Download IEM_RWO_Proposal_PhaseIII_20160531

AK RWO 224
Title: Application of an Integrated Ecosystem Model: A multi-institutional and multidisciplinary effort to understand potential landscape, habitat and ecosystem change in
Alaska and Northwest Canada.
Project Period: 9/1/2016 – 8/31/2021
Total Project Funding Requested: $X,XXX,XXX
Principal Investigator:
Amy Breen, [email protected], Scenarios Network for Alaska and Arctic Planning,
International Arctic Research Center, University of Alaska, Fairbanks, Alaska
Co-Principal Investigator:
Eugenie Euskirchen, [email protected], Institute of Arctic Biology, University of
Alaska, Fairbanks, Alaska
Co-Investigators:
W. Robert Bolton, [email protected], International Arctic Research Center, University of
Alaska, Fairbanks, Alaska
Hélène Genet, [email protected], Institute of Arctic Biology, University of Alaska,
Fairbanks, Alaska
Sergey Marchenko, [email protected] , Geophysical Institute and Permafrost
Laboratory, University of Alaska, Fairbanks, Alaska
T. Scott Rupp, [email protected], Scenarios Network for Alaska and Arctic Planning,
International Arctic Research Center, University of Alaska, Fairbanks, Alaska
Vladimir Romanovsky, [email protected], Geophysical Institute and Permafrost
Laboratory, University of Alaska, Fairbanks, Alaska
Collaborators:
Mark Lara, [email protected], Institute of Arctic Biology, University of Alaska, Fairbanks,
Alaska (relocating to University of Illinois in August 2016)
Dave McGuire, [email protected], U.S. Geological Survey, Alaska Cooperative Fish and
Wildlife Research Unit, University of Alaska, Fairbanks, AK, USA
Mark Waldrop, [email protected], U.S. Geological Survey, Menlo Park, California
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Research Work Order
Introduction:
The overarching goal of this research work order is continued development and
application of the Integrated Ecosystem Model (IEM) that integrates the driving
components for, and the interactions among, disturbance regimes, permafrost
dynamics, hydrology, and vegetation in Alaska and Northwest Canada. The outputs
from the integrated model will provide natural resource managers and decision
makers an improved understanding of the potential response of ecosystems to a
changing climate. These projections of key ecological variables of interest (e.g.,
wildlife habitat conditions) can facilitate the integration of how landscapes may
respond to climate change into resource management decisions.
Background:
Ongoing climate change throughout Alaska and Northwest Canada has the potential
to affect terrestrial ecosystems and the services they provide to the people of Alaska
and the nation. These services include the provisioning of food and fiber by Alaskan
ecosystems, the importance of ecosystems to recreation, cultural, and spiritual
activities of people in Alaska, and the role Alaska ecosystems play in regulating the
climate system.
Assessment of the effects of climate change on ecosystem services has in part been
hindered by the lack of tools capable of forecasting how landscape structure and
function might change in response to climate change. In Alaska and Northwest
Canada, such tools are needed to consider how ecological processes play out in both
space and time. Landscapes may change substantially in time and space because of
shifting species dominance (e.g., an increase of shrubs in tundra) and species
migration (e.g., treeline advance). These shifts in landscape structure and function
may be caused by changes in disturbance regimes (e.g., fire, insects, wind throw),
permafrost integrity, and hydrology across the landscape.
In this study, we will continue our development and application of an integrated
model that couples three stand-alone state-of-the-art models of ecosystem dynamics
for Alaska and Northwest Canada:
1) ALFRESCO - a model of disturbance dynamics and species establishment
(Alaska Frame-Based Ecosystem Code Model)
2) TEM - a model of soil dynamics, hydrology, vegetation succession, and
ecosystem biogeochemistry (the Dynamic Organic Soil (DOS) and Dynamic
Vegetation Model (DVM) version of the Terrestrial Ecosystem Model)
3) GIPL - a model of permafrost dynamics (the Geophysical Institute
Permafrost Lab Model)
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The IEM is capable of forecasting how landscape structure and function might
change in response to how climate change influences interactions among
disturbance regimes, permafrost integrity, hydrology, vegetation succession and
migration. This tool will provide scenarios of changes in landscape structure and
function that can be used by resource-specific impact models to assess the effects of
climate change on natural resources.
Previous research:
Phase I Scoping Study:
This Research Work Order is to fund Phase III of the IEM project, building upon two
previous phases. Phase I was a scoping study funded by the Arctic Landscape
Conservation Cooperative (LCC) that began in March 2010. The scoping study
identified a general conceptual framework for the IEM and included an initial proof
of concept study that was an asynchronous coupling of driving TEM based on future
fire scenarios from ALFRESCO, and of driving GIPL based on future scenarios of
changes in organic soil structure from TEM. These simulations were focused on
interior Alaska and were driven by downscaled climate change scenarios of the
fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC
AR4; Walsh et al. 2008). With the lessons learned from the scoping study, we were
poised to begin the second phase.
Phase II Study:
Phase II of the project was a 5-year study that began in September 2011 and will
end in August 2016 funded by the USGS/UAF Alaska Climate Science Center and the
Arctic, Western and Northwest Boreal LCCs. In this phase the objectives were to:
1) synchronously couple the models, 2) develop data sets for Alaska and Northwest
Canada, and 3) phase in additional capabilities that are necessary to address effects
of climate change on landscape structure and function (Table 1a). The synchronous
coupling of the models is both a technical activity that is necessary so the models
exchange data in real-time, while they are running in parallel for the same climate
scenario, and a scientific activity to evaluate that the temporal and spatial dynamics
of the model are operating properly.
While we have made substantial progress with the synchronous coupling, we will
not complete an operational beta version of the fully coupled IEM until December
2016. The delay is because we learned of the need to refactor the DVM-DOS-TEM
codebase to address several concerns before the model could be included within a
coupling framework. These concerns included computational efficiency, and the
ability for DVM-DOS-TEM to grow and adapt to reflect the current best model
practices and scientific understanding of ecosystem dynamics for vegetation, fire,
and permafrost. The major components of the refactoring effort were to re-write the
Input/Output format to better conform to industry standards for large geo-spatial
datasets and to create a new interface for model calibration and parameter tuning.
Re-writing the Input/Output format for DVM-DOS-TEM greatly streamlined the
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efficiency of pre- and post- processing work for model runs as well as laying the
groundwork to achieve the necessary computational efficiency by means of
parallelization. Creating a new interface for model calibration allowed us to identify
several issues within the model codebase that were preventing reliable model
results. As we have carried out this large scale refactoring effort, we have taken the
opportunity to apply software engineering best practices to the model development,
including using version control and carrying out work with incremental, testable
changes.
We identified three priority issues to incorporate into the IEM in Phase II to more
fully address issues throughout the study region: 1) tundra fire and treeline/tundra
succession dynamics, 2) landscape-level thermokarst dynamics, and 3) wetland
dynamics. We successfully incorporated tundra fire and treeline/tundra succession
dynamics into ALFRESCO which has allowed us to better forecast changes in
landscape structure and function in northern and northwest Alaska. We also
successfully created a conceptual model to represent landcover dynamics associated
with thermokarst in Alaska’s Interior and Arctic Coastal Plain. The set of rules
associated with thermokarst dynamics are in the process of being coded to the
Alaska Thermokarst Model (ATM). Proof of concept studies using the ATM over the
Tanana Flats, the Yukon Flats, and the Arctic Coastal Plain will be completed by
December 2016. The wetland dynamics aspect of the project is less well developed
thus far, although a landscape-level modeling study for the Tanana Flats was
completed using DOS-TEM.
Proposed Research:
Model Coupling. Our primary objective for the IEM is to synchronously couple the
models together. This is a technical activity that requires bringing all of the models
into a common computer platform/operating system and setting up communication
between the models so they exchange datasets at appropriate time steps. In the
Generation 1 (Gen 1) coupling, the models are linked linearly, which allows for the
exchange of information between models to occur in series. For example, data
generated by the first model is used as input for a second model, and that output is
the input for the next model. In the Generation 2 (Gen 2) coupling, the models are
linked cyclically, which allows data outputs to be exchanged among all the models
and incorporates the outputs into the next time step. In the Gen 1 coupling, the
ALFRESCO, TEM, and GIPL models were driven by a mid-range emissions scenario
(A1B) based on the climate outputs from two global circulation models (ECHAM-5
and CCCMA) used in the Fourth Assessment Report (AR4) of the Intergovernmental
Panel on Climate Change (IPCC; Walsh et al. 2008). For the Gen 1 DVM-DOS-TEM
and Gen 2 couplings, the models will be driven by the more recent suite of general
circulation models used in the IPCC Fifth Assessment Report (AR5; Moss et al.
2010), including the NCAR-CCSM4 and MRI-CGCM3, focusing on a scenario of high
greenhouse gas emissions and rate of warming (Resource Concentration Pathway
8.5, RCP 8.5).
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We anticipate an operational beta version of the fully coupled IEM will be completed
by December 2016. As noted above, the Gen 1 DVM-DOS-TEM and Gen 2 coupling
were delayed due to the need to refactor the DVM-DOS-TEM codebase. Once the
technical issues of the refactoring effort are complete and the Gen 2 coupling is
addressed, a scientific evaluation of the model needs to be conducted to determine if
the spatial and temporal dynamics of the application of the synchronous model are
sound and meet expectations. To the degree that there are retrospective data
available for model evaluation, we will make use of those data for testing the
application of the coupled model in a retrospective context. In the first year of Phase
III, a full assessment of the coupled model’s responses to climate change scenarios
will be conducted over the model domain in Alaska and Northwest Canada.
Years 2, 3, and 4 of Phase III will be devoted to work on incorporating thermokarst
dynamics, wetland dynamics, and herbivory and vegetation dynamics into the IEM,
respectively. Years 3, 4, and 5 will be devoted to conducting assessments involving
these activities, respectively, to future scenarios of climate change.
Dataset Development. This project will require ongoing data set development to
support the various activities of the project. Based on what we have learned from
the asynchronous coupling, we have developed downscaled (1 x 1 km) spatial data
sets of climate drivers for the model domain based on the IPCC AR5 scenarios, as
discussed above. As existing model inputs evolve, and new model inputs become
available, we will work with best practices for version control and incorporate these
advances into the model. For example, if a sixth IPCC assessment report (IPCC AR6)
or an ice content of permafrost data set for the model domain becomes available in
the next 5 years we will work toward downscaling these data as climate drivers for
Gen 3 of the IEM.
There will also be a need to prepare retrospective data sets pertaining to
biogeophysical (e.g., soil temperatures, active layer depths) and vegetation (e.g.,
productivity) variables for model evaluation. The existing retrospective data sets
used for validation also must be updated annually (e.g., fire perimeters compiled by
the Alaska Fire Service and the Canadian Forest Service). Finally, it is likely that data
sets will be needed for driving the additional IEM capabilities to be added
concerning thermokarst dynamics, wetland dynamics, and herbivory and vegetation
dynamics.
Our project budget includes salary for technical staff to accomplish these dataset
development tasks. If significant adjustments or expansion is needed beyond these
anticipated tasks, we will seek additional funding by leveraging from other projects
or seeking outside funding.
Thermokarst Processes. By the end of IEM Phase II, the ATM will be parameterized
and tested for the Barrow Peninsula, Tanana Flats and Yukon Flats. In the first year
of Phase III project, we will extend the application of the ATM outside of the original
test areas, to include all of Interior Alaska, and the Alaska Arctic Coastal Plain. The
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validation of the ATM application will be conducted using existing and new repeat
imagery analysis quantifying historical land cover change. During Year 1 and 2 of
the project, the IEM will undergo the technical developments necessary to represent
thermokarst dynamics at the regional-level including: 1) representing thermokarst
dynamics within a landscape resolution of 1km, the IEM needs to be modified to
simulate multiple vegetation communities within a 1 km pixel, and 2) developing
DVM-DOS-TEM to accommodate vegetation transitions associated with thermokarst
disturbance. During the third year of the project, the ATM will be integrated to the
IEM to characterize the consequences of thermokarst disturbance on land cover
dynamics and ecosystem biogeochemical cycles. Information will be communicated
at an annual time step (e.g., landcover composition, time since disturbance) from the
ATM to the IEM framework, and about fire occurrence and permafrost dynamics
from the IEM to the ATM. During the fourth year of the project, the coupled model
ATM-IEM will be run across the four test sites (Barrow Peninsula, Tanana and
Yukon Flats and Yukon-Kuskokwim Delta) from 2010 to 2100 at a monthly time
step and a 1-km spatial resolution for an ensemble of climate projections. We will
assess the impact of thermokarst dynamics on regional landcover and carbon
dynamics by comparing this set of simulations with the IEM Gen 2 simulations.
During Years 4 and 5 of the project, we will develop and apply a resource impact
model to assess how thermokarst dynamics affect wildlife habitat in three test sites
(Barrow Peninsula, Yukon Flats, and Yukon-Kuskokwim Delta). The main focus will
be on birds that constitute management priorities for the three test sites and are
characterized by consistent aerial surveys.
Wetland Processes. We will continue our collaboration with Dr. Waldrop’s (USGS
Menlo Park) field program studying wetland dynamics. Our understanding from
these field studies has been, and will continue to be, incorporated into the IEM
framework. The largest opportunity for these field studies comes from an ongoing
field project involving Dr. Euskirchen of the TEM group and Dr. Waldrop in
conducting flux scaling studies at the Alaska Peatland Experiment (APEX), where
work has been ongoing since 2005. In particular, the data from eddy covariance flux
towers examining seasonal and interannual controls on carbon, water, and energy
fluxes across a range of permafrost conditions -- combined with continued studies of
nitrogen availability, water table manipulations and isotopic experiments -provides information on scaling, sources of CO2 and methane flux, and edaphic and
biotic controls on wetland processes. There are additional opportunities at APEX for
expanding this scaling research, and we plan to work with Dr. Waldrop to design the
expansion of this research to understand how thermokarst, water table dynamics,
and warmer soils influence ecosystem function in lowland ecosystems. In Phase II
of the IEM, we developed a peatland version of the dynamic organic soil layer
(PDOS) version TEM and applied it to develop the carbon dynamics of an
intermediate age collapse scar bog. In Phase III of the IEM, we will work towards
implementing the PDOS version of TEM into DVM-DOS-TEM to gain an improved
understanding of the climate change responses on wetlands across the IEM domain.
We also note the wetland model development will be guided by impact studies that
will be defined through engaging with stakeholders about priorities for the focus of
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these impact studies, and with interactions with the thermokarst modeling
component of the IEM. It is expected that the impact models for these studies will be
developed in parallel with funding outside this project, and that ongoing
collaboration with the developers of the impact models would lead to substantial
interactions near the end of this project.
Herbivory and Vegetation Dynamics. ALFRESCO has been used to study herbivory
and vegetation dynamics in the past, although not recently. There is a need to
consider how these processes should be incorporated into the IEM as in the tundra
herbivory, particularly by reindeer and caribou, has been shown to counteract
climatically induced encroachment of trees and shrubs in tundra and the impact can
be strong enough to cause transitions between vegetation states in these
ecosystems. The first year of this project would be devoted to developing a
conceptual approach to represent reindeer and caribou herbivory and vegetation
dynamics in ALFRESCO, and the exchange of this information between ALFRESCO
and TEM. While TEM has been used to examine how changes in plant functional
types may impact caribou populations and ongoing work will investigate how
changes in plant functional types may impact moose populations, the impact of
herbivory on plant functional types in TEM has not been assessed. The second year
of this project would involve model development, testing and evaluation of an
herbivory and vegetation dynamics module in ALFRESCO. In the third year of the
project we anticipate fully incorporating these dynamics into the IEM and
conducting a proof of concept study, most likely for the Seward Peninsula where
retrospective testing can be accomplished as the history of reindeer grazing from
the early 1900s to the present is well documented. In Years 4 and 5, we will work on
assessment of these dynamics in the IEM, and in Year 5 we will work on a resource
impact study involving herbivory and vegetation dynamics. It is expected that this
work would be developed through engagement with stakeholders about priorities
for the focus of these impact studies, and in parallel with funding outside this
project.
Project Management:
Breen and Euskirchen will direct the overall project. The postdoctoral researcher
will act as coordinator and schedule monthly project meetings and record decisions
made at those meetings. Euskirchen will direct the activities involving TEM in the
overall modeling effort. Rupp and Breen will direct the activities involving
ALFRESCO in the overall modeling effort and will direct all of the project-wide data
set development and delivery by SNAP. Romanovsky will direct activities involving
the GIPL model in the overall modeling effort. Bolton and Genet, with input from
Lara, will lead the thermokarst modeling component of the project. Euskirchen will
lead the wetland modeling component of the project. Breen will lead the herbivory
and vegetation dynamics component of the project. Genet will be responsible for the
implementation of TEM in the project. Marchenko will be responsible for the
implementation of the GIPL model in the project. Technical staff will work on
development aspects of the component models of the project.
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Educational Training Experience:
This project will provide support for two early career researchers (Breen and
Genet) and one postdoctoral researcher throughout the course of the project.
Products:
The key products to come out of the proposed activities are assessments of climate
change responses to be conducted over the course of the project. The results of
these assessments have been, and will continue to be, provided as spatially and
temporally explicit data sets of landscape structure and function through SNAP’s
data portal. A list of these products is included in the IEM project fact sheet
supplement and is updated quarterly. Numerous papers have already been
published in scientific journals that document model development and application.
We anticipate many additional peer-reviewed publications to follow in the next
phase of the project.
Below we focus on Phase III Year 1 deliverables. In each year of the project, we
expect to go through a similar sequence of events to interact with the Alaska Climate
Science Center to define specific deliverables for out years. In addition, we will
submit annual reports each year.
The IEM models already provide an important tool to natural resource managers
with respect to understanding upland boreal ecosystems and the interactions
between climate, fire, and vegetation. This project will further develop that
understanding for wetland ecosystems, and specifically address thermokarst and
wetland dynamics. Furthermore, the project will support development of an
herbivory and vegetation dynamics module that will be implemented within the
ALFRESCO platform.
The Year 1 focus on refining thermokarst dynamics will provide information
important for the management of natural resources within the IEM domain that are
underlain by permafrost. We propose several deliverables specific to this modeling
activity. These deliverables will be focused on improved retrospective and future
projections of permafrost and thermokarst regimes. Preliminary proof of concept
studies and simulations will have been completed for the Tanana Flats, Yukon Flats
and Alaska Arctic Coastal Plain by the end of 2016. In Year 1 of Phase III, a land
cover map and a new set of rules driving thermokarst dynamic will be developed for
the Yukon-Kuskokwim Delta as part of a project funded by the Western Alaska LCC.
1.
2.
3.
4.
ATM code publically available via GitHub – April 2017.
Output data streams/layers available via the SNAP data portal – June 2017.
Peer-reviewed manuscript submitted – August 2017.
Webinar to share and discuss Alaska Thermokarst Model simulation results
& interpretation for the initial three test cases (Tanana Flats, Yukon Flats and
Arctic Coastal Plain)– September 2017.
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5. Annual report for Year 1 activities submitted – October 2017.
Safety Compliance:
All personnel involved in fieldwork funded by this RWO and directly or indirectly
supervised by USGS personnel will receive training and appropriate personal
protective equipment to meet or exceed USGS safety program requirements. All field
personnel are required to hold current certifications in basic first aid and adult CPR
and individuals working more than an hour from the nearest medical facility are
required to hold current certification in wilderness first aid. Bear safety, firearms
safety, and a firearms range qualification will be completed if bears are expected to
be a significant component of the field operations. Personnel using aircraft will
complete Aviation Safety training as required based on their specific activities and
type of mission and fly only with Aviation Management Directorate (AMD (formerly
OAS)) certified pilots and aircraft. Personnel conducting water-oriented fieldwork
will complete over the water safety training, and motorboat operators will complete
the DOI Motorboat Operator Certification Course (MOCC). Specialized activities
beyond those specifically mentioned here may require additional training per USGS
policy or as appropriate.
References:
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D.
P., Carter, T.R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F.,
Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P. &
Wilbanks, T. J. (2010). The next generation of scenarios for climate change
research and assessment. Nature 463 (7282):747-56.
Walsh, J.E. et al. 2008. Global climate model performance over Alaska and
Greenland. Journal of Climate 21:6156-6174, doi:10.1175/2008JCLI2163.1
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Timeline of Research Activities
Table 1a) 2013-2016: Work accomplished in Phase II of the project that commenced September 1, 2011 and will end August 31,
2016. The table lists the major activities that occurred, or will occur, each year.
Year
Model Coupling and Dataset Development
2013
 Began development of Generation 1 IEM with
new fire and vegetation dynamics.
 Began preparation of all data sets required to
drive fully Generation 1 IEM with AR4 climate
scenarios.
 Began development of Generation 2 (fully
coupled) IEM.
2014
 Completed development of Generation 1 IEM
with new fire and vegetation dynamics.
 Completed preparation of all data sets required
to drive Generation 1 IEM with AR4 climate
scenarios.
 Supported assessment using Generation 1 IEM
over the complete IEM domain driven by AR4
climate scenarios.
 Continued development of Generation 2 (fully
coupled) IEM.
 Began preparation of all data sets required to
drive Generation 2 IEM with AR5 climate
scenarios.
 Supported assessment using Generation 1 IEM
over the complete IEM domain driven by AR4
climate scenarios.
 Completed preparation of all data sets required
to drive Generation 2 IEM with AR5 climate
scenarios.
 Developing an operational “beta” version of the
Generation 2 (fully coupled) IEM.
 Supporting assessment using Generation 2 IEM
over the complete IEM domain driven by AR5
climate scenarios.
 Supporting applications for the coupling of IEM
outputs to resource impact models.
2015
2016
Tundra Fire and Treeline Dynamics
Thermokarst and Wetland Dynamics
 Incorporated new tundra fire and treeline
dynamics program code into the IEM.
 Began study of Generation 1 IEM application to
model changing ecosystem services in the
Nuiqsut region (collaboration with EPSCoR
Northern Test Case).
 Supported development of Generation 2 (fully
coupled) IEM.
 Began assessment using Generation 1 IEM with
new fire and vegetation dynamics over the IEM
domain driven by AR4 climate scenarios.
 Continued study of Generation 1 IEM
application to model changing ecosystem
services in the Nuiqsut region.
 Supported development of Generation 2 (fully
coupled) IEM.
 Began development of the Thermokarst
Predisposition Model and the Alaska
Thermokarst Model (ATM).
 Recruited postdoctoral scientist for
development of wetland dynamics aspects of
the IEM.
 Supported development of Generation 2 (fully
coupled) IEM.
 Began collaboration with the three resource
impact models funded by the Alaska Climate
Science Center.
 Continued development of the ATM.
 Began proof of concept studies for the ATM
over the Tanana Flats, Arctic Coastal Plain, and
Yukon Flats driven by AR4 climate scenarios.
 Beginning assessment using Generation 2 IEM
over the IEM domain driven by AR5 climate
scenarios.
 Continuing collaboration with the three
resource impact models funded by the Alaska
Climate Science Center.
 Completing study of Generation 1 IEM
application to model changing ecosystem
services in the Nuiqsut region.
 Continuing development of the Alaska
Thermokarst Model.
 Completing proof of concept studies for the
ATM over the Tanana Flats, Arctic Coastal Plain
and Yukon Flats driven by AR5 climate
scenarios.
 Continuing development of wetland dynamics
model being designed for incorporation into the
IEM framework and beginning proof-of-concept
study.
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 Completed development of the Permafrost
Predisposition Model.
 Continued development of ATM.
Table 1b) 2017-2021: Work to be accomplished in Phase III of the project that commence September 1, 2016 and will end
August 31, 2021. The table lists the major activities will occur each year. All modeling activities will be driven by AR5 climate
scenarios.
Year
Model Coupling and Dataset Development
2017
 Assessment using Generation 2 IEM over the
complete IEM domain.
 Prepare additional datasets required to drive
resource impact models funded by the Alaska
Climate Science Center.
 Update existing datasets as needed.
 Assessment of thermokarst dynamics.
 Prepare additional datasets required to drive
thermokarst dynamics in IEM.
 Update existing datasets as needed.
2018
2019
2020
2021
Herbivory and Vegetation Dynamics
Thermokarst and Wetland Dynamics
 Conceptual development of approach to
represent herbivory and vegetation dynamics
in ALFRESCO.
 Validation of the ATM across Interior Alaska
and the Arctic Coastal Plain.
 Complete proof of concept study for the ATM
over the Yukon-Kuskokwim Delta region.
 Model testing and evaluation of herbivory and
vegetation dynamics module in ALFRESCO.
 Development of the IEM to represent
vegetation transition associated with
thermokarst disturbance.
 Development of the IEM to represent landscape
heterogeneity.
 Assessment of disturbance and vegetation
dynamics.
 Prepare additional datasets required to drive
disturbance and vegetation dynamics in IEM.
 Update existing datasets as needed.
 Assessment of wetland dynamics.
 Prepare additional datasets required to drive
wetland dynamics in IEM.
 Update existing datasets as needed.
 Incorporation of herbivory and vegetation
dynamics component into the IEM and proof of
concept study.
 Integration of ATM into the IEM.
 Model testing and evaluation of the wetland and
thermokarst dynamics module of IEM.
 Work on assessment of herbivory and
vegetation dynamics module in ALFRESCO.
 Develop an operational “beta” version of the
Generation 3 (fully coupled with thermokarst,
wetland, and disturbance and vegetation
dynamics) IEM.
 Assessment using Generation 3 IEM over the
complete IEM domain.
 Update existing datasets as needed.
 Development and testing of a resource impact
model involving herbivory and vegetation
dynamics module for ALFRESCO.
 Application of the ATM across Interior Alaska
and the Arctic Coastal Plain.
 Evaluation of the importance of thermokarst on
regional land cover and carbon dynamics.
 Development of a resource impact model to
evaluate the effect of thermokarst.
 Test resource impact model.
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