and parasite infestations, and observations of body mass changes throughout
the annual cycle are being documented (see Chapter 1; drivers), but data are currently lacking for
buntings. Such data however can contribute in the future to a robust monitoring programme for this
species. Investigating health and body condition in response to a specific hypothesis in a situation where
it is known a local breeding population is showing adverse change may be more cost effective than using
precious monitoring resources in gathering regular monitoring data without purpose that is not likely to
be used.
79
2096
2097
2098
2099
2100
Fig. 4.2. The Arctic terrestrial birds monitoring conceptual model showing focal ecosystem component examples, key drivers, attributes and
their inter-relationships.
80
Essential
Essential
Local density;
presence/absence,
habitat selection,
migration patterns
1) local global; 2)
regional; 3)
regional global; 4)
local
1) Various aerial
and ground
surveys; 2) nonbreeding census;
3) banding
(Capture-MarkRecapture); 4)
citizen science
(TK)
81
COMMENTS
TEMPORAL
RECURRENCE
PROTOCOL
COMPLEXITY
METHOD
SCALE
PARAMETER
Population size,
number, habitat
selection
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
annual; 4)
continuous
Must be included; ptarmigan
may be poorly covered by
these methods
Distribution
PRIORITY
ATTRIBUTE
Abundance
and trends
1) local global; 2)
regional; 3)
regional global; 4)
local
1) Various aerial
and ground
surveys; 2) nonbreeding census;
3) banding
(Capture-MarkRecapture); 4)
citizen science
(TK)
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
annual; 4)
continuous
Must be included
Herbivores (geese, swan, ptarmigan)
FOCAL
ECOSYSTEM
COMPONENT
Table 4.2. List of focal ecosystem components for terrestrial birds (FECs: major biodiversity elements), their attributes (compositional,
structural, and functional aspects), monitoring priority of attributes, parameters of attributes (individual measures/methods to quantify
attributes), geographic scale, method (monitoring technical approach or reference to methods), protocol complexity (basic or advanced) and
temporal recurrence (how frequently monitoring should be conducted).
Essential
Community
structure
Recommended
Diversity index,
habitat selection
Health
Recommended
Prevalence
pathogens,
parasites,
contaminants
1-2) regional
to global; 3)
local; 4) local
1) banding
(Capture-MarkRecapture); 2)
hunter collected:
wing surveys
(see Glossary); 3)
site-specific
studies; 4) egg
collectors
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
annual; 4)
annual
See rows
above
See rows above
ADVANCED
See rows
above
1) local, 2)
regional to
global; 3)
local - global
1) specific
projects; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
ADVANCED
1) as req;
2) annual; 3)
as req;
82
feeds directly into
Under some circumstances, Relative abundance of all species Demography
population
size
is of high
this may become imperative within defined area. Lower priority priority. Often, and
it
is
the only
requiring policy changes
but data can be obtained from
measurable
attribute
at the
(i.e.. H5N1 outbreak).
population abundance parameters.
flyway scale.
Demography
Propensity; clutch
size; brood size;
age ratio; nest
success; age
specific survival;
genetic diversity;
breeding
behavior;
phenology
Essential
Population size,
numbers, habitat
selection
1) local, 2)
regional to
global; 3)
local - global
1, 3) regional
(North
America); 2)
regional /
global; 4)
global; 5)
local global; 6)
local
1) Arctic PRISM:
shorebirds; 2)
non-breeding
surveys: flyway;
3) CBC:
passerines; BBS;
4) Arcticbreeding Birds
Conditions
Survey; 5)
single-species
surveys; 6) local
knowledge (TK)
83
ADVANCED
1) as req;
2) annual; 3)
as req;
Could be considered an
aspect of health
Abundance
and trends
Recommended
Diet, fat index,
feeding rate
BASIC and
ADVANCED
1) every 15 20 years;
2) annual;
3) annual; 4)
annual; 5)
annual; 6)
continuous
Must be included; statistically valid.
Insectivores (shorebirds, passerines)
Body
condition
1) specific
projects; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
1) regional /
global; 2)
global; 3)
local; 4)
regional /
global; 5)
regional /
global
1) ASDN; 2)
ABBCS; 3)
Specific projects;
4) citizen science
(incl. TK); 5) nonbreeding ground
surveys (CBC,
MAPS, juvenile
ratios)
Recommended
Diversity index,
habitat selection
See rows
above
84
See rows above
Various
(annual to
continuous)
Must be included. Data should be
gathered through population
abundance parameters and doing
so on a long term standardized
basis is important.
Community
structure
Essential
propensity; clutch
size; brood size;
age ratio; nest
success; age
specific survival,
genetic diversity,
breeding behavior,
phenology
BASIC and
ADVANCED
BASIC and
ADVANCED
1) annual; 2)
annual; 3) as
req.; 4)
continuous;
5) annual
Demography feeds directly into
population size - It has to be high
priority. Often it is the only
measurable attribute at the flyway
scale
Demography
Essential
1) regional /
global; 2)
local; 3) see
above; 4)
regional global
ADVANCED
As req.;
annual if
possible
Relative abundance of
all species within
defined area.
Distribution
Local density;
presence/
absence, habitat
selection,
migration patterns
1) citizen science
(eBird, TK, BBS);
2) research
stations; 3) see
row above
except CBC; 4)
banding and
tracking studies
(refers to
migration
pattern)
Abundance
Recommended
Essential
Diet, fat index,
feeding rate
1) regional;
2) local; 3)
regional global
1) ASDN; 2)
specific projects;
3) citizen science
(harvest
information)
ADVANCED
1) annual; 2)
as req.; 3)
annual
1-2)
regional; 3)
regional; 4)
global
1) boat surveys
(raptors); 2)
aerial surveys
(jaegers, owls,
some falcons); 3)
ground
migration
surveys
(raptors); 4)
ArcticWOLVES
Observatories
Network
BASIC and
ADVANCED
1-2) annual;
3) annual; 4)
annual
Population size;
numbers, habitat
selection
85
ADVANCED
1) as req.;
2) annual; 3)
continuous;
4) as req.
Must be included. Limited harvest in
various places in some countries.
Carnivores (raptors, jaegers, ravens
and owls)
Body
condition
Recommended
1) local; 2)
regional; 3)
regional global; 4)
local - global
Could be considered an Under
some circumstances,
aspect of health. However - this
may
become imperative
if the bird is in hand low
requiring
policy changes
cost monitoring contributing (i.e..
H5N1
outbreak).
to long term perspective.
Health
Prevalence
pathogens,
parasites,
contaminants
1) specific
projects; 2)
ASDN projects;
3) citizen
science; 4)
opportunistic or
targeted
samplings as
needed
Essential
propensity; clutch
size; brood size;
age ratio; nest
success; age
specific survival,
genetic diversity,
breeding behavior
BASIC and
ADVANCED
1-2) annual;
3) annual; 4)
annual; 5)
annual
Must be included
Demography
Essential
1-2)
regional; 3)
regional; 4)
global; 5)
regional
1) global; 2)
regional; 3)
local
1) ArcticWOLVES
Observatories
Network; 2)
citizen science
(Cornell TK); 3)
site specific
study
BASIC and
ADVANCED
1-3) annual
Demography feeds directly into
population size - It has to be high
priority. Often it is the only
measurable attribute at the flyway
scale
Distribution
Local density;
presence/absence,
habitat selection,
migration patterns
1) boat surveys
(raptors); 2)
aerial surveys
(jaegers; owls,
some falcons); 3)
ground
migration
surveys
(raptors); 4)
ArcticWOLVES
Observatories
Network; 5)
citizen science
(eBird, TK)
86
Health
Body
condition
Recommended
Diversity index,
habitat selection
See rows
above
See rows above
ADVANCED
As req.;
annual if
possible
Recommended
Prevalence
pathogens,
parasites,
contaminants
1 )regional;
2) local
1) citizen science
(Cornell TK); 2)
site specific
study
ADVANCED
1-2) annual
Recommended
Diet, fat index,
feeding rate
1) regional;
2) local
1) citizen science
(Cornell; TK); 2)
site specific
study
ADVANCED
1-2) annual
87
Under some circumstances, this
Relative abundance of all
Could be
may become imperative requiring species within defined area.
considered an
policy changes (i.e.. H5N1
Low priority but data will be
aspect of health outbreak). Elevated relevance gathered through population
because of the high trophic level.
abundance parameters.
Community
structure
Demography
Essential
Local density;
presence/absence,
habitat selection,
migration patterns
Essential
propensity; clutch
size; brood size;
age ratio; nest
success; age
specific survival,
genetic diversity,
breeding behavior
1) local global; 2)
regional; 3)
regional global; 4)
local
1) various aerial
and ground
surveys; 2) nonbreeding census;
3) banding
(Capture-MarkRecapture); 4)
citizen science
(TK)
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
annual; 4)
continuous
1-2) regional
to global; 3)
local; 4) local
1) banding
(Capture-MarkRecapture); 2)
wing surveys; 3)
site specific
studies; 4) egg
collectors
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
annual; 4)
annual
88
Must be included
BASIC and
ADVANCED
Must be included
Distribution
Essential
1) annual; 2)
annual;
3)annual; 4)
continuous
Demography feeds directly
into population size - It has to
be high priority. Often it is the
only measurable attribute at
the flyway scale
Omnivores (ducks, cranes)
Abundance
Population size;
numbers, habitat
selection
1) local global; 2)
regional; 3)
regional global; 4)
local
1) various aerial
and ground
surveys; 2) nonbreeding census;
3) banding
(Capture-MarkRecapture); 4)
citizen science
(TK)
Health
Body
condition
Recommended
Recommended
Recommended
Diversity index,
habitat selection
Prevalence
pathogens,
parasites,
contaminants
Diet, fat index,
feeding rate
See rows
above
See rows above
ADVANCED
As req.;
annual if
possible
1) local; 2)
regional to
global; 3)
local - global
1) site-specific
projects; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
ADVANCED
1) as req.;
2) annual;
3) as req.
1) local; 2)
regional to
global; 3)
local - global
1) site-specific
projects; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
ADVANCED
1) as req.;
2) annual;
3) as req.
89
This could under certain
Relative abundance of all
circumstances
H5N1
species
within defined area.
(i.e..
Could be considered an outbreak) quickly elevate to Low priority
but data will be
aspect of health
high and may result in
gathered through population
legislation.
abundance parameters.
Community
structure
Demography
Essential
Local density;
presence/absence,
habitat selection,
migration patterns
Essential
propensity; clutch
size; brood size;
age ratio; nest
success; age
specific survival,
genetic diversity,
breeding behavior
Must be included;
grebes may not be
represented in a
defined Arctic region.
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
continuous
1) local global; 2)
regional; 3)
local
1) various aerial
and ground
surveys; 2) nonbreeding
surveys; 3)
citizen science
(eBird, TK)
BASIC and
ADVANCED
1) annual; 2)
annual; 3)
continuous
Must be included.
Distribution
Essential
1) local global; 2)
regional; 3)
local
1, 2) local; 3)
regional
1) site-specific
studies; 2) egg
collectors; 3)
aerial surveys for
propensity
BASIC and
ADVANCED
1-2) annual;
3) annual
Demography feeds directly into
population size - It has to be high
priority. Often it is the only
measurable attribute at the flyway
scale
Piscivores (loons, merganser and grebes)
Abundance
Population size;
numbers, habitat
selection
1) various aerial
and ground
surveys; 2) nonbreeding
surveys; 3)
Citizen science
(TK)
90
Body
condition
Recommended
Recommended
Diversity index,
habitat selection
Prevalence
pathogens,
parasites,
contaminants
Diet, fat index,
feeding rate
See rows
above
See rows above
ADVANCED
As req.;
annual if
possible
1, 2) local; 3)
local
1) site-specific
studies; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
ADVANCED
1-2) annual;
3) as req.
1, 2) local; 3)
local
1) site-specific
studies; 2)
citizen science;
3) opportunistic
or targeted
samplings as
needed
ADVANCED
1-2) annual;
3) as req.
91
Could be considered an
aspect of health.
Health
Recommended
Under some circumstances, this may Relative abundance of all
become imperative requiring policy species within defined area.
changes (i.e.. H5N1 outbreak).
Lower priority but data can
Elevated relevance because of the be obtained from population
high trophic level.
abundance parameters.
Community
structure
2101
2102
4.4
Mammals
2103
2104
2105
2106
2107
2108
2109
2110
The mammal species in the Arctic are a variety of sizes, occupy various trophic positions and assume a
variety of life strategies. While many of the Arctic species resides in the same area year-round (e.g.
lemmings), some species are either true migratory species (reindeer/caribou) or roam over vast areas
(e.g. wolf). Unlike the Arctic birds (see section 4.3), the Arctic mammal species are generally widely
distributed year-round and therefore cannot be censused at aggregation areas. Some species, such as
the reindeer/caribou, are hunted by local people, and their abundance and demographics are therefore
often monitored by the local communities. Population monitoring of the Arctic mammal species
therefore includes an array of methodologies and approaches.
2111
2112
2113
2114
2115
2116
2117
2118
The on-going monitoring of mammal populations in the Arctic is highly fragmented, and only the
reindeer/caribou populations are monitored across the pan-Arctic following standardised protocols
through the CARMA network (Circum Arctic Rangifer Monitoring and Assessment Network). For the
remaining mammal species, some countries may have well-developed monitoring programs for some
species or groups of species. However, the vast majority of mammal species in the Arctic are currently
either not sufficiently monitored or the on-going monitoring is not sufficiently coordinated to allow for a
pan-Arctic assessment of status and trends. Moreover, there are only few examples of mammal species
being monitored in an ecosystem framework.
2119
2120
2121
2122
The CBMP-Terrestrial Plan aims at coordinating, expanding, and harmonising the on-going monitoring of
mammals on the pan-Arctic scale in order to fulfil the needs of stakeholders and other end-users. This
will be achieved through the presentation of a generic mammal monitoring scheme, based on an
ecosystem approach and based on methodologies of agreed best-practices.
2123
2124
2125
4.4.1
Mammal monitoring questions
2126
2127
2128
2129
2130
2131
2132
Many of the core management questions related to mammals are related to understanding the
interactions in the ecosystem centered on mammals, and hence to understand the key attributes such
as abundance, demographics and health, but also likely stressors. The selection of the latter is based on
expert opinion in connection with the development of the ecosystem-based conceptual models. Other
management questions are related to specific conservation issues, such as securing sustainable hunting
or meeting the international requirements for reporting on biodiversity issues (e.g. in connection with
the Convention on Biological Diversity (CBD)).
2133
2134
2135
The elements in the mammal monitoring programs are selected during the process of conceptual model
formulation, whilst also taking into account logistic limitations etc. The mammal monitoring program
should therefore be focused on species that are the focal ecosystem components (FEC; see Chapter 3),
92
2136
2137
species that acts as indicators for other species or processes, species that are rare, threatened or rapidly
declining species, species that are exploited by man, and finally species that are invasive.
2138
Specifically, the overall management questions related to the mammals are:
2139
2140
1. What are the status and trends of the relevant mammal populations (species or groups of
species, i.e. FEC’s) in the Arctic?
2141
2. Where in the Arctic are the populations changing?
2142
2143
2144
3. What and how do the primary biotic, abiotic and anthropogenic drivers influence the various
mammal species/FECs, and hence, influence the mammal diversity and ecosystem function?
2145
2146
4.4.2
Potential contributors to the mammal monitoring scheme
2147
2148
2149
2150
2151
The present mammal monitoring scheme is based on existing monitoring supplemented with new
coordinated initiatives. Though some countries have developed extensive programs for the monitoring
of mammals, generally the current monitoring of mammals in the pan-Arctic is fragmented. One
exception is the pan-Arctic coordinated monitoring of reindeer/caribou conducted within the CARMA
network (http://caff.is/carma).
2152
2153
2154
2155
2156
Generally, the mammal monitoring in the Arctic is conducted at permanent field stations/sites. The aim
of the present monitoring plan is therefore to utilize for example the INTERACT project, an existing
network of field stations in the Arctic (http://www.eu-interact.org/ ), to improve the coordinated
monitoring within the CBMP-Terrestrial Plan. Also, this will allow the monitoring program to be truly
ecosystem-based, as seen at Zackenberg in Northeast Greenland.
2157
2158
2159
4.4.3
Mammal conceptual model in relation to monitoring
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
Mammals are affected by processes that affect their food base. Grazing herbivores may be affected by,
for example, the start of the growing season, which is influenced by the climate (bottom-up). The same
species may be influenced/controlled by predator species (top-down). Also, the anthropogenic influence
on, for example, caribou/reindeer may have a major impact at a population level. Therefore it is
sometimes necessary to monitor not only the species in question but also other relevant taxa. These
interactions around a key species are projected in a food web or a conceptual model. The mammal
conceptual model (Fig. 4.2a) was developed by the mammal expert team and it illustrates the
conceptualization of the six functional mammal groups operating at a Pan-Arctic scale. The three most
important functional groups are the large herbivores, the medium-sized predators and the small
herbivores. In several geographic distinct areas not all functional groups are present. We therefore also
93
2170
2171
2172
illustrate two localized conceptual models with only some of the functional groups included (Fig. 4.2b
and 4.2c). The models help to illustrate other taxonomic groups that may interact with mammals, such
as birds, and vegetation groups.
2173
2174
2175
4.4.4
Terrestrial mammal monitoring design principles and components
2176
2177
2178
2179
2180
The classification into the six FEC groups is based upon the theory that different-sized mammals
(functional groups) interact differently with other ecosystem components, i.e. occupy different positions
in the food web. Thus, one can outline a conceptual model where the interactions between the mammal
FECs (and those with other FECs) are visualized as a food web (Figs. 4a-c). The Arctic terrestrial
ecosystems have relatively few mammalian species, and hence only few food web links.
2181

Large herbivores (reindeer/caribou, musk ox, moose)
2182

Medium-sized herbivores (hares)
2183

Small herbivores (lemmings, voles)
2184

Large predators (wolves, bears)
2185

Medium-sized predators (wolverine, lynx, foxes)
2186

Small predators (small mustelids)
2187
2188
2189
2190
2191
As shown in Figs. 4a-c there are some FECs that occupy more central spaces in the conceptual model,
than others. For instance, small herbivores play an important role, as they interact with a comparatively
high number of other FECs. However, how many and which of the mammal FECs that are present in any
given geographical region vary across the Arctic. Therefore, localized conceptual models are outlined in
Figs. 4b and 4c (and section 4.1.8).
2192
2193
4.4.4.1 Large herbivores
2194
2195
2196
2197
2198
2199
2200
The large herbivore functional group in the Arctic proper includes caribou/reindeer (Rangifer tarandus)
and Musk ox (Ovibus moschatus), while in the alpine ecosystems the Moose (Alces alces) is also
included. This group is widely distributed across the Arctic. The large sized herbivores are long-lived
(more than 10 years) and produce normally only one young every year or every other year. The large
herbivores are important in many parts of the Arctic, both as consumers but also as prey (including
carcasses) for the large and medium-sized predators. Caribou/reindeer in particular have especially
strong linkages to human communities in the Arctic.
94
2201
4.4.4.2 Medium-sized herbivores
2202
2203
2204
2205
2206
The medium-sized herbivore functional group in the Arctic includes three hare species (i.e. Arctic hare
(Lepus arcticus), Snowshoe hare (Lepus americanus) and Mountain hare (Lepus timidus). Hares are
widely distributed across the Arctic. The medium-sized herbivores has a lifespan of approximately 4-5
years, and may reproduce once a year with litters of varying size. Besides being important herbivores,
the medium-sized herbivores function as important prey for mainly the medium-sized predators.
2207
4.4.4.3 Small herbivores
2208
2209
2210
2211
2212
2213
2214
2215
The small herbivore functional group in the Arctic includes species of lemmings (Dicrostonyx sp. and
Lemmus sp.) and voles (Microtus sp. and Clethrionomys sp.). This group is widely distributed across the
Arctic, and is the key prey for a number of both avian and mammalian predators. Lemmings and voles
are short-lived, but can reproduce fast because they can produce several, large litters per year. The
population dynamics of voles and lemmings is often characterised by large inter-annual fluctuations. The
Arctic Ground Squirrel (Spermophilus parryi) is a true hibernating species, and this sets it somewhat
apart from the other small herbivores. In general, the small herbivores function as prey for a wide
spectrum of predator species.
2216
4.4.4.4 Large predators
2217
2218
2219
2220
2221
2222
2223
The large predator functional group in the Arctic proper only includes the Grey wolf (Canis lupus), while
in the alpine ecosystem the Brown bear (Ursus arctos) and the American black bear (Ursus americanus)
are also included. The group is distributed across most of the Arctic. However, only the wolf is present in
Greenland, and no species of large predators are found in Iceland or on Svalbard. Population densities
are generally very low. The large predators are generally long-lived, and while the wolf may reproduce
every year, the brown bear reproduces only every two to three years. Polar bear, an important predator
on land also, (Ursus maritimus) is considered under the CBMP-Marine Plan.
2224
4.4.4.5 Medium-sized predators
2225
2226
2227
2228
2229
2230
The medium-sized predator functional group in the Arctic consists of Wolverine (Gulo gulo), Eurasian
lynx (Lynx lynx), Canada lynx (Lynx canadensis), Red fox (Vulpes vulpes) and Arctic fox (Vulpes lagopus).
The group is truly circumpolar in its distribution; especially so for the Arctic fox. As for large predators,
population densities are generally low, especially in the High Arctic. The medium-sized predators are of
varying longevity, may reproduce every year, with varying litter sizes. The litter size of the Arctic fox in
particular is linked to the availability of voles and lemmings.
2231
4.4.4.6 Small predators
2232
2233
2234
2235
The small predator functional group in the Arctic proper consists of Stoat/Weasel/Ermine (Mustela
erminea) and Least weasel (Mustela nivalis). The small mustelids are distributed across the Arctic, and
with generally low densities. The small mustelids are short-lived, and reproduce frequently depending
on the availability of their vole and lemming prey.
2236
95
2237
2238
4.4.5
Existing monitoring capacity
2239
2240
2241
2242
2243
2244
2245
Currently, as described above, comprehensive and integrated circumarctic mammal monitoring is
lacking, but through existing programs and infrastructure, the capacity exists to implement monitoring
strategies (see Appendix A). In addition, opportunities exist for knowledge exchange through existing
expert groups and initiatives through academic (several universities that also have research stations),
community, and government groups (for example, in North America, Alaska Department of Fish and
Game: http://www.adfg.alaska.gov/; Canadian Territorial governments: http://env.gov.nu.ca/,
http://www.env.gov.yk.ca/ and http://www.enr.gov.nt.ca/_live/pages/wpPages/home.aspx ).
2246
2247
2248
4.4.6
Mammal sampling protocols
2249
2250
2251
2252
For each of the mammal FECs, a number of attributes have been identified (see section 4.1.7 below).
The sampling protocol includes a number of essential and recommended attributes that should be
monitored in the mammal program. For each of the attributes, a number of parameters have also been
identified.
2253
The attributes are summarized below:
2254
2255
2256
2257
2258
I.
Abundance
Knowing the abundance of a given species is essential for the overall monitoring as this attribute
allows for the evaluation of status and trends of a given species/group of species. Depending on
the species, the most efficient tool to monitor population abundance is through standardized
censuses / counts in designated / well-defined areas of interest.
2259
2260
2261
2262
2263
2264
II.
Distribution and spatial use
As most mammal monitoring in the Arctic is based on permanent field stations, the spatial
coverage is inherently fragmented. It is therefore hard to assess changes in the spatial
distribution of most mammal species. Knowledge of the spatial distribution is therefore
recommended only in all species except for the migratory reindeer/caribou populations, where
it is essential. Changes in spatial use by migratory populations are a likely in a changing Arctic.
2265
2266
2267
2268
2269
III.
Demographics. Changes in abundance are likely to be caused by changes in the demographics of
given species, i.e. attributable to changes in fecundity, mortality etc. Knowledge on mammal
demographics is therefore regarded as essential for large and medium sized herbivores and
large predators. For the small herbivores and predators, which have the ability to reproduce at a
high rate, information on demographic is only recommended.
2270
2271
IV.
Health. Both changes in abundance and demographics may ultimately be attributable to
changes in the health of individuals in a population. Knowledge on the prevalence of zoonoses
96
2272
2273
2274
2275
2276
2277
and diseases, level of contaminants, and body condition in general, is possible at field stations or
with designated projects and is regarded as essential.
V.
Genetics. Low genetic diversity may result from population bottlenecks or metapopulation
dynamics that reduce the level of diversity thus resulting in reduced ability to survive at the
population level. Genetic diversity information may provide relevant information about the
demographics of a population also. Knowledge on genetics is recommended.
2278
2279
2280
4.4.7
Sampling protocols
2281
2282
2283
2284
2285
2286
2287
2288
2289
Not all the mammal functional groups are represented across the whole pan-Arctic area, and this is even
more evident when it comes to the individual species within each functional group. Thus, identifying
which FEC to monitor will depend largely on geography and, hence, local conditions. Nevertheless, it is
possible to highlight three of the functional groups, which play a major role in the ecosystem and a PanArctic (or near Pan-Arctic) distribution. These are the large and small herbivores, and the medium-sized
predators. Consequently, these three functional groups are considered most important to monitor, from
a Pan-Arctic perspective. However, when feasible, one should also endeavour to monitor the other
functional groups. Metadata and abiotic data should be gathered at each monitoring location, where
this is feasible.
2290
2291
2292
Table 4.3 summarizes the minimum recommended key parameters and indicators to monitor for each
focal ecosystem component (FEC). Also, recommended types of methods are included. Where there are
existing detailed protocols, such as the CARMA program, these should be used as guidelines.
97
2293
2294
Fig. 4.3a. The Arctic terrestrial mammals conceptual model for monitoring showing focal ecosystem components and interactions.
2295
98
2296
2297
2298
2299
2300
2301
2302
2303
2304
2305
2306
2307
2308
2309
Fig. 4.3b. Conceptual model for Arctic terrestrial mammals monitoring on Svalbard.
2310
99
2311
2312
Fig. 4.3c. Conceptual model for Arctic terrestrial mammals monitoring on Zackenberg.
100
Basic
3 years
Essential
Age structure,
mortality,
fecundity
Local/
regional
Aerial/land-based
surveys, telemetry, cue
counts
Basic
3 years
Basic/
advanced
Varies (from
seasonally and
upwards)
Spatial use
Essential
Distribution of
migratory herds
Local/
regional
Telemetry; aerial/ landbased surveys, harvest
records, tissue
samples
Health
Recommended
Prevalence
Local/
regional
Harvest records, tissue
samples, fecal analysis
Basic/
advanced
Genetics
Recommended
Heterozygosity
Local
DNA analysis
Advanced
101
COMMENTS
Aerial/land-based
surveys, cue counts
METHOD/
REFERENCE
Local/
regional
SCALE
Number, density
PARAMETER
TEMPORAL
RECURRENCE
(Minimum)
Demographics
Essential
PRIORITY
ATTRIBUTE
Abundance
PROTOCOL
COMPLEXITY
LARGE HERBIVORES (caribou/ reindeer, musk ox,
moose)
FOCAL ECOSYSTEM
COMPONENT
Table 4.3. List of focal ecosystem components for terrestrial mammals (FECs: major biodiversity elements), their attributes (compositional, structural, and
functional aspects), monitoring priority of attributes, parameters of attributes (individual measures/methods to quantify attributes), geographic scale,
method (monitoring technical approach or reference to methods), protocol complexity (basic or advanced) and temporal recurrence (how frequently
monitoring should be conducted). Where there are existing detailed protocols, such as CARMA (the CircumArctic Rangifer Monitoring and Assessment
Network; http://caff.is/about-carmahttp://caff.is/about-carma), these should be used as guidelines. Methods that are particularly recommended are in
italics. Although the identified FECs are all considered very important, the most critical are in written in all capitals.
Large predators
(brown bear, black
bear, grey wolf)
SMALL HERBIVORES
(lemmings, voles)
Medium-sized herbivores
(hares)
Abundance
Essential
Number, density
Age structure,
mortality,
fecundity
Temporal
distribution
Local/
regional
Local/
regional
Land-based surveys,
cue counts
Land-based surveys,
harvest records, tissue
samples
Land-based surveys,
telemetry, cue counts
Harvest records, tissue
samples, fecal analysis
DNA analysis
Basic
Annually
Basic/
advanced
Annually
Demographics
Essential
Spatial use
Recommended
Health
Recommended
Prevalence
Genetics
Recommended
Heterozygosity
Local/
regional
Local/
regional
Local
Abundance
Essential
Number, density
Local
Land-based surveys,
cue counts
Basic
Demographics
Recommended
Local
Land-based surveys,
telemetry, cue counts
Basic
Spatial use
Recommended
Local
Live/ snap trapping
Basic
Health
Genetics
Recommended
Recommended
Age structure,
mortality,
fecundity
Temporal
distribution
Prevalence
Heterozygosity
Local
Local
Tissue samples
DNA analysis
Advanced
Advanced
Abundance
Essential
Number, density
Regional
Cue count, aerial/landbased surveys
Basic
3 years
Essential
Age structure,
mortality,
fecundity
Regional
DNA analysis, den
surveillance
Advanced
3 years
Demographics
102
Basic
Basic/
advanced
Advanced
Annually
Temporal
distribution
Health
Recommended
Prevalence
Genetics
Recommended
Heterozygosity
Abundance
Essential
Demographics
Regional
Telemetry
Basic*
Local/
regional
Local
Harvest records, tissue
samples, fecal analysis
DNA analysis
Basic/
advanced
Advanced
Number, density
Local/
regional
Den surveillance
Basic
Recommended
Age structure,
mortality,
fecundity
Local/
regional
Den surveillance
Basic
Spatial use
Recommended
Temporal
distribution
Regional
Telemetry
Basic*
Health
Recommended
Prevalence
Genetics
Recommended
Heterozygosity
Local/
regional
Local
Harvest records, tissue
samples, fecal analysis
DNA analysis
Basic/
advanced
Advanced
103
* Methods are not
difficult but require
specialised technology
(can be expensive)
Recommended
Annually
* Methods are not
difficult but require
specialised
technology (can be
expensive)
MEDIUM SIZED-PREDATORS (wolverine, Eurasian lynx,
Canada lynx, red fox, Arctic fox)
Spatial use
Small predators (mustelids)
Number, density
Local
Cue counts, land-based
surveys
Basic
Local
DNA analysis, live
trapping
Basic/
advanced
Local
Telemetry
Basic/
advanced
Abundance
Essential
Demographics
Recommended
Spatial use
Recommended
Health
Recommended
Prevalence
Local
Genetics
Recommended
Heterozygosity
Local
Age structure,
mortality,
fecundity
Temporal
distribution
104
Tissue samples, fecal
analysis
DNA analysis
Advanced
Advanced
Annually
2313
2314
4.5
Arthropods and Invertebrates
2315
2316
4.5.0
Introduction and scope
2317
2318
2319
2320
2321
2322
2323
2324
2325
2326
2327
2328
2329
2330
Arctic invertebrates exhibit high diversity (Danks 1981) are biologically fascinating (Strathdee and
Bale 1998), and there is an increased recognition that arthropods play key ecological roles in
northern systems: they pollinate plants (Kevan 1972), are tightly linked to the decomposition
process in the Arctic (Coulson, et al. 2000), are pests of wildlife (Hughes, et al. 2009), and are prey to
highly valued vertebrates (McKinnon, et al. 2012; Tulp and Schekkerman 2008). In a broader foodweb context, there is growing evidence about the role of arthropods in the north (Hodkinson and
Coulson 2004; Legagneux, et al. 2012). Research is starting to show how arthropods are being
affected by shifts in global temperatures, including (for example) effects on wildlife parasites
(Hughes, et al. 2009), shifts in the biomass of vertebrate prey (Tulp and Schekkerman 2008), changes
in parasitic wasp assemblages (Fernandez-Triana, et al. 2011) and shifts in the sexual dimorphism of
spiders (Høye, et al. 2009). It is essential that these effects do not go unnoticed, and that additional
research, including long-term monitoring, be completed on key species in northern systems
including invertebrates – a topic that remains as critical today as when Callaghan et al. (1992) and
Danks (1992) discussed it 20 years ago.
2331
2332
2333
2334
2335
2336
For the purposes of this report, the focus is on invertebrates that occur in terrestrial environments,
although some taxa have aquatic larval stages. Of these, the benthic invertebrates are largely
covered by the CBMP- Freshwater Plan (Culp, et al. 2012), although we will cover some aspects of
biting flies (i.e., some families of Diptera) with a slightly different focus. Overall, this chapter focuses
on the ecological functions of aboveground arthropods, i.e., insects and spiders, and soil living
invertebrates, e.g., microarthropods, enchytraeids and earthworms.
2337
2338
4.5.1
Pan-Arctic sampling approach
2339
4.5.1.1 Key arthropod monitoring questions:
2340
2341

What is the status (abundance, diversity) of functionally important terrestrial invertebrate
taxa occurring in the Arctic?
2342
2343

What are the main trends in the status of these taxa (i.e., changes in the diversity,
distribution, abundance) and relevant ecological functions?
2344
2345

What are the key drivers behind the trends in key invertebrate taxa and associated
ecological function
2346
2347

What is the status and trends of invertebrate species of special interest, including invasive
and introduced species, occurring in the Arctic?
2348
105
2349
4.5.1.2 Arthropod conceptual model
2350
2351
2352
2353
2354
Invertebrate sampling is developed from the perspective of key ecosystem processes (see
conceptual model, Fig. 3.2) in the Arctic. For invertebrates we highlight the following processes as
being highly relevant: decomposition and nutrient cycling, herbivory, invertebrates as prey for birds,
pollination, and blood-feeding (e.g., biting flies). There are complex food-webs embedded within
each of these processes as illustrated by Figure 4.4 for soil-based food webs.
2355
2356
2357
2358
2359
2360
2361
2362
2363
Other processes are also important (see conceptual model, Fig. 3.2), but not included in detail in this
monitoring report. For example, parasitic wasps play a key role in Arctic systems, as one type of topdown control on various arthropods (e.g. spiders (Bowden and Buddle In press); caterpillars
(Klemola, et al. 2010)). These wasps will, however, be collected as part of the required plan (see
below) and can be stored long-term and available for scientists in the future. We have also excluded
monitoring of parasitic arthropods of large and small mammals, such as bot and warble flies, bloodfeeding lice and ticks. Although these taxa and processes are important in the Arctic (e.g. see
Hughes, et al. 2009) it is expected that mammal health will be monitored as part of the mammal
monitoring plan (see section 4.4).
2364
2365
2366
2367
2368
2369
2370
2371
2372
The decomposer ecosystem of the soil has a trophic structure spanning a broad range of taxonomic
groups including microorganisms, mites, hexapoda and earthworms. The food web holds microbial
feeders, detritivores and predators also characterized as primary and secondary decomposers, as
they may form detritus food-chains with a few links before being eaten by a predator (decomposer
food web, Fig. 4.4). Although monitoring capacity is limited at this time for these important microbes
(Chapter 1), we suggest requiring the monitoring of the mesofauna with collembolans at the species
level, as this group hitherto is the most feasible concerning availability of expertise and equipment
(cf. Bispo, et al. 2009). The vertical distribution and corresponding contrasting life-forms guarantees
capturing environmental changes.
2373
2374
4.5.1.3 Existing capacity to deliver the CBMP
2375
2376
2377
2378
2379
2380
Monitoring of terrestrial invertebrates is rare in the Arctic (Figure A1); with the exception of
Zackenberg (Eastgreenland), Nuuk (Westgreenland), Svalbard (Norway) and some recent efforts to
monitor arthropod biomass in North America (Bolduc, et al. 2013). There are other regional models
of arthropod monitoring in other parts of the world (e.g., Alberta Biodiversity Monitoring Institute,
http://www.abmi.ca/abmi/home/home.jsp) and these can be used as model in the development
of an Arctic monitoring program.
2381
2382
2383
2384
2385
2386
2387
There are also some important areas in which arthropod research occurs (Figure A1), but presently
these areas do not have long-term monitoring in place. Existing monitoring programs are often
based on specific research projects, or monitoring for specific and focused research questions (e.g.,
biomass sampling in Bylot, Nunavut, for assessment of prey availability for shorebirds (Bolduc, et al.
2013)). Greenland monitoring is an exception, as methods at these sites include broad taxonomic
coverage, diversity, abundance, phenology, and many ecosystem processes (biotic, abiotic) (e.g., see
Box 4B and http://www.zackenberg.dk/ ).
106
2388
2389
2390
2391
2392
2393
2394
2395
2396
2397
4.5.1.4 Arthropod monitoring design principles & components
Given the limited coverage of monitoring programs for invertebrates, it is very difficult to prioritize
locations and habitats for future monitoring. Instead we suggest invertebrate monitoring be
included with other monitoring efforts as a required sampling 'module'. In other words, whenever
vegetation, bird, or mammal monitoring occurs, so should invertebrate sampling. We also suggest
that all active research stations in the Arctic consider adding a monitoring program for invertebrates.
After invertebrate monitoring has been initiated at a pan-Arctic scale, it will be possible to prioritize
for additional key locations and habitats. At a local scale, terrestrial invertebrate monitoring should
ideally be done at more than one location, and more than one habitat, with plant communities and
moisture gradients as key considerations in selecting habitats.
2398
2399
2400
2401
2402
2403
2404
The monitoring can be approached with different levels of detail, and the capacity of individual
monitoring programs depends on personnel, funding and infrastructure. Given these constraints,
we have considered a sub-set of all possible attributes for each function as being required, meaning
they should be part of any monitoring programs (Table 4.4). However, it is recognized that some
monitoring programs may not be able to complete all required monitoring of invertebrates, and thus
should pick and choose (i.e., from Table 4.4) the key attribute given logistical or financial constraints
and/or if more specific management questions are a focus for a given monitoring location.
2405
2406
2407
4.5.2
Sampling protocols and design
2408
4.5.2.1 Frequency of monitoring
2409
2410
2411
2412
2413
Invertebrate abundance and diversity varies from year to year in the Arctic (Bolduc, et al. 2013), and
a single season of monitoring will not provide answers to the management questions. It is therefore
recommended that required sampling protocols be done on a yearly basis until yearly variation is
tracked for several seasons. Once the natural range of variation is tracked, it may be possible to
move into a five-year cycle of monitoring.
2414
4.5.2.2 Sampling protocols
2415
2416
2417
2418
2419
2420
2421
2422
Protocols outlined below are separated by Essential and Recommended methods. Additional
specifics about methods can be found in the included references (and see Chapter 9). When
multiple traps are required per site (e.g., pan or pitfall traps), it is recommended that at least 10
traps be used per habitat. Addition of a preservative is required to allow for subsequent DNA
extraction. Duration of trapping depends on specific methods. If possible, taxon sampling curves
(see Buddle et al. 2005) should be used to assess whether sampling has been sufficient in reference
to number of taxa collected, and in reference to sampling effort (e.g., whether 10 or more traps
would be required).
2423
2424
2425
2426
2427
The required set of protocols is considered as covering a 'minimum set' of attributes, but we
advocate for a larger set of attributes to be collected if logistically possible and/or if specific
management or research questions trigger the need for additional invertebrate data. We have
included some of these additional protocols as recommended in a monitoring program (Table 4.4,
and references therein). This strategy includes broader taxonomic coverage, but more notably,
107
2428
2429
2430
phenology and abundance or density estimates of many taxa. Critical thresholds and ecological
tipping points, however, may not be detected with sampling that only completes the required
protocols.
2431
2432
2433
2434
2435
2436
We recognize much potential in engaging local communities, schools, amateur entomologists, and
other interested peoples in a 'citizen scientist' approach to monitoring aspects of invertebrates. For
example, date(s) of first appearance of butterflies or biting flies, range extensions of native species,
and species introductions could be tracked. On model could be something akin to the "e-butterfly"
on-line resource (http://ebutterfly.ca/), or a 'bug-guide' (http://bugguide.net/) with a northern
focus.
2437
2438
4.5.2.3 Essential protocols:
2439
1) Blood-feeding insects.
2440
2441
Metric: species richness per sampling location - taxonomic
resolution - species; DNA Barcoding (COI barcode, or additional barcodes)
2442
2443
2444
2445
2446
2447
2448
2449
2450
2451
2452
2453
2454
2455
Methods: larval and pupal Simuliidae and Culicidae collected by
hand from lotic and lentic waters, respectively. Minimum of 6 streams/rivers and six ponds/pools
required. Emphasis should be on sampling as many different habitats and microhabitats as possible.
For simuliids, these include streams of various sizes and velocity, pond outlets, and flows that
originate from groundwater or ice melt. Substrate from which larvae and pupae should be sampled
includes trailing grasses, rocks, and submerged twigs. For culicids, standing water of various sizes
and with different types of emergent vegetation should be sampled, including small pools in
hummocky terrain or in rock crevices. For aquatic sampling, minimum of 30 minutes per habitat
(e.g., individual river or pond). When sampling culicids from exceptionally small bodies of water
(e.g., water-filled depressions in hummocky terrain), then 30 minutes should be devoted to
collecting larvae and pupae from multiple pools in a particular area. All specimens should be fixed in
95% ethanol to facilitate DNA barcoding. Adults of simuliids and culicids, and those of other families
(e.g., Tabanidae) can be collected opportunistically using a sweep-net or aspirator, or will be
collected in malaise traps as part of other protocols (see below)
2456
Attribute: species richness
(References: Adler, et al. 2004; Silver 2008)
2457
2458
2) Pollination:
Attribute 1: Species richness
2459
2460
2461
2462
2463
Metric: flower (or inflorescence) visitation per hour, recorded by
plant species; taxonomic diversity per visitation period, number of pollinators per pan trap; COI
barcodes (or other barcodes); taxonomic resolution: dependent on expertise for Diptera, but species
is required for Apoidea (i.e., including the families Megachilidae, Colletidae, Halictidae, Andrenidae
and Apidae)
2464
2465
Methods: flower visitation rates; flower visitation should be done
with dominant flowering plants, standardize by time per plant, or by area depending on habitat
108
2466
2467
2468
structure. Standardize grids of yellow, white and blue pan traps (minimum 10 traps, placed > 10 m
apart), or vane traps (blue/yellow), opportunistic sweep-net collections with floral hosts recorded
when possible.
2469
(References: Dafni, et al. 2005; Elberling and Olesen 1999; Stephen and Rao 2005)
2470
Attribute 2: Pollination success
2471
Metric: grains per stigma, % fruit set, % fruit yield
2472
2473
2474
2475
2476
Methods: Pollination success can be measured indirectly by
comparative studies of fruit set and fruit yield, requiring repeated visits to plants, i.e., done
separately for different target species of plants. A more direct measure is pollen grains per stigma:
this is done by comparative studies of plant stigma, with aid of field microscope. This requires
repeated visits to the same plants.
2477
(References: Dafni, et al. 2005; Stephen and Rao 2005)
2478
3) Prey availability for birds:
2479
2480
Metric: number or mg of arthropods per trap per day (phenology is
the abundance or biomass data, over time); Taxonomic resolution: family-level.
2481
2482
2483
2484
2485
2486
Methods: For ground-dwelling arthropods, standardized grids of
pan or pitfall traps, minimum of 10 traps per habitat, established as soon as possible after snowmelt
until the end of the active snow-free season. For flying arthropods (e.g., Diptera), one standard
malaise trap per habitat, sampled for the same time period as pan and pitfall traps. Note: modified
trap types are possible (e.g., combined pan trap with malaise head, and horizontal screening);
Specimens preserved for later DNA extraction.
2487
(References: Bolduc, et al. 2013; Ernst and Buddle (In press); Karlsson, et al. 2005; Salmela 2011)
2488
4) Decomposition & Nutrient Cycling:
2489
2490
Attribute 1 & 2: Species richness and abundance. These two
attributes are collected at the same time, and together allow for assessment of community diversity.
2491
2492
2493
Metric: abundance of dominant taxa per m2 at specific depths,
result in measure of community diversity per location; taxonomic resolution: Species-level for
Collembola, higher levels for Acari, Enchytraeidae, and other taxa.
2494
2495
2496
2497
2498
Methods: Soil and turf cores, taken on site, returned to the
laboratory for extraction, with validated extraction apparatus (i.e., Berlese funnels or MacFadyen
high gradient extractors, O'Connor's Funnel for wet extraction). For each habitat, minimum of 10
samples per sample location recommended to provide a mean population density m-2 with
variability estimate, 95% confidence limits. Minimum stratum is the top A-horizon.
2499
2500
Attribute 1 & 2: Relative abundance / Biomass and Phenology
(References: Aastrup, et al. 2009; ISO 2006)
5) Herbivory
Attribute 1: species richness
109
2501
2502
2503
Metric: number of species of herbivores, per plant, or per area
sampled. Taxonomic resolution: family-level, but stored for DNA extraction or further taxonomic
research.
2504
2505
2506
2507
Method: timed visual surveys for dominant taxa of herbivores
including but not restricted to Lepidoptera Hymenoptera larvae, Hemiptera. Timed surveys done on
dominant vegetation; timed beat-sheet samples for woody vegetation (done for dominant plant
type/species, repeated per habitat).
2508
(References: Mjaaseth, et al. 2005; Raimondo, et al. 2004)
2509
Attribute 2: herbivory
2510
2511
Metric: plant damage (as percent or category) expressed on a per
plant basis, separated by damage type (e.g., skeletonize, mine, gall).
2512
2513
2514
2515
Methods: dominant plant type selected and recorded, minimum of
five leaves per plant, five plants per vegetation type (or: selective plant parts for gall counts).
Randomly select leaves/shoots for examination, record & damage per leaf or use categorical class as
necessary; repeated for dominant vegetation type per habitat.
2516
(References: Roininen, et al. 2002; Rossiter, et al. 1988)
2517
4.5.2.4 Recommended protocols:
2518
2519
2520
2521
2522
2523
2524
2525
2526
2527
2528
2529
2530
2531
2532
2533
2534
2535
2536
2537
2538
2539
2540
An expanded set of Recommended protocols can be added to the Essential protocols in order to
provide data about more attributes. The recommended protocols may be important to document
the full range of natural variation and to assess thresholds and tipping points. In many cases, the
additional data collection involves expanding the taxonomic scope and/or timing of sampling.
1) Blood-feeding: Abundance of blood-feeding insects (e.g., mosquitoes) can be estimated with
standardized sweep-net samples taken around the collector's bodies; index is relative number of
biting flies.
2) Pollination: The additional attribute for this process is distribution. Here, opportunistic sampling
of key pollinators can be done through community-based monitoring efforts, with a focus on Apidae.
Bumble bees are readily sampled with a sweep-net. It is also straightforward, and simple to
establish grids of pan traps (yellow/white/blue) and/or vane traps.
3) Predation by birds: protocols for expanding to relative abundance and distribution will require
additional laboratory work for measures of species richness and abundance.
4) Decomposition & Nutrient Cycling: broader taxonomic approach by including a selection of more
than one of the main taxonomic groups. Measures of ecological functioning in terms of
decomposition rate (litter-bag, native foliage); inorganic nutrient levels in soil. Response variables:
community diversity, distribution, % mass loss, NPK levels Taxonomic resolution: species, when
possible.
110
2541
4.5.2.5 Abiotic data collection:
2542
2543
2544
2545
Metadata to be collected at each location: dereference (latitude : longitude, elevation), slope,
aspect, disturbance, land-use, proximity to roads/human settlements, local weather conditions, soil
type, geology, proximity to ocean, proximity to snow or glaciers, hydrology, dominant vegetation,
permafrost depth, organic matter depth, active layer depth
2546
2547
2548
4.5.3
Site establishment data
2549
2550
Recommended abiotic data to be collected at each location: decomposition (litter bags with native
foliage), nutrient budgets (N by compartments), pH, temperature, humidity.
2551
2552
2553
4.5.4
Sampling sorting, long-term storage, and DNA barcoding
2554
2555
2556
2557
2558
2559
2560
2561
2562
Any invertebrate monitoring program requires a short and long-term plan for specimens. In the
short-term, bulk samples should be sorted minimally to Order (or lowest taxonomic level whenever
possible) as soon as possible after collecting. Samples should be data-based (with metadata)
immediately and residues put into ethanol for long-term cold-storage so that DNA can be preserved
and later extracted for DNA Barcoding analyses (e.g., see application in Mutanen, et al. 2012). Longterm, environmental barcoding methods have potential for use in Arctic monitoring plans (e.g., next
generation sequencing, (see Hajibabaei, et al. 2011)), but in the shorter-term (10-15 years),
specimens (sorted, identified) are required to fill in the immense gaps in knowledge about Arctic
invertebrates.
2563
111
2564
2565
2566
2567
2568
Figure. 4.4. The Arctic terrestrial invertebrates monitoring conceptual model; the bottom panel
shows a model of the soil ecosystem.
112
Recommended
Relative
abundance,
terrestrial and
aquatic, via
sweep sample
/ in ponds /
densities
COMMENTS
TEMPORAL
RECURRENCE
Basic /
Advanced
(for
taxonomy)
3-5 yrs
Examples: # per unit effort
(time, or number of
Basic /
sweeps), density per unit Advanced
area/volume; baited
(for
traps; for aquatic, may
taxonomy)
need special nets
3-5 yrs
Larvae collections in
aquatic habitats, sweep
net samples for adults;
sweep net samples
around ungulates
Local
Local
PROTOCOL
COMPLEXITY
METHOD
SCALE
PARAMETER
Essential
Species
richness
(estimates) local
Knowledge of the entire
community is important;
invertebrates such as biting flies
are important for wildlife and
humans, as disease vectors, etc.
Community monitoring could be
used to collect data on species
richness.
Abundance
PRIORITY
ATTRIBUTE
Community
structure
(diversity;
species
richness)
Difficult to get accurate
estimates of density,
although a relative activity
index may be possible.
Abundance of these species
could act as a driver for large
mammals.
BLOOD-FEEDING: Diptera (e.g., Culicidae, Simuliidae,
Ceratopogonidae, Tabanidae)
FOCAL
ECOSYSTEM
COMPONENT
Table 4.4. List of focal ecosystem components for terrestrial arthropods (FECs: major biodiversity elements), their attributes (compositional, structural,
and functional aspects), monitoring priority of attributes, parameters of attributes (individual measures/methods to quantify attributes), geographic scale,
method (monitoring technical approach or reference to methods), protocol complexity (basic or advanced) and temporal recurrence (how frequently
monitoring should be conducted).
113
Community
Structure
(Diversity)
Same as above &
historical collections (i.e.,
previously collected
material)
Basic /
Advanced
(for
taxonomy)
3-5 yrs
Recommended
Date of first
emergence,
seasonal
activity
Local
Same as above, plus
traditional knowledge
(local, community)
Basic
3-5 yrs
Recommended
Body
condition, life
stage; sexes
Local
Analyses of sample sets;
identification of sexes and
stages
Basic /
Advanced
(for
taxonomy)
Varies by
group: As
req. (min
5 yrs)
Local
Flower visitation
observations, sweep nets,
Basic /
passive sampling, i.e.,
Advanced
collections in standardized
(for
yellow / white / blue pan
taxonomy)
traps (grids of traps), vane
traps
3-5 yrs as
a
minimum;
annually if
possible
Bees are important in arctic systems, and
taxonomically well-known but standardized
techniques that are quick/efficient are lacking.
POLLINATION: Hymenoptera (e.g. Colletidae,
Andrenidae, Halictidae, Megachilidae,
Apidae), Diptera (many families)
Demographics
Important Understanding
but requires
range
full season expansions of
monitoring these species
which may
could be
not be
important in
possible some locations.
Phenology
Recommended
Regional/
panArctic?
Perhaps in
the future
blood
samples
could be
analyzed
(DNA
barcodes)
Distribution
Species
presence/
absence
Essential
Species
richness
(estimates)
114
Distribution
Essential
Presence /
Absence
Phenology
Recommended
Seasonal
activity
patterns
Pollination
success, fruitset, and yield
Essential
Fruit set and
seeds
Basic /
Advanced
(for
taxonomy)
Ideally,
Annually
Local to
panArctic
Same as above, plus other
published literature,
historical collections &
consultation with experts
Basic /
Advanced
(for
taxonomy)
Ideally,
Annually
Local
Traditional/ community
knowledge
Basic
Ideally,
Annually
Basic and
Advanced
3-5 yrs as
a
minimum;
annually if
possible
Some focal surveys
required; traditional/
community knowledge
Local
115
Difficult to
standardize
'relative
abundance' in
monitoring
program
Local
# visitations per unit time;
number of specimens per
sweep, net transect, or
timed sweep-net surveys
Potentially
This process is facilitated
Some pollinator
important
but not species (e.g.
by arthropods, but is not feasible without
a direct measure of
could be
specialist and Apidae)
pollinator species; this
monitored via
intense
attribute is a driver for
community
monitoring
all
plant fitness.
efforts.
season
Abundance
Relative
number per
Recommended
sweep
transect, or
flower surveys
Essential
Relative
number per
trap
Local
As above; can conduct
standardized area
sampling to achieve
density estimates also
(labour intensive)
Distribution
Recommended
Presence /
Absence
Regional,
panArctic
As above, but include
consultation with experts,
historical collections
Basic and
Advanced
3-5 yrs
See above
Local
Same passive sampling
approach but done over
entire active season, from
snowmelt until snow
arrival; possible
community / local
knowledge?
Basic
(some
taxonomy
req.)
3-5 yrs
Phenology
Essential
Seasonal
activity
patterns
Local
Standard grids of pan
and/or pitfall traps
Basic
(some
taxonomy
req.)
3-5 yrs
Basic and
Advanced
3-5 yrs
Possible if standard
protocols can be Spiders as top predators and
used. This is a key
as easily sampled taxa
driver for
should be a priority
insectivorous birds.
Relative
abundance &
Biomass
Potentially important
(e.g. for vertebrate
feeding), but requires
season-long monitoring
plan
FOOD PREY FOR BIRDS: Araneae, Diptera (e.g., Tipulidae), Lepidoptera
Recommended
Species
richness
(estimates) local level
Community
Structure
(Diversity)
116
DECOMPOERS & NUTRIENT- CYCLING: Soil Mesofauna (Collembola,
Acari Enchytraids), Detrivores s.l. (Fungivores, Bacterivores,
Saprophages), macroinvertebrates (e.g., earthworms), microfauna,
microorganisms
Body condition
Community
Structure
(Diversity)
Essential (wolf
spiders)
Essential
Wolf spiders only: body
size index; clutch size of
females, parasitism rates
Basic and
Advanced
3-5 yrs
Simple to conduct
for some taxa, e.g.
wolf spiders
Species
richness
(estimates) local
Local
Local
Soil and turf cores, taken
on site, returned to
laboratory for extraction
(i.e., Berlese funnels or
MacFadyen high gradient
extractors, O'Connor's
funnel for wet extraction)
Basic and
Advanced
Annual
Sampling can be conducted over a short time should that be all that
logistics allow. Collembolans are feasible to include concerning
taxonomy. A trait-based (light-weight pseudotaxonomy short-cut)
approach may be proposed in the future. Enchytraids and mites are
difficult to identify. DNA Barcoding will provide a solution to this
obstacle and deliver presence/ absence data (CBOL programme). It is
also possible to use higher level taxonomy instead of species to
increase feasibility.
Body
condition
index, body
size index,
clutch size
(wolf spiders)
117
Distribution
Demographics
Local
Numbers calculated per
sq. m at a specified depth
Basic and
Advanced
Annual
Essential
Presence/
absence
Local/
regional/
panArctic
All collembolan life-forms
(~4 types, representing
the vertical stratification
from epi-phytic to true
soil-dwelling). The
horizontal distribution is
not included in
environmental surveys,
except for variance
estimates between
samples collected in a
random but stratified
manner. [Same species
and target species/groups.
Consult historical
collections / experts]
Basic and
Advanced
3-5 yrs
Recommended
Phenology,
voltinism, pgr
(population
growth rate)
Local
Repeated sampling
Basic and
Advanced
Monthly
Essential
118
Abundance data (i.e.
For some taxa, getting presence/ absence is
density)
are collected with
possible and high priority, given high feasibility the
same
protocols as used
(i.e. taking soil cores); DNA barcoding will
for
determining
species
facilitate this in the future
richness; straight-forward.
Abundance
Density
estimates i.e.,
number per
standard soil
core
HERBIVORES (Lepidoptera, Symphyta, Aphidae, Hempitera,
Coleoptera, Acari)
Decomposition Recommended
Community
Structure
(Diversity)
Abundance
NPK
Local
Sampling nitrogen,
phosphate, potassium:
chemical analyses
Advanced
As req.
% mass loss
Local
Method to be updated
Basic and
Advanced
As req.
Local
Opportunistic collection of
adults and/or
standardized sweep
samples) / systematic
surveys of plants for
larvae
Basic
(some
taxonomy
req.)
3-5 yrs
Local
Opportunistic collection of
adults; standardized
sweep samples;
standardized beat-sheet
sample / systematic
surveys of plants for
larvae
Basic
(some
taxonomy
req.)
Annually
Essential
Species
richness
(estimates) local
Recommended
Relative
number per
sweep
transect;
visual surveys,
number per
beat-sheets
(density)
119
These nutrients These nutrients
are a result of
are a result of
invertebrate
invertebrate
activity within the activity within
soil/ tundra. the soil/ tundra.
Recommended
Given the popularity of
Difficult to achieve by nonbutterflies, and ease of
specialist
identification, local estimates
of species could be worthwhile
Nutrient levels
This is an
indirect measure Feasible and
of insect feeding, important (e.g.
Time consuming;
range
may be difficult expansions)
to achieve.
3-5 yrs
Essential
Presence /
Absence
Herbivory
Essential
Plant damage
Local
% leaf area lost, index of
leaf damage, leaf miner
damage
Basic
Annually
Body
Condition
(resource
acquisition,
stress levels)
Recommended
Body size,
pupal mass
Local
Weight of caterpillars,
pupal cases
Basic
3-5 yrs
Recommended
Seasonal
activity
patterns
Local
Timing of first
appearance, local/
traditional knowledge,
season-long sampling
Basic
Annually
Recommended
Population
estimates
(cycles),
larvae/adult
dynamics
Local
See methods above for
abundance
Basic
Annually
May be high
priority if
damage is
significant
Basic and
Advanced
Distribution
Requires seasonlong monitoring,
which is time
consuming and
difficult, but
potentially of high
priority to monitor
outbreaks
Same, but also using
expert knowledge, edatabases (e.g., ebutterfly), community/
local knowledge
Local/
regional/
panArctic
Phenology
Demographics
120
2569
2570
5
Data Management Framework for the Arctic Terrestrial
Monitoring Plan
2571
2572
5.1
Data Management Objectives for the CBMP
2573
2574
2575
2576
2577
2578
2579
2580
2581
CAFF’s CBMP data management objectives are focused on the “art of the possible”—developing
data-management systems that facilitate improved access to existing and current biodiversity data
and integration of these data among disciplines, while maintaining the data holders’ ownership and
control of the data. The CBMP aims to create a publicly accessible, efficient, and transparent
platform for collecting and disseminating information on the status and trends in Arctic biodiversity.
In essence, the primary objective is to create linkages to data where it already resides. However, in
instances where this is too onerous, CBMP aims to provide alternative data management structures
to host the data for partners. This objective will be instrumental in achieving the Program’s mandate
to report on trends in a timely and compelling manner so as to enable effective policy responses.
2582
2583
2584
2585
2586
2587
2588
It is expected that each country would still be responsible for supporting data management (e.g.,
QA/QC of data and compilation of existing national datasets) and providing data from their
individual monitoring networks (i.e., the data holders). In contrast, the CBMP will focus efforts on
building the mechanisms to access and integrate these data across countries and networks, as well
as promoting a common, standardized data-management approach among the countries. For this
approach to be successful, it is imperative that appropriate national and sub-national datasets are
identified (metadatabases) and made available (interoperable linkages) to the CBMP.
2589
2590
2591
2592
2593
2594
2595
2596
2597
2598
Biodiversity data sources and formats vary widely across the Arctic. Thus, it will be challenging to
access, aggregate, and depict the immense, widely-distributed, and diverse amount of this terrestrial
biodiversity data from the many contributors involved in this monitoring. A related challenge is to
integrate and correlate this information with other relevant data (e.g., physical, chemical, etc.) to
better understand the possible causes driving biodiversity trends at various scales (regional to
global). Furthermore, it is critical to deliver this information in effective and flexible reporting
formats to facilitate decision-making at a variety of scales from local to international. Meeting these
challenges will significantly improve policy and management decisions through better and timelier
access to current, accurate, and integrated information on biodiversity trends and their underlying
causes at multiple scales.
2599
2600
2601
2602
2603
2604
2605
2606
In some cases, especially for the higher trophic levels, biodiversity data and relevant abiotic data
layers are already available and can be integrated into the CBMP’s Data Portal system
(www.abds.is). However, the task of aggregating, managing, and integrating data for the lower
trophic levels is arduous, and it may be some time before such information can be accessed readily
via the CBMP Data Portal. The establishment of national Terrestrial Expert Networks (TEN) as
defined in Section 8.1, and support from each nation and the CAFF Data Manager will facilitate this
process through the adoption of common data and metadata standards and the development of
common database structures.
2607
2608
The following sections provide an overview of the data-management framework to be used for
managing the outputs of the CBMP-Terrestrial Plan. Such a framework is essential to ensure
121
2609
2610
effective, consistent, and long-term management of the data resulting from coordinated monitoring
activities.
2611
2612
5.2
2613
2614
2615
2616
2617
2618
Effective and efficient data management is fundamental to the success of the CBMP and its
monitoring plans. A measure of success will be the ability to effectively connect individual partners,
networks, and indicator-development efforts into a coordinated data-management effort that
facilitates data access and effectively communicates Arctic biodiversity status and trends to a wide
range of audiences and stakeholders. Executed correctly, data management can fulfill the following
functions:
2619
2620
Quality Assurance: ensures that the source data sets and indicator development methodologies are
optimal and that data integrity is maintained throughout processing;
2621
2622
Consistency: encourages the use of common standards and consistent reference frames and base
data sets across parameters and networks;
2623
Efficiency: reduces duplicate efforts by sharing data, methodologies, analysis, and experience;
2624
Sustainability: ensures archiving capability and ongoing indicator production;
2625
2626
Enhanced Communications: produces and distributes information through integrated web-based
services, making indicator methodologies accessible and providing source metadata;
2627
2628
2629
2630
Improved Linkages: ensures complementarities between various networks and partnerships and
with other related international initiatives, other indicator processes (national, regional, and global),
and global assessment processes (e.g., the Global Biodiversity Outlook and Millennium Ecosystem
Assessment); and
2631
2632
Enhanced Credibility: provides transparency with respect to methodologies, data sets, and
processes.
2633
2634
2635
2636
2637
2638
2639
Implementation of the CBMP-Terrestrial Plan will rely on participation from many partners. An
efficient and user-friendly metadata and data management system will facilitate this collaboration,
providing multiple benefits as outlined above. It will offer unique opportunities for monitoring
networks to exchange data, draw comparisons between data sets, and correlate biodiversity data
with data derived from other networks, using a common, web-based platform. A roadmap for data
management, the CBMP Data Management Strategy (C. Zöckler, 2010; unpublished), has been
developed to guide the management and access of metadata and data among the CBMP networks.
Purpose of Data Management
2640
2641
2642
2643
5.3 Coordinated Data Management and Access: the CBMP Web-based Data
Portal
122
2644
2645
2646
2647
2648
While a large amount of terrestrial biodiversity information is produced by various networks in
diverse formats, much of it is inaccessible, not reported, or in user-unfriendly formats. New, webbased data management tools and new computational techniques have provided an opportunity for
innovative approaches for the data management and integration that is critical for a complex,
international initiative such as the CBMP.
2649
2650
2651
2652
2653
2654
2655
2656
2657
CAFF’s CBMP has developed a state-of-the-art data portal (www.abds.is ), which is a simple, webbased and geo-referenced information network that accesses and displays information on a
common platform to encourage data sharing over the Internet. The data portal represents a
distributed data management structure where data holders and publishers retain ownership,
control, and responsibility for their data. Such a system provides access to immediate and remotely
distributed information on the location of Arctic biological resources, population sizes, trends, and
other indicators, including relevant abiotic information. As well as providing a point for Arctic
biodiversity information, the data portal provides a simple approach for experts to share
information through the web and allows for the integration and analysis of multiple data sets.
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
The CBMP’s data portal requires the establishment of a series of data nodes, with each data node
representing a data type or discipline (e.g., caribou, shorebirds). Each data node will be established
and supported nationally, most likely through connections to the TEN that will be established in each
country (see Chapter 8 for details). The CAFF Data Manager will interact with the national nodes to
ensure inter-operability and data aggregation and will provide overall maintenance and
management of the resulting pan-Arctic aggregated data in the most efficient way possible. In some
cases, where appropriate, the CBMP will establish web-based data-entry interface systems (web
services) tailored to each data node/discipline, allowing researchers in each country to enter their
data on an annual or semi-annual basis (depending on the frequency of data collection) via the
Internet. This information will be aggregated, automatically populating a database established at an
organization of the national TEN’s choosing. The TEN leads will have overall administrative privileges
(password-controlled) to view, maintain, and edit the database. Each expert within a discipline
group will have access (via a password) to enter and maintain their own data. Each TEN will be
responsible for defining and implementing the analytical approaches to generating the indicators.
The CBMP will work with each TEN to establish analytical outputs, via the Data Portal, tailor-made
for the data collected and housed at the data node. Priority indicator data will be managed via the
web portal whereas other dataset compilations can be directly archived at the CAFF Secretariat or
through an agreement with an existing data center.
2676
2677
2678
2679
2680
2681
Users (e.g., scientists, decision-makers, and the public) will have password-controlled access to the
data outputs via the CBMP Data Portal. Users will be able to perform set analyses (defined by each
TEN) on the Portal, which will immediately access the most current data at the data node and
display the output of the queried analysis. Much of the initial work in the implementation phase of
the CBMP-Terrestrial Plan will involve aggregating existing data sets to create pan-Arctic data layers.
The life cycle of the data, from collection to presentation, is shown in Fig. 5.1.
2682
2683
2684
2685
2686
The CBMP Data Portal will be flexible, freely accessible or password driven as appropriate, and
customizable to serve a diversity of clients (Fig.5.2). The general public will have access to broad
indicators and general information on Arctic biodiversity data trends. National and sub-national
governments as well as the national TENs will have the opportunity to customize the Portal for their
own purposes (e.g., display only the geographic scope of relevance to them). Both governments and
123
2687
2688
2689
TENs will have the authority to choose which data layers are publicly available. In addition, they will
have a password-controlled domain to allow the inclusion of other data layers that are not publically
accessible (e.g., unpublished data or draft reports).
2690
2691
2692
2693
This model of operation allows for user involvement at a variety of stages and can accommodate a
large number of participants. The aim is to facilitate complete access to the collective knowledge,
analysis, and presentation tools available from the many participants and stakeholders both within
and outside the Arctic community.
2694
2695
2696
2697
2698
2699
2700
The web-based portal will serve two purposes for the CBMP. First, it will provide access to georeferenced information from within partner networks, as well as providing a common platform with
multiple entry points for controlled data access, integration, harmonization, and delivery. Secondly,
it will enable a wide range of user groups to explore trends, synthesize data, and produce reports
with relative ease. The web-based data portal will generate indicators representing status and trend
analyses, which in turn will be reported by the CBMP through a variety of means. These could
include turnkey web-based reports and status and trends reports at multi-year intervals.
2701
2702
2703
2704
2705
2706
2707
Development of this distributed system will necessitate the adoption and use of existing and widely
accepted standards for data storage and query protocols, along with high-quality and standardized
metadata and web servers (spatial and tabular). The metadata will be housed on an existing metadatabase system (Polar Data Catalogue http://www.polardata.ca/whitesnow/ ) allowing for simple
and efficient access to a large and constantly updated, web-based, searchable, geo-referenced
metadata system. The Arctic terrestrial monitoring identified as core to the implementation of the
Terrestrial Plan will be input into this meta-database.
2708
2709
2710
2711
2712
Geo-referencing will be critical to the successful integration of disparate data sets. Resolving the
different spatial recording schemes used between the various data nodes and data holders—as well
as the ranges of data volumes and bandwidth—will be challenges to overcome. Techniques will be
devised to convert data into a standard format for integration. These technical issues will be
addressed during the implementation phase.
2713
2714
2715
5.4
Data Storage, Policy and Standards
2716
2717
2718
2719
2720
A decentralized data storage system is proposed for the CBMP web portal because it offers a
solution to concerns over data ownership and copyright. Through this system, the storage,
responsibility for and ownership of the data will always remain with the data collector, publisher
and/or holder. Although the data are decentralized, access to and depiction of the data is unified,
allowing for multiple integrations for the user.
2721
2722
2723
2724
2725
2726
2727
CAFF’s CBMP encourages data providers to comply with the Conservation Commons
(http://conserveonline.org/workspaces/commons/ ) and IPY Data Policy (http://ipy.org ) on the
delivery of free biodiversity data to the public, and equivalent legislation in the European Union for
spatial information, such as the INSPIRE Directive (http://inspire.jrc.ec.europa.eu/ ). The web portal
will allow for organized and restricted access to data where necessary. Compliance with accepted
data policies and provision of data to the CBMP Data Portal system will result in password access
being provided to the data layers found on the Data Portal. This incentive-driven approach should
124
2728
2729
2730
2731
encourage scientists and others to contribute their data to the Portal as it will result in their access
to other data layers relevant to them. Depending on the project and publication circumstances, the
CBMP suggests a delay of no more than two years before information is released to the public,
according to data type and project history.
2732
2733
2734
2735
2736
2737
2738
2739
2740
In order for the various networks involved in implementing the CBMP-Terrestrial Plan to collaborate,
input, and share data and metadata, common data and metadata standards should be followed.
Freely available software allows users to apply these metadata conveniently and post them online
with the clearinghouses (e.g., Polar Data Catalogue: http://www.polardata.ca/). Because data that
lack details about their origin, methods, dates, collector names, and so on (metadata) can be
virtually unusable, both data and their metadata are crucial requirements and thus requested by
funding agencies and the data initiatives cited here. CBMP will encourage access to interoperable
metadata nodes or storage at CBMP’s main metadata node (at the Polar Data Catalogue) as the first
step in enhancing access and coordination of Arctic data.
2741
2742
2743
2744
2745
Collection
Aggregation
Analysis &
Synthesis
Presentation
2746
2747
2748
2749
2750
Monitoring
Networks &
Terrestrial
Expert
Nations
Networks
2751
2752
2753
Terrestrial Expert
Data Portal
Networks & Portal
2754
2755
2756
2757
Figure 5.1. A simplified overview of the steps involved in accessing, integrating, analyzing, and
presenting biodiversity information via an interoperable web-based data portal and an indication of
the responsibilities at each step.
125
2758
2759
2760
2761
2762
Figure 5.2. Illustration depicting the Data Portal concept and how clients can utilize the system to meet their specific needs.
126
2763
6
Data, Samples and Information Analysis
2764
2765
6.1
Basis for Analysis
2766
2767
6.1.1
Start-up phase
2768
6.1.1.1 Stakeholder and partner engagement
2769
2770
2771
2772
2773
2774
The successful implementation of the CBMP-Terrestrial Plan will depend entirely upon the
engagement and participation of Arctic terrestrial biodiversity monitoring practitioners, stakeholders
and users. The start-up phase will continue to recruit partners and engage them in the monitoring
strategy. This outreach was initiated at the planning phase and must continue through the
implementation phase. Active dialogue and communication with existing and new partners will be
essential throughout the process.
2775
2776
6.1.1.2 Understanding baselines and natural variation
2777
2778
2779
2780
2781
2782
As described in section 3.7 and 3.8, the CBMP TEMG aims to characterize the range of natural
variation for each identified parameter, at the appropriate scale. This context will help to interpret
the significance of an observed biological condition and trend. Moreover, assessing the range of
variation needs to be at the appropriate ecological scale. For example, for cyclical populations, the
CBMP-Terrestrial Plan may assess both the population amplitudes and the range of changes in the
cycle of populations.
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
During the start-up phase, temporal and spatial information of selected parameters will identify
baseline conditions ascribed to a particular point in time or space and describe a parameter’s range
of natural variation. Sources for this historical information will include traditional ecological
knowledge and existing long-term monitoring data. Initiatives such as the International Polar Year
“Back to the Future” research project (http://www.btf.utep.edu/) are particularly helpful for
establishing long-term trends and natural variation. Historical satellite imagery can be compiled to
establish baselines dating back to the 1970’s or 1980’s. Museum records, inventory data and
published literature will also assist in building the historical ecological conditions or baselines. An
International Arctic Vegetation Database (Walker and Raynolds 2011) will be a helpful tool for
assessing the baseline of Arctic vegetation communities. To this end, additional Identification and
digitization of historic datasets may be required. Where this has been done, access and
coordination of historical datasets would follow. Natural archives in sediment can also be
investigated using pollen and microfossil identification (e.g. Jørgensen, et al. 2012) and new
advances in DNA barcoding to complement modern data on historical trends (see below), within the
capacity and requirements of the program. Establishing baselines from existing data may not be
possible for all taxa, notably those which are data-deficient (e.g., terrestrial invertebrates). Several
years of data collection following implementation of the CBMP-Terrestrial Plan may be required to
identify spatial and temporal baselines.
127
2801
2802
2803
2804
2805
2806
2807
2808
During the start-up phase of implementation, methods to harmonize and integrate data from
differing monitoring protocols, including traditional knowledge, for the key parameters in the CBMPTerrestrial Plan will be identified, and need to be developed as required. This may involve creating
strategies to calibrate data from one protocol to another and to calibrate between differing levels of
study precision or resolution. Maintaining documentation for the transformation or calibration
process will be essential. Where these integration methods already exist (e.g. Elmendorf, et al.
2012), and have proven to be robust and rigorous, these will be reviewed by the CBMP-Terrestrial
Plan and considered for adoption.
2809
2810
2811
2812
Once these harmonization methods are in place, the integration and meta-analysis of existing data is
recommended to inform an assessment of baseline conditions and trends to date. The data
assessment tools or method will depend on the focal ecosystem component, attribute and
parameter of interest and the spatial scale over which the analysis is required.
2813
2814
6.1.1.3 Statistical analysis of existing data and requirements for future data
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
Power analysis quantifies the relationship between the elements of a statistical inference including
effect size, variation, confidence, power and sample size. It is a tool to assess the costs and benefits
of alternative sampling designs and to estimate the quality of information that will result. A power
analysis of existing integrated datasets related to the CBMP-Terrestrial Plan parameters is
recommended to identify, where possible, the confidence in observed changes based on existing
data relative to the monitoring question. Power analysis on data deficient taxa may not be possible,
however, as a result of, for example, a lack of a priori information on variance estimates. An
assessment existing and anticipated monitoring capacity to assess change across the spatial scales of
interest for each CBMP-Terrestrial Plan parameter, using the spatial strata identified in Chapter 4
will be undertaken.
2825
2826
2827
2828
2829
2830
2831
2832
2833
2834
Power analysis should also be used to resolve the appropriate sample size required to detect change
with the confidence desired at the scale desired. This will necessarily require further discussion of
desired precision and confidence of the monitoring scheme with Arctic stakeholders. Power analysis
has been conducted for some CBMP-Terrestrial Plan parameters at specific spatial scales. For
example, a power analysis of four Arctic plant communities in Canada at two sites recommended
monitoring between 10 and 20 plots within each plant community and grouping abundances by
functional group, rather than by species (Hudson and Ouimet 2011). In the start-up phase,
oversampling is recommended where capacity exists in order to support analysis of required sample
size to obtain sufficient confidence and power. These analyses can be used to identify priority areas
to identify partnerships for future data collection in support of the CBMP-Terrestrial Plan.
2835
2836
2837
6.1.2 Implementation phase
2838
2839
2840
Chapter 4 describes the recommended monitoring methods and temporal sampling frequency for
each priority parameter. CBMP-Terrestrial Plan implementation partners and stakeholders will be
encouraged and supported, as possible, to gather and process data following the recommended
128
2841
2842
2843
2844
2845
sampling design and to share and integrate the data as described in Chapter 5. Digitization and
sharing, using common accepted standards, and creating comprehensive metadata will be
paramount to the long-term use and accurate interpretation of data. As data is gathered, adaptation
and tailoring of the CBMP-Terrestrial Plan to suit the needs of users and enhance data quality and
monitoring effectiveness may be required.
2846
2847
2848
6.2
Data Samples
2849
2850
6.2.1
Sample processing
2851
2852
2853
2854
2855
2856
2857
Some CBMP-Terrestrial Plan recommended parameters will require sample processing and further
analysis, including specimen sorting, taxonomic work, genomic testing or contaminant testing.
Methods for sample processing should follow recommended protocols. Where required,
coordinated, clear procedures for sample processing should be developed. The procedures must
describe the chain of responsibility for sample processing and maintain high standards. Where such
procedures exist, they should be harmonized. Some methods for sample processing are described in
Chapter 4.
2858
2859
2860
6.2.2
Sample archiving
2861
2862
2863
2864
2865
2866
2867
2868
2869
The CBMP-Terrestrial Plan recommends that participating monitoring agencies follow standardized
protocols for appropriately storing and archiving biological data collections. This will be true for all
data sources including remotely sensed products, genomic data, and biological samples. For
example, vegetation samples may be stored in herbaria, including digital herbaria, and invertebrate
samples should be sorted, preserved in ethanol, and stored in long-term cold storage, as described
in Chapter 4. Appropriate DNA preservation of samples will enable future barcoding analyses. Longterm, environmental barcoding methods have potential for use in Arctic monitoring plans (e.g., next
generation sequencing (Hajibabaei, et al. 2011)), but in the shorter-term (10-15 years), specimens
(sorted, identified) are required to fill in the immense gaps in knowledge about Arctic invertebrates.
2870
2871
2872
6.2.3
Tools, samples, and baselines to complement monitoring and future surveillance efforts
2873
2874
2875
2876
2877
2878
The potential of powerful new approaches for inclusion in current and future monitoring activities
was mentioned briefly in Chapter 1. Such approaches include technology-based tools such as
analyses of genetic data and stable isotope signatures, and satellite-based tracking. Novel tools are
improving our knowledge on the ecology of species, enable monitoring changes in population
connectivity and health, and provide a method to detect the effects of shifting drivers from human
activities and climate change (e.g. the immigration of non-native lineages, transport of
129
2879
2880
contaminants, and adaptive potential of populations). To illustrate the value of such tools, some
applications are discussed below.
2881
2882
2883
2884
2885
2886
2887
2888
2889
2890
2891
2892
2893
2894
2895
2896
2897
2898
2899
2900
2901
2902
2903
2904
2905
2906
2907
2908
2909
2910
2911
2912
2913
2914
2915
Ancient DNA methodology and advances in wildlife forensics have been invaluable in studies of
populations even when species have migrated out of an area, are rare or difficult to study, or are
sensitive to direct disturbance. Through improvements in technology in laboratory equipment (e.g.
Next-generation sequencing technologies) and computing (e.g. computation-intensive analyses and
data storage), and through the continued optimization of sample-collection, preservation,
extraction, and screening methods, hair, feathers, egg fragments, degraded carcasses, museum
skins, and even fecal samples can be used for studies of species. For example, even short fragments
may be useful for species identification and clarifying systematics (e.g. DNA Barcoding and
environmental sequencing)(Allcock, et al. 2011; Spies, et al. 2006; Thomsen, et al. 2012), and for
inferring the presence or origin of taxa in historic samples (Lee and Prys-Jones 2008; Lindqvist, et al.
2010; Martin-Gonzalez, et al. 2009). Novel cryptic species and their status as endemics or
representatives of cosmopolitan taxa have been uncovered by complementing other morphology –
based taxonomic or lab culturing approaches (D'Elia, et al. 2008; Darling, et al. 2007; Friesen, et al.
1996; Kreier, et al. 2010; Vecchione, et al. 2009). Genetic studies can complement behavioural
studies of reproduction (Ibarguchi, et al. 2004; Lunn, et al. 2000), and even of the future
reproductive potential of species through dormant egg or seed banks (Gómez and Carvalho 2000).
Combining phylogeographic (distribution of lineages) and phylogenetic (relationships among
lineages) analyses can facilitate the distinction between expanding immigrant lineages from endemic
taxa, tracing the origin of individuals, following colonization routes, and tracing species invasions
and epidemics (Caldera, et al. 2008; Diaz-Perez, et al. 2008; Holderegger, et al. 2003). Fecal samples,
even from small avian taxa, are yielding DNA for population studies, and even providing insight into
the prey species and diet of these taxa (Deagle, et al. 2007; Idaghdour, et al. 2003). Population
genetics (sampling individuals within or/and among populations) enables investigating diversity
(heterozygosity, the number of alleles and their frequency), genetic structure and meta-population
dynamics (sources and sinks; population age), inbreeding and/or outbreeding depression (in small
populations, the negative effects of breeding with close kin, or of locally-adapted populations
becoming ‘swamped’ by immigrating individuals with unsuitable alleles from elsewhere)(Faria, et al.
2010; Ludwig 2006). Comparative genomics and functional genomics approaches continue to be
costly, but the availability of freely-accessible bioinformatics databases such as the Barcode of Life
Database (http://www.barcodinglife.com/), GenBank (http://www.ncbi.nlm.nih.gov/genbank/),
and the European Bioinformatics Institute (http://www.ebi.ac.uk/Databases/), provide outstanding
resources to facilitate low-cost but high-quality and high-impact research. Furthermore,
comparative studies of functional genes can provide insight into the ability of species and
populations to adapt to future change (e.g. hemoglobins of cold-adapted taxa and warming
temperaturesAndersen, et al. 2009; Pörtner, et al. 2007).
2916
2917
2918
2919
2920
2921
2922
Biogeochemical analyses of stable isotope signatures and trace elements provide broad to fine-scale
geographic and temporal reference points for samples. Such analyses in conjunction or in addition to
the use of genetics, satellite-based tracking technologies, and other tools, can provide crucial
information on species movements, population declines, diet, and environmental conditions
including the presence of contaminants. For example, temporal diet shifts and population
bottlenecks have been inferred for some avian species following DDT exposure (Brown, et al. 2007;
Nocera, et al. 2012). For migratory species, stable isotope signatures have been invaluable to study
130
2923
2924
2925
2926
2927
2928
2929
2930
2931
2932
2933
2934
2935
2936
2937
2938
2939
movements and diet (particularly δ 13C and δ 15N to infer trophic level, and δ 2H to infer latitudinal
and altitudinal gradients in a general sense), and in combination with genetics and satellite-based
tracking tools (e.g. data loggers and accelerometers), these approaches are revolutionizing our
studies of migratory species which are difficult to observe outside of the reproductive period
(Chabot, et al. 2012; Clegg, et al. 2003; Kristensen, et al. 2011; Webster, et al. 2002). Furthermore,
behavioral focal studies of species or even individuals in conjunction with these approaches can
provide much insight into the movement, habitat use, and adaptive potential of populations as prey
distributions shift or as food webs change (Suryan and Fischer 2010; Webster, et al. 2002; Woo, et
al. 2008). Similarly, through these approaches, it is now possible to trace the origins of contaminants
within and outside the Arctic. For example, biogeochemical analyses have been used to trace the
input of contaminants through migratory species functioning as vectors, including birds and
migratory fish (Choy, et al. 2010; Krummel, et al. 2003; Pisaric, et al. 2011). Birds, and colonial
species in particular, create nutrient-rich ornithogenic soils near colonies that support a diversity of
and abundance of species (Ellis 2005; Zmudczyńska, et al. 2012), and thus have the potential of
introducing contaminants into foodwebs via soil and water transport. Using advanced tools in
combination, however, may enable the tracking of migrants and their origins, the early detection of
contaminants, and thus the identification of pollution sources.
2940
2941
2942
2943
2944
2945
2946
Archived samples and artifacts (from collections to crafts), as well as specimens from archaeological
sites, or preserved in-situ at locations throughout the Arctic, provide a wide range of temporal and
spatial scales to serve as baselines and for monitoring. As opportunities arise, incorporating
advanced approaches into current monitoring or occasional collaborative studies is encouraged. As a
first step, participation in the archival process of valuable baselines, the planning of future strategies
and collaborative initiatives, and even in the sampling and storage of data and tissues for future
study is recommended.
2947
2948
2949
2950
2951
2952
2953
2954
2955
2956
2957
2958
2959
2960
2961
2962
2963
2964
2965
2966
Because of current logistic challenges, costs, and constraints due to monitoring capacity, or even the
perception of complexity, advanced tools are not being used to their full potential at present. While
challenges exist particularly related to costs and the advanced applied knowledge required in some
cases, the perception of complexity may be needlessly limiting our ability to visualize the enormous
value of such baselines and snapshots of current states of change. Shifts in our perception are
required to encourage the planning of sampling strategies that can be implemented in the short or
long term, but that include the foresight of future needs. In fact, with some initial effort, overcoming
some of our current limitations for the first steps may be feasible today through collaboration with
academic, community, corporate or industrial partners. Accommodating existing infrastructure,
matching needs with resources, and building on existing training opportunities and capacitybuilding, communication and networking resources, may be possible now. As an illustration, even
the initial collection and storage of data or samples that could eventually serve as unrecoverable
baselines can be critical for future monitoring needs, but may be accommodated with some
modifications now through existing models as a first step. Subsequent steps in the implementation
of new tools (including sample screening or advanced data analyses) can be followed as time and
resources permit. The underscored value of ‘baselines’ in archives, libraries, sources of grey
literature and maps, electronic records, museum collections, and herbaria, and even living biological
collections (zoological parks and aquaria, conservatories and botanical gardens) continues to grow
rapidly (Casas-Marce, et al. 2010; Thomsen, et al. 2009; Tsangaras and Greenwood 2012; Vo, et al.
2011). Currently, existing infrastructure may be available, and samples and data sources may already
131
2967
2968
2969
exist from the local level within communities to international networks in educational institutions
and schools, private collections, government records and laboratories, cultural and heritage
collections, and everyday local objects, from photographs to clothing.
2970
2971
2972
6.3
2973
2974
2975
2976
2977
2978
2979
Once integrated data from CBMP-Terrestrial Plan partners is generated following the recommended
sample design from Chapter 4, improved assessment of baseline conditions and natural variation in
the CBMP-Terrestrial Plan parameters will be conducted. This will be followed by power analysis for
those parameters for which data were insufficient in the start-up phase where possible. This power
analysis will enable a refinement of the monitoring design to maximize the generation of useful data
with a minimum of resource requirements. The power analysis will inform the number of replicate
samples within each ecological strata of interest required.
2980
2981
2982
Regular analysis and reporting on observed trends related to the key monitoring questions will be
conducted. The analysis used will be tailored to the parameter under study and could include for
example:
2983
2984
2985
2986
2987
2988
2989
2990
2991
2992
2993
2994
2995
2996
2997
2998
2999
3000
3001
3002
3003
3004
Data analysis strategy
 Multi-variate analysis, ordination methods, or Permutational Multivariate Analysis of
Variance (PERMANOVA) to look at changes in community structure over time or against a
spatial reference
 Analyses of Taxon sampling curves for high diversity taxa to assess completeness of sampling
efforts and for estimations of species richness at various spatial or temporal scales
 Time series analysis of trends and parametric statistical analyses, such as ANOVAs, where
possible and relevant
 Indicator species analysis to assess patterns of specific species across spatial or temporal
scales
 Analyses of population genetic structure and phylogeography, when relevant and when
capacity exists, to asses dispersal patterns or changes in these patterns, over longer time
series
The analyses will be conducted at the appropriate spatial scale as identified in the CBMP-Terrestrial
Plan, and as relevant to the taxa of interest. Field and remotely sensed data will be integrated and
fed, as appropriate, into spatial models to extrapolate locally observed data to broader spatial
scales, as described in Chapter 4. The analysis will also include reporting against indicators, as
described in Chapter 8 and integration into policy and management tools and needs. Effective and
on-going dialogue between biodiversity monitoring data providers, integrators and analyzers and
data users will be required to maximize the utility of the monitoring strategy. It will be important to
demonstrate early successes of the monitoring plan through the generation of useful products
related to particular management and or community needs.
3005
3006
132
3007
7
Reporting
3008
3009
3010
3011
3012
3013
3014
3015
3016
3017
3018
3019
3020
This chapter outlines the methods by which activities related to the CBMP-Terrestrial Plan will be
reported. These reports will include results of the data collection (both existing and new data), as
well as information on the creation, development, and assessment of aspects of a coordinated
monitoring plan. The audiences for this information range from international, national and regional
policy and decision makers to local community residents, and as such, several types of reporting and
timelines will be necessary. An initial State of Arctic Terrestrial Biodiversity Report (to be completed
in 2016) will provide a follow-up and expanded assessment of the state of terrestrial ecosystems in
the Arctic using the Arctic Biodiversity Assessment’s Terrestrial Ecosystems and related chapters
(CAFF-ABBA 2013 ) as a baseline. These assessments will be conducted every five years to allow for
an ongoing review of expected changes in Arctic terrestrial ecosystems with a specific focus on
facilitating appropriate policy responses that can reverse, mitigate and/or adapt to these changes.
Regular assessment reports will evaluate changes beyond the baseline conditions established in the
Arctic Biodiversity Assessment.
3021
3022
3023
7.1
Audiences
3024
3025
3026
3027
3028
3029
3030
3031
3032
3033
3034
Table 7.1 lists the target audiences to be addressed by each type of reporting (for more details on
target audiences, see the CAFF Communications Plan at
http://caff.is/images/Meeting_Docs/Board_meetings/CommsPlan_CAFF_Sept2011.pdf). Regular
reports on scientific results and program performance will be made to the Arctic Council and
national and regional authorities that deal with biodiversity and/or land management issues to
support programs, policies and decision-making. Program results are also relevant to local
community residents across the Arctic, the scientific community (e.g., through peer-reviewed
scientific publications), non-government and other international organizations, other partners and
collaborators. Furthermore, information on the status and trends in biodiversity of Arctic terrestrial
ecosystems is anticipated to be contributed to international forums and processes (e.g. National
reporting for the Convention of Biological Diversity, Convention on Migratory Species, etc.).
3035
3036
3037
7.2
Types and Timing of Reporting
3038
3039
3040
3041
3042
3043
Tables 7.1 and 7.2 list the types of reports and reporting formats that will be used to summarize
activities related to the CBMP-Terrestrial Plan for each audience. Reporting types include general
communications, performance reports for the plan and chosen indicators, status reports, and
scientific publications. The frequency with which these reports will be produced is presented in
Table 7.2. In part, the frequency and direction of these reports depends upon the success of the
initial assessment of Arctic terrestrial biodiversity and the results that come from that assessment.
3044
3045
3046
3047
3048
3049
An initial State of Arctic Terrestrial Biodiversity Report will be completed in 2016, allowing
approximately three years to prepare this report after the publication of the CBMP-Terrestrial Plan.
This report will provide an initial assessment of the current state of Arctic terrestrial ecosystems and
the biodiversity they support with some assessment of historical trends where possible. A
subsequent status report will be completed in 2020 to synchronize report timing with the schedule
for the Marine and Freshwater Steering Groups, followed by regular reports every 5 years. These
133
3050
3051
3052
status reports will use monitoring data obtained from the national Terrestrial Expert Networks
(Chapter 8) to provide information on changes that have occurred since the initial assessment and
previous report.
3053
3054
7.3
Reporting Results
3055
3056
7.3.1
State of Arctic Terrestrial Biodiversity Report
3057
3058
3059
The first State of Arctic Terrestrial Biodiversity Report is targeted for production in 2016, three years
after the release of the Arctic Biodiversity Assessment full scientific report (CAFF-ABBA 2013 ). It will
describe:
3060
3061
1. the baseline conditions for FECs and spatial comparisons, where possible, within and among the
different Arctic terrestrial subzones;
3062
3063
2. temporal changes that have occurred since the baseline periods, in addition to historical trends,
where data permits; and,
3064
3. differences that have occurred spatially within and between terrestrial subzones.
3065
3066
3067
3068
3069
3070
The results (e.g., trends, spatial differences, and changes in variability) will be described and
interpreted, to the extent possible, both statistically and from a biophysical perspective. Emphasis
will be placed on the implications of these changes for the Arctic terrestrial ecosystem, as well as
within Subarctic regions and zones. The results will be presented as distribution maps, and graphs
showing spatial and temporal trends for FECs and monitoring areas. It will be important to discuss
the statistical significance, spatial representativeness, and confidence levels of the results.
3071
3072
Subsequent reports are planned in 2020 and then every five years, and will include an analysis of
how changes in biodiversity may be linked to human stressor activities (drivers).
3073
3074
3075
7.3.2
Status of indicators
3076
3077
The status of selected indicators for biotic FECs (see Chapter 4) will be updated bi-annually and
published on the CBMP’s Arctic Biodiversity Data Service (see Chapter 5).
3078
3079
3080
7.3.3
Program review
3081
3082
3083
3084
3085
3086
Internal review and independent external review will be used to evaluate and adjust the monitoring
program periodically. Internal review will occur in 2016, 2020 and subsequently every 5 years, and
will involve the evaluation of chosen parameters and indicators, sampling methods, data
management, and analysis and reporting. The results of this review will be used to update the
CBMP-Terrestrial Plan and make any necessary adjustments to the outlined methodology. Every 10
years beginning in 2020, there will be an additional independent external review of the program.
134
3087
3088
3089
The review process, although intended to assess the performance of the program and identify any
shortcomings, should be conservative to provide statistically sound long-term measurements, and
would, ideally, add to rather than remove aspects of the program.
3090
3091
3092
7.3.4
Scientific publications
3093
3094
3095
3096
3097
3098
Scientific publications will be used to share the results of the status reports with the scientific
community. Additional scientific publications are also expected to follow from the status
assessments, and may be specific to a particular FEC or sampling region, or may be multidisciplinary
and/or multiregional in scope. These articles are intended to address the links between changes to
the biotic and abiotic FECs and possible driving mechanisms at a broader or more detailed scale than
may be possible with the status reports.
3099
3100
3101
7.3.5
Performance reports and work plans
3102
3103
3104
3105
3106
3107
Performance reports and work plans will be submitted to the Arctic Council through CAFF-CBMP on
an annual basis. The performance reports will detail the steps that have been made to implement
the plan in the previous year, and will outline the progress in managing the program. The work plans
will outline the work that is anticipated to be completed during the following year, the budget for
that work, and the deliverables. This process will begin with the submission of a work plan in 2013
following the publication of the CBMP-Terrestrial Plan.
3108
3109
3110
7.3.6
Summaries and other communications material
3111
3112
3113
3114
3115
Summaries and non-technical communication material will be prepared for local community
residents, partners and collaborators, and non-scientific audiences to make the results of the status
assessments and updates accessible to the general public. The CBMP will also use its existing
communications network and media (e.g., newsletter, media releases, websites, etc.) to provide
regular information on progress and results to these audiences.
3116
3117
3118
135
3119
Table 7.1. Overview of the type of reports that will be associated with the CBMP-Terrestrial Plan and the target audience for each report type.
Type of Report
State of Arctic
Terrestrial
Biodiversity
Report,
including status
reports
Status of
selected
indicators
Review of indicator
performance, selection
of additional
parameters, new
techniques, sampling
approaches, data
management approach,
analysis and reporting
Arctic Council
X
X
X
National and Regional
Authorities
X
X
Local Communities
X
X
Scientific Community
X
Other International
Organizations
X
X
Partners and
Collaborators
X
X
NGOs and the public
X
X
Primary Target
Audience
Scientific output as
scientific publications,
either by discipline or
multidisciplinary, by
Arctic Terrestrial
subzone and across the
Arctic
Performance
reports and
work plans
Various
summaries and
other
communications
material
X
X
X
X
X
X
X
X
X
X
X
136
3120
3121
Table 7.2. The timing and frequency with which each type of report will be produced.
Type of Reporting
Timing/Frequency
Performance reports and work plans
Annually, starting with a work plan in
2013
Scientific output as scientific publications, either
by discipline or multidisciplinary, by Arctic
Terrestrial subzone and across the Arctic
Ongoing, beginning in 2014
Various summaries and other communications
material
Ongoing, starting in 2014
Status of selected indicators
Bi-annually, starting in 2016
State of Arctic Terrestrial Biodiversity Report,
including status reports
2016, 2020, and subsequently every 5
years
Review of indicator performance, selection of
additional parameters, new techniques, sampling
approaches, data management approach, analysis
and reporting
2016, 2020, and subsequently every 5
years
3122
3123
137
3124
8
Administration and Implementation of the Monitoring Program
3125
3126
3127
3128
3129
3130
3131
3132
3133
3134
Implementation of the CBMP-Terrestrial Plan requires a governing structure and process for program
review that will ensure this monitoring effort is relatively simple, cost-effective and addresses the
monitoring objectives and questions posed in Chapters 1, 3 and 4. In addition to international bodies of
the Arctic Council, other groups involved in the implementation of the CBMP-Terrestrial Plan will include
national, sub-national and local jurisdictions across the Arctic that already undertake terrestrial
biodiversity monitoring. The implementation and review structure described below incorporates the
CBMP’s network-of-networks approach and aims to provide value-added information on the state of
Arctic terrestrial ecosystems and the biodiversity they support that is useful for global (e.g. CBD),
national, sub-national and other reporting needs (Fig. 8.1). Ultimately, it will be the responsibility of
each Arctic country to implement the CBMP-Terrestrial Plan in order for the program to succeed.
3135
3136
3137
8.1
Governing Structure
3138
3139
3140
3141
3142
3143
3144
3145
3146
CAFF will establish a CBMP Terrestrial Steering Group (CBMP-TSG) to implement, coordinate and track
progress of work undertaken in response to the CBMP-Terrestrial Plan, and to oversee the activity of the
eight national Terrestrial Expert Networks (TENs) (Fig. 8.1). Composition of the CBMP-TSG will include
one representative and an alternate from each Arctic nation (i.e., Canada, Denmark-Greenland-Faroes,
Finland, Iceland, Norway, Russia, Sweden, and the United States of America). The CBMP-TSG will be
directed by co-leads drawn from these Arctic nation representatives. Permanent Participants will
collaborate depending on their capacity and interest, and are invited to appoint at least two members to
the CBMP-TSG. Other relevant Arctic Council working groups (e.g., AMAP) may appoint one member
each to the CBMP-TSG.
3147
3148
3149
3150
3151
3152
3153
3154
3155
3156
3157
Each national CBMP-TSG representative will be responsible for (1) facilitating implementation of the
monitoring plan within their own nation; (2) building strong and ongoing connections with the relevant
agencies, institutes and experts within their countries by coordinating and providing direction to their
national TEN members; (3) gathering information and reporting on the implementation status of the
plan within their respective nation to the CBMP-TSG; and (4) contributing to reporting to the CBMP and
CAFF. As a group, the CBMP-TSG will be responsible for setting the overall course of the evolving
monitoring program, providing ongoing program oversight and adjusting the implementation approach
as necessary. The CBMP-TSG will be responsible for reporting on the status of the monitoring plan to
CAFF and the CBMP Office. A number of value-added services will be provided to the CBMP-TSG by the
CBMP Office. These services include the establishment of a common web portal and web-based data
nodes, communication products and other reporting tools (Chapters 5 and 7).
3158
3159
3160
It is the responsibility of each country representative to the CBMP-TSG to identify national experts (both
scientific and traditional knowledge) to be included in their TEN. Each national TEN will include the
expertise required to assess the status and trends of the Focal Ecosystem Components and Attributes
138
3161
3162
3163
3164
3165
3166
3167
3168
3169
3170
3171
3172
3173
3174
3175
3176
identified in Chapter 3. In addition, they will be responsible for (1) identifying, aggregating, analyzing,
and reporting on existing datasets to contribute to indicators and assessments; and (2) suggesting
adjustments to the parameters, attributes and sampling schemes if needed. Each member country will
benefit from the formation of its TEN as network activities will contribute to domestic reporting
mandates and needs and improved coordination of domestic monitoring leading to cost-efficiencies and
more powerful monitoring. The CBMP-TSG may facilitate coordination and cooperation among the
various TENs as needed.
Figure 8.1. Governing structure for the implementation and ongoing operation of the CBMP
Arctic Terrestrial Biodiversity Monitoring Plan. National Terrestrial Expert Networks report their
output to the CBMP Terrestrial Steering Group, which in turn organizes and coordinates
reporting to the CBMP Office and CAFF Board.
139
3177
3178
8.2
3179
3180
3181
3182
3183
3184
3185
3186
3187
3188
3189
3190
3191
3192
The CBMP-TSG will initiate an internal review of the program beginning in 2016. A second review will
take place in 2020 and will be followed by regular internal reviews every 5 years to align with the
production of State of the Arctic Terrestrial Biodiversity reports. The internal review will assess progress
towards the completion of program objectives (Table 8.1), with the goal of assessing indicator
(attribute) performance, determining if additional parameters, techniques or sampling approaches are
needed to improve the program or if some parameters or attributes should be dropped due to lack of
sampling power, and evaluating the approach to data management. The review will determine if
progress has been made in terms of answering questions related to the status and trends of Arctic
terrestrial ecosystems and the biodiversity they support. In addition, an external review of these aspects
of the program is recommended every 10 years with the first external assessment anticipated for 2020.
Changes recommended by either internal or external reviews should be implemented with caution to
ensure that recommended changes to the monitoring plan do not compromise data integrity. Besides
the formal reviews scheduled every 5 years, the CBMP-TSG should ensure that yearly milestones are
met and that concerns identified during the year are addressed in a timely fashion.
3193
3194
3195
Program Review
Table 8.1. Program objectives and performance measures of the CBMP-Terrestrial Plan to be assessed
every 6 years beginning in 2016.
Objective
Performance Measure(s)
Identify an essential set of indicators (attributes) for
terrestrial ecosystems that are suited for measurement
and implementation on a circumpolar level.
Common indicators in use in three or more
countries by 2016.
Identify abiotic parameters that are relevant to
terrestrial biodiversity and require ongoing monitoring.
Relevant abiotic networks identified, and
linkages made between common biotic
indicators and abiotic data (2013-2016).
Identify harmonized or standardized protocols and
optimal sampling strategies for Terrestrial Plan
monitoring.
Arctic-based monitoring networks adopt
sampling approaches (2013-2016).
Identify and organization of existing research and
operational monitoring capacity and information
(scientific, community-based, and TK).
Identify monitoring groups and accumulate
available data for use in reports on the state
of Arctic terrestrial biodiversity (2013-2016).
Establish and promote effective communication and
linkages among Arctic terrestrial researchers and
monitoring groups.
Utilization of CBMP web portal and webbased data nodes (Arctic Biodiversity Data
Service) for CBMP-TSG reporting and
communication outputs (2013-2016).
Address priority gaps in monitoring coverage
(elemental, spatial and temporal).
Identification of priority data and sampling
gaps and solutions to broaden monitoring
coverage (2016).
Respond to identified scientific and TK science
questions and user needs.
Indicators developed and reported in state of
Arctic Terrestrial Biodiversity report (2016).
140
3196
3197
3198
8.3
Implementation Schedule and Budget
3199
3200
3201
3202
3203
3204
3205
Table 8.2 lists the major milestones involved with the implementation of the CBMP-Terrestrial Plan. The
CBMP-TSG should use these as guidelines for outlining their annual work plans. These milestones
include the initial publishing of the plan, the activation of the governing structure and establishment of
the data nodes, the collection and analysis of existing monitoring data and establishment of coordinated
monitoring, production of reports, and program review. A number of activities and deliverables are
associated with each milestone, and the start year for each activity or first year in which the deliverable
will be produced is indicated to provide a timeline for this implementation plan.
3206
3207
3208
3209
3210
3211
3212
3213
3214
3215
3216
3217
3218
The budget for the implementation of the CBMP-Terrestrial Plan reflects the estimated costs for panArctic coordination of the monitoring and assessment of the status and trends in Arctic terrestrial
biodiversity (Table 8.3). These estimates do not include current and planned expenditures by each
country to conduct their own Arctic terrestrial biodiversity monitoring. Similarly, costs for coordinating
and holding in-country meetings with TEN members have not been included because of the large
differences in cost anticipated among the countries. For an annual average investment of $35-65K USD
per country in 2013 and $65-125K USD per country per year in 2014-2016, the value of current national
monitoring efforts can be increased through a more coordinated, pan-Arctic approach. The budget for
2017 and beyond will be developed at a later date when activities and deliverables for ongoing
assessment have been established. Even with an improved, harmonized approach, critical gaps in our
monitoring coverage will still remain and new resources will be needed to address these gaps. Also, it is
critical to acknowledge the ongoing need to sustain the monitoring activities that the CBMP-Terrestrial
Plan aims to harmonize.
3219
141
3220
3221
3222
Table 8.2. Implementation schedule for the CBMP-Terrestrial Plan, including activities, deliverables, and
start year for each milestone associated with the implementation of the plan. These activities will form
the foundation of the annual work plans of the CBMP-TSG.
Milestone
Activities & Deliverables
Start
Year
1. Plan published
a. Final plan endorsed by CAFF Board and published
2013
b. Executive Summary report published (if needed)
2013
a. CBMP-TSG established
2013
b. National TENs established
2013
a. Data nodes and hosts, web-entry and data standards
established for each national TEN
2014
b. Nodes linked to portal and web portal analysis tools
developed
2014
c. Metadata added to Polar Data Catalogue
2013
a. Existing data sets identified and aggregated
2014
b. Existing data sets analyzed to establish indicator baselines
2014
c. Indicators updated based on performance assessments
(annually)
2016
a. Recommended monitoring protocol manuals developed
Arctic terrestrial biodiversity monitoring networks
2014
b. Monitoring stations selected within each country
2015
c. Arctic-based monitoring networks adopt parameters and
sampling approaches
2016
a. Annual performance reports and work plans
2013
b. State of the Arctic Terrestrial Biodiversity report (initial
assessment of contemporary and historical data)
2016
2. Governing structure
activated
3. Data management
4. Indicator development
5. Establish coordinated
monitoring in each country
6. Reporting
142
7. Program review
c. Arctic Terrestrial Biodiversity Status reports (incorporating
new monitoring data) – 4 years after initial report (to align
with Marine and Freshwater Steering Groups) and
subsequently every 5 years
2020
d. Indicator Status reports – every 2 years
2016
e. Scientific publications (ongoing)
2013
f. General communications
2013
a. Review of parameters, sampling approaches, data mgmt.
approach, analysis, and reporting (second review 4 years
after initial review and subsequently every 5 years)
2016
b. External independent review of parameters, sampling
approaches, data management approach, analysis, and
reporting (9 years after initial report and subsequently every
10 years)
2020
3223
3224
143
3225
3226
3227
3228
3229
Table 8.3. The operating budget for the implementation of the CBMP-Terrestrial Plan, outlining
estimated costs for the activities and deliverables, and the responsibility for each cost. Note: the costs
outlined in the table are focused on new efforts to harmonize terrestrial biodiversity monitoring, data
management and reporting. They do not reflect the actual ongoing monitoring costs.
Milestone
Activities &
Deliverables
Total Cost (USD)
Cost Details
Responsibility
50K (10 people at
5K each) plus 5K
venue costs per
year
Meeting costs (travel
support for CBMPTSG members and
venue costs) and
conference call costs
Arctic nations for
travel support for
their members.
Lead TSG country
for venue costs.
Web-entry interface
and web-based
databases and nodes
and data entry
manuals established
CAFF CBMP
Office
1. Governing
and
operational
structure
activated
a. 2013 Inaugural
meeting of CBMPTSG
2. Data
management
structures
established
a. Data nodes and
hosts, web-entry
interfaces, and
data standards
established
2014: 30K (data
node
establishment)
b. Data nodes linked
to web portal and
analytical tools
developed
2014 onwards: 20K
(web portal
maintenance)
Data Portal linked to
data nodes via XML,
and canned analysis
tools developed
CAFF CBMP
Office
c. Metadata added to
Polar Data
Catalogue
2013 onwards: 0K
(in-kind support
from PDC and CAFF
Data Manager)
Metadata entry by
University of Laval
and CAFF Data
Manager free of
charge
CAFF CBMP
Office
a. Identification of
existing data sets
and historical data,
collection of
metadata, and
spatial assessment
of data coverage
for national report
(Project 1)
2014: 30-60K per
country
Costs for 1 person for
3-6 months per
country (depending
on country).
Arctic nations
3. Indicator
development
b. Annual meeting of
CBMP-TSG
2014 onwards: 10K
per year (data
node
management)
144
Milestone
4. Reporting
Activities &
Deliverables
Total Cost (USD)
Cost Details
b. Aggregation of
existing data,
national and
regional dataset
compilations,
QA/QC, data
agreements, and
formatting (Project
2)
2014-2015: 30-60K
per year per
country
Costs will vary
depending on state
of national datasets.
Costs for 1 person for
3-6 months per year
per country
(depending on
country).
Arctic nations
c. Analysis of
indicator baseline
status for each
nation,
summarized in
national report
(Project 3)
2015-2016: 30-60K
per year per
country
Costs for 1 person for
3-6 months per year
per country
(depending on
country).
Arctic nations
d. Dataset
compilations
archived
Minimal cost (10K).
CAFF Data
manager staff
time.
All datasets compiled
and used to be
archived at CAFF
Secretariat.
CAFF Secretariat
e. Accumulation of
links to national/
regional protocols,
identification of
intercalibration
needs, and
definition of
indicator
comparison limits
(Project 4)
2014-2015: 30K
Costs for 1 person for
3 months.
CBMP-TSG
a. Annual
performance
reports and work
plans
Cost to be
determined:
per year starting in
2014
Performance
report/work-plan
layout and digital
publication
CBMP-TSG
b. Compilation of
national reports to
create State of
Arctic Terrestrial
Biodiversity Report
50K (10 people at
5K each) plus 5K
venue costs per
year
Meeting costs (travel
support for CBMPTSG members and
venue costs) and
conference call costs
Arctic nations for
travel support.
Lead TSG country
for venue costs.
145
Responsibility
Milestone
5. Program
Review and
adjustments
TOTALS
Activities &
Deliverables
Total Cost (USD)
a. Review of
parameters and
sampling
approaches.
0K – costs
reflected above.
b. Independent
review of data
management
approach, analysis,
and reporting using
performance
measures
30K every ten
years starting in
2016
2013: 5-10K per
country
2014-2016: 65125K per year per
country
3230
3231
3232
146
Cost Details
Responsibility
CBMP-TSG
Contract
independent review
of Monitoring
Program
CBMP Office
3233
9
Literature Cited
3234
3235
3236
Aastrup P, Nymand J, Raundrup KR, Lauridsen TL, Krogh PH, Schmidt NM, Illeris L, Ro-Poulsen H. 2009.
NuukBasic. Conceptual design and sampling procedures of the biological programme of NuukBasic, NERI
Technical Report no. 745. Aarhus University, National Environmental Research Institute. 70.
3237
3238
Abraham KF, Jefferies RL, Rockwell RF. 2005. Goose-induced changes in vegetation and land cover
between 1976 and 1997 in an arctic coastal marsh. Arctic Antarctic and Alpine Research 37: 269-275.
3239
3240
ACIA. 2005. Arctic Climate Impact Assessment. Cambridge University Press. http://www.acia.uaf.edu;
http://amap.no/acia/.
3241
3242
ACIA. 2004. Impacts of a Warming Arctic: Arctic Climate Impact Assessment. Cambridge University
Press. http://www.acia.uaf.edu; http://amap.no/acia/.
3243
3244
Adler PH, Currie DC, Wood DM. 2004. The Black Flies (Simuliidae) of North America. Cornell University
Press, Ithaca, NY.
3245
3246
3247
3248
Allcock AL, Barratt I, Eleaume M, Linse K, Norman MD, Smith PJ, Steinke D, Stevens DW, Strugnell JM.
2011. Cryptic speciation and the circumpolarity debate: A case study on endemic Southern Ocean
octopuses using the COI barcode of life. Deep-Sea Research Part Ii-Topical Studies in Oceanography 58:
242-249.
3249
3250
3251
Andersen O, Wetten OF, De Rosa MC, Andre C, Alinovi CC, Colafranceschi M, Brix O, Colosimo A. 2009.
Haemoglobin polymorphisms affect the oxygen-binding properties in Atlantic cod populations.
Proceedings of the Royal Society B-Biological Sciences 276: 833-841.
3252
3253
3254
3255
3256
3257
3258
Anisimov O, Fitzharris B. 2001. Ch. 16: Polar Regions (Arctic and Antarctic). In: McCarthy JJ, Canziani SF,
Leary NA, Dokken DJ, White KS, editors. Climate Change 2001: Impacts, Adaptation, and Vulnerability.
Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on
Climate Change. Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge,
UK p. 801-841.
http://snifferdogonline.com/reports/Global%20Warming/climchange01/impacts/Working%20Group
%20II%20-%20Impacts%20-%20Ch%2016.pdf
3259
3260
3261
Anttonen M, Kumpula J, Colpaert A. 2011. Range Selection by Semi-Domesticated Reindeer (Rangifer
tarandus tarandus) in Relation to Infrastructure and Human Activity in the Boreal Forest Environment,
Northern Finland. Arctic 64: 1-14.
3262
3263
AOU. 1983 [onward]. The AOU Check-list of North American Birds, 7th Edition. American Ornithologists'
Union, Washington, D. C. The AOU Check-list of North American Birds, 7th Edition.
3264
3265
3266
3267
Baker AJ, Gonzalez PM, Piersma T, Niles LJ, do Nascimento IDS, Atkinson PW, Clark NA, Minton CDT,
Peck MK, Aarts G. 2004. Rapid population decline in red knots: fitness consequences of decreased
refuelling rates and late arrival in Delaware Bay. Proceedings of the Royal Society of London Series BBiological Sciences 271: 875-882.
3268
3269
Bale JS, Masters GJ, Hodkinson ID, Awmack C, Bezemer TM, Brown VK, Butterfield J, Buse A, Coulson JC,
Farrar J, Good JEG, Harrington R, Hartley S, Jones TH, Lindroth RL, Press MC, Symrnioudis I, Watt AD,
147
3270
3271
Whittaker JB. 2002. Herbivory in global climate change research: direct effects of rising temperature on
insect herbivores. Global Change Biology 8: 1-16.
3272
3273
Ballantyne K, Nol E. 2011. Nesting Habitat Selection and Hatching Success of Whimbrels Near Churchill,
Manitoba, Canada. Waterbirds 34: 151-159.
3274
3275
Barnes DKA, Hodgson DA, Convey P, Allen CS, Clark A. 2006. Incursion and excursion of Antarctic biota:
past, present and future. Global Ecology and Biogeography 15: 121-142.
3276
3277
Bean D, Henry G, Rolph S. 2003. CANTTEX Field Manual. Part B – Additional Methods and Experimental
Manipulations. EMAN North, Canada.
3278
3279
Beever EA, Woodward A. 2011. Design of ecoregional monitoring in conservation areas of high-latitude
ecosystems under contemporary climate change. Biological Conservation 144: 1258-1269.
3280
3281
Berkes F, Berkes MK, Fast H. 2007. Collaborative Integrated Management in Canada's North: The Role of
Local and Traditional Knowledge and Community-Based Monitoring. Coastal Management 35: 143-162.
3282
3283
3284
Bispo A, Cluzeau D, Creamer R, Graefe U, Krogh PH, Sousa JP, Pérès G, Rutgers M, Winding A, Römbke J.
2009. Indicators for Monitoring Soil Biodiversity. Integrated Environmental Assessment and
Management 5: 717-719.
3285
3286
Blais JM, Macdonald RW, Mackey D, Webster E, Harvey C, Smol JP. 2007. Biologically mediated transport
of contaminants to aquatic systems. Environmental Science & Technology 41: 1075-1084.
3287
3288
Blais JM, Schindler DW, Muir DCG, Kimpe LE, Donald DB, Rosenberg B. 1998. Accumulation of persistent
organochlorine compounds in mountains of western Canada. Nature 395: 585-588.
3289
3290
3291
3292
Bolduc E, Casajus N, Legagneux P, McKinnon L, Gilchrist HG, Leung M, Morrison RIG, Reid D, Smith PA,
Buddle CM, Bêty J. 2013. Terrestrial arthropod abundance and phenology in the Canadian Arctic:
modelling resource availability for Arctic-nesting insectivorous birds. The Canadian Entomologist
FirstView: 1-16.
3293
3294
3295
Boulanger J, Poole KG, Gunn A, Wierzchowski J. 2012. Estimating the zone of influence of industrial
developments on wildlife: a migratory caribou Rangifer tarandus groenlandicus and diamond mine case
study. Wildlife Biology 18: 164-179.
3296
3297
Boutin S, Haughland DL, Schieck J, Herbers J, Bayne E. 2009. A new approach to forest biodiversity
monitoring in Canada. Forest Ecology and Management 258S: S168-S175.
3298
3299
Bowden JJ, Buddle CM. In press. Egg sac parasitism of Arctic wolf spiders (Araneae: Lycosidae) from
northwestern North America. The Journal of Arachnology 40: 348–350.
3300
3301
3302
Brown JW, de Groot PJV, Birt TP, Seutin G, Boag PT, Friesen VL. 2007. Appraisal of the consequences of
the DDT-induced bottleneck on the level and geographic distribution of neutral genetic variation in
Canadian peregrine falcons, Falco peregrinus. Molecular Ecology 16: 327-343.
148
3303
3304
3305
CAFF-ABBA. 2013 CAFF Arctic Biodiversity Assessment (full version upcoming Spring 2013). Conservation
of Arctic Flora and Fauna; Arctic Council. [Accessed: 2013; full version upcoming Spring 2013]. Available
from: http://caff.is/aba
3306
3307
3308
3309
CAFF-ABT. 2010. Arctic Biodiversity Trends 2010 – Selected indicators of change. Report (May 2010).
CAFF International Secretariat, Akureyri, Iceland. [Accessed: 2010]. Available from:
http://www.caff.is/assessment-series/view_document/162-arctic-biodiversity-trends-2010-selectedindicators-of-change
3310
3311
3312
CAFF. 2013. International Arctic Vegetation Database. Conservation of Arctic Flora and Fauna; Arctic
Council. [Accessed: 2013]. Available from: http://www.caff.is/flora-cfg/international-arctic-vegetationdatabase
3313
3314
CAFF. , in press. Red List of Arctic Vasular Plants. Conservation of Arctic Flora and Fauna; Arctic Council.
[Accessed: 2013]. Available from: http://www.caff.is/flora-cfg/rare-plants
3315
3316
Caldera E, Ross K, DeHeer C, Shoemaker DD. 2008. Putative native source of the invasive fire ant
Solenopsis invicta in the USA. Biological Invasions 10: 1457-1479.
3317
Callaghan DA, Green AJ. 1993. Wildfowl at risk, 1993. Wildfowl 44: 149-169.
3318
3319
3320
Callaghan TV, Sonesson M, Somme L, Walton DWH, Christensen T, Block WC. 1992. Responses of
Terrestrial Plants and Invertebrates to Environmental Change at High Latitudes [and Discussion].
Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 338: 279-288.
3321
Casadevall A, Fang FC. 2008. Descriptive Science. Infection and Immunity 76: 3835-3836.
3322
3323
Casas-Marce M, Revilla E, Godoy JA. 2010. Searching for DNA in museum specimens: a comparison of
sources in a mammal species. Molecular Ecology Resources 10: 502-507.
3324
3325
CAVM Team. 2003. Circumpolar Arctic Vegetation Map. Scale 1:7,500,000. Conservation of Arctic Flora
and Fauna (CAFF) Map No. 1 In. US Fish and Wildlife Service, Anchorage, Alaska.
3326
3327
3328
Chabot AA, Hobson KA, Van Wilgenburg SL, McQuat GJ, Lougheed SC. 2012. Advances in Linking
Wintering Migrant Birds to Their Breeding-Ground Origins Using Combined Analyses of Genetic and
Stable Isotope Markers. PLoS ONE 7: e43627.
3329
3330
3331
Chen W, Li J, Zhang Y, Zhou F, Koehler K, Leblanc S, Fraser R, Olthof I, Zhang Y, Wang J. 2009a. Relating
biomass and leaf area index to non-destructive measurements in order to monitor changes in arctic
vegetation. Arctic 62: 281-294.
3332
3333
3334
3335
3336
Chen W, Russell DE, Gunn A, Croft B, Chen W, Fernandes R, Zhao H, Li J, Zhang Y, Koehler K, Olthof I,
Fraser RH, Leblanc SG, Henry GR, White RG, Finstad GL. 2009b. Habitat indicators for migratory tundra
caribou under a changing climate: winter and pre-calving migration ranges. Unpublished report.
[Accessed: 2009]. Available from: the Wekʼèezhìi Renewable Resources Board (WRRB);
http://wrrb.ca/sites/default/files/public_registry/Chen.2009.CaribouWinterHabitat-txt-v6.pdf
3337
3338
Chen Z, Chen W, Leblanc S, Henry G. 2010. Digital photograph analysis for measuring plant cover in the
Arctic. Arctic 63: 315-326.
149
3339
3340
3341
Chown SL, Convey P. 2007. Spatial and temporal variability across life's hierarchies in the terrestrial
Antarctic. Philosophical Transactions of the Royal Society B: Biological Sciences 362: 2307-2331 %R
2310.1098/rstb.2006.1949.
3342
3343
Chown SL, Lee JE, Shaw JD. 2008. Conservation of Southern Ocean Islands: Invertebrates as exemplars.
Journal of Insect Conservation 12: 277-291.
3344
3345
3346
Choy ES, Kimpe LE, Mallory ML, Smol JP, Blais JM. 2010. Contamination of an arctic terrestrial food web
with marine-derived persistent organic pollutants transported by breeding seabirds Environmental
Pollution 158: 3431-3438.
3347
3348
3349
3350
3351
Christensen T, Payne JF, Schmidt NM, Madsen J, Taylor JJ, Doyle M, Gill M, Nymand J, Svoboda M, Rosa
C, Shuchman B, Soloviev M, Aronsson M, Paakko E, Fosaa AM, Heidmarsson S, Solberg BØ. 2011.
Terrestrial Expert Monitoring Plan – background paper. A Supporting Publication to the CBMP
Framework Document. CAFF International Secretariat, CAFF Monitoring Series Report Nr. 6. ISBN 9789935-431-11-0.
3352
3353
3354
Clegg SM, Kelly JF, Kimura M, Smith TB. 2003. Combining genetic markers and stable isotopes to reveal
population connectivity and migration patterns in a Neotropical migrant, Wilson's warbler (Wilsonia
pusilla). Molecular Ecology 12: 819-830.
3355
3356
Clements J. 2007 [onwards]. The Clements Checklist of Birds of the World, 6th Edition. In. Cornell
University Press, Ithaca, NY.
3357
3358
Conrad C, Hilchey K. 2011. A review of citizen science and community-based environmental monitoring:
issues and opportunities. Environmental Monitoring and Assessment 176: 273-291.
3359
3360
Coulson SJ, Leinaas HP, Ims RA, Søvik G. 2000. Experimental manipulation of the winter surface ice layer:
the effects on a high arctic soil microarthropod community. Ecography 23: 299-306.
3361
3362
3363
3364
3365
3366
Culp JM, Goedkoop W, Lento J, Christoffersen KS, Frenzel S, Guðbergsson G, Liljaniemi P, Sandøy S,
Svoboda M, Brittain J, Hammar J, Jacobsen D, Jones B, Juillet C, Kahlert M, Kidd K, Luiker E, Olafsson J,
Power M, Rautio M, Ritcey A, Striegl R, Svenning M, Sweetman J, Whitman M. 2012. The Arctic
Freshwater Biodiversity Monitoring Plan. CAFF International Secretariat, CAFF Monitoring Series Report
Nr. 7. CAFF International Secretariat. Akureyri, Iceland.
http://caff.is/publications/view_document/196-arctic-freshwater-biodiversity-monitoring-plan.
3367
3368
D'Elia T, Veerapaneni R, Rogers SO. 2008. Isolation of microbes from Lake Vostok accretion ice. Applied
and Environmental Microbiology 74: 4962-4965.
3369
3370
Dafni A, Kevan PG, Husband BC, editors. 2005. Practical Pollination Biology. Enviroquest, Ltd.,
Cambridge, Ontario.
3371
3372
3373
3374
3375
Danielsen F, Burgess ND, Balmford A, Donald PF, Funder M, Jones JPG, Alviola P, Balete DS, Blomley
TOM, Brashares J, Child B, Enghoff M, FjeldsÅ JON, Holt S, HÜBertz H, Jensen AE, Jensen PM, Massao J,
Mendoza MM, Ngaga Y, Poulsen MK, Rueda R, Sam M, Skielboe T, Stuart-Hill G, Topp-JØRgensen E,
Yonten D. 2009. Local Participation in Natural Resource Monitoring: a Characterization of Approaches.
Conservation Biology 23: 31-42.
150
3376
3377
Danks HV. 1981. Arctic Arthropods: A review of systematics and ecology with particular reference to the
North American fauna. Entomological Society of Canada, Ottawa.
3378
Danks HV. 1992. Arctic insects as indicators of environmental change. Arctic 45: 159-166.
3379
3380
3381
Darling KF, Kucera M, Wade CM. 2007. Global molecular phylogeography reveals persistent Arctic
circumpolar isolation in a marine planktonic protist. Proceedings of the National Academy of Sciences
104: 5002-5007.
3382
3383
3384
Deagle BE, Gales NJ, Evans K, Jarman SN, Robinson S, Trebilco R, Hindell MA. 2007. Studying seabird diet
through genetic analysis of faeces: a case study on Macaroni Penguins (Eudyptes chrysolophus). PLoS
ONE 9: e831.
3385
3386
3387
Descamps S, Forbes MR, Gilchrist HG, Love OP, Bety J. 2011. Avian cholera, post-hatching survival and
selection on hatch characteristics in a long-lived bird, the common eider Somateria mollisima. Journal of
Avian Biology 42: 39-48.
3388
3389
3390
Descamps S, Gilchrist HG, Bety J, Buttler EI, Forbes MR. 2009. Costs of reproduction in a long-lived bird:
large clutch size is associated with low survival in the presence of a highly virulent disease. Biology
Letters 5: 278-281.
3391
3392
3393
Diaz-Perez A, Sequeira M, Santos-Guerra A, Catalan P. 2008. Multiple Colonizations, In Situ Speciation,
and Volcanism-Associated Stepping-Stone Dispersals Shaped the Phylogeography of the Macaronesian
Red Fescues (Festuca L., Gramineae). Systematic Biology 57: 732-749.
3394
3395
Dickey M-H, Gauthier G, Cadieux M-C. 2008. Climatic effects on the breeding phenology and
reproductive success of an arctic-nesting goose species. Global Change Biology 14: 1973-1985.
3396
3397
Dietz R, Outridge PM, Hobson KA. 2009. Anthropogenic contributions to mercury levels in present-day
Arctic animals-A review. Science of The Total Environment 407: 6120-6131.
3398
Dunster J, Dunster K. 1996. Dictionary of Natural Resource Management. UBC Press, Vancouver.
3399
3400
3401
Durner GM, Whiteman JP, Harlow HJ, Amstrup SC, Regehr EV, Ben-David M. 2011. Consequences of
long-distance swimming and travel over deep-water pack ice for a female polar bear during a year of
extreme sea ice retreat. Polar Biology 34: 975-984.
3402
3403
Elberling H, Olesen JM. 1999. The structure of a high latitude plant-flower visitor system: the dominance
of flies. Ecography 22: 314-323.
3404
3405
Ellis JC. 2005. Marine birds on land: a review of plant biomass, species richness, and community
composition in seabird colonies. Plant Ecology 181: 227-241.
3406
3407
3408
3409
3410
Elmendorf SC, Henry GHR, Hollister RD, Bjork RG, Boulanger-Lapointe N, Cooper EJ, Cornelissen JHC, Day
TA, Dorrepaal E, Elumeeva TG, Gill M, Gould WA, Harte J, Hik DS, Hofgaard A, Johnson DR, Johnstone JF,
Jonsdottir IS, Jorgenson JC, Klanderud K, Klein JA, Koh S, Kudo G, Lara M, Levesque E, Magnusson B, May
JL, Mercado-Diaz JA, Michelsen A, Molau U, Myers-Smith IH, Oberbauer SF, Onipchenko VG, Rixen C,
Martin Schmidt N, Shaver GR, Spasojevic MJ, orhallsdottir oE, Tolvanen A, Troxler T, Tweedie CE,
151
3411
3412
Villareal S, Wahren C-H, Walker X, Webber PJ, Welker JM, Wipf S. 2012. Plot-scale evidence of tundra
vegetation change and links to recent summer warming. Nature Clim. Change 2: 453-457.
3413
3414
3415
Elven Re. 2011 [onwards]. Annotated checklist of the Panarctic Flora (PAF) Vascular plants. National
Centre of Biosystematics, Natural History Museums and Botanic Garden, University of Oslo. Available
from: www.nhm.uio.no/english/research/infrastructure/paf/
3416
3417
Elzinga CL, Salzer DW, Willoughby JW. 1998. Measuring and monitoring plant populations. USDA-Bureau
of Land Management Technical Reference 1730-1. Denver, Colorado.
3418
3419
Ernst CM, Buddle CM. (In press). Seasonal patterns in the structure of epigeic beetle (Coleoptera)
assemblages in two subarctic habitats in Nunavut, Canada. Canadian Entomologist.
3420
3421
Fancy SG, Gross JE, Carter SL. 2009. Monitoring the condition of natural resources in US national parks.
Environmental Monitoring & Assessment 151: 161-174.
3422
3423
3424
Faria PJ, Campos FP, Branco JO, Musso CM, Morgante JS, Bruford MW. 2010. Population structure in the
South American tern Sterna hirundinacea in the South Atlantic: two populations with distinct breeding
phenologies. Journal of Avian Biology 41: 378-387.
3425
3426
3427
Fernandez-Triana J, Smith MA, Boudreault C, Goulet H, Hebert PDN, Smith AC, Roughley R. 2011. A
Poorly Known High-Latitude Parasitoid Wasp Community: Unexpected Diversity and Dramatic Changes
through Time. PLoS ONE 6: e23719.
3428
3429
3430
Fisk AT, de Wit CA, Wayland M, Kuzyk ZZ, Burgess N, Robert R, Braune B, Norstrom R, Blum SP, Sandau
C, Lie E, Larsen HJS, Skaare JU, Muir DCG. 2005. An assessment of the toxicological significance of
anthropogenic contaminants in Canadian arctic wildlife. Science of The Total Environment 351: 57-93.
3431
3432
3433
Forbes BC, Stammler F, Kumpula T, Meschtyb N, Pajunen A, Kaarlejarvi E. 2009. High resilience in the
Yamal-Nenets social-ecological system, West Siberian Arctic, Russia. Proceedings of the National
Academy of Sciences of the United States of America 106: 22041-22048.
3434
3435
3436
Foster KL, Kimpe LE, Brimble SK, Liu H, Mallory ML, Smol JP, Macdonald RW, Blais JM. 2011. Effects of
Seabird Vectors on the Fate, Partitioning, and Signatures of Contaminants in a High Arctic Ecosystem.
Environmental Science & Technology 45: 10053-10060.
3437
3438
Fox AD. 2003. The Greenland White-fronted Goose Anser albifrons flavirostris - the annual cycle of a
migratory herbivore on the European continental fringe. Doktordisputats, University of Copenhagen.
3439
3440
3441
3442
Fox AD, Ebbinge BS, Mitchell C, Heinicke T, Aarvak T, Colhoun K, Clausen P, Dereliev S, Faragó S,
Koffijberg K, Kruckenberg H, Loonen M, Madsen J, Mooij J, Musil P, Nilsson L, Pihl S, van der Jeugd H.
2010a. Current estimates of goose population sizes in the western Palearctic, a gap analysis and an
assessment of trends. Ornis Svecica 20: 115-127.
3443
3444
Fox AD, Francis I. 2004. Report of the 2003/2004 Census of Greenland White-fronted Geese in Britain.
Greenland White-fronted Goose Study. Kalø, Denmark.
3445
3446
Fox AD, Francis IS, Madsen J, Stroud JM. 1987. The breeding biology of the Lapland Bunting Calcarius
lapponicus in West Greenland in two contrasting years. Ibis 129: 541-552.
152
3447
3448
Fox AD, Francis IS, Walsh AJ. 2010b. Report of the 2009/2010 international census of Greenland Whitefronted Geese. Greenland White-fronted Goose Study and National Parks and Wildlife Service. 27 pp.
3449
3450
Fox AD, Glahder CM. 2010. Post-moult distribution and abundance of white-fronted geese and Canada
geese in West Greenland in 2007. Polar Research 29: 413-420.
3451
3452
Friesen VL, Piatt JF, Baker AJ. 1996. Evidence from cytochrome b sequences and allozymes for a 'new'
species of alcid: The long-billed Murrelet (Brachyramphus perdix). Condor 98: 681-690.
3453
3454
Gaston AJ, Hipfner JM, Campbell D. 2002. Heat and mosquitoes cause breeding failures and adult
mortality in an Arctic-nesting seabird. Ibis 144: 185-191.
3455
3456
3457
Gauthier G, Berteaux D, Eds. 2011. ArcticWOLVES: Arctic Wildlife Observatories Linking Vulnerable
EcoSystems. Final synthesis report. Centre d’Études Nordiques. Université Laval, Quebec City, Quebec,
Canada.
3458
3459
Gensuo J, Epstien H, Walker D. 2009. Vegetation greening in the Canadian Arctic related to decadal
warming. Journal of Environmental Monitoring 11: 2231-2238.
3460
3461
Gerasimov YN, Gerasimov NN. Proceedings: 2nd International Ornithological Conference (16-19 May
2003). 2003 Ulan-Ude, Russia. 36-37.
3462
3463
3464
Gilissen N, Haanstra L, Delany S, Boere G, Hagemeijer W. 2002. Numbers and Distribution of Wintering
Waterbirds in the Western Palearctic and Southwest Asia in 1997, 1998 and 1999 - Results from the
International Waterbird Census. Wetlands International Global Series No 11.
3465
3466
3467
3468
3469
3470
Gill MJ, Crane K, Hindrum R, Arneberg P, Bysveen I, Denisenko NV, Gofman V, Grant-Friedman A,
Gudmundsson G, Hopcroft RR, Iken K, Labansen A, Liubina OS, Melnikov IA, Moore SE, Reist JD, Sirenko
BI, Stow J, Ugarte F, Vongraven D, Watkins J. 2011. Arctic Marine Biodiversity Monitoring Plan (CBMPMARINE PLAN), CAFF Monitoring Series Report No.3 (April 2011). CAFF International Secretariat,
Akureyri, Iceland. http://caff.is/monitoring-series/view_document/3-arctic-marine-biodiversitymonitoring-plan [ISBN 1. 978-9979-9778-7-2].
3471
3472
3473
3474
Gill MJ, Zöckler C. 2008. A Strategy for Developing Indices and Indicators to Track Status and Trends in
Arctic Biodiversity. CAFF CBMP Report No. 12. CAFF International Secretariat, Akureyri, Iceland.
http://caff.is/publications/view_document/58-a-strategy-for-developing-indices-and-indicators-totrack-status-and-trends-in-arctic-biodiversity.
3475
3476
3477
3478
3479
Gillespie LJ, Aronsson M, Ickert-Bond SM, Väre H, Westergaard KB. 2012. Monitoring of Red Listed
Species in the Arctic. In: Talbot SS, editor Proceedings of the 7th International: Conservation of Arctic
Flora and Fauna (CAFF) Flora Group Workshop, Akureyri, Iceland, January 28 - February 3, 2011. CAFF
International Secretariat, CAFF Flora Expert Group (CFG), CAFF Proceedings Series Report Nr. 8. ISBN:
978-9935-431-18-9.
3480
3481
Gillespie LJ, Saarela JM, Ford BA, Eds. 2012 [onwards]. Arctic Flora of Canada and Alaska. Available
from: http://arcticplants.myspecies.info/
153
3482
3483
3484
Giroux M-A, Berteaux D, Lecomte N, Gauthier G, Szor G, Bêty J. 2012. Benefiting from a migratory prey:
spatio-temporal patterns in allochthonous subsidization of an arctic predator. Journal of Animal Ecology
81: 533-542.
3485
3486
Gómez A, Carvalho GR. 2000. Sex, parthenogenesis and genetic structure of rotifers: microsatellite
analysis of contemporary and resting egg bank populations. Molecular Ecology 9: 203-214.
3487
3488
3489
3490
Groffman PM, Baron JS, Blett T, Gold AJ, Goodman I, Gunderson LH, Levinson B, Palmer MA, Paerl HW,
Peterson GD, Poff NL, Rejeski DW, Reynolds JF, Turner MG, Weathers KC, Wiens J. 2006. Ecological
thresholds: the key to successful environmental management or an important concept with no practical
application? Ecosystems 9: 1-13.
3491
3492
3493
Gross J. 2003. Developing Conceptual Models for Monitoring Programs. NPS Inventory and Monitoring
Program. [Accessed: 2010]. Available from:
http://science.nature.nps.gov/im/monitor/docs/Conceptual_Modelling.pdf
3494
3495
3496
Hajibabaei M, Shokralla S, Zhou X, Singer GAC, Baird DJ. 2011. Environmental Barcoding: A NextGeneration Sequencing Approach for Biomonitoring Applications Using River Benthos. PLoS ONE 6:
e17497.
3497
3498
3499
Hargreaves AL, Whiteside DP, Gilchrist G. 2011. Concentrations of 17 elements, including mercury, in the
tissues, food and abiotic environment of Arctic shorebirds. Science of The Total Environment 409: 37573770.
3500
3501
Heiman MK. 1997. Science by the People: Grassroots environmental monitoring and the debate over
scientific expertise. Journal of Planning Education and Research 16: 291-299.
3502
3503
Hirons AC, Schell DM, Finney BP. 2001. Temporal records of delta(13)C and delta(15)N in North Pacific
pinnipeds: inferences regarding environmental change and diet. Oecologia 129: 591-601.
3504
3505
Hodkinson ID, Coulson SJ. 2004. Are high Arctic terrestrial food chains really that simple? - The Bear
Island food web revisited. Oikos 106: 427-431.
3506
3507
3508
3509
Hohn J, Jaakkola E. 2010. Introduction to the Arctic Biodiveristy Trends 2010: Selected Indicators of
Change report (CAFF). Conservation of Arctic Flora and Fauna. [Accessed: 2013]. Available from:
http://www.caff.is/component/dms/view_document/101-arctic-biodiversity-trends-2010introduction?Itemid=217
3510
3511
Holderegger R, Stehlik I, Smith RIL, Abbott RJ. 2003. Populations of Antarctic hairgrass (Deschampsia
antarctica) show low genetic diversity. Arctic Antarctic and Alpine Research 35: 214-217.
3512
3513
Holling CS. 1973. Resilience and stability of ecological systems. Annual Review of Ecology and
Systematics 4: 1-23.
3514
3515
3516
Hoye BJ, Munster VJ, Nishiura H, Fouchier RAM, Madsen J, Klaassen M. 2011. Reconstructing an annual
cycle of interaction: Natural infection and antibody dynamics to avian influenza along a migratory
flyway. Oikos 120: 748-755.
154
3517
3518
Høye TT, Hammel JU, Fuchs T, Toft S. 2009. Climate change and sexual size dimorphism in an Arctic
spider. Biology Letters 5: 542-544.
3519
3520
Hudson J, Henry GHR. 2010. High Arctic plant community resists 15 years of experimental warming.
Journal of Ecology 98: 1035-1041.
3521
3522
3523
Hudson J, Ouimet C. 2011. Northern Park Manager’s Monitoring Tool Box: Potential and Limitations of
the ITEX Pin-Drop Protocol for Tundra Vegetation Monitoring. White paper produced for Parks Canada
during the International Polar Year.
3524
3525
Hughes J, Albon SD, Irvine RJ, Woodin S. 2009. Is there a cost of parasites to caribou? Parasitology 136:
253-265.
3526
3527
Hussell DJ, Montgomerie R. 2002. Lapland Longspur (Calcarius lapponicus). In: Poole A, editor The Birds
of North America Online. Cornell Lab of Ornithology, Ithaca, New York.
3528
3529
3530
Ibarguchi G, Gissing GJ, Gaston AJ, Boag PT, Friesen VL. 2004. Male-biased mutation rates and the
overestimation of extrapair paternity: Problem, solution, and illustration using thick-billed murres (Uria
lomvia, Alcidae). Journal of Heredity 95: 209-216.
3531
3532
Idaghdour Y, Broderick D, Korrida A. 2003. Faeces as a source of DNA for molecular studies in a
threatened population of great bustards. Conservation Genetics 4: 789-792.
3533
3534
3535
3536
Ihrmark K, Bödeker ITM, Cruz-Martinez K, Friberg H, Kubartova A, Schenck J, Strid Y, Stenlid J,
Brandström-Durling M, Clemmensen KE, Lindahl BD. 2012. New primers to amplify the fungal ITS2
region – evaluation by 454-sequencing of artificial and natural communities. Fems Microbiology Ecology
82: 666-677.
3537
International Barcode of Life Project. 2011. [Accessed: 2013]. Available from: http://ibol.org/
3538
3539
3540
ISO. 2006. ISO 23611-2:2006 Soil quality -Sampling of soil invertebrates. Part 2: Sampling and extraction
of microarthropods (Collembola and Acarina). International Organization for Standardization.
http://www.iso.org.
3541
3542
Jefferies RL, Gauthier G, Lévesque E. 2008. ArcticWOLVES sampling protocols – v2.1 25/04/2008.
Vegetation sampling: Standing crop and primary production.
3543
3544
Jefferies RL, Jano AP, Abraham KF. 2006. A biotic agent promotes large-scale catastrophic change in the
coastal marshes of Hudson Bay. Journal of Ecology 94: 234-242.
3545
3546
3547
3548
Jørgensen T, Haile J, Möller P, Andreev A, Boessenkool S, Rasmussen M, Kienast F, Coissac E, Taberlet P,
Brochmann C, Bigelow NH, Andersen K, Orlando L, Gilbert MTP, Willerslev E. 2012. A comparative study
of ancient sedimentary DNA, pollen and macrofossils from permafrost sediments of northern Siberia
reveals long-term vegetational stability. Molecular Ecology 21: 1989-2003.
3549
3550
3551
Karlsson D, Pape T, Johanson KA, Liljeblad J, Ronquist F. 2005. Svenska Malaisefälleprojektet, eller hur
många arter steklar, flugor och myggor finns i Sverige? [The Swedish Malaise Trap Project, or how many
species of Hymenoptera and Diptera are there in Sweden?]. Entomologisk Tidskrift 126: 43-53.
155
3552
3553
Kell DB, Oliver SG. 2004. Here is the evidence, now what is the hypothesis? The complementary roles of
inductive and hypothesis-driven science in the post-genomic era. BioEssays 26: 99-105.
3554
3555
Kendrick A, Lyver POB, Lutsel Ke Dene First N. 2005. Denesoline (Chipewyan) knowledge of barrenground caribou (Rangifer tarandus groenlandicus) movements. Arctic 58: 175-191.
3556
Kevan P. 1972. Insect pollination of high arctic flowers. Journal of Ecology 60: 831-847.
3557
3558
Klemola N, Andersson T, Ruohomäki K, Klemola T. 2010. Experimental test of parasitism hypothesis for
population cycles of a forest lepidopteran. Ecology 91: 2506-2513.
3559
Koffijberg K. 2005? ***CORRECT REFERENCE NEEDED.
3560
3561
Kondratyev AV. 1995. Status of goose populations in North East Asia (Chukotka) and its conservation.
Goose Study 9: 15-18.
3562
3563
3564
3565
Kreier H-P, Feldberg K, Mahr F, Bombosch A, Schmidt AR, Zhu R-L, von Konrat M, Shaw B, Shaw AJ,
Heinrichs J. 2010. Phylogeny of the leafy liverwort Ptilidium: Cryptic speciation and shared haplotypes
between the Northern and Southern Hemispheres. Molecular Phylogenetics and Evolution 57: 12601267.
3566
3567
3568
Kristensen DK, Kristensen E, Forchhammer MC, Michelsen A, Schmidt NM. 2011. Arctic herbivore diet
can be inferred from stable carbon and nitrogen isotopes in C-3 plants, faeces, and wool. Canadian
Journal of Zoology-Revue Canadienne De Zoologie 89: 892-899.
3569
3570
Krummel EM, Macdonald RW, Kimpe LE, Gregory-Eaves I, Demers MJ, Smol JP, Finney B, Blais JM. 2003.
Aquatic ecology: Delivery of pollutants by spawning salmon. Nature 425: 255-256.
3571
3572
Kubartová A, Ottosson E, Dahlberg A, Stenlid J. 2012. Patterns of fungal communities among and within
decaying logs, revealed by 454 sequencing. Molecular Ecology 21: 4514-4532.
3573
3574
Lee PLM, Prys-Jones RP. 2008. Extracting DNA from museum bird eggs, and whole genome amplification
of archive DNA. Molecular Ecology Resources 8: 551-560.
3575
3576
3577
Legagneux P, Gauthier G, Berteaux D, Bety J, Cadieux MC, Bilodeau F, Bolduc E, McKinnon L, Tarroux A,
Therrien JF, Morissette L, Krebs CJ. 2012. Disentangling trophic relationships in a High Arctic tundra
ecosystem through food web modeling. Ecology 93: 1707-1716.
3578
3579
3580
Li ZWD, Mundkur T. 2004. Numbers and distribution of Waterbirds and wetlands in the Asia-Pacific
Region.Results of the Asian Waterbird Census 1997-2001. Wetlands International, Kuala Lumpur,
Malaysia.
3581
3582
3583
Lindahl BD, Nilsson RH, Tedersoo L, Abarenkov K, Carlsen T, Kjøller R, Kõljalg U, Pennanen T, Rosendahl
S, Stenlid J, Kauserud H. 2013. Fungal community analysis by high-throughput sequencing of amplified
markers – a user’s guide. [Submitted].
3584
3585
Lindenmayer DB, Likens GE. 2010. The science and application of ecological monitoring. Biological
Conservation 143: 1317-1328.
156
3586
3587
3588
3589
Lindqvist C, Schuster SC, Sun YZ, Talbot SL, Qi J, Ratan A, Tomsho LP, Kasson L, Zeyl E, Aars J, Miller W,
Ingolfsson O, Bachmann L, Wiig O. 2010. Complete mitochondrial genome of a Pleistocene jawbone
unveils the origin of polar bear. Proceedings of the National Academy of Sciences of the United States of
America 107: 5053-5057.
3590
3591
Ludwig A. 2006. A sturgeon view on conservation genetics. European Journal of Wildlife Research 52: 38.
3592
3593
Lunn NJ, Paetkau D, Calvert W, Atkinson S, Taylor M, Strobeck C. 2000. Cub adoption by polar bears
(Ursus maritimus): determining relatedness with microsatellite markers. Journal of Zoology 251: 23-30.
3594
3595
Ma J, Hung H, Tian C, Kallenborn R. 2011. Revolatilization of persistent organic pollutants in the Arctic
induced by climate change. Nature Clim. Change 1: 255-260.
3596
3597
3598
Madsen J, Cracknell G, Fox AD, editors. 1999. Goose populations of the Western Palearctic: A review of
status and distribution. Wetlands International Publication No.48. Wetlands International, Wageningen,
The Netherlands; National Environmental Research Institute, Ronde, Denmark
3599
3600
3601
Madsen J, Jaspers C, Tamstorf M, Mortensen CE, Riget F. 2011. Long-Term Effects of Grazing and Global
Warming on the Composition and Carrying Capacity of Graminoid Marshes for Moulting Geese in East
Greenland. Ambio 40: 638-649.
3602
3603
Madsen J, Riget FF. 2007. Do embedded shotgun pellets have a chronic effect on body condition of pinkfooted geese? Journal of Wildlife Management 143: 1427-1430.
3604
3605
Malecki RA, Fox AD, Batt BDJ. 2000. An aerial survey of nesting White-fronted and Canada Geese in
West Greenland. Wildfowl 51: 49-58.
3606
3607
Mallory ML, Gaston AJ, Gilchrist HG. 2009. Sources of Breeding Season Mortality in Canadian Arctic
Seabirds. Arctic 62: 333-341.
3608
3609
Marchi C, Sanz IF, Blot E, Hansen J, Walsh AJ, Frederiksen M, Fox AD. 2010. Between-winter emigration
rates linked to reproductive output in site-faithful Greenland White-fronted Geese. Ibis 152: 410-413.
3610
3611
Martin-Gonzalez A, Wierzchos J, Gutierrez JC, Alonso J, Ascaso C. 2009. Microbial Cretaceous park:
biodiversity of microbial fossils entrapped in amber. Naturwissenschaften 96: 551-564.
3612
3613
3614
McKinnon L, Picotin M, Bolduc E, Juillet C, ty J. 2012. Timing of breeding, peak food availability, and
effects of mismatch on chick growth in birds nesting in the High Arctic. Canadian Journal of Zoology 90:
961-971.
3615
3616
3617
Miljeteig C, Gabrielsen GW, Strom H, Gavrilo MV, Lie E, Jenssen BM. 2012. Eggshell thinning and
decreased concentrations of vitamin E are associated with contaminants in eggs of ivory gulls. Science of
The Total Environment 431: 92-99.
3618
3619
Mjaaseth RR, Hagen SB, Yoccoz NG, Ims RA. 2005. Phenology and abundance in relation to climatic
variation in a sub-arctic insect herbivore-mountain birch system. Oecologia 145: 53-65.
157
3620
3621
3622
3623
Mulder BS, Noon BR, Spies TA, Raphael MG, Palmer CJ, Olsen AR, Reeves GH, Welsh HH. 1999. The
strategy and design of the effectiveness monitoring program for the Northwest Forest Plan. Gen. Tech.
Rep. PNW-GTR-437. Department of Agriculture, Forest Service, Pacific Northwest Research Station,
Portland, Oregon. 138.
3624
3625
3626
Mutanen M, Hausmann A, Hebert PDN, Landry J-F, de Waard JR, Huemer P. 2012. Allopatry as a Gordian
Knot for Taxonomists: Patterns of DNA Barcode Divergence in Arctic-Alpine Lepidoptera. PLoS ONE 7:
e47214.
3627
3628
Nancarrow TL, Chan HM. 2010. Observations of environmental changes and potential dietary impacts in
two communities in Nunavut, Canada. Rural and Remote Health 10.
3629
Nichols JD, Williams BK. 2006. Monitoring for conservation. Trends in Ecology & Evolution 21: 668-673.
3630
3631
3632
Nielsen SE, Bayne EM, Schieck J, Herbers J, Boutin S. 2007. A new method to estimate species and
biodiversity intactness using empirically derived reference conditions. Biological Conservation 137: 403414.
3633
3634
3635
Nocera JJ, Blais JM, Beresford DV, Finity LK, Grooms C, Kimpe LE, Kyser K, Michelutti N, Reudink MW,
Smol JP. 2012. Historical pesticide applications coincided with an altered diet of aerially foraging
insectivorous chimney swifts. Proceedings of the Royal Society B: Biological Sciences.
3636
Noss R. 2002. Citizen scientist or amateur naturalist? Wild Earth 11: 14-17.
3637
3638
3639
Orthmeyer DL, Takekawa JY, Ely CR, Yee JL, Rothe TR, St. Louis M. 2002. Estimating the population Size
of the Tule Greater White-fronted Goose (Anser albifrons gambeli): A comparison of three estimation
techniques. (Unpublished report).
3640
3641
3642
3643
Pachauri RK, Reisinger A, editors. 2007. IPCC Fourth Assessment Report: Climate Change 2007.
Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change. Intergovernmental Panel on Climate Change, Geneva, Switzerland.
http://www.ipcc.ch/publications_and_data/ar4/syr/en/contents.html
3644
3645
3646
Perennou CP, Mundkur T, Scott DA. 1994. The Asian Waterfowl Census 1987-1991: distribution and
status of Asian waterfowl. IWRB Spec. Publ. No. 24; AWB Spec. Publ. No. 86. Slimbridge, UK and Kuala
Lumpur, Malaysia.
3647
3648
3649
Pisaric MFJ, Thienpont JR, Kokelj SV, Nesbitt H, Lantz TC, Solomon S, Smol JP. 2011. Impacts of a recent
storm surge on an Arctic delta ecosystem examined in the context of the last millennium. Proceedings of
the National Academy of Sciences 108: 8960-8965.
3650
Polar Barcode of Life. 2010. Available from: http://www.polarbarcoding.org
3651
3652
Pörtner HO, Peck L, Somero G. 2007. Thermal limits and adaptation in marine Antarctic ectotherms: an
integrative view. Philosophical Transactions of the Royal Society B: Biological Sciences 362: 2233-2258.
3653
3654
Post E, Forchhammer MC, Bret-Harte MS, Callaghan TV, Christensen TR, Elberling B, Fox AD, Gilg O, Hik
DS, Høye TT, Ims RA, Jeppesen E, Klein DR, Madsen J, McGuire AD, Rysgaard S, Schindler DE, Stirling I,
158
3655
3656
Tamstorf MP, Tyler NJC, van der Wal R, Welker J, Wookey PA, Schmidt NM, Aastrup P. 2009. Ecological
Dynamics Across the Arctic Associated with Recent Climate Change. Science 325: 1355-1358.
3657
3658
3659
Prowse TD, Furgal C, Chouinard R, Melling H, Milburn D, Smith SL. 2009. Implications of Climate Change
for Economic Development in Northern Canada: Energy, Resource, and Transportation Sectors. AMBIO:
A Journal of the Human Environment 38: 272-281.
3660
3661
Raimondo S, Strazanac JS, Butler L. 2004. Comparison of sampling techniques used in studying
Lepidoptera population dynamics. Environmental Entomology 33: 418-425.
3662
3663
3664
Reid DG, Ims RA, Schmidt NM, Gauthier G, Ehrich D. 2012. Lemmings (Lemmus and Dicrostonyx spp.). In:
Jeffries MO, Richter-Menge JA, Overland JE, editors. Arctic Report Card 2012 (NOAA).
http://www.arctic.noaa.gov/reportcard
3665
3666
Roininen H, Danell R, Zinovjev A, Vikberg V, Virtanen R. 2002. Community structure, survival and
mortality factors in Arctic population of Eupontania leaf gallers. Polar Biology 25: 605-611.
3667
3668
3669
Rolshausen G, Segelbacher G, Hobson KA, Schaefer HM. 2009. Contemporary Evolution of Reproductive
Isolation and Phenotypic Divergence in Sympatry along a Migratory Divide. Current biology : CB 19:
2097-2101.
3670
3671
Rossiter M, Schultz JC, Baldwin IT. 1988. Relationships among defoliation, red oak phenolics, and Gypsy
moth growth and reproduction. Ecology 69: 267-277.
3672
3673
Roth JD. 2002. Temporal variability in arctic fox diet as reflected in stable-carbon isotopes; the
importance of sea ice. Oecologia 133: 70-77.
3674
3675
3676
Rouse WR, Douglas MSV, Hecky RE, Hershey AE, Kling GW, Lesack L, Marsh P, McDonald M, Nicholson
BJ, Roulet NT, Smol JP. 1997. Effects of climate change on the freshwaters of Arctic and Subarctic North
America. Hydrological Processes 11: 873-902.
3677
3678
Saarela J. 2011. Sample protocol for material to be used in DNA barcoding. International Barcode of Life.
http://www.polarbarcoding.org/protocols.php.
3679
3680
3681
Salmela J. 2011. The semiaquatic fly (Diptera, Nematocera) assemblages of three wetland habitats and
concordance with plant species composition, a case study from subalpine Fennoscandia. Journal of
Insect Science 11: 1-28.
3682
3683
SCBD. 1992. Convention on Biological Diversity. Article 2. Secretariat - Convention on Biological Diversity
(UN). [Accessed: 2012]. Available from: http://www.cbd.int/convention/text/
3684
3685
SCBD. 2010. Global Biodiversity Outlook 3. Secretariat of the Convention on Biological Diversity.
https://www.cbd.int/gbo3/.
3686
3687
3688
Schmidt NM, Ims RA, Hoye TT, Gilg O, Hansen LH, Hansen J, Lund M, Fuglei E, Forchhammer MC, Sittler
B. 2012. Response of an arctic predator guild to collapsing lemming cycles. Proceedings of the Royal
Society B-Biological Sciences 279: 4417-4422.
159
3689
3690
Scott DA, Rose PM. 1996. Atlas of Anatidae populations in Africa and western Eurasia. Wetlands
International Publication No. 41. Wetlands International, Wageningen, Neatherlands.
3691
Silver JB. 2008. Mosquito Ecology: Field Sampling Methods. 3rd Ed. Springer, New York.
3692
3693
3694
3695
3696
Skjoldal HR, Thurston D, Baff Rey M, Crandall B, Dahle S, Gilman A, Huntington HP, Klungsøyr J, Lockhart
L, Macdonald C, Mosbech A, Thomas D. 2010. OGA – Chapter 7 - Scientific Findings and
Recommendations. In: AMAP, 2010, Assessment 2007: Oil And Gas Activities in the Arctic – Effects and
Potential Effects. Volume 2. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway p. Vii
+ 277 pp.
3697
3698
Smith PA, Elliott KH, Gaston AJ, Gilchrist HG. 2010. Has early ice clearance increased predation on
breeding birds by polar bears? Polar Biology 33: 1149-1153.
3699
3700
3701
Spies IB, Gaichas S, Stevenson DE, Orr JW, Canino MF. 2006. DNA-based identification of Alaska skates
(Amblyraja, Bathyraja and Raja : Rajidae) using cytochrome c oxidase subunit I (coI) variation. Journal of
Fish Biology 69: 283-292.
3702
3703
Stephen WP, Rao S. 2005. Unscented color traps for non-Apis bees (Hymenoptera: Apiformes). Journal
of the Kansas Entomological Society 78: 373-380.
3704
3705
Stirling I, Derocher AE. 2012. Effects of climate warming on polar bears: a review of the evidence. Global
Change Biology 18: 2694-2706.
3706
3707
Strathdee AT, Bale JS. 1998. Life on the edge: Insect Ecology in Arctic Environments. Annual Review of
Entomology 43: 85-106.
3708
3709
3710
Suryan RM, Fischer KN. 2010. Stable isotope analysis and satellite tracking reveal interspecific resource
partitioning of nonbreeding albatrosses off Alaska. Canadian Journal of Zoology-Revue Canadienne De
Zoologie 88: 299-305.
3711
3712
3713
Taylor J, Toevs G, Spurrier C, Karl J, Bobo M, Miller S. 2012. AIM-Monitoring: A Component of the
National Assessment, Inventory, and Monitoring Strategy. U.S. Department of the Interior, Bureau of
Land Management, National Operations Center, Denver, Colorado.
3714
3715
Thomsen PF, Elias S, Gilbert MTP, Haile J, Munch K, Kuzmina S, Froese DG, Sher A, Holdaway RN,
Willerslev E. 2009. Non-Destructive Sampling of Ancient Insect DNA. PLoS ONE 4.
3716
3717
Thomsen PF, Kielgast J, Iversen LL, Moller PR, Rasmussen M, Willerslev E. 2012. Detection of a Diverse
Marine Fish Fauna Using Environmental DNA from Seawater Samples. PLoS ONE 7.
3718
3719
Timling I, Dahlberg A, Walker DA, Gardes M, Charcosset JY, Welker JM, Taylor DL. 2012. Distribution and
drivers of ectomycorrhizal fungal communities across the North American Arctic. Ecosphere 3: art111.
3720
3721
3722
Toevs GR, Taylor JJ, Spurrier C, MacKinnon WC, Bobo M. 2011. Bureau of Land Management National
Assessment,Inventory and Monitoring Strategy. U.S. Department of Interior Bureau of Land
Management, Washington, D.C.
160
3723
3724
Tsangaras K, Greenwood AD. 2012. Museums and disease: Using tissue archive and museum samples to
study pathogens. Annals of Anatomy-Anatomischer Anzeiger 194: 58-73.
3725
3726
3727
Tulp I, Schekkerman TH. 2008. Has prey availability for arctic birds advanced with climate change?
Hindcasting the abundance of tundra arthropods using weather and seasonal variations. Arctic 61: 4860.
3728
3729
3730
3731
3732
US Fish & Wildlife Service. 2010. Productivity Surveys of Geese, Swans and Brant Wintering in North
America 2009. Department of the Interior, U. S. Fish and Wildlife Service, Division of Migratory Bird
Management, Arlington, Virginia.
http://www.fws.gov/migratorybirds/NewReportsPublications/PopulationStatus/GeeseSwansBrants/
ProductivitySurveysGSB09combo.pdf.
3733
3734
3735
3736
US Fish & Wildlife Service. 2001. Waterfowl Population Status, 2001. US Department of the Interior,
Washington, D. C. 50.
http://www.fws.gov/migratorybirds/NewReportsPublications/PopulationStatus/Waterfowl/status01
Reduced.pdf.
3737
3738
US Fish & Wildlife Service. 2005. Waterfowl Population Status, 2005. US Department of the Interior,
Washington, D. C. http://www.fws.gov/migratorybirds/reports/status05/final_status_05.pdf.
3739
3740
3741
3742
US Fish and Wildlife Service. 2012. Waterfowl population status, 2012. U.S. Department of the Interior,
Washington, D.C.
http://www.fws.gov/migratorybirds/NewReportsPublications/PopulationStatus/Waterfowl/StatusRe
port2012_final.pdf.
3743
3744
Van der Wal R. 2006. Do herbivores cause habitat degradation or vegetation state transition? Evidence
from the tundra. Oikos 114: 177–186.
3745
3746
Vecchione M, Allcock L, Piatkowski U, Strugnell J. 2009. Benthoctopus rigbyae, N. SP., a new species of
cephalopod (Octopoda; Incirrata) from near the Antarctic peninsula. Malacologia 51: 13-28.
3747
3748
3749
Vermaire JC, Pisaric MFJ, Thienpont JR, Courtney Mustaphi CJ, Kokelj SV, Smol JP. 2013. Arctic climate
warming and sea ice declines lead to increased storm surge activity. Geophysical Research Letters: n/an/a.
3750
3751
3752
3753
Verocai GG, Lejeune M, Beckmen KB, Kashivakura CK, Veitch AM, Popko RA, Fuentealba C, Hoberg EP,
Kutz SJ. 2012. Defining parasite biodiversity at high latitudes of North America: new host and geographic
records for Onchocerca cervipedis (Nematoda: Onchocercidae) in moose and caribou. Parasites &
Vectors 5.
3754
3755
Vincent WF. 2010. Microbial ecosystem responses to rapid climate change in the Arctic. ISME J 4: 10871090.
3756
3757
Vistnes I, Nellemann C. 2008. The matter of spatial and temporal scales: a review of reindeer and
caribou response to human activity. Polar Biology 31: 399-407.
161
3758
3759
3760
Vo ATE, Bank MS, Shine JP, Edwards SV. 2011. Temporal increase in organic mercury in an endangered
pelagic seabird assessed by century-old museum specimens. Proceedings of the National Academy of
Sciences of the United States of America 108: 7466-7471.
3761
3762
3763
3764
Walker DA, Raynolds MK. 2011. An International Arctic Vegetation Database: a foundation for panarctic
biodiversity studies. Concept Paper. CAFF Strategy Series Report Nr. 5. ISBN: 978-9935-431-12-7. CAFF
International Secretariat. http://caff.is/strategies-series/view_document/57-international-arcticvegetation-database-iavd-a-foundation-for-pan-arctic-biodiversity-studies-concept-paper.
3765
3766
3767
Walpole B, Nol E, Johnston V. 2008. Breeding habitat preference and nest success of Red-necked
Phalaropes on Niglintgak Island, Northwest Territories. Canadian Journal of Zoology-Revue Canadienne
De Zoologie 86: 1346-1357.
3768
3769
Webster MS, Marra PP, Haig SM, Bensch S, Holmes RT. 2002. Links between worlds: unraveling
migratory connectivity. Trends in Ecology & Evolution 17: 76-83.
3770
3771
Wetlands International. 2012. Waterbird Population Estimates, Fifth Edition. Summary Report. Wetlands
International
3772
3773
3774
Wageningen, The Netherlands.
http://www.wetlands.org/WatchRead/Currentpublications/tabid/56/mod/1570/articleType/downlo
adinfo/articleId/3376/Default.aspx.
3775
3776
Wetlands International Specialist Groups. Information supplied by Wetlands International Specialist
Groups. [Unpublished].
3777
3778
3779
Wong C, Iverson K. 2004. Range of natural variability: Applying the concept to forest management in
central British Columbia. BC Journal of Ecosystems and Management 4(1).
http://www.forrex.org/jem/2004/vol4/no1/art3.pdf.
3780
3781
3782
Woo KJ, Elliott KH, Davidson M, Gaston AJ, Davoren GK. 2008. Individual specialization in diet by a
generalist marine predator reflects specialization in foraging behaviour. Journal of Animal Ecology 77:
1082-1091.
3783
3784
3785
Zmudczyńska K, Olejniczak I, Zwolicki A, Iliszko L, Convey P, Stempniewicz L. 2012. Influence of
allochtonous nutrients delivered by colonial seabirds on soil collembolan communities on Spitsbergen.
Polar Biology 35: 1233-1245.
3786
3787
162
3788
10
GLOSSARY
Term
Advanced protocols
Description
Monitoring protocols that consist of methodology requiring
comprehensive scientific expertise and oversight for proper application
Strategic plan goals to promote, protect, and enhance biodiversity by
2020; CBD
surface reflectivity; fraction of solar radiation that is reflected back into
space
Arctic Biodiversity Assessment
Arctic Monitoring and Assessment Program, Arctic Council
American Ornithologists' Union
Association of Polar Early Career Scientists
Arctic Palaeoclimate and its Extremes
Land north of the Arctic Circle (approx. 66° 33' N); ecologically, the land
north of treeline at present corresponding to the 10°C (50°F) July
isotherm
Reference or resource
Arctic Breeding Bird
Conditions Survey
(ABBC)
Project to collate data on environmental conditions on breeding grounds
particularly of waders and waterfowl in the Arctic in a regularly updated
database (Wetlands International and Wader Study Group)
http://www.arcticbirds.net/
Arctic Council
an intergovernmental forum formalised in 1996 to facilitate collaboration
among the Arctic States (Canada, Denmark including Greenland and the
Faroe Islands, Finland, Iceland, Norway, the Russian Federation, Sweden,
and USA), Arctic Aboriginal Peoples and other Arctic inhabitants on
sustainable development and environmental protection in the Arctic.
http://www.arctic-council.org
Arctic PRISM
see PRISM
http://www.ec.gc.ca/reommbs/default.asp?lang=En&n=FC881C1B-1
Arctic WOLVES
Arctic Wildlife Observatories Linking Vulnerable EcoSystems
http://www.cen.ulaval.ca/arcticwolves/en_i
ntro.htm
Aichi Biodiversity
Targets
albedo
ABA
AMAP
AOU
APECS
APEX
Arctic
163
http://www.cbd.int/sp/targets/
http://caff.is/aba
http://www.amap.no/
http://www.aou.org/
http://www.apecs.is/
http://www.apex.geo.su.se/
Attributes
Basic protocols
BBS
characteristics and descriptors of focal ecosystem components
Monitoring protocols that consist of simplified methodology that can be
used at sites with minimum monitoring capacity
Breeding Bird Survey
https://www.pwrc.usgs.gov/bbs/about/
Biodiversity
the variability among living organisms from all sources including, inter
alia, terrestrial, marine and other aquatic ecosystems and the ecological
complexes of which they are part; this includes diversity within species,
between species and of ecosystems (CBD)
CBD (http://www.cbd.int/)
BIP
Biotic group
Biodiversity Indicators Partnership
Set of organisms that share some characteristics (e.g. taxonomy, habitat,
functional groups, communities, etc.). In the CBMP-Terrestrial Plan, these
are the major groups consisting of Vegetation, Birds, Mammals, and
Invertebrates.
http://www.bipindicators.net/
Black-listed species
Non-native species that are invasive or harmful in the introduced region
(e.g. term used in Norway and other countries, but other terms have not
been standardised in other countries); compare with Red List species
(IUCN)
CAFF
Conservation of Arctic Flora and Fauna Working Group of the Arctic
Council
Circumarctic Active Layer Monitoring Network
CALM
CANNTEX
Capture-MarkRecapture
Canadian Tundra and Taiga Experiment; a network of scientists and sites
across the Canadian North (and see ITEX)
A general group of ecological methods based on the initial capture of
individuals which are tagged and the subsequent re-trapping of the same
or a portion of the original captured individuals; CMR data can be used to
study population dynamics, movement of individuals, territoriality,
population size, survival and demographics, etc.
CARMA
Circumarctic Rangifer Monitoring and Assessment Network
164
http://www.caff.is/
http://www.udel.edu/Geography/calm/abou
t/program.html
http://www.taiga.net/canttex/index.html
http://caff.is/carma
CAVM
Circumpolar Arctic Vegetation Map
(CAVM Team 2003; Christensen, et al. 2011)
http://www.geobotany.uaf.edu/cavm/
CBC
Christmas Bird Count, Audubon Society
http://birds.audubon.org/christmas-birdcount
CBD
CBM
CBMP
Convention on Biological Diversity
See Community-based monitoring
Circumpolar Biodiversity Monitoring Program; created by the CAFF
Working group of the Arctic Council
CBMP’s Data Portal system (www.abds.is)
Arctic Terrestrial Monitoring Plan; created by the TEMG
http://www.cbd.int/
CBMP Data Portal
CBMP-Terrestrial
Plan
CBMP-TSG
http://www.abds.is
Circumpolar Biodiversity Monitoring Program - Terrestrial Steering Group
CEMG
CIMP
Coastal Expert Monitoring Group (see EMG)
Cumulative Impacts Monitoring Program
CMR
COI Barcode
see Capture-Mark-Recapture
DNA Barcoding: fragment of the cytochrome oxidase c I gene that is
sequenced systematically and is useful for species identification in many
taxonomic groups (additional markers may be needed in groups such as
plants)
Conceptual model
A working hypotheses about ecosystem organization, function, and key
system inter-relationships
Observation and measurement activities involving participation by
community members; activities are designed to learn about ecological
and social factors affecting a community
Community-based
monitoring
http://www.caff.is/monitoring
http://www.aadncaandc.gc.ca/eng/1100100027498/11001000
27499
165
http://www.barcodeoflife.org/content/abou
t/what-dna-barcoding
(Beever and Woodward 2011)
Cumulative Impacts
Monitoring Program
A community-based program in the Northwest Territories, Canada, that
coordinates, supports, disseminates, and conducts monitoring-related
initiatives incorporating both scientific and traditional knowledge, and
builds capacity
Critical component
Elements considered to play a crucial role in a system and that would
lead to detrimental changes if these ceased to exist; elements which may
be considered as priorities for long term monitoring.
DEM
DNA Barcoding
Digital Elevation Model
System of protocols and databases of biodiversity taxonomy and
identification based on standardised sequences of DNA
model to assess and manage environmental problems (Driving forces;
Pressures; State of the environment; Impacts; Responses)
DPSIR framework
Driver
An ecological biotic or abiotic component that causes a change in an
organism, population, habitat, ecosystem, or other element of the
landscape
Driving forces
Socio-economic and socio-cultural forces driving human activity that may
increase or decrease pressures on the environment (DPSIR framework)
Ecosystemic
Ecological tipping
points
Related to the environment
Points along a gradient of change where a small change in external
conditions can result in a drastic change in the structure and composition
of a system
EMG
Expert Monitoring Group (see CBMP); one of four groups of collaborating
scientists, managers, and community members with expertise in
Terrestrial (TEMG), Marine (MEMG), Coastal (CEMG) and Freshwater
(FEMG) environments.
Essential Attribute
Attributes of focal ecosystem components that must be measured at any
given monitoring site to capture a minimum set of biodiversity
information for the FEC under study; considered critical
166
http://www.aadncaandc.gc.ca/eng/1100100027498/11001000
27499
http://www.barcodeoflife.org/
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
(Groffman, et al. 2006)
Focal Ecosystem
Components
Ecosystem components (indicators) that are considered critical to the
functioning and resiliency of Arctic ecosystems and are of fundamental
importance to the subsistence and economies of Northern communities
FEMG
Function
Freshwater Expert Monitoring Group (see EMG)
Ecosystem function; the ecological role performed by a species or
functional group (e.g. nutrient cycling, herbivory, etc.)
Global Biodiversity Information Facility (and Data Portal)
Group on Earth Observations Biodiversity Observation Network
GBIF
GEO BON
GLORIA
Gray literature (or
grey literature)
Global Observation Research Initiative in Alpine Environments
Manuscripts and articles that may be unpublished and typically do not
undergo the same peer-review process as journal articles; material may
consist of reports, technical papers, white papers, etc.
High Arctic
Northern region of the Arctic particularly including the island in the
north; ecologically, the area consisting of polar semidesert to desert
where mean July temperatures range from 6° to 2° C
Historic monitoring
Relevant monitoring previously conducted which could be incorporated
into the monitoring scheme
Effects of environmental degradation (DPSIR framework)
Impacts
Indicator
INTERACT
IPBES
IPCC
IPY
ITEX
IUCN
see Focal Ecosystem Components
International Network for Terrestrial Research and Monitoring in the
Arctic
Intergovernmental Platform on Biodiversity and Ecosystem Services
Intergovernmental Panel on Climate Change
International Polar Year Programme
International Tundra and Taiga Experiment
International Union for Conservation of Nature and Natural Resources
167
http://www.gbif.org/
http://www.earthobservations.org/geobon.s
html
http://www.gloria.ac.at/
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
http://www.eu-interact.org/
http://www.ipbes.net/
http://www.ipcc.ch/
http://www.ipy.org/ (NOTE: domain name
and site may be down temporarily)
http://www.geog.ubc.ca/itex/
http://www.iucnredlist.org/
Key elements
Landscape
Life forms,
Vegetation
Low Arctic
Management,
Wildlife or
Ecosystem
MEA
MEMG
Mire
MODIS
NDVI
PAME
Parameter
see Focal Ecosystem Components
A geographic area including its properties of physical terrain, land cover,
water bodies, climate, land use patterns, and other characteristics
Functional type of vegetation related to ecosystem function (e.g. trees,
shrubs, forbs, graminoids, bryophytes, fungi, lichens, bare ground, etc.)
Southern region of the Arctic; ecologically, area with higher diversity in
vegetation where mean July temperatures range from 6° to 12° C
Decision-making and applied ecology to preserve and enable sustainable
use of wildlife populations in a manner that strikes a balance between
the needs of those populations and the needs of people
Multilateral Environmental Agreements
Marine Expert Monitoring Group (see EMG)
Boggy habitat
Moderate Resolution Imaging Spectroradiometer; satellite-borne imaging
instrument that gathers data on the Earth's surface
MODIS Normalized Difference Vegetation Index; satellite-based data
collected on land cover changes that can be used to monitor vegetation
growth conditions, climate, and land use.
http://modis.gsfc.nasa.gov/
http://glcf.umd.edu/data/ndvi/
Protection of the Arctic Marine Environment
Traits or items that are measured in the field and that are elements and
integral parts of attributes
Norwegian IPY program: Present day processes, Past changes, and
Spatiotemporal variability of biotic, abiotic and socio-environmental
conditions and resource components along and across the Arctic
delimitation zone
http://www.pame.is/
Pressures
Stresses that human activities place on the environment (DPSIR
framework)
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
PRISM
Program for Regional and International Shorebird Monitoring
PPS Arctic
168
http://ppsarctic.nina.no/
Range of temporal
variation
Recommended
attribute
Temporal and spatial distribution of ecological processes and structures
prior to European settlement of North America
Attributes that can be measured at some sites when additional capacity
and/or expertise is available to capture information on the processes
driving biological change
(Wong and Iverson 2004)
Red List of species
(IUCN)
Redundancy
Framework for the classification of taxa according to their extinction risk
and including species with near threatened to extinct status
Ecologically, when a species or group of species can perform the
equivalent ecosystem function of another species or group of species
Spatial area demarcated by political borders (territorial or settlements),
socioeconomic categories, geology, watersheds, or biogeography
Amount of disturbance that ecosystem can withstand without changing
key processes and structures (alternative stable states); time needed to
return to a stable state
http://www.iucnredlist.org/
Responses
Responses by society to the environmental situation (DPSIR framework)
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
SAON
SCANNET
Sustaining Arctic Observing Network
Circumarctic network of terrestrial field bases; see INTERACT
http://www.arcticobserving.org/
http://www.scannet.nu/ (NOTE: main site
may be experiencing problems); http://faroarctic.org/fileadmin/Resources/DMU/GEM/f
aro/2010_SCANNET_Rasch.pdf
SDWG
SMART
Sustainable Development Working Group, Arctic Council
Specific, Measurable, Achievable, Results-oriented, and Temporarilydefined
Condition of the environment (DPSIR framework)
http://portal.sdwg.org/
Region
Resilience
State of the
environment
169
(Holling 1973)
http://www.grida.no/graphicslib/detail/dpsi
r-framework-for-state-of-environmentreporting_379f
Stressor
Driver (e.g. an agent, force or external factor) that exerts detrimental
pressure on an ecosystem, community, biotic group, organism, or on
natural ecological processes or ecosystem functions.
Subarctic
Ecotone between timberline (taiga) and treeline (tundra) with
connections to the Arctic via alpine zones, coastal tundra, and forest
tundra
SWIPA
Snow, Water, Ice, Permafrost in the Arctic assessment (produced by
AMAP)
Traditional ecological knowledge (and see Traditional Knowledge)
Terrestrial Expert Monitoring Group (see EMG)
Terrestrial Expert Networks (established by country for coordinating
metadata accessibility; CAFF)
Circumpolar Biodiversity Monitoring Plan for terrestrial biodiversity
The ecological tipping point of an ecosystem; point where abrupt change
in a quality, property or phenomenon, or where small changes in a driver,
produce large responses
TEK
TEMG
TEN
Terrestrial Plan
Threshold
Timberline
The altitudinal or latitudinal boundary or transition zone that delineates
the ecological conditions of climate (especially temperature,
precipitation, and wind) beyond which forests no longer form a closed
canopy ecosystem (and see treeline)
Tipping point
Traditional
Knowledge (TK)
See Threshold
Knowledge and values which have been acquired through experience,
observation, from the land or from spiritual teachings, and taught
through generations.
Traditional
Ecological
Knowledge (TEK)
Cumulative body of knowledge about people and organisms in relation to
their environment, and that has been acquired through experience and
taught through generations (and see Traditional Knowledge as broader
term)
170
http://amap.no/swipa/
Treeline (or tree
line)
The altitudinal or latitudinal boundary or transition zone that delineates
the ecological limit beyond which trees can no longer grow due to harsh
climatic conditions, especially temperature, precipitation, and wind (and
see timberline)
TSG
Vegetation
Terrestrial Steering Group
Comprehensive term referring to land cover components including all
plants and their growth forms, and fungi.
Wing Surveys (or Tail Harvested bird species provide opportunities to estimate the numbers
Surveys)
and species, age and sex composition of the harvest. Hunters
participating in surveys submit one wing and/or the tail of bird that they
shoot during the hunting season; programs run by governments in
collaboration with experts identify the tissues to gather demographic and
abundance data.
3789
3790
171
Examples: http://www.flyways.us/surveysand-monitoring/hunter-surveys/partscollection-surveys
https://www.ec.gc.ca/reommbs/default.asp?lang=En&n=CFB6F561-1
3791
11
3792
A
Appendix: Metadata and Sampling Coverage Maps by Focal Ecosystem
Elements - ONGOING
3793
3794
Appendices
Section to be completed – Work is still ongoing to compile master file of METADATA.
3795
3796
3797
METADATA will be uploaded to the Polar Data Catalogue (http://www.polardata.ca/whitesnow/ ).
Data files are undergoing final updates and will include all circumpolar countries part of the CBMPTerrestrial Plan.
3798
3799
i. Introduction and Description
Brief description will be included here.
3800
3801
3802
3803
ii. MAPS
Maps will be included here (GIS) based on geographic coordinates of long-term monitoring programs
and infrastructure (e.g. research stations). Maps will show monitoring capacity for various biotic groups
(e.g. vegetation, birds, mammals, arthropods, and others).
3804
3805
PLACE-HOLDER FOR METADATA MAPS (INVENTORY SITES)
3806
3807
3808
(For illustration purposes only: example of Canadian research facilities in the North from
http://www.polarcom.gc.ca )
3809
3810
3811
3812
Figure A1: Location of long-term monitoring sites, programs and infrastructure that can contribute to
monitoring capacity as part of the CBMP-Terrestrial Plan. (When completed, maps may be separate for
different types of programs or for different biotic groups; some types will be pooled and distinguished
by different marker types on GIS maps).
3813
3814
B
Appendix: What Can We Monitor with Satellite Data in the Arctic?
3815
i. Remote Sensing
172
3816
3817
3818
3819
3820
3821
3822
3823
3824
3825
3826
3827
3828
3829
Remote sensing is a tool that can support an integrated Arctic terrestrial biodiversity monitoring
program. Remote sensing observations can provide information at a variety of scales (cm-km). Synoptic
satellite spatial and temporal information as presented in Table B1 can be generated. Presented on the
table are both biotic and abiotic parameters, hence remote sensing provides useful information on both
indicators and drivers. Remote sensing observations can also support modeling efforts, particularly
those that are geospatially based. Ground based observation can be used to truth remote sensing data
which can then be used to classify areas of the Arctic which are inaccessible. Fine spatial resolution
remote sensing data combined with on-the-ground-sampling can also be combined to better interpret
coarse resolution (1km) satellite data so that Arctic-wide classifications are possible. Combining the
ground sampling with remote sensing observations provide insight into how to put detailed ground
measurements into a regional context. Remote sensing technologies are also rapidly evolving; Lidargenerated topography and vegetation-height data are one example. The monitoring activities should
take advantages of these emerging technologies when budgets can support such new technology based
projects.
3830
3831
3832
3833
3834
3835
3836
Remote sensing supports the measurement of biodiversity parameters such as vegetation type, indices
(NDVI, EVI, and others), phenology (start, end, duration of growing season-SOS, EOS, and DOS), and leaf
area index (LAI), as well as providing important information on abiotic drivers such as temperature,
cloud cover, snow cover, soil moisture, active layer, land cover, anthropogenic change, hydrology, fire
burn areas, and freeze /thaw cycles (see Table B1). Remote-sensing-derived information on weather,
climate, sea ice and the coastal marine environment are also useful driver information to support the
terrestrial biodiversity monitoring activities that include models.
3837
3838
3839
3840
3841
3842
3843
3844
3845
3846
3847
3848
Table B2 presents a recommended series of satellite systems that can support long term monitoring in
the Arctic. Presented on the table by satellite system is the organization, sensor type, resolution on the
ground, spatial and temporal coverage, data type, and derived products per system. These satellite
systems were selected based on the following criteria: (1) polar orbit, (2) ten year duration or longer, (3)
electro-optical, and active/ passive microwave, and (4) data available at little or no cost. Generation of
the time series products identified in Tables B1 and B2 would be an invaluable set of observations to
support the overall monitoring effort. Some of the derived satellite products identified in the table are
partially completed; however, a comprehensive complete time series of the entire pan- Arctic in a user
friendly Arctic map projection does not exist. A number of time –series investigations using these
satellite systems have been performed, but are incomplete from a time and space perspective.
However, if available in a common database (portal), these would be very valuable to the terrestrial
monitor efforts.
3849
3850
3851
3852
3853
3854
3855
A series of gaps in the satellite derived products (Table B2) have been identified. These include: 1) 1980
–present seasonally integrated NDVI using POES data, 2) Landsat derived pan- Arctic land cover for
1980, 1990, 2000, and 2010, with separate hydrology layers, 3) The suite of MODIS- derived product in
polar user-friendly projection formats, 4) MODIS and AVHRR derived fire occurrence maps 2002present, 5) Annual and inter-annual surface temperature maps 1980- present for the pan-Arctic, and 6)
Annual maximum snow cover map for the Arctic 2003-present (from MODIS). The gaps identified above
should be rectified as an early step in the implementation of the terrestrial monitoring activity. In
173
3856
3857
3858
3859
addition to the six recommended time series generations based on the gap analysis, the synthetic
aperture radar (SAR) ERS-1/2 should be utilized to classify shallow/deep (frozen/some liquid water at
maximum freeze) for 1992, 2000, and 2010 to provide information on lake depth change and
freeze/thaw history.
3860
3861
3862
Before and after photography whether collect on the ground, air or in space can also be a very
important tool to quantify change. The back to the future concept has documented significant changes
in vegetative state over a few decades.
3863
3864
3865
3866
3867
3868
3869
In addition to the satellite based synoptic pan-Arctic time series derived products identified above,
remote sensing data of varying platforms (ground, air, and space) spatial resolution (cm to km) and
sensor types (electro-optic, infrared, and microwave) will be used to support the recommended on the
ground observations summarized in the vegetation sampling strategy tables presented in Chapter 4
(Table 4.1). The multiple roles of remote sensing in supporting the CBMP-Terrestrial Plan by providing
information at different scales and time periods on biotic and abiotic indicators and drivers should be
noted.
3870
174
3871
3872
Table B1. Ecosystem changes, components, and drivers that can be monitored at various spatial and
temporal scales.
Climate
Land
Hydrology
Coastal erosion
(time series)
Freeze/thaw cycle
Anthropogenic
–
Ocean
Sea Ice
–
Ground and sea temperature
Snow cover
Sea ice extent
Aerosols/emissions
Digital Elevation Maps (DEM)
Soil moisture
Active layer/permafrost
Vegetation type (land cover)
Vegetation indices (NDVI, EVI, and many others)
Vegetation phenology (start/end/duration of growing season [SOS, EOS,
DOS])
Snow cover
Albedo
Fire/Burned Area
Leaf Area Index (LAI)
Lake extent and relative depth
Fluvial (gravel bars, channel locations)
Requires fine resolution data (1-2 m)
Lakes
Active layer
Ice break-up
Snow cover
Oil and gas development (ice roads, pipelines, drill pads, etc.)
Infrastructure/development
Surface wind speeds
Wave height
Ocean current dynamic height method
Wavelength and direction
Ocean frontal boundaries
Ocean temperature
Color (chl, doc, sm)
Oil spills and surfactants
Sea ice concentration
Sea ice dynamics
Ice type (age)
Detailed ice movement and rheology
Leads
Marginal ice zone (MIZ)
Land fast ice
Ice edge
Ice free-board
175
3873
3874
Table B2: Recommended satellite systems that have potential for supporting long-term monitoring over ranges of temporal and spatial scales.
Some of the derived products here are partially completed, and efforts will be made to address gaps as described in the CBMP-Terrestrial Plan.
Satellite
System
Organization Sensor Type
Spatial
Resolution
Spatial
Coverage
Temporal
Coverage
Polar
Orbiting
Platform
(POES)
ERS-1/2
Envisat
Radarsat-1
USA-NOAA
Visible and
infrared
(AVHRR)
1 km
All pan-Arctic 1978daily
present
Visible and
infrared images
ESA
Canada
SAR
25 m
1991present
DMSP
USA-DOD
AVHRR and
passive
microwave
1 km
25 km
100 km
swaths all
pan-Arctic
over time
All pan-Arctic
daily
Landsat
USA-USGS
Visible and
infrared
30-100 m
165 km
frames all
pan-Arctic
over time
1973present
Radar backscatter Frozen/nonimages
frozen lakes
Active layer Ice
cover
Visible and
Sea ice type
thermal imagery Sea ice cover
and microwave
Surface time
brightness temp Clouds
Snow cover
Visible and
Land cover
infrared images
Hydrology
Snow cover
Ice cover
MODIS
(Aqua and
Terra)
USA-NASA
Visible and
infrared
250 m1 km
Entire earth
every 1-2
days
2002present
1960spresent
3875
176
Data Type
Visible and
infrared images
Derived
Products
Surface Temp
NDVI
Clouds
Remarks
1978-TIROS-N under recalibration
Radarsat-2 can provide
continuity but costly
Best source of long-term
ice coverage
1979-present SMMRSMMI
Landsat 7 has data gaps
at scene edges, Landsat 5
current limited data
collects over US only
Ocean ice,
Potential for generating a
time, and
comprehensive suite of
productivity
pan-Arctic observations
Enhanced
Vegetation
Index (EVI)
Fire events
Snow cover
Surface temp.
Cloud cover
3876
3877
3878
3879
3880
3881
3882
3883
3884
3885
3886
3887
ii. Satellite Imaging of Pan-Arctic Research Stations
Table B3 and Figure A1 address the imaging requirements of satellites to map the suite of Pan-Arctic
Research Stations. Represented on the figure are the locations of the Pan-Arctic Research Stations, the
Arctic Circle, the CAFF Pan-Arctic Boundary, and the different footprints (coverage) of Landsat, MODIS,
and AVHRR for the region. The map of long-term Pan-Arctic Research Stations and satellite swath widths
(footprints) provides the information needed to determine approximately how many satellite scenes of
a given sensor are needed to cover all of the stations. For example, Landsat provides data at a fine
spatial resolution (~30 m) but at the cost of a small satellite footprint (185 km). Each AVHRR scene
covers a large geographic area but the spatial resolution is coarse (~1 km). MODIS has irregular shaped
satellite footprints at the poles due to the use of a sinusoidal projection, but several research stations
are covered in one image scene in many areas. In terms of spatial resolution, MODIS data is provided at
250 m – 1 km depending on the portion of the electromagnetic spectrum (i.e. satellite band) utilized.
3888
3889
3890
Table B3 summarizes the satellite sensor, spatial resolution, footprint or swath width, temporal revisit
time, and number of scenes necessary to image each station one time. For example to image each
station once a year for ten years with Landsat would require 330 images.
3891
3892
Table B3. Number of satellite scenes required to image the suite of Pan-Arctic research stations
Spatial
Footprint
Temporal
# of Satellite Scenes
Satellite Sensor
Needed to Cover All PanResolution
Size
Revisit
Arctic Research Stations
Landsat
30 m
185 km
16 Days
~33
MODIS Aqua and Terra
250 m – 1 km
1,000 –
1,500 km
Daily
~16
AVHRR
1 km
2,500 km
Daily
~8
3893
3894
177
3895
3896
3897
3898
3899
Figure B1: Locations of the Pan-Arctic Research Stations (red dots), the Arctic Circle (black line), the CAFF
Pan-Arctic Boundary (purple line) along with the different footprints of Landsat (blue boxes), MODIS (red
lines), and AVHRR (green box) for the region.
178
3900
C
Appendix: Workshop Participants
3901
3902
i. Workshop 1 (October 11-13, 2011, Hvalsø, Denmark) - Designing an Arctic Terrestrial Biodiversity
Monitoring Plan
Niels Martin Schmidt
Aarhus University – Institute of Bioscience, Demark
Peter Aastrup
Aarhus University – Institute of Bioscience, Demark
Christian Bay
Aarhus University – Institute of Bioscience, Demark
Jesper Madsen
Aarhus University – Institute of Bioscience, Demark
Mads Forchammer
Aarhus University - Institute of Bioscience, Denmark
Tony Fox
Aarhus University – Institute of Bioscience, Denmark
Tom Christensen
Aarhus University – Institute of Bioscience, Denmark
Hans Meltofte
Aarhus University, Denmark
Tom Barry
CAFF, Iceland
Michael Svoboda
CBMP, Canada
Mike Gill
CBMP, Canada
Mikala Klint
Danish Environmental Protection Agency, Denmark
Marlene Doyle
Environment Canada, Canada
Katarzyna Biala
European Environment Agency
Anna Maria Fosaa
Faroese Museum of Natural History, Faroes
Ulla-Maija Liukko
Finnish Environment Institute, Finland
Inge Thaulow
Greenland Homerule Government, Greenland
Christine Cuyler
Greenland Institute of Natural Resources, Greenland
Josephine Nymand
Greenland Institute of Natural Resources, Greenland
Starri Heidmarsson
Icelandic Institute of Natural History, Iceland
Anne Brunk
Indigenous Peoples Secretariat, Denmark
Elisa Pääkkö
Metshallitus Natural Heritage Services, Finland
Bob Shuchman
Michigan Tech Research Institute, USA
Morten Skovgaard
Ministry of Energy and Climate, Denmark
Mikhail Soloviev
Moscow State University, Dept. of Vertebrate Zoology, Russia
John Payne
North Slope Science Initiative, USA
Dagmar Hagen
Norwegian Institute for Nature Research (NINA), Norway
Bård Øyvind Solberg
Norwegian Institute for Nature Research (NINA), Norway
Donald McLennan
Parks Canada, Canada
Mora Aronsson
Swedish Species Information Centre (SLU), Sweden
Hans Gardfjell
Swedish University of Agricultural Sciences (SLU), Sweden
Wenche Eide
Swedish Species Information Centre (SLU), Sweden
Cheryl Rosa
U.S. Arctic Research Commission, USA
Lawrence Hislop
UNEP GRID Arendal
Donald Walker
University of Alaska, Fairbanks, USA
Rolf Anker Ims
University of Tromsø, Norway
Bud Cribley
US Bureau of Land Management, USA
Jason J. Taylor
US Bureau of Land management, USA
Carl Markon
US Geological Survey, USA
Kristine Bakke
Westergaard Norwegian Institute for Nature Research (NINA), Norway
179
Tatiana Minaeva
Wetlands International, Russia
3903
3904
3905
ii. Workshop 2 (May 15-17, 2012, Anchorage, Alaska, USA) - Designing an Integrated Arctic Terrestrial
Biodiversity Monitoring Plan
Elmer Topp-Jorgensen
Niels Martin Schmidt
Tom Christensen
Maryann Smith
Don Russell
Marlene Doyle
Michael Svoboda
Mike Gill
Katarzyna Biala
Christine Cuyler
Josephine Nymand
Starri Heidmarsson
Carolina Behe
Christopher Buddle
Robert Shuchman
Mikhail Solovyev
Robert Winfree
Denny Lassuy
John Payne
Morten Wedege
Dagmar Hagen
Kristine Bakke Westergaard
Donald McLennan
Mora Aronsson
Jason J. Taylor
Cheryl Rosa
Catherine Moncrieff
Aarhus University
Aarhus University
Aarhus University
Aleut International Association
CircumArctic Rangifer Monitoring Network
Environment Canada
Environment Canada
Environment Canada
European Environment Agency
Greenland Institute of Natural Resources
Greenland Institute of Natural Resources
Icelandic Institute of Natural History
Inuit Circumpolar Council Alaska
McGill University
Michigan Tech Research Institute
Moscow State University
National Park Service
North Slope Science Initiative
North Slope Science Initiative
Norwegian Directorate for Nature Management
Norwegian Institute for Nature Research
Norwegian Institute for Nature Research
Parks Canada Agency
Swedish Species Information Centre
U.S. Department of the Interior - Bureau of Land Management
United States Arctic Research Commission (USARC)
Yukon River Drainage Fisheries Association
Representatives
APECS (Association of Polar Early Career Scientists)
3906
180