Download BSIERP EMC Apr5

BERING SEA INTEGRATED
ECOSYSTEM RESEARCH
PROGRAM 2007-2012
Progress Report on the
development of an
Implementation Plan
Francis K. Wiese
September 2006 Board meeting
• Adopt 6 questions as suggested by SP,
expanded to climate change
– $1.2M for 1-2 year modeling and retrospective studies
• Set aside funds for Bering Sea IERP planning
• Establish and Ecosystem Modeling Committee
(EMC)
• Develop an Implementation Plan for the BSIERP
by August 2006 for incorporation into 2007 RFP
GOALS
• Predict of future ecosystem states in response
to natural variability and human activities
• Determine the limits of ecosystem predictability
• Develop information useful to resource
managers and decision makers
BSIERP efforts
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Bering Sea Interagency Working Group
(BIAW)
BSIERP workshop
Project 502: Integration of Ecological
Indicators for the North Pacific with emphasis
on the Bering Sea: workshop will be held in
Seattle on June 1-2
Project 516: Seabirds as indicators of marine
ecosystems: workshop was held in Girdwood
on February 16-18
Related efforts
• Loss of Sea Ice (HEPR)
Implementation Plan
• Bering Sea Ecosystem Study
(BEST)
Implementation Plan
• Project components (common)
• IERP Committee
• Series of 5-6 year modules:
– 1-synthesis
– 2-4 field work
– 5-6 integration and write-up
• ~$2.3M/yr ($11-12M):
– 1st year: $250K
– 2-4 year: $3.5M/yr
– 5-6 year: $500K
Project components
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Assessment of current programs and activities
Synthesis and identification of research and funding gaps
Model framework: integrate with the EMC, and include evidence of
linkages between the scientific question and management needs
Interdisciplinary research teams : Co-investigators from both
scientific (university) and management (agency) entities to ensure a clear
application to resource management issues
Project management: University and agency scientists; management
structure with a Team Leader, lead Principle Investigator, or Project
Manager, Data Manager, post docs and graduate students (see Gulf of
Alaska IERP)
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Research Topics
Local Traditional Knowledge (LTK): Links to local research
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priorities and outline community involvement if possible. NPRB can
recommending local expertise to assist in the LTK program development
Data capture, quality control, and transfer: Data management
plan, including the storage of data and any collections, transfer of all
metadata and data to the AOOS/NPRB data archive at UAF
Process
– Scientific Steering Committee
– Public Input (July 2006)
– Pre-Proposals (Oct-Nov 2006)
– Start with synthesis-define gaps (BIAW)
– Integrate modeling
– Teams are multi-disciplinary and multiinstitutional
– Projects relevant to resource management
Timing
• Apr-Aug 2006: Development of Implementation
Plan
- BSIERP SSC
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- July BIAW/BEST meeting in Seattle
• Sep 2006: Develop 2007 RFP
• Oct 2006: Launch 2007 RFP
•Spring/Summer 2007: start BSIERP
Timing
Table 1. Timelines for IERP and regular proposals in the 2007 RFP
IERP proposals
Regular Proposals
Release of 2007 RFP
6 October 2006
6 October 2006
IERP Pre-Proposals due
10 November 2006
Action
Regular Proposals due
8 December 2006
Invite full IERP proposals
8 December 2006
Full IERP proposals due
2 March 2007
Decision on regular
proposals
Decisions on IERP
proposals
End March 2007
End May 2007
Six broad questions
1. Are the distributions (range, spawning and breeding locations) and
abundances of species in the Bering Sea ecosystem changing in
response to climate change? If so, how?
2. Are the physical and chemical attributes of the ecosystem
changing in response to climate change? If so, how?
3. Is lower trophic level production (quantity and form) changing in
response to climate change? If so, how?
4. What are the principal processes controlling energy
pathways in the Bering Sea? What is the role of climate
change in these processes?
5. What are the linkages between climate change and vital rates
of living marine resources in the Bering Sea?
6. What are the economic and sociological impacts of a changing
ecosystem on the coastal communities and resource users of the
Bering Sea?
Research Topics (initial ideas)
• Use of indicators (ecological, economic)
– Short/long term, small/large scale, process
• Complement existing programs in time,
space or organisms (e.g. BEST – spring,
AFSC – commercial fish)
• High stress areas: e.g. Northern BS
• Range shifts and temp effects on
ecotones/ecoregions
John Piatt et al. 2005
Research Topics (initial ideas)
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Anticipatory sampling
Hotspots
Broad scale sampling
Functional realms
Multi-forcing mechanisms (ecological analogues
between LME’s)
Process studies and prediction
Temperature effects across eco-components
Benthic-pelagic coupling
Key processes for upper level productivity and
variability
Overall goal of IERP
GOAL: Increase predictability of fluctuations
in fish stocks over a 3-5 year period by x%
NEED: Current accuracy and predictability
of models
EMC input
• General model design criteria (p.147
GOA)
EMC input
General model design criteria
• Define who will use the model and for what
• Define the questions the model is supposed to answer and directly link
those questions to the key questions and hypotheses for research
• Argue convincingly that the model structure is adequate for the purpose,
and that no better (cheaper, faster, more comprehensive, more direct) way
exists to answer these questions
• Show a schematic (flowchart) that is clear, complete and concise
• Explain how uncertainty and variability will be represented and analyzed
• Describe the system characteristics that will be left out or simplified and
how the analysis will evaluate the impacts
• Define data needs and show how the modeling effort will be coordinated
with data assimilation and data management efforts
• Define validation approach
• Define how the modeling efforts will be communicated to other scientists,
managers, and the public
• Describe how the model will assimilate data from lower trophic level
models and in turn how the outputs from this model will feed into other
models
• Describe how model outputs can be compared to other model outputs
EMC input
• General model design criteria (p.147 GOA)
• Overall framework that links modeling, field work
and decision making
– Determine data sets and data gaps
• Identify specific needs for predictability, spatiotemporal resolution, error at each model level,
model diversity, links among models
– Measures of success
• Interaction with current modeling efforts
NPRB modeling studies
• 305: Monitoring and modeling predator-prey relationships (complete)
• 313:Effects of prey availability and predation risk on the foraging ecology
and demography of harbor seals in PWS: development and test of a
dynamic state variable model (complete)
• 419: Modeling of multispecies groundfish interactions in the eastern
Bering Sea (complete-525)
• 505: EBS walleye pollock: a spatially explicit model (30 APR 06)
• 508: Female reproductive output of snow crab in eastern Bering Sea (30 June
06)
• 509: Retrospective analysis of Kodiak Red King Crab (30 June 06)
• 523: Pollock recruitment and stock structure (30 June 06)
• 524: Productivity of capelin and pollock (30 June 06)
• 525: Modeling multispecies groundfish interactions (33 Dec 07)
• 531: Seabird-fish models (30 Oct 06)
2006 RFP modeling
605: Modeling Growth and Survival of Early Life-Stages of Pacific Cod in
Response to Climate-Related Changes in Sea Ice Conditions in the Bering Sea
606: Modeling Climate Effects on Interdecadal Variation in Southeastern
Bering Sea Jellyfish Populations
607: Modeling study on the response of lower trophic level production to
climate change (link to 613)
608: Response of the Bering Sea Integrated Circulation-Ice-Ecosystem to Past
(1955-2005) and Future (2005-2055) Forcing by Climate and the Adjacent
North Pacific and Arctic Oceans
613: Bering Sea Lower Trophic Level Responses to Climate Change (link to
607)
614: Optimization of a nutrient-phytoplankton-zooplankton ecological model for
quantifying physical and biological interactions on the Gulf of Alaska shelf.
624: Modeling transport and survival of larval crab: Investigating the contraction
and variability in snow crab stocks in the Eastern Bering Sea using IndividualBased Models