U.S. Fish & Wildlife Service

Wildlife Response to 

Environmental Arctic Change

Predicting Future Habitats of Arctic Alaska
Workshop Sponsors

University of Alaska Fairbanks (UAF) International Arctic Research Center

ABR Inc. 

UAF Institute of Arctic Biology

Wildlife Conservation Society

Workshop and Report Coordination

The Arctic Research Consortium of the U.S. (ARCUS) coordinated workshop planning and implementation, and 

report layout and editing.

Workshop Speakers

David Atkinson, Erik Beever, Eugenie Euskirchen, Brad Griffith, Geoffrey Haskett, Larry Hinzman, 

Torre Jorgenson, Doug Kane, Peter Larsen, Anna Liljedahl, Vladimir Romanovsky, Martha Shulski, 

Matthew Sturm, Amy Tidwell, and Mark Wipfli.

Report Reviewers

Brian Lawhead, Anna Liljedahl, Wendy Loya, Neil Mochnacz, Larry Moulton, Stephen Murphy, Tom Paragi, 

Jim Reist, Vladimir Romanovsky, John Walsh, Matthew Whitman, and Steve Zack.

Photo Contributors

Doug Canfield, Stephanie Clemens, Bryan Collver, Fred DeCicco, Elizabeth Eubanks, Richard Flanders, 

Larry Hinzman, Marie-Luce Hubert, Benjamin Jones, M. Torre Jorgenson, Jean-Louis Klein, Catherine Moitoret, 

Mitch Osborne, Leslie Pierce, Jake Schaas, Ted Swem, Ken Tape, Øivind Tøien, Ken Whitten, Chuck Young, 

Steve Zack, and James Zelenak.

Cover Image

Ice floating in a lagoon near Collinson Point in the Arctic National Wildlife Refuge. Photo by Philip Martin. 

Suggested Citation

Martin, Philip D., Jennifer L. Jenkins, F. Jeffrey Adams, M. Torre Jorgenson, Angela C. Matz, David C. Payer, 

Patricia E. Reynolds, Amy C. Tidwell, and James R. Zelenak. 2009. Wildlife Response to Environmental Arctic 

Change: Predicting Future Habitats of Arctic Alaska. Report of the Wildlife Response to Environmental Arctic 

Change (WildREACH): Predicting Future Habitats of Arctic Alaska Workshop, 17-18 November 2008. Fairbanks, 

Alaska: U.S. Fish and Wildlife Service. 138 pages.

nI ternational Arctic Research Center

University of Alaska Fairbanks
Report from the 

Wildlife Response to Environmental Arctic Change (WildREACH): 

Predicting Future Habitats of Arctic Alaska Workshop

17–18 November 2008

Westmark Hotel

Fairbanks, Alaska

Authors: Philip D. Martin, Jennifer L. Jenkins, F. Jeffrey Adams, M. Torre 

Jorgenson, Angela C. Matz, David C. Payer, Patricia E. Reynolds, Amy C. Tidwell, 

and James R. Zelenak

U.S. Fish & Wildlife Service

101 12th Avenue, Room 110

Fairbanks, Alaska 99701

Phone: 907-456-0325

http://alaska.fws.gov/

Wildlife Response to 

Environmental Arctic Change

Predicting Future Habitats of Arctic Alaska

Table of Contents

Chapter 1: Executive Summary ........................................................................................................ 2

Chapter 2: Introduction...................................................................................................................... 8

Chapter 3: Arctic Alaska in a Changing Climate .......................................................................... 12

Chapter 4: Habitat Change.............................................................................................................. 38

Chapter 5: Climate Effects on Fish and Wildlife .......................................................................... 60

Chapter 6: Working Groups’ Summaries: Common Themes and Research Gaps ................... 94

Chapter 7: Conclusions and Recommendations .......................................................................... 110

Appendices

Appendix 1: Methods for Climate Projections ............................................................................ 117

Appendix 2: Description and Distribution of Northern Alaska Ecotypes .............................. 120

Appendix 3: WildREACH Workshop Agenda ............................................................................. 127

Appendix 4: WildREACH Workshop Participants ..................................................................... 129

Appendix 5: Working Group Charges and Members.................................................................. 135
2

Chapter 1 

Executive Summary
3

Climate is changing worldwide, 

but the Arctic is warming at a 

rate almost twice the global average. Changes already observed in 

arctic terrestrial landscapes include 

rapidly eroding shorelines, melting 

ground ice, and increased shrub 

growth at high latitudes. Because 

the Arctic will likely experience 

early and disproportionately large 

impacts of climate change, the U.S. 

Fish and Wildlife Service (Service) 

has identified America’s Arctic as a 

priority region for developing management strategies to conserve fish, 

wildlife, and their habitats. 

The Service convened a Wildlife 

Response to Environmental Arctic 

Change (WildREACH) workshop on 

17–18 November 2008 in Fairbanks, 

Alaska. Our goal was to identify the 

priority research, modeling, and 

synthesis activities necessary to 

advance our understanding of the 

effects of climate change on birds, 

fish, and mammals of arctic Alaska, 

focusing on terrestrial and freshwater systems. We used a conceptual 

modeling approach to identify the 

potential changes that would most 

strongly influence habitat suitability 

for a broad suite of arctic species. In 

doing so, we embarked on the first 

essential step toward incorporating 

climate considerations into biological 

planning and conservation design 

for the Arctic. The workshop was attended by over 100 participants representing federal and state agencies, 

academia, and commercial and nonprofit organizations. WildREACH 

provided a forum for communication 

among specialists from multiple 

disciplines, a vital first step toward 

establishing effective partnerships. 

Summaries of each workshop report 

chapter are provided below. 

Climate, Permafrost, Hydrology

The average annual temperature of 

Alaska’s North Slope is projected 

to rise approximately 7°C by 2100. 

The magnitude of change is imprecisely known, but Global Circulation 

Models identify northern Alaska as 

one of the fastest warming regions 

of the planet. Annual precipitation is 

also expected to increase, although 

there is less certainty surrounding 

this prediction.

In the Arctic, climate affects habitat 

uniquely through the interdependencies of permafrost, hydrology, and 

vegetation. The deep, cold, continuous permafrost of the North Slope 

represents a reservoir of resilience 

for this landscape. Nevertheless, 

enhanced seasonal melting of nearsurface ice is already measurably 

altering habitats and hydrology. 

Understanding how variation in 

the type and quantity of ground ice 

influences a landscape’s susceptibility to warming is fundamental to 

predicting the extent and magnitude 

of habitat change.

Hydrologic processes are a pivotal 

determinant of climate-influenced 

habitat change in arctic Alaska. 

Changes in overall water balance 

and in timing and magnitude of seasonal water and energy fluxes will 

strongly affect habitat availability 

and quality for arctic-adapted species of fish and wildlife. The seasonal 

allocation of precipitation is key to 

ecosystem response in an environment where water remains frozen 

most of the year. Despite the expectation of higher annual precipitation, 

models predict a generally drier 

summer environment. Refining models to more confidently predict water 

balance and the resultant water 

supply available to various habitat 

types is one of our most important 

challenges.

The presence of ice-rich permafrost 

soils makes arctic tundra uniquely 

vulnerable to the effects of warming. 

Photo from USFWS, Ikilyariak 

Creek, Arctic National Wildlife 

Refuge.
4

Habitat Change

Effects of climate change on North 

Slope habitats will vary depending on the permafrost-influenced 

geomorphic processes specific to 

particular ecosystems. It is useful to 

consider the coastline, Coastal Plain, 

Foothills, and floodplains separately. 

• In the coastal zone, rapid shoreline 

erosion is occurring, associated 

with the retreat of summer sea 

ice. Rising ocean temperatures, 

sea level rise, permafrost degradation, increased storm surges, and 

changes to river discharge and 

sediment transport will continue to 

affect habitat availability and quality in the coastal zone. 

• The vast shallow wetlands of the 

Coastal Plain landscape are sensitive to changes in water balance 

that could lead to drying. Lakes 

may enlarge through melting and 

erosion at their edges. Alternatively, lakes may drain if surrounding ice wedges degrade, resulting 

in the formation of new drainage 

networks. 

• The hilly terrain of the Arctic 

Foothills is prone to thaw slumps 

and gully formation. In the lower 

Foothills, extremely ice-rich soils 

are susceptible to ice wedge degradation, melting of massive ice, and 

formation or drainage of thermokarst lakes.

• Floodplains are very dynamic 

landscapes and could respond to 

climate change in a variety of ways. 

Floodplain processes are influenced more strongly by extreme 

flood events than by average conditions, and models of future flood 

frequency and severity must be 

better developed in order to predict 

habitat change.

Historically, tundra fires have been 

rare on the North Slope, but fire 

frequency will likely increase as the 

climate warms. A positive feedback 

relationship exists whereby soils 

tend toward a warmer and drier 

condition after fire, which in turn 

promotes shrub growth and a more 

fire-prone landscape. Although widespread conversion of North Slope 

tundra to spruce forest is not expected within this century, increased 

shrub cover has been documented 

in the Brooks Range and Foothills, 

a trend that is expected to continue. 

Changes in plant phenology (e.g., 

earlier green-up and senescence) 

are certain to occur as spring melt 

comes earlier. 

Climate change may increase availability and uptake of contaminants 

for fish, wildlife, and their habitats. 

Contaminants currently contained 

within glacial ice, multi-year sea ice, 

and permafrost, including persistent 

organic pollutants and mercury, 

will almost certainly be released to 

aquatic ecosystems as the temperature rises.

Climate Effects on Fish and Wildlife 

WildREACH workshop participants 

formed working groups for birds, 

fish, and mammals. Each working 

group developed conceptual models 

to illustrate hypotheses of likely 

pathways by which fish and wildlife 

populations of arctic Alaska may be 

affected by climate change. Hydrologic process models for summer 

and winter provided linkages among 

climate variables, physical processes 

(hydrologic and permafrost), and 

habitat change. These processes 

were relevant to all species groups.

The bird working group developed 

conceptual models organized around 

four broad topics: abundance and 

distribution of surface water, vegetation community change, invertebrate 

community change, and coastal 

processes. Spring melt is accompanied by a sharp peak in flow for rivers that arise in 

the Brooks Range—changes in precipitation and warming temperatures 

may change flow regimes and sediment transport in arctic rivers. Photo 

from USFWS, Sadlerochit Mountains, Arctic National Wildlife Refuge.
5

The fish working group developed a 

single conceptual model emphasizing pathways related to the effects 

of increased water temperature and 

hydrologic changes related to soil 

moisture, glacial input, drainage 

changes related to permafrost degradation, and changes in lake area.

The mammal working group developed separate models for the summer and winter seasons. Key factors 

in winter included changes in the 

timing, amount, and nature of precipitation (e.g., rain-on-snow events, 

deeper snow). In summer, changes in 

plant species composition, amount of 

forage, and seasonality were expected to have the greatest potential for 

affecting mammal populations. 

Common Themes and Research Gaps

Despite the uncertainty in projecting climate change impacts on arctic 

species and habitats, workshop participants identified monitoring, research, and modeling priorities that 

will help improve our understanding 

of future conditions. Specific information gaps varied among species 

groups, but most fell into four crosscutting themes: 1) changes in precipitation and hydrology; 2) changes 

in vegetation communities and phenology; 3) changes in abundance and 

timing of invertebrate emergence; 

and 4) coastal dynamics. 

All working groups emphasized that 

predictions regarding climate effects 

on fish and wildlife populations must 

be tentative, given the uncertainty 

surrounding climate forecasts and 

unavailability of models that couple 

climate, geophysical, and ecological 

processes at appropriate spatial and 

temporal scales. All working groups 

agreed that in order to more accurately predict climate change effects 

on species and habitats, multidisciplinary work is needed to better 

understand the underlying biological 

and physical processes that drive 

terrestrial and aquatic ecosystem 

function and the response of those 

systems to climate change. Hydrologic processes, in particular, are pivotal determinants of climate-related 

habitat change, and enhanced data 

collection and modeling in this area 

will benefit multiple users. 

All working groups emphasized that 

information available on life history, 

habitat requirements, distribution, 

abundance, and demography is 

inadequate for many arctic species. 

Basic biological studies, therefore, 

are also needed. Focal species should 

be chosen based on their predicted 

vulnerability to climate change and 

potential to serve as indicators of 

hypothesized habitat changes. 

Conclusions and Recommendations 

WildREACH workshop discussions 

revealed several specific information 

gaps within the four major thematic 

areas previously listed (see Table 

on page 7). These gaps represent 

the highest scientific priorities for 

scientific inquiry, which should be 

pursued in an organized, multidisciplinary fashion. Specific recommendations include:

1. Establishment of at least three 

long-term observatories on the 

North Slope to collect integrated 

hydrologic, climate, and geophysical data. The central mission of 

these observatories should be to 

develop an understanding of the 

response of permafrost (active 

layer dynamics), hydrologic, and 

ecological systems to changes in 

thermal regime. To ensure applicability to fish and wildlife biology, 

water budgets should be estimated 

for key ecotypes.

2. Intensive observations at the 

observatory sites should be supplemented by instrumentation (e.g., 

meteorology, radiation, stream discharge, soil moisture) at dispersed 

sites arrayed across important 

environmental gradients. 

3. Modeling that dynamically 

couples soil thermal and hydrologic 

regimes, and biological systems at 

appropriate spatial and temporal 

scales. 

4. Centralized data storage and interpretation for the mutual benefit 

of multiple end-users.

A flock of black brant migrate along the Beaufort Sea coast. Optimal timing 

for bird migration could change under an altered climate regime. Photo by 

Philip Martin from Canning River delta, Arctic National Wildlife Refuge.
6

We also recommend immediate 

attention to developing predictive 

models of habitat change, focusing 

initially on processes that are occurring now and that act on short (e.g., 

decadal) time scales. Priority topics 

include:

1. Coastal processes (e.g., erosion, 

storm surge, deposition, vegetation 

succession);

2. Seasonality (e.g., plant phenology, 

animal migration, life stages of 

aquatic invertebrates); 

3. Shrub advance;

4. Fire regime (as a function of interactions among climate, permafrost, 

and vegetation); and 

5. Thermokarst effects on surface 

water storage, drainage systems, 

and lakes.

The Service should engage the U.S. 

Geological Survey (USGS) and others in a structured decision-making 

process to refine the selection of 

indicator species/parameters as 

components of a long-term climate 

monitoring program. Upon reaching 

consensus, management agencies 

should seek stable funding for monitoring these species/attributes.

The Service recognizes that we 

must change the way we do business to succeed in managing fish, 

wildlife, and their habitats in a 

rapidly changing climate. We can no 

longer manage for the status quo—

we must manage for an uncertain 

future. These challenges exceed the 

capacity of any one agency, and we 

must pool our collective resources. 

By strategically targeting financial 

resources, we can build Landscape 

Conservation Cooperatives that 

increase capacity, eliminate redundancy, and provide the technical 

expertise to implement conservation, 

research, and management at all 

scales.

The Service will improve communication and collaboration with the 

arctic research community to initiate 

building of wide-ranging partnerships. On a local, regional, and 

national level the Service will:

1. Work with the National Science 

Foundation (NSF) to define climate 

research priorities relevant to resource management agencies; 

2. Increase collaboration with 

academia and other researchers to 

develop grant proposals that address priority questions; 

3. Participate in planning and implementation of the interagency Study 

of Environmental Arctic Change 

(SEARCH) Program to ensure 

inclusion of research relevant to 

resource management agencies;

4. Work with arctic science program 

managers in the research agencies 

(e.g., NSF, USGS, National Oceanic 

and Atmospheric Administration) 

to obtain funding for work that addresses priority questions; and

5. Promote a collaborative approach 

to acquire, process, archive, and 

disseminate essential satellitebased remote sensing data products (e.g., snow cover, green-up, 

and surface water) needed for 

regional-scale monitoring.

Climate change presents an unprecedented challenge to managers of 

arctic natural resources. By initiating a collaborative process among 

biologists, physical scientists, and 

managers, the WildREACH workshop successfully identified priority information gaps and activities 

needed to provide the basis for 

adaptive management of arctic fish 

and wildlife resources. Since the 

workshop, the Service has identified America’s Arctic as Alaska’s 

first Landscape Conservation 

Region, which will be supported by 

the technical capacity housed in the 

Northern Alaska Landscape Conservation Cooperative. Adopting the 

WildREACH recommendations is 

the next step in strengthening our 

capacity to anticipate climate-related 

habitat change and to identify the 

most promising strategies to conserve fish and wildlife populations in 

America’s Arctic.

An undercut 

bluff on the 

Beaufort Sea 

coast, the result 

of a severe storm 

in August 1980, 

illustrates the 

susceptibility 

of ice-rich 

coast to rapid 

erosion. Photo 

by Catherine 

Moitoret, 

Canning River 

delta, Arctic 

National 

Wildlife Refuge.
7

Scientific Priorities

Workshop participants identified important information gaps in our understanding of climate change effects 

on birds, mammals, and fish populations. The specific gaps varied among species groups, but most fell into four 

cross-cutting thematic areas and underlying research questions (see Chapter 6 for more details):

1. Precipitation, Water Balance, and Distribution of Surface Water 

a. How reliable are the projections for increasing precipitation and evapotranspiration?

b. How will the annual precipitation input on the Coastal Plain and Foothills be allocated between winter (snow 

pack) and summer?

c. How will changes in precipitation, evapotranspiration, and active layer depth alter summer surface water 

availability in shallow-water and mesic/wet tundra habitats?

d. How will changing patterns of seasonal runoff affect stream flow?

e. What is the contribution of groundwater in various systems, and is it sufficient to maintain year-round flow? 

f. Will drought conditions and changes in drainage patterns decrease water body connectivity?

g. Which Coastal Plain lakes are susceptible to tapping (rapid drainage) and on what time scale?

h. What are the expected changes in snowpack characteristics (depth, density, presence of ice layers) and how 

might these vary on a regional and local scale?

i. How much change will occur in the timing of snow melt and snow onset?

j. How will the frequency of rain-on-snow and severe winter storm events change?

2. Vegetation Community Composition and Phenology

a. How will changes in the length and timing of the growing season influence plant phenology, including seasonal 

changes in nutritional quality?

b. How will plant species composition shift in response to long-term climate change, and what are the implications for habitat structure and quality of the prevalent available forage (i.e., digestibility, nutrient content)?

c. What is the time scale of expected shrub increase, and how will this vary by species/growth form (low vs. tall 

shrub) and ecoregion? 

d. What is the likelihood of widespread conversion from sedge and sedge-shrub meadow to bog meadow (paludification) and how would this affect herbivore and detritus-based trophic systems?

e. How will changes in the seasonality of stream discharge and occurrence of flood events influence development 

of riparian vegetation communities? 

3. Abundance and Phenology of Invertebrates

a. How does earlier spring thaw affect timing of life cycle events and peak availability to predators?

b. How does temperature affect growth and development of aquatic insects?

c. What climate-related changes are likely in community composition of macroinvertebrates in stream, lake, and 

saturated soil environments?

d. How will changes in the distribution and quality of surface waters and shifts from pelagic to benthic productivity in deep lakes affect availability of macroinvertebrates to fish and wildlife? 

e. How will warming and changing seasonality affect abundance and peak activity periods of biting insects and 

what are the bioenergetic consequences for caribou in particular?

f. How will warming and changing seasonality affect the prevalence of parasites and disease vectors (e.g., nematode parasites of muskoxen and Dall’s sheep)? 

4. Coastal Dynamics 

a. Will higher water temperatures, sea level rise, and retreat of summer sea ice cause degradation of the barrier 

island systems of the Beaufort and Chukchi seas?

b. Will alluvial deltas continue to build or will rising sea levels outpace potential increases in sedimentation 

rates?

c. How quickly will shoreline retreat result in newly breached lake basins? 

d. To what extent will coastal erosion, in combination with sea level rise, cause salinization of low-lying coastal 

areas?

e. Will coastal wet sedge meadows establish at a rate equal to loss of this habitat through erosion and inundation?

f. Will increased fogginess/cloudiness exert a negative or positive feedback effect on air temperature in the 

coastal zone? What is the expected spatial extent of this effect?
8

Chapter 2 

Introduction

Climate warming is having 

profound effects on fish, 

wildlife, and their habitats, 

challenging resource agencies 

to manage ecosystems that are 

being fundamentally altered. 
9

Climate is changing across the 

planet, but the Arctic is warming at 

a rate almost twice the global average, and precipitation is projected 

to increase significantly by the end 

of the century. Sea ice extent has 

decreased steadily over the past 40 

years, and the Arctic may be ice-free 

in the summer within a decade. Arctic terrestrial landscapes are also being altered by warming with rapidly 

eroding shorelines, melting ground 

ice, and increased shrub growth 

at high latitudes. The presence of 

frozen ground creates an environment uniquely sensitive to warming, 

because permafrost holds water at 

the surface, creating vast wetlands 

and aquatic habitats in a region that 

would otherwise be classified as arid. 

If unabated, melting ground ice will 

ultimately result in the drying of 

northern Alaska with profound consequences for fish and wildlife. 

The mission of the U.S. Fish and 

Wildlife Service is, in part, to conserve fish, wildlife, and their habitats for future generations. To date, 

the Service’s management objectives 

have generally been defined in terms 

of maintaining the status quo or 

restoring past conditions. Climate 

change forces us to consider a future 

in which ecosystems and species 

assemblages will differ dramatically from the historical condition. 

Because the Arctic will likely experience early and disproportionately 

large impacts of climate change, the 

Service has identified America’s 

Arctic as a priority region for 

developing management plans and 

adaptation strategies to conserve 

fish, wildlife, and their habitats. 

The North Slope of Alaska encompasses America’s terrestrial 

Arctic and is a large and relatively 

non-impacted landscape north of 

the Brooks Range. It is the only 

example of the arctic biome within 

the United States. Two well-known 

areas of high-value wildlife habitat 

are the portion of the Arctic Coastal 

Plain within the Arctic National 

Wildlife Refuge and the Teshekpuk 

Lake Special Area in the National 

Petroleum Reserve–Alaska. The 

Teshekpuk Lake region is a unique 

molting area for Pacific black brant 

and three other species of geese, and 

is used by many other water birds 

for feeding, nesting, and molting. 

The refuge's Coastal Plain is best 

known as the calving ground of 

the Porcupine Caribou herd. Highvalue wildlife habitat is by no means 

restricted to these discrete locations, however. Wetland and coastal 

habitats across the North Slope 

provide nesting and rearing habitat 

for millions of birds that migrate 

north from four continents to exploit 

this seasonally productive habitat. 

Four distinct caribou herds roam the 

North Slope, from the Chukchi Sea 

to the Canadian border. This rich 

landscape also provides habitat for 

three threatened species, a variety 

of resident and anadromous fish species, muskoxen, and furbearers. 

Across this region, the Service 

manages significant trust resources 

including threatened species (Steller’s eider, spectacled eider, and polar 

bear) and migratory bird species of 

concern (Pacific black brant, yellowbilled loons). Refuge-held lands 

within the Arctic are not only significant for their habitat values, as illustrated in part by their importance 

to caribou, fish, and migratory birds, 

but also contain the only designated 

Wilderness in the Arctic. In addition, 

the Service is responsible for providing opportunities to the residents of 

North Slope villages for continued 

subsistence harvest. In the Arctic, 

climate change is already impacting 

Native cultures and natural resources. It is vital that stakeholders work 

collaboratively to develop systematic 

approaches for monitoring impacts, 

predictive models, and strategies for 

management and conservation.

The Service convened a Wildlife 

Response to Environmental Arctic 

Change workshop (WildREACH) on 

Caribou (Rangifer tarandus)

in the Arctic National Wildlife 

Refuge. Photo by Doug Canfield, 

USFWS.
10

17–18 November 2008 in Fairbanks, 

Alaska, to identify the priority 

research, modeling, and synthesis 

activities necessary to advance 

our understanding of the effects of 

climate change on birds, fish, and 

mammals dependent on the terrestrial and freshwater systems of 

arctic Alaska (see Appendix 3 for the 

workshop agenda). Scientists from 

a variety of disciplines joined fish 

and wildlife managers to discuss the 

linkages between climate, hydrologic and geomorphic processes, and 

ecosystem change (see Appendix 4 

for list of participants). A conceptual modeling approach was used to 

identify potential changes that would 

most strongly influence habitat 

suitability for a broad suite of arctic 

species. The conceptual models are 

considered the forerunners to a later 

generation of spatially explicit models that will be designed to forecast 

changes in habitat availability and 

quality. Landscape-change models 

are critical to the Service and others 

working toward identifying those 

species and habitats most vulnerable 

to adverse climate-related impacts. 

As models are refined and informed 

by new research and monitoring 

data, we will improve our ability 

to design and implement management strategies that are responsive 

to urgent conservation problems 

and are logistically and financially 

achievable.

The WildREACH workshop also 

was a first step in establishing a 

Landscape Conservation Cooperative (LCC). Because the scope 

and complexity of climate change 

problems surpass the abilities and 

budget of any one agency or organization, the Service envisions building 

shared capacity among scientists to 

design and implement conservation 

strategies via LCCs. By identifying 

areas of common interest among 

researchers and managers and 

promoting collaborative efforts, we, 

as a conservation community, will 

improve the quality of information 

available to support management 

decisions. WildREACH was the 

beginning of a collaborative process 

to develop conceptual models and to 

highlight areas of uncertainty and 

information gaps, including aspects 

of both geophysical and biological 

processes. Since the workshop, the 

Service has identified America’s 

Arctic as Alaska’s first Landscape 

Conservation Region, which will be 

supported by the technical capacity 

housed in the Northern Alaska LCC. 

In order to provide better information and decision-making tools for 

managers, our next steps will be to 

begin to address information gaps 

and development of habitat change 

models. The Service recognizes 

that our success in conserving fish, 

wildlife, and their habitats depends 

on building shared capacity and 

establishing effective collaborative 

partnerships with specialists from 

multiple disciplines. 

This report synthesizes the information presented at the workshop. 

Background information on the 

region’s current and projected 

climate, permafrost, and hydrology 

is presented in Chapter 3; processes of geomorphic and habitat 

change are outlined in Chapter 4; 

and conceptual models of fish and 

wildlife response to climate change 

are developed in Chapter 5. Priority 

research, monitoring, and modeling 

tasks are summarized in Chapter 

6, and final recommended actions 

are in Chapter 7. The priorities and 

conclusions are those of the Fish 

and Wildlife Service, as informed 

by input from the diverse group of 

workshop attendees. We recognize 

this as a first of many steps toward 

coordinating efforts with other 

resource agencies, researchers, and 

non-governmental organizations. At 

present, the scale of our knowledge 

does not match the scale of our management responsibilities. We look 

forward to continuing to develop this 

coordinated partnership to assess, 

monitor, and predict the impacts of 

climate change on terrestrial and 

freshwater landscapes in America’s 

Arctic so that we may conserve this 

landscape and the animals who live 

there for future generations. 

Tussock tundra covers vast areas 

of the Arctic Foothills and Brooks 

Range. USFWS photo.
11

Ice remnants in Lake Ikpikpuk in July 2005. Photo by Leslie Pierce, TREC 2005, courtesy of ARCUS.
12

Chapter 3

Arctic Alaska in a 

Changing Climate

This background chapter 

provides a brief introduction 

to the ecoregions of the North 

Slope of Alaska, an overview 

of both observed and projected 

climate change in the region, 

and some general information 

about permafrost and 

hydrologic processes in the 

Arctic.
13

North Slope 

Ecoregions

Alaska’s North Slope covers approximately 204,000 km2

 of arctic 

lands, extending from the shores 

of the Beaufort and Chukchi seas 

to the crest of the Brooks Range 

mountains. Human population within 

the region is about 7,000 residents 

(2004 census), with activity and 

infrastructure concentrated within 

eight small communities and the 

widespread industrial zone with a 

hub at Deadhorse/Prudhoe Bay. 

Land management and ownership 

is partitioned among seven major 

entities (Figure 3.1). The Bureau of 

Land Management (Department of 

the Interior [DOI]) is responsible 

for management of a large portion 

of the region—nearly 45% of the 

total area or roughly 91,000 km2. The 

State of Alaska is the second largest 

landowner, responsible for 41,000 

km2 (20%). Fish and Wildlife Service 

(DOI) lands account for approximately 35,000 km2

 (17%), and Native 

lands encompass about 26,000 km2

(13%). The remaining lands are held 

by the National Park Service (DOI), 

private owners, and the Department 

of Defense. 

The North Slope is divided into 

three ecoregions: Arctic Coastal 

Plain, Arctic Foothills, and Brooks 

Barrow

Nuiqsut

Atqasuk Kaktovik

Point Lay Deadhorse

Point Hope

Wainwright

Anaktuvuk Pass

0 50 100 200 300 400 500

Kilometers

C H U K C H I S E A

B E A U F O R T S E A

Land ownership and

infrastructure

Bureau of Land Management

Fish and Wildlife Service

National Park Service

Native Corporation

State of Alaska

Existing infrastructure

Figure 3.1. Land ownership and location of human infrastructure on Alaska’s North Slope. Map by USFWS from 

Alaska Department of Natural Resources data.

Range (Figure 3.2). Information for 

each ecoregion is derived from Gallant et al. (1995).

Arctic Coastal Plain

The 50,000 km2 Arctic Coastal Plain 

is the northernmost ecoregion in 

Alaska. The Coastal Plain is bounded on the west and north by the 

Chukchi and Beaufort seas and extends east nearly to the U.S.-Canada 

border. The region is underlain by 

thick permafrost, up to 650 m deep 

at Deadhorse/Prudhoe Bay. Permafrost-related surface features are 

common, including pingos, ice wedge 

polygons, peat ridges, and frost 

boils. Most major streams originate 

from the other ecoregions to the 

south. Lakes of both thermokarst 

and non-thermokarst origin are 

ubiquitous, constituting over 14% of 

the landscape. Streams west of the 

Colville River are interconnected 

with lakes and tend to be sluggish 

and meandering, while those east of 

the Colville River are braided and 

build deltas into the Arctic Ocean. 

Most of the smaller streams freeze 

completely during winter. 
14

Arctic Foothills

The Arctic Foothills, a 96,000 km

2

band of rolling hills and plateaus, 

grades from the Coastal Plain to the 

Brooks Range. The Foothills stretch 

from the Chukchi Sea in the west to 

the U.S-Canada border. The ecoregion is underlain by permafrost, and 

permafrost-related surface features 

are common on the landscape. The 

Foothills have better defined drainage networks than the Coastal Plain. 

Most streams tend to be swift, but 

portions may be braided and smaller 

streams dry or freeze during winter. 

Flooding and channel shifting is 

common during breakup of river ice. 

Lakes of glacial origin and oxbow 

lakes, located along major streams, 

are the predominant types in the 

region.

Brooks Range

The Brooks Range ecoregion is the 

Alaskan extension of the Rocky 

Mountains, of which 58,000 km

2

 lies 

north of the continental divide. The 

ecoregion covers most of the eastwest extent of northern Alaska—

from the U.S.-Canada border to 

within 100 km of the Chukchi Sea. In 

contrast to the Arctic Coastal Plain 

and Arctic Foothills, this ecoregion 

was extensively glaciated during 

the Pleistocene epoch, but the few 

remaining glaciers are limited to 

the eastern sector. The terrain is 

dominated by rugged mountain complexes, and continuous permafrost 

underlies the region. The combination of harsh climate, shallow soils, 

and highly erodible slopes result in 

sparse vegetation cover that is generally limited to valleys and lower 

hill slopes. Streams in the Brooks 

Range often have braided drainage patterns, with larger streams 

draining north and their tributaries 

flowing east or west. Lakes constitute less than 1% of the landscape 

and tend to occur in rock basins at 

the mouths of large glaciated valleys, in areas of ground and terminal moraines, and on floodplains of 

major rivers. 

Figure 3.2 (top). Ecoregions on 

the North Slope of Alaska. Map by 

USFWS from USGS data (Gallant 

et al. 1995).

Figure 3.3 (bottom). Annual and 

seasonal temperature trends for the 

northern hemisphere, 1958–2008. 

The scale indicates temperature 

change (°C) over the period, based 

on local linear trend. Data from 

Goddard Institute for Space Studies 

(http://data.giss.nasa.gov/gistemp), 

downloaded January 15, 2009.

Dec–Jan–Feb

Mar–Apr–May

J

u

n–Jul–Aug

Sept–Oct–Nov

Annual

-8 -4 -2 -1 -0.5 0.2 0.5 1 2 4 8
15

Climate Trends in the Arctic

The arctic climate has warmed rapidly over the past 50 years. Annual 

average temperature has increased 

nearly twice as fast as the rest of the 

world (ACIA 2004: 10). This polar 

amplification of warming is attributed to: 1) positive feedback effects of 

greater heat absorption associated 

with reduced snow and ice cover 

on land and sea, 2) larger fraction 

of energy going to warming rather 

than evaporation relative to the tropics, 3) shallower troposphere (lower 

atmosphere) and frequent surfacebased temperature inversions, and 

4) atmospheric and oceanic circulation (ACIA 2004: 20). Compared to 

the rest of the circumpolar Arctic, 

terrestrial areas in northern Alaska, 

western Canada, and central Russia 

have experienced the most rapid 

warming (Figure 3.3). In northern 

Alaska, the most pronounced warming has occurred during winter and 

spring.

Observed Climate Change in Arctic 

Alaska

Recent warming notwithstanding, 

the climate of arctic Alaska is cold 

and dry (Figure 3.4) with a mean 

annual air temperature (MAAT) 

of -12°C (10.4°F) and mean temperatures below 10°C (50°F) in 

every month of the year. Surface 

air temperature on land is strongly 

influenced by proximity to the 

coast, with inland areas experiencClimate

Figure 3.4 (top). Average monthly 

high (red line) and low (blue line) 

temperatures and precipitation 

(green bars) in the Arctic from 

1971–2000. Data courtesy M. 

Shulski.

Figure 3.5 (bottom). 50-year trend 

in mean annual temperature at 

seven sites on the North Slope. Data 

courtesy M. Shulski.

ing warmer summers and colder 

winters in comparison to the coastal 

zone (Figures 3.6, 3.7, and 3.8 top 

panels). Annual precipitation ranges 

from 150 mm (6 in) near the coast at 

Barrow to 600 mm (24 in) or more 

in portions of the Brooks Range 

(Figure 3.9 top panel). There are 

only four stations in the region with 

multi-decadal weather records, and 

only one (Barrow) with a continuous 

record from the early 1900s until 

present (Shulski and Wendler 2007), 

resulting in a data-poor historical 

record. Despite considerable annual variation, however, the 50-year 

trend in mean annual temperature is 

positive (Figure 3.5), rising at a rate 

of 0.45°C (0.81°F) per decade. Based 

on the two best time series (Barrow 1949–1996 and Barter Island 

1949–1988), precipitation on the 

Coastal Plain has declined in recent 

decades (Curtis et al. 1998). 
16

continued page 21

Projected Climate Change in Arctic 

Alaska

Climate projections here are based 

on the composite of outputs from 5 

of the 15 General Circulation Models 

(GCMs) from the Intergovernmental 

Panel on Climate Change Fourth 

Assessment Report (IPCC 2007), 

chosen for their superior performance at high latitudes and available 

through the Scenarios Network for 

Alaska Planning (SNAP, http://www.

snap.uaf.edu; for details see Appendix 1). Based on these outputs, 

temperatures are projected to rise 

during the 21st century. Mean annual air temperature for the decade 

2091–2100 is expected to increase 

6.5–7.5°C (Table 3.1, Figure 3.6) 

compared to the baseline period 

1961–1990, depending on location. 

Most of this warming will occur 

during winter (October–May) and is 

expected to affect coastal areas more 

than inland areas, most likely due 

to the influence of a longer marine 

ice-free period (Table 3.1, Figure 

3.7). Projected summer temperature 

increases are of a lesser magnitude 

and more pronounced in inland areas 

(Table 3.1, Figure 3.8). 

By the end of the century, annual 

precipitation is projected to increase 

by 20–60%, depending on location, 

compared to the baseline period 

1961–1990 (Table 3.1, Figure 3.9). 

Most of this increase is expected to 

occur in winter, thereby contributing to a deeper snow pack. In both 

summer and winter, the relative 

precipitation increase in coastal areas is anticipated to be nearly twice 

that of the Brooks Range (Table 

3.1, Figures 3.9 and 3.10). As noted 

above, the climate records from 

Barrow and Barter Island indicate 

a decrease in precipitation over the 

past half-century, unlike the increasing trend projected for the future by 

the GCMs. 

Along with warming temperatures 

and increased precipitation, the 

length of the frost-free season is 

projected to increase across all three 

ecoregions (Table 3.2). By the end of 

the century, frost-free season length 

is projected to increase by 27–33 

days over baseline values, depending on location. Projected change 

in season length is due primarily to 

delayed onset of freezing in the fall, 

but also to an advance in first-thaw 

date in spring (Table 3.2). Increases 

Mid-century

Temperature (increase °C)

Ecoregion Winter Summer Annual

Arctic Coastal Plain 5.7 1.6 4.4

Arctic Foothills 5.5 1.8 4.3

N. Brooks Range 5.2 2.0 4.1

Precipitation (% increase)

Winter Summer Annual

Arctic Coastal Plain 48 12 28

Arctic Foothills 33 10 21

N. Brooks Range 13 12 13

End of century

Temperature (increase°C)

Ecoregion Winter Summer Annual

Arctic Coastal Plain 9.5 3.0 7.3

Arctic Foothills 9.1 3.3 7.2

N. Brooks Range 8.6 3.4 6.9

Precipitation (% increase)

Winter Summer Annual

Arctic Coastal Plain 77 27 50

Arctic Foothills 53 23 38

N. Brooks Range 36 19 22

Table 3.1. Projected magnitude of increase from historic1 values for temperature and precipitation for mid-century (2051–2060) and end of century (2091–

2100) time series. Seasonal2

 and annual data are summarized by ecoregion.

1. Baseline temperature and precipitation values are based on the ParameterElevation Regression on Independent Slopes Model (PRISM) 1961–1990 dataset 

created by the PRISM Group.

2. Summer is calculated as the average of June–September. Winter is calculated as 

the average of October–May.

Mid-century

Ecoregion

increase in 

frost-free 

season length 

(days)

Advance of 

thaw Delay in freeze

Arctic Coastal Plain 18 5 13

Arctic Foothills 16 6 10

N. Brooks Range 16 7 9

End of century

Arctic Coastal Plain 33 8 25

Arctic Foothills 28 10 17

N. Brooks Range 27 11 15

Table 3.2. Projected magnitude of increase from historic1 values for frost-free 

season length for mid-century (2051) and end of century (2100) time series. 

Regression equations for calculation of frost-free season length, advance of 

thaw, and delay in freeze provided by The Wilderness Society. 

1. Baseline temperature and precipitation values are based on the ParameterElevation Regression on Independent Slopes Model (PRISM) 1961–1990 dataset 

created by the PRISM Group.
17

Figure 3.6. Average annual air temperatures (°C), baseline (top panel, 1961–1990) and projected (middle panel, 

2051–2060, bottom panel, 2091–2100). Insets depict North Slope ecoregions (top panel) and projected change 

from baseline for periods 2051–2060 (middle panel) and 2091–2100 (bottom panel). Map created by The Nature 

Conservancy, Anchorage, Alaska.

Average Annual Air Temperatures (°C)
18

Figure 3.7. Winter air temperatures (°C), baseline (top panel, 1961–1990) and projected (middle panel, 2051–2060, 

bottom panel, 2091–2100). Insets depict North Slope ecoregions (top panel) and projected change from baseline 

for periods 2051–2060 (middle panel) and 2091–2100 (bottom panel). Map created by The Nature Conservancy, 

Anchorage, Alaska.

Winter Air Temperatures (°C)
19

Figure 3.8. Summer air temperatures (°C), baseline (top panel, 1961–1990) and projected (middle panel, 2051–2060, 

bottom panel, 2091–2100). Insets depict North Slope ecoregions (top panel) and projected change from baseline 

for periods 2051–2060 (middle panel) and 2091–2100 (bottom panel). Map created by The Nature Conservancy, 

Anchorage, Alaska.

Summer Air Temperatures (°C)
20

Figure 3.9. Average annual precipitation (mm), baseline (top panel, 1961–1990) and projected (middle panel, 

2051–2060, bottom panel, 2091–2100). Insets depict North Slope ecoregions (top panel) and projected change 

from baseline for periods 2051–2060 (middle panel) and 2091–2100 (bottom panel). Map created by The Nature 

Conservancy, Anchorage, Alaska.

Average Annual Precipitation (mm)
21

in summer temperature and duration of the frost-free period are 

expected to result in an increase in 

evapotranspiration, with drying projected across the three ecoregions 

(Figure 3.10). Near the middle of the 

century (2035–2044), the landscape 

may be 10–16% drier, and near the 

end of the century (2075–2084), the 

North Slope could be 23–37% drier 

(Figure 3.10). 

Cloud cover, including fog, can 

substantially alter the amount of 

solar energy available at ground 

level by intercepting and reflecting solar energy away from the 

earth’s surface and by emitting 

longwave radiation (i.e., heat) back 

towards the ground (e.g., Weller and 

Holmgren 1974). During summer, 

the balance between reflected and 

emitted energy tends to be negative, 

meaning that the net effect of cloud 

cover is a cooling of the surface 

(Chapin et al. 2005). Historical data 

from Barrow shows that peak cloudiness occurs in August and September, coinciding with the presence of 

open water along the coast (Maykut 

and Church 1973). Cloudiness in the 

Arctic is expected to increase as sea 

ice retreats, creating larger areas 

of relatively warm open water for a 

longer period (Walsh and Chapman 

1998). While there is agreement that 

changes in cloud cover will affect the 

arctic landscape, there is substantial 

uncertainly regarding the magnitude 

of those effects (ACIA 2005, Walsh 

and Chapman 1998).

Model Confidence

The point estimates for change 

in temperature and precipitation 

should be considered in the context 

of model reliability. Figure 3.11 

depicts the geographic pattern of 

among-model variance in temperature and precipitation for the midcentury. The differences in model 

output can be attributed largely to 

differences in the way each of the 

five models treats the seasonal retreat of sea ice, which substantially 

influences projections for fall and 

winter temperatures (John Walsh, 

International Arctic Research Center, personal communication). Sea 

ice distribution is difficult to model 

and was one of several deficiencies 

noted by Kattsov and Källén (2005) 

in GCMs. Other identified areas 

of deficiency included representation of clouds, atmospheric boundContinued from page 16

-500 

-400 

-300 

-200 

-100 

0 

100 

200 

300 

400 

500 

mm 

Time Period 

Mean June-September water balance for the Arctic Coastal Plain 

P PET P-PET 

1961-1990 2035-2044 2075-2084 

10% Drier 23% Drier 

-500 

-400 

-300 

-200 

-100 

0 

100 

200 

300 

400 

500 

600 

mm 

Time Period 

Mean May-September water balance for Arctic Foothills 

P PET P-PET 

1961-1990 2035-2044 2075-2084 

12% Drier 

25% Drier 

-400 

-300 

-200 

-100 

0 

100 

200 

300 

400 

500 

600 

mm 

Time Period 

Mean June-August water balance for Northern Brooks Range 

P PET P-PET 

1961-1990 2035-2044 2075-2084 

37% Drier 

16% Drier 

Figure 3.10. Growing season water balance, baseline (1961–1990) and 

projected (2036–2044 and 2075–2084) for the three North Slope ecoregions. 

Top panel: Arctic Coastal Plain, middle panel: Arctic Foothills, bottom 

panel: Northern Brooks Range. P=precipitation; PET=potential 

evapotranspiration. When the difference between these two quantities 

(P-PET) is negative, a drier condition is indicated. Figures courtesy Wendy 

Loya and Brendan O’Brien, The Wilderness Society, Anchorage, Alaska.
22

ary layers, freshwater discharge 

into marine waters, and vegetation 

feedbacks. 

Differences among models are not 

the only potential source of uncertainty in climate projections. Another source of variation includes 

assumptions regarding atmospheric 

concentrations of greenhouse gases; 

the results presented here are based 

on just one of the many potential 

emissions scenarios assembled by 

the IPCC Special Report on Emissions Scenarios (Nakicenovic et al. 

2000). We chose to base our discussions on a “middle-of-the-road” 

scenario (scenario A1B) but there 

is no assurance that this is the most 

probable scenario.

Potential within-model variation 

is also not incorporated into this 

discussion; rather, results are based 

on a single run of each model with 

initial conditions set to the average over the period 1961–1990 (see 

Appendix 1). An “initial condition 

ensemble” approach would employ 

multiple runs of a single model with 

variable initial conditions. This type 

of analysis would permit the inclusion of natural variability through 

the statistical distribution of climatic 

conditions and the probability of 

extreme events (Kattsov and Källén 

2005).

A retrospective analysis of the 

performance of the five models 

(SNAP 2008) demonstrated that 

model output corresponded reasonably well to actual climate records 

from 1980–2000 at 32 stations across 

Alaska. That analysis, however, 

included only one arctic site (Barrow). Models performed better for 

temperature than precipitation due 

to the inherent variability of precipitation over time and space. At 

Barrow, model outputs accounted for 

85–91% of the variation in monthly 

mean temperature, but only 21–51% 

of the variation in precipitation aggregated into four-month intervals. 

On the circumpolar scale, Walsh 

(2005) also reported a large range of 

uncertainty in projections of future 

precipitation regimes. Given the importance of water balance to habitat 

conditions, improvements in the reliability of projections of precipitation 

and evapotranspiration are urgently 

needed. 
23

Figure 3.11. Model uncertainty for annual temperature (°C; upper panel) and precipitation (mm; lower panel) 

projections for 2051–2060. Insets depict projected temperature change relative to baseline (upper panel) and 

projected precipitation increase relative to baseline (lower panel). Map created by The Nature Conservancy, 

Anchorage, Alaska.
24

Permafrost is earth material (soil, 

rock, ice, and organic material) that 

remains at or below 0°C for at least 

two consecutive years (van Everdingen 1988). Permafrost is unique to 

those areas characterized by low 

mean annual air and ground temperatures (Smith and Riseborough 

2002) and is believed to underlie approximately 13–18% of the exposed 

land in the northern hemisphere 

(Zhang et al. 2000). The areal distribution of permafrost is divided 

into four zones based on the relative 

proportions of the land underlain 

by permafrost (Brown et al. 1997): 

continuous (>90%), discontinuous 

(50–90%), sporadic (10–50%), and 

isolated (0–10%). These zones are 

loosely related to mean annual air 

temperature (MAAT), with continuous permafrost generally beneath 

areas with MAAT at or below -6° to 

-8°C (Smith and Riseborough 2002). 

The North Slope falls within the 

zone of continuous permafrost, and 

thermokarst and thermal erosion 

features are found across most of the 

region (Figure 3.12). Thawing of icerich permafrost causes the surface 

to subside, creating characteristic 

surface landforms termed thermokarst features. Processes associated 

with thermokarst include thaw, 

ponding, surface and subsurface 

drainage, surface subsidence, and 

erosion (Yoshikawa and Hinzman 

2003). Along the Beaufort Sea 

coastline, permafrost thickness is 

generally in the range of 200–400 m 

(650–1,300 ft) although a thickness of 

650 m (2,130 ft) has been measured 

at Prudhoe Bay (Gold and Lachenbruch 1973). 

At the surface, above the permafrost, soil thaws during the summer 

and freezes again in winter—this 

zone is termed the “active layer.” 

Soil texture and moisture play a 

key role in determining active layer 

depth; gravelly soils tend to be well 

drained with deep active layers, 

whereas organic soils tend to be 

poorly drained with shallow active 

layers. Active layer depth also varies 

across the terrain: it can be as little 

as 35 cm (14 in) in upland tussock 

tundra, with organic-rich soils to as 

deep as 130 cm (51 in) in riverine tall 

willow shrub with sandy soils, and 

up to 4 m or more in coarse-grained 

sediments and in the Brooks Range 

(Jorgenson et al. 2003). In addition 

to influencing active layer depth, topography and texture of the predominant soil type determine the ground 

ice content of permafrost (Box 3.1). 

Within the permafrost layer, pockets 

of perennially unfrozen ground, or 

taliks, can form in locations where 

temperature is maintained above 

Permafrost 

Figure 3.12. Permafrost distribution and associated thermokarst and thermal erosion landforms on the North 

Slope of Alaska. Map by USFWS from Jorgenson et al. 2008.
25

0°C, such as under lakes, rivers, or 

in areas influenced by groundwater 

movement (van Everdingen 1988).

The thermal regime of permafrost 

is mediated by topography, surface 

water, soil moisture, groundwater 

movement, vegetation, and snow. 

Wet, near-surface soils increase 

heat transferred into the ground in 

summer, while drier soils reduce that 

heat transfer. Unfrozen water provides an important positive feedback 

by enhancing permafrost degradation when impounded on the surface, 

when moving through the active 

layer, or flowing through taliks. 

During the warm season, vegetation protects permafrost from thaw 

by shading the ground surface from 

incoming solar radiation and acting as insulation (Streletskiy et al. 

2008). Similarly, interception of snow 

by shrubs can act to insulate soils 

against extremely cold air temperatures in winter. Because permafrost 

is strongly influenced by ecological components such as vegetation 

structure and composition, its properties evolve along with successional 

patterns of ecosystem development 

(Jorgenson et al. 1998). In turn, the 

patterns of ice accumulation and 

degradation influence the patterns 

of vegetation and soil development. 

This co-evolution of permafrost 

and ecological characteristics at the 

ground surface is most evident after 

disturbance, such as river channel 

migration, lake drainage, and fire 

(Shur and Jorgenson 2007). 

Over the past 2–3 decades, permafrost temperatures have generally 

increased 1–2°C at sites throughout 

the northern hemisphere, although 

some are stable (for review see 

Brown and Romanovsky 2008). Permafrost warmed about 2–3°C near 

Prudhoe Bay from the mid-1980s to 

1997 (Romanovsky and Osterkamp 

1997). Long-term monitoring of deep 

wells along a north-south transect 

from Prudhoe Bay to the Brooks 

Range shows a general warming 

trend over the past 25 years, but 

with stable and cooling periods 

(Figure 3.13; Osterkamp 2005). The 

Figure 3.13. Temperature records from deep wells along a north-south 

transect from Prudhoe Bay to the Brooks Range. Figure from Romanovsky 

et al. 2007.

greatest change in temperature 

at the surface of the permafrost, a 

warming of 3–4°C, was detected on 

the Arctic Coastal Plain. In Alaska, 

the changes in permafrost temperature coincide with warming air 

temperatures in winter (Osterkamp 

2005, 2007).

Sensitivity of the landscape to climate warming is greatly influenced 

by the quantity and nature of ground 

ice (Box 3.1). On a local scale, the 

stability of permafrost is affected by 

terrain, surface water, groundwater 

movement, soil properties, vegetation, and snow (Osterkamp 2007). If 

permafrost does degrade, the type 

of thermokarst and the ecological implications vary depending on 

climate, landscape position, soils, 

hydrology, and amounts and types of 

ice (Jorgenson and Osterkamp 2005). 
26

The dependence of permafrost stability on both air temperatures and 

ecological factors adds complexity to 

the task of forecasting the biological consequences of climate change.

Landscape-level models have been 

developed to project the distribution 

of permafrost under scenarios of climate change. For example, the GIPL 

model (http://www.gi.alaska.edu/snowice/Permafrost-lab/methods/modelling.html) incorporates the effects 

of surface geology, lithology, ground 

temperatures, soil properties, snow 

cover, vegetation, air temperature, 

and precipitation into a numerical model of heat transfer through 

the atmosphere, snow, vegetation, 

and active layer. The model outputs 

predicted mean annual ground 

temperature at various depths, from 

which the persistence of permafrost 

may be inferred. When applied to 

long-term (decadal and longer time 

scale) averages, this approach shows 

an accuracy of +0.2–0.4oC for mean 

annual ground temperature (Sazonova and Romanovsky, 2003). Using 

climate projections based on the 

SNAP data set under the A1B emissions scenario, permafrost distribution in arctic Alaska is expected to 

remain stable through the end of the 

century, as evidenced by projected 

mean annual soil temperature below 

0°C (Figure 3.14).

Despite the relative stability projected for permafrost in arctic Alaska, 

recent observations suggest that 

warming temperatures can accelerate thermokarst processes at mean 

annual ground temperatures well below 0°C, as evidenced by an increase 

in both area and density of degrading ice wedges in a study area on the 

Arctic Coastal Plain (Jorgenson et 

al. 2006). In the near term, thermokarst processes, such as the degradation of ice wedges, that affect 

local drainage and vegetation are 

the likely agents of habitat change, 

rather than widespread deepening of 

the active layer or a shift to discontinuous permafrost. 

Figure 3.14. Projected mean annual soil temperatures for Alaska at 1 m 

depth, 2050–2059 (above) and 2090–2099 (below). Based on output from 

the GIPL 1.3 Permafrost Model using the SNAP climate data set. Figure 

courtesy of S. Marchenko and V. Romanovsky (Geophysical Institute 

Permafrost Laboratory, University of Alaska Fairbanks) and SNAP 

(University of Alaska Fairbanks).
27

Box 3.1 Ground Ice Formation

Permafrost—frozen ground—varies in the amount and type of ice contained. 

Ground ice can take the form of: 

1. massive ice (e.g., ice wedges and pingo ice), 

2. ice contained within microscopic soil pores, or 

3. discrete lenses of segregated ice that are highly variable in size and shape 

(van Everdingen 1988). 

On the Arctic Coastal Plain, ice wedge polygons are the most common form 

of massive ice. The process of ice wedge formation was described by Lachenbruch (1962). Ice wedges begin to form when frozen soil contracts and cracks 

in response to abrupt temperature drops during winter. In spring, water 

seeps down into the crack and freezes when it reaches the permafrost zone. 

The following winter, the growing ice wedge cracks in nearly the same location. In spring, the cracks are again filled with water that soon freezes after 

it enters the ice wedge. This iterative process of cracking and freezing forms 

a polygonally patterned network, which is, from above, similar in appearance 

to the cracks in drying mud, but with polygons measuring 5–40 m in diameter. Over a period of hundreds to thousands of years (Jorgenson et al. 1998), 

growing subterranean ice wedges 

displace soil upward, forming a 

polygonal-patterned surface with 

a microtopography consisting 

of troughs, rims, and basins 

(see diagram). Local 

hydrology and vegetation is strongly 

influenced by the 

density and 

form of ice 

wedge 

polygons.

Above: Schematic illustrating formation of ice wedges by R. Mitchell/Inkworks from cited sources. 

Ice wedge

Basin

Permafrost

Active layer

Polygon rims Trough
28

Hydrology This section provides an overview of 

the hydrology of the Alaskan Arctic 

and a number of potential future impacts of increasing air temperature 

and possible increasing precipitation. There is a considerable amount 

of uncertainty associated with our 

description of current conditions, 

as well as projections of how arctic 

hydrology may differ in the future. 

The uncertainty derives from many 

sources, including difficulty measuring hydrologic parameters in an 

extreme environment, limited observational data sets covering time periods of several decades or less from 

only a few locations, and climate 

modeling errors. The arctic hydrologic cycle exhibits high natural 

variability that can make it difficult 

to clearly detect changes. Furthermore, the system is highly complex 

and involves many feedbacks that 

may accelerate some changes while 

inhibiting and restoring stability in 

reaction to other changes. 

The vast Arctic Coastal Plain is covered with lakes and ponds. Photo by Steve Zack, Wildlife Conservation Society. 

Hydrologic processes are a pivotal 

determinant of climate-influenced 

habitat change. In arctic Alaska, 

continuous permafrost forms an 

impermeable layer below a shallow 

seasonally frozen surface soil layer. 

In the Arctic Foothills, limited soil 

storage capacity and topographic 

gradients result in high runoff ratios 

in spring and summer. On the Coastal Plain, the underlying permafrost 

and low topographic gradient results 

in a landscape dominated by wetlands, ponds, and lakes (see photo 

this page) in a region that would 

otherwise be classified as arid on the 

basis of annual precipitation. Deep, 

continuous permafrost is expected to 

persist for centuries in arctic Alaska, 

even under scenarios of continued 

arctic warming. Nevertheless, 

changes in overall water balance 

(Box 3.2) and timing and magnitude 

of seasonal water and energy fluxes 

could significantly affect the aquatic 

and semi-aquatic habitats upon 

which many species depend. 
29

Box 3.2. Water Balance

The water budget of a basin can be described by the following equation:

(Ps + Pr) – (Es + ET) – R = Δ (Ssurface + Ssoil), 

where input occurs as either snow (Ps ) or rain (Pr) and output can take 

the form of either sublimation (Es), evapotranspiration (ET), or surface 

runoff (R). When this quantity is positive, there is a net increase in basin 

storage, partitioned into surface water storage (Ssurface) and soil moisture 

(Ssoil). When this quantity is negative, as occurs in a dry summer, a soil water storage deficit ensues. The larger the deficit at the end of the summer 

season, the greater proportion of next spring’s snow melt will be taken up 

to recharge ponds and lakes and absorbed into surface and near-surface 

soils.

In arctic Alaska, the best available water balance data are from the Kuparuk watershed, including Imnavait Creek in the Kuparuk headwaters, 

and the adjacent Putuligayuk River (Bowling et al. 2003, Kane et al. 2000, 

2008, Kane and Yang 2004; see map in Box 3.3, page 33).

Imnavait Creek and the Upper Kuparuk River are representative of 

systems in the Arctic Foothills, whereas the Putuligayuk River lies wholly 

within the Arctic Coastal Plain. Water input to the systems is represented 

by Snow Water Equivalent (SWE) and rainfall; water loss is through ET 

and runoff (snow and summer). As indicated in the figure, the hydrologic 

regime on the Coastal Plain (Putuligayuk River) is dominated by snowfall 

and snowmelt-generated runoff. Although snowfall and snowmelt are 

also very significant in the Foothills, it can be seen that summer rainfall 

is typically greater than end-of-winter SWE, and rainfall yields considerable runoff.

Average Water Balance Components

69

115 95

163

262

85

109

140

60

80

57

74

179

34

100

0

100

200

300

400

500

600

700

800

Imnavait Upper Kuparuk Putuligayuk

(1985-2003) (1996-2002) (1999-2007)

Basin

Water Depth (mm)

SWE Rain ET Snow Runoff Summer Runoff

Figure by Amy Tidwell for WildREACH from cited sources.
30

Overview of Hydrologic Processes 

by Season

Figure 3.15 is a generalized representation of the current hydrologic 

processes in arctic Alaska. 

Winter

Winter generally lasts from October 

until mid- to late May. During the 

cold season, precipitation falls as 

snow and is temporarily stored in 

the snow pack at the ground surface. 

Snow accumulation is reduced to 

some extent by sublimation (vaporization directly from the solid phase). 

Water stored in the snow pack at 

the end of winter is an important 

hydrologic quantity and is referred 

to as the end-of-winter snow water 

equivalent or SWE (Figure 3.15: 

A). On average, SWE represents 

approximately 40% of annual North 

Slope precipitation. However, this 

can vary greatly from year to year 

and by location. For example, in the 

upper Kuparuk River basin, SWE 

represents approximately one-third 

of total precipitation (minimum 14% 

in 1999; maximum 42% in 2000), 

while the lower Kuparuk region 

on the Coastal Plain receives an 

average one-half of its precipitation as snow (minimum 41% in 2002; 

maximum 85% in 2007; Kane et al. 

2004, 2008). 

Winter snow cover and winter temperatures strongly affect soil temperatures. Snow acts as an insulator 

between the relatively warm soil and 

cold air temperatures throughout 

the winter. Therefore, greater snow 

depth and warmer air temperatures 

act to reduce winter heat loss from 

the soil, while more shallow snow 

and lower air temperatures lead to 

colder soil temperatures.

Spring Melt

The spring season is very brief, 

with snow melt, spring flood, and 

leaf-out occurring within a period of 

2–3 weeks beginning in mid- to late 

May. During the spring, the snow 

pack that developed during winter is 

lost through combined processes of 

melting and evaporation (ablation) in 

a short period of time, usually within 

1–2 weeks (Figure 3.15: B). Once 

ablation is complete, surface soil 

temperatures begin to increase and 

soils begin to thaw. As surface soils 

thaw, they become much more permeable, and water can more readily 

Figure 3.15. Generalized representation of hydrologic processes in arctic Alaska in seasonal sequence. Specific 

features of the illustration are discussed in the text. Processes above the thick black line represent the primary 

mechanism of water movement from the surface to the atmosphere for each season. Processes below the black line 

represent movement of water from atmosphere to surface. Figure by Amy Tidwell for WildREACH from data in 

Kane et al. 2003, 2004, 2008.
31

enter the soil column, provided that 

it is not saturated (Figure 3.15: C). 

Water released from the snow pack 

during spring melt recharges lakes, 

ponds, and emergent wetlands, and 

drains off the surface into streams 

(Figure 3.15: D). 

Shortly following snow ablation, 

streamflow rises sharply. Although 

much of the snowmelt drains into 

the Arctic Ocean, a considerable 

portion remains on the surface in 

the form of lakes, ponds, wetlands, 

and soil moisture. Over the course 

of a few weeks, the inundated land 

surface area, and thus surface water 

storage, rapidly decreases as lakes 

and wetlands drain downslope until 

water surface elevations fall below their outlets (Figure 3.15: E). 

Surface water storage is further 

decreased as surface (lakes, ponds, 

etc.) and soil-stored water is lost to 

the atmosphere through evapotranspiration (the sum of evaporation and 

plant transpiration from the earth’s 

surface to the atmosphere). 

Summer

From early June through August 

and potentially into September, 

average daily temperatures remain 

above 0°C, and most precipitation occurs as rain and condensation. Early 

summer tends to have much lower 

precipitation than late summer. During this period, evapotranspiration 

often exceeds precipitation (Bowling 

et al. 2003), and the landscape undergoes progressive drying (Figure 

3.15: F). Rainfall typically increases 

throughout the season, while evapotranspiration declines due to reduced evaporation from the ground 

surface and plant transpiration. Consequently, late summer and early 

fall precipitation may reduce much 

of the surface drying that occurs in 

early summer (Figure 3.15: G). 

Currently, the Coastal Plain exhibits 

little stream response to summer 

rainfall events. This is due to the 

high surface storage capacity, low 

topographic gradient, and progressive surface drying during summer. 

As rainfall arrives at the surface, 

it replenishes soil moisture and 

surface storage and typically does 

not result in significantly increased 

streamflow (Bowling et al. 2003). In 

contrast, significant rainfall events 

do result in streamflow response in 

the Foothills (Box 3.3), where there 

is considerably less surface storage 

and steeper topographic gradients 

(Kane et al. 2003, 2008). 

Fall Freeze

Freezing temperatures may occur 

throughout the summer, but a hard 

freeze is likely any time between 

late August and mid-September. The 

onset of persistent snow cover usually occurs in September. In early 

fall, surface soils begin to cool and 

eventually reach the freezing point. 

Between mid- and late fall, the active 

layer undergoes freeze-back, primarily at the surface but also at the 

interface with the permafrost table 

(Figure 3.15: H).

The Kuparuk River in winter. Photo by J. Benstead, University of 

Alabama.
32

Implications of Climate Change to 

Hydrologic Processes

A climate shift toward higher 

temperatures and/or increased 

precipitation will likely alter the 

seasonal pattern described previously. Potential changes as compared 

to current conditions are presented 

in the following descriptions.

Winter

Increasing winter temperatures 

may not directly impact the water 

balance on the North Slope but 

will alter depth and qualities of the 

snow pack, such as density. These 

factors will affect several mammal 

species by altering access to forage 

for grazers, quality of subnivean 

habitats for small mammals, and 

soil temperatures for hibernators. 

Warmer winter temperatures may 

be accompanied by an increased frequency of rain-on-snow events, midwinter snow melt, and ice formation 

within the snowpack (Kane 1997). 

As discussed previously, increasing 

winter temperatures may also lead 

to warmer soil temperatures, with 

important implications for nutrient 

cycling and vegetation (Sturm et al. 

2005). 

Many climate model projections 

suggest that winter snowfall may 

also increase in the coming decades. 

Potential changes to winter precipitation can directly impact the water 

balance, spring floods, soil temperatures, and wildlife foraging. Increasing winter precipitation would yield 

greater end-of-winter SWE and 

more effectively insulate soils from 

winter air temperatures.

Spring Melt

Given a scenario of increased 

temperature and snowfall, effects 

on the timing of spring melt may 

be offsetting to some extent—increasing air temperatures facilitate 

earlier snowmelt, while increasing 

snow depth retards it. Alternatively, 

if the winter snow accumulation does 

not increase due to a shorter winter 

season and/or if winter precipitation 

does not increase, then the average timing of spring melt would be 

earlier in spring. If earlier snowmelt does develop, it would result 

in earlier surface storage recharge, 

peak streamflow, and onset of active 

layer thaw. Furthermore, because 

rainfall tends to be at a minimum 

early in the warm season, an earlier 

melt may result in a longer period 

of surface drying prior to increasing 

rainfall later in the summer season. 

Surface soils remain frozen during 

snow ablation and the active layer 

plays little role in the spring streamflow peak. In the Arctic Foothills, 

where lakes and ponds are less 

prominent, spring peak flows will be 

determined largely by the end-ofwinter SWE. On the Coastal Plain 

as well as Foothills areas with little 

topographic relief and significant 

surface storage (lakes and ponds), 

spring hydrologic response will 

depend on end-of-winter SWE as 

well as on the water content of the 

organic mat and soils. If the surface 

and near-surface water storage deficit is high due to dry conditions in 

the previous summer, then a larger 

volume of snowmelt the following 

spring will go directly to recharge 

surface water bodies and soils (see 

Box 3.2). Alternatively, if fall surface 

storage is high and vegetation and 

soil are wet, spring peak flow may be 

larger relative to available SWE. It 

is important to note that fall surface 

storage depends on many factors, 

such as the timing of precipitation, 

summer air temperatures, and vegetation changes.

Summer

Soil moisture is an important 

determinant of summer hydroPolygonal ground and ponds on the Arctic Coastal Plain. USFWS photo. logic response. Runoff response to a 
33

Box 3.3 Inputs into Stream Ecosystems

The source and timing of freshwater inputs into stream systems of arctic Alaska varies 

by ecoregion. The Putuligayuk River is representative of a Coastal Plain watershed, 

with input dominated by snowmelt. As illustrated by the hydrograph in Panel 1, this 

system is characterized by a single large peak coinciding with the spring freshet, 

resulting from the rapid melting of the snowpack. After 

the initial peak, discharge declines sharply and remains 

low throughout the mid-summer, with a slight rise at the 

end of summer corresponding to the period of increased 

precipitation. The Upper Kuparuk River (Panel 2) in 

the Foothills exemplifies a rainfall-dominated headwater stream. The spring snowmelt peak is still seen as 

a significant hydrologic event, yet this regime is also 

characterized by multiple peaks associated with rainfall 

throughout the summer. Relative to the Putuligayuk, the 

Upper Kuparuk is susceptible to flash floods, such as the 

one in mid-August 2002. The Kuparuk River flows through 

all three ecoregions, and the Lower Kuparuk (Panel 3) has 

a hydrologic regime with a mix of characteristics typical 

of both Coastal Plain watersheds and rainfall-dominated 

headwater systems. In the Lower Kuparuk, the spring 

freshet produces a readily detectable peak in stream flow 

that quickly declines. Large precipitation events do produce additional increases in stream flow; these spikes in 

streamflow, however, are less pronounced than those seen 

in the upper reaches of the river. 

Groundwater can also be a significant input into the annual 

water budget of arctic stream systems. There are three 

general types of groundwater in the Arctic: suprapermafrost (within the active layer in summer), intra-permafrost 

(in taliks), and sub-permafrost (beneath the permafrost 

table). Although the thick, continuous permafrost of arctic 

Alaska restricts the input of sub-permafrost groundwater 

to surface waters, spring-fed stream systems are distributed widely in the eastern Brooks Range, most commonly 

in limestone areas at an elevation of about 600 m (Yoshikawa et al. 2007). Groundwater enters streams, becoming 

baseflow, by migrating through the organic mat or unfrozen soil until it enters a drainage network or by flowing 

directly into the system (i.e., spring flow).

Glacial discharge can also be a significant water source for systems originating in the 

Brooks Range between the Sagavanirktok and Kongakut rivers. Glacier-fed systems 

are less sensitive to summer precipitation events, exhibit more diurnal variation, and 

less among-year variability in runoff (Hock et al. 2005). In the initial stages of warming, 

as melt rate increases, summer runoff will increase. Ultimately, however, loss of glacial mass will reduce overall runoff and render these systems more susceptible to reduced 

flows in summer.

Data sources:

Upper Kuparuk and Putuligayuk Rivers:

Kane DL and Hinzman LD. 2008. Climate data from the 

North Slope Hydrology Research project. University of 

Alaska Fairbanks, Water and Environmental Research Center. URL: http://www.uaf.edu/water/projects/NorthSlope/. 

Fairbanks, Alaska, variously paged. November 2008.

Lower Kuparuk:

U.S. Geological Survey. 2009. Surface Water data for Alaska: 

USGS Surface-Water Daily Statistics. URL: http://waterdata.usgs.gov/ak/nwis/dvstat? Accessed March 31, 2009.

Putuligayuk River

0

20

40

60

80

9-May 8-Jun 8-Jul 7-Aug 6-Sep

Discharge (m3/s)

2001

2002

Upper Kuparuk River

0

40

80

120

160

9-May 8-Jun 8-Jul 7-Aug 6-Sep

Discharge (m3/s)

2001

2002

Lower Kuparuk River 

0

400

800

1200

1600

9-May 8-Jun 8-Jul 7-Aug 6-Sep

Discharge (m3/s)

2001

2002

1

2

3

Map (left) shows 

location of Kuparuk 

and Putuligayuk 

rivers. Numbers 

indicate the location 

of gauging stations 

used to generate 

the hydrographs 

(above). Map by 

USFW. Hydrographs 

by Amy Tidwell for 

WildREACH from 

cited sources.
34

given storm can be vastly different 

depending on soil conditions, such 

as moisture content and active layer 

depth. For example, when the soil 

water deficit is high, there is greater 

capacity for soil to store water 

temporarily for gradual release over 

a longer period, with the effect of 

reducing peak flow and prolonging 

flow recession.

The magnitude and direction of 

change in soil moisture under 

changing climate scenarios is not 

well understood. The state of soil 

moisture depends on total soil storage capacity, recharge from rainfall, 

evapotranspiration, the ability of 

plants to access and exploit available 

soil water, and topographic gradients. Although increasing temperatures will provide additional energy 

to drive evaporation and transpiration, actual evapotranspiration can 

be water- or energy-limited. If early 

summer rainfall does not change 

considerably, then summer evapotranspiration can be expected to 

become water-limited earlier in the 

season than is currently observed. 

Fall evapotranspiration tends to be 

limited by available energy, as well 

as the onset of plant senescence. 

Therefore, changes in late summer 

and early fall rainfall can potentially 

have significant impacts on the state 

of surface water storage at the onset 

of winter.

Warmer soil temperatures and 

earlier onset of active layer thaw 

will enhance the potential depth of 

seasonal thaw and, thus, soil water 

storage capacity. Actual active layer 

thickness is complicated by soil 

moisture-energy balance-vegetation 

feedbacks. Soil water content affects 

the absorbtion of solar energy at the 

surface—a wet surface is darker and 

hence absorbs more heat than a dry 

surface. Dry near-surface (upper 10 

cm) organic soils act as an efficient 

insulator, reducing heat transferred 

into soil in summer (suppressing 

active layer depth) and heat flux out 

of the soils in winter. In contrast, 

wet soils in late summer retard the 

freezing of the soil in fall due to the 

large amounts of latent heat associated with the phase change from 

water to ice. Similarly, ice-rich soils 

require more energy to thaw than 

ice-poor soils.

If active layer thickness increases, 

the distribution of stored water may 

shift downward. This redistribution 

of water in storage may produce a 

drier surface in both wetlands and 

uplands even if the absolute volume 

of stored water is higher. It is important to note, however, that this effect 

may be offset by ground settlement and vegetation changes. In 

the Foothills, a longer warm season 

may prolong the time available for 

soil moisture to move down gradient 

and into drainage networks. This 

may lead to late summer and early 

fall soil drying, while baseflows, the 

portion of streamflow derived from 

subsurface sources, may increase 

due to additional shallow groundwater flow. 

Increasing soil storage capacity and 

more rapid moisture export through 

evapotranspiration may lead to 

decreased hydrologic response to 

summer storms. As the active layer 

depth increases and surface storage decreases, the Foothills will 

have muted hydrologic response to 

storms but greater base flow due to 

suprapermafrost groundwater flow 

from soil moisture. On the Coastal 

Plain, reduced surface storage (e.g., 

lower lake levels) and drier soils will 

require greater rainfall recharge 

before significant surface runoff to 

streams can occur, absent changes 

to drainage systems (see Coastal 

Plain, Chapter 4). Changes in 

evapotranspiration and soil storage 

capacity can also lead to drier surface conditions, which then require a 

larger amount of the following year’s 

spring snowmelt for recharge. This 

redistribution of water in spring may 

reduce peak streamflow to some 

extent. 

Fall Freeze

Warmer soil temperatures and a 

prolonged fall season will lead to 

later and more gradual soil freezing. In extreme scenarios, warmer 

fall soil temperatures and increased 

winter snowfall may lead to talik 

formation if the active layer does not 

fully refreeze. Although this may 

occur in some cases, it is not likely 

to occur on a large scale for a very 

long time—on the order of centuries. 

In the Foothills, prolonged thaw and 

formation of taliks could mean continued soil drainage throughout the 

winter and drier spring soil moisture. This winter drainage may lead 

to greater under-ice streamflow. Fall 

and winter drainage may be less important on the Coastal Plain where 

soil moisture distribution is largely 

determined by microtopography. 
35

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37

Alder shrubs (Alnus crispa) colonizing the rims of polygons on the Colville River Delta. The colonizing seeds were 

dispersed by water movement along the floodplain corridor. This novel habitat may increase across the North 

Slope. Photo by M.T. Jorgenson.

A male American tree sparrow 

(Spizella arborea) sings after 

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Shrub-dependent songbird species 

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Photo by Ted Swem, USFWS.
38

Chapter 4

Habitat Change

This chapter describes four 

North Slope landscapes 

influenced by the presence of 

permafrost—the coastline, 

coastal plain, foothills, and 

floodplains—and what we can 

project about how they may 

change under a warming 

climate. This chapter also 

outlines how processes such 

as fire, vegetation community 

change, and contaminant 

mobilization may affect future 

habitats in the region.
39

Permafrostinfluenced 

Geomorphic 

Processes 

Coastline

The Beaufort and Chukchi sea 

coasts are characterized by lagoons 

with sandy barrier islands, exposed 

coast with high peat bluffs, deltas, 

and low-lying drained lake basins 

that are occasionally flooded by 

storm surges (Figure 4.1). These 

dynamic environments are greatly 

affected by sea ice, wind-driven 

waves and storm surges, surface 

water temperatures, coastal erosion 

and accretion, sedimentation by rivers and eroding coastal bluffs, and 

long-shore currents. 

The Beaufort and Chukchi sea 

coasts are ice-free for 3–4 months 

per year, with the open-water period 

occurring from July–September. 

By early September, the sea ice 

retreats to a distance of 300–500 

km off Barrow, and 100–300 km off 

Kaktovik (Jorgenson and Brown 

2005). In the past few decades, the 

length of the ice-free period in the 

Chukchi and western Beaufort seas 

has increased dramatically. From the 

late 1970s to 2006, the ice-free period 

increased by an average of 50–95 

days, depending on the region, with 

Figure 4.1. Schematic of arctic coastline landscape, current (above) and projected (below). The projected 

landscape illustrates elements likely to change as a result of climate warming. Figure by R. Mitchell/Inkworks for 

WildREACH from cited sources.

Current

Projected
40

the greatest increase between Point 

Lay and Barrow where the ice-free 

season grew from approximately 30 

to 125 days (Rodrigues 2008, unpublished). Arctic sea ice extent reaches 

its annual minimum at summer’s end 

and has declined at a rate of 11% per 

decade since 1972 (Richter-Menge 

et al. 2008). Open-water conditions 

increase the probability that strong 

wind conditions will result in a storm 

surge, because the presence of ice 

would otherwise inhibit wave formation (Reimnitz and Maurer 1979).

Sea level rise measured at nine tide 

stations in Siberia averaged 2–3 mm 

per year from 1954–2007 (RichterMenge et al. 2008). Global sea 

level rise in the period since 1993 is 

estimated to have occurred at a rate 

of 3 mm per year, and projections 

for cumulative rise by the end of the 

21st century range from 0.18–0.59 

m, but do not account for potential 

changes in ice flow of the Greenland 

and Antarctic ice shelves (IPCC 

2007). Some researchers believe that 

accelerated ice sheet melt will result 

in mean sea level rise exceeding 1 

m by the end of this century (http://

climatecongress.ku.dk/newsroom/ 

rising_sealevels/, retrieved March 

14, 2009).

Sea-surface temperature trends for 

the Arctic Ocean over the past century are characterized by a period 

of cooling from 1930–1965, followed 

by a period of warming, particularly 

pronounced since 1995 (Steele et al. 

2008). Sea-surface temperatures for 

the Beaufort and Chukchi seas have 

been especially warm in this decade, 

e.g. 2–3°C higher in 2007 than the 

average for the previous 25 years 

(Richter-Menge et al. 2008). 

The combined effect of sea level rise, 

increased frequency of storm surges, 

and increased water temperature 

has already resulted in a substantial increase in erosion rates on 

the Beaufort Sea coast (Jorgenson 

and Brown 2005, Jones et al. 2009). 

Lunar tides along the Beaufort Sea 

coast are only on the order of 20 

cm, but water levels are strongly 

affected by wind direction, with 

west winds associated with higher 

tidal stage (Jorgenson 2009). Strong 

winds can raise water levels as much 

as 2 m (Reimnitz and Maurer 1979), 

and these storm surges can result in 

very rapid coastline erosion, particularly in sectors characterized by 

exposed ice-rich peat bluffs. Erosion 

of ice-rich bluffs involves formation 

of a thermoerosional niche (Figure 

4.2) and subsequent collapse of bluff 

materials (Reimnitz and Maurer 

1979). Unlike coastlines in temperate 

areas, erosion is affected by thawing as well as mechanical processes. 

Erosional rates of 1–2 m per year 

are typical for many sectors of the 

Beaufort coast, excluding river 

deltas, where accretion is occurring. 

The 60-km section north of Teshepuk Lake is retreating much more 

rapidly, however, with mean annual 

erosion rates having increased from 

an average of 6.8 m per year (1955–

Figure 4.2 (above). The effects of a major storm with strong west winds on 

Barter Island in August 2008. The undercutting of thermoerosional niches 

and the collapse of large blocks helps fragment and accelerate the rate of 

coastal erosion along ice-rich portions of the Beaufort Sea coast. Below the 

human figure, a cross section of the thin active layer and an ice wedge is 

clearly visible. Photo by Mitch Osborne, USFWS. 

Figure 4.3 (below): Salt-killed tundra is prevalent along low-lying portions 

of the coast that have been inundated by storm surges. After inundation by 

salt water, iron staining and a white salt crust at the surface are common. 

Photo by M.T. Jorgenson.
41

1979) to 13.6 m per year (2002–2007). 

For most shoreline types the rate 

was even higher—18 m per year—in 

the most recent period (Jones et al. 

2009). If this rate were to remain 

constant over the next century, a 

coastal retreat of 1.8 km would be 

expected, representing a loss of 8% 

of the Teshekpuk Lake Goose Molting Area (see box 5.1 on page 72). 

By comparison, the coastal reach 

between the Colville and Sagavanirktok rivers (within which 

most of the North Slope oil and gas 

infrastructure is located) retreated 

at a historic rate of less than 2 m per 

year (Jorgenson and Brown 2005). 

At a hypothetical higher rate of 4 m 

per year held constant over the next 

century, the resultant 200 m retreat 

would represent a loss of less than 

1% of the Arctic Coastal Plain terrestrial habitats in this sector.

In addition to accelerating shoreline 

erosion, increased storm heights accompanied by the projected sea level 

rise will cause additional flooding 

and salinization of low-lying terrain. Inundation with salt water may 

kill the existing vegetation, resulting in relatively barren patches of 

salt-killed tundra (Figure 4.3). A 

distinctive coastal wet sedge tundra 

community characterized by salt 

tolerant species (e.g., Puccinellia 

phryganodes and Carex subspathacea) may develop in wetter areas 

(Flint et al. 2008). Coastal wet sedge 

tundra is currently rare, 

and its future abundance 

will reflect the equilibrium between loss from 

erosion and inundation 

and increase due to 

colonization in salinized 

terrain.

The persistence of coastal delta environments 

depends on the degree 

to which sedimentation 

keeps pace with sea 

level rise. Information 

on the baseline rates of 

sedimentation for North 

Slope rivers is very limited. On the Colville River 

Delta, a large breakup or 

precipitation event can 

result in accumulation 

of 10 cm or more, and an 

average nearshore deposition rate of 1 kg/m/year 

was estimated (Brown 

and Jorgenson 2005). 

In general, sediment 

discharge in arctic rivers is much 

less than the global average, due 

to watershed characteristics that 

include a thin weathering crust, low 

precipitation, extensive permafrost, 

low temperatures, wetland-dominated landscape, and low level of human 

activity (Gordeev 2006). Models 

predict a 30% increase in sediment 

load for every 2°C of warming in the 

drainage basin, and a 10% increase 

in sediment transport for a 20% 

increase in discharge (Syvitski 2002, 

Morehead et al. 2003). Projected 

increases in temperature and precipitation in arctic Alaska suggest 

a trend toward increased rates of 

sedimentation. The increased supply 

of sediment to river deltas may compensate for, or outpace, the effect of 

sea level rise.

The barrier island-lagoon system 

provides important summer feeding habitat and migration corridors 

for waterfowl and anadromous fish. 

The barrier islands are believed to 

be erosional remnants of ancient 

mainland shores and composed of 

materials not generally supplied 

by modern depositional processes 

(Hopkins and Hartz 1978, Morack 

and Rogers 1981). Some retain 

remnant vegetated tundra underlain 

by permafrost, but most are constructional islands largely devoid of 

vegetation and in a continual state 

of migration (westward and towards 

the mainland) and morphological 

Erosion along a segment of the 

Beaufort Sea coastline based 

upon vertical aerial photography 

captured in 1955, 1979, and 2002. 

Image from B. Jones, USGS.

1979 2002

1979 2002
42

period of open water and increased 

occurrence of larger waves is at least 

partially responsible for this acceleration. Ice-push events require the 

coincidence of strong onshore winds 

and a high density of broken ice, and 

this may occur less frequently as sea 

ice retreats farther offshore in summer. Warming ocean temperatures 

also may play a role, however, as 

even the constructional islands may 

be partially composed of ice-bonded 

sediments (Morack and Rogers 

1981), which inhibit longshore sediment transport (Thomas Ravens and 

William Lee, University of Alaska 

Anchorage, personal communication). These trends suggest that 

the deterioration or disappearance 

of the existing system of barrier 

islands is possible over a relatively 

short period.

The coastline is a dynamic environment subject to continual change. 

Climate change may affect the 

equilibrium among various coastal 

processes, however, and result in a 

net change in habitat availability. 

The linkages among coastal processes, as affected by temperature and 

precipitation changes, are illustrated 

in a conceptual model (Figure 4.4).

Figure 4.4. Conceptual model 

illustrating linkages between 

physical processes and coastal 

habitat. Grey boxes identify climate 

drivers, blue boxes indicate physical 

processes, and white boxes indicate 

landscape responses. The light-blue 

box contains habitats for which we 

are less certain of the direction of 

the habitat change.

change. These islands are typically 

less than 1 m in elevation and no 

higher than 3 m (Hopkins and Hartz 

1978) and, therefore, are subject 

to overwash during storm events. 

Storm-associated erosion commonly 

breaches the islands and splits them 

into smaller pieces, which may later 

coalesce due to longshore transport 

and redeposition of sediments. Icepush events, during which gravel is 

dredged and deposited by wind-driven ice floes, may play an important 

role in maintaining the islands by 

periodically concentrating materials 

in a discrete zone. 

Preliminary evidence suggests that 

the Beaufort Sea barrier island 

system may be disintegrating. For 

example, Narwhal Island, which is 

east of Prudhoe Bay, has greatly 

diminished in surface area since 

1955, and the migration rate from 

1990–2007 (24 m/yr) greatly exceeds 

that from 1955–1990 (5 m/yr). Total 

surface area of barrier islands in the 

central Beaufort Sea (Colville River 

to Point Thomson) has decreased 

approximately 4% from the 1940s 

to the 2000s, and the rate of change 

is greater during the period since 

1980 (Gibbs et al. 2008). A longer 

! Barrier islands

! TEMPERATURE

↑ Degradation of 

coastal permafrost

Temperature, precipitation and coastal processes

↓ Protected 

lagoons

! PRECIPITATION

↑ Coastal erosion

↑ Nearshore deposition 

of nutrients and deltaic 

sediments

↑ Sea-level

↑ Breached 

lakes

! Terrestrial 

habitats along 

coastline ∆ Delta mudflats

(accretion or erosion)

Δ Salt-killed tundra 

Δ Saline mud flats and 

coastal wet sedge tundra

↑ River discharge 

and sediment 

transport 

↑ Ocean 

temperature

Opposing influences create 

uncertainty regarding direction of 

change for mudflats, coastal wet 

sedge tundra, and salt-killed tundra

↑ Storm Surge 

(↓ Sea Ice)
43

Arctic Coastal Plain

Regional differences in the distribution of late-Pleistocene surficial deposits (Figure 4.5) strongly influence 

the presence and characteristics of 

lake basins. Ice-rich deposits, such 

as delta and glacio-marine deposits, 

are associated with abundant thaw 

lakes and drained basins. Lakes 

in ice-poor deposits, such as eolian 

sand and slightly pebbly till, formed 

in low-lying swales during the early 

Holocene and expanded through erosion of fine-grained sediments (Jorgenson and Shur 2007) because the 

volume of ground ice was insufficient 

to allow thaw lake development. 

The development and expansion 

of a drainage network during the 

Holocene has resulted in drainage 

of many large lakes, particularly 

over the past 5,000 years (Hinkel et 

al. 2003, Jorgenson and Shur 2007). 

Lake drainage may be triggered by 

a variety of processes, such as ice 

wedge erosion, headward stream 

erosion, tapping, bank overflow, 

or coastal erosion. Once lakes are 

drained, the relatively warm water 

in deep waterbodies that promotes 

talik formation is lost, and the 

exposed sediments are once again 

subject to permafrost aggradation. 

The sandy margins tend to aggrade 

little ice, while ice segregation 

and ice wedge development in the 

organic-rich silty centers is prevalent. This differential ice accumulation typically causes the drained 

centers to dome up and shift water 

to the lower lying sandy margins. 

Small ponds created by this hydrologic shift are abundant around the 

margins. These typically fill in with 

limnic sediments in the center and 

sedge peat around the margins. 

Stabilization of a drained lake basin 

and re-establishment of polygonal 

terrain is a process that may take 

centuries to millennia (Jorgenson 

and Shur 2007).

The response of Coastal Plain deposits to a warmer and wetter environment is expected to have a dramatic 

effect on the stability of ice wedges 

accompanied by redistribution of 

water on the landscape. Because ice 

wedges are formed just below the 

active layer and are in close equilibrium with the existing climate, an 

abrupt warming will cause nearly all 

ice wedges to degrade (Box 4.1, Figure 4.6). The redistribution of water, 

however, will depend on whether the 

site is a water-shedding slope or a 

water-gathering basin. 

In low-lying basins, the water of 

deep lakes and shallow ponds will be 

fully recharged by spring snow melt 

with excess water running off, assuming constant or increased winter 

precipitation. Under a warming 

scenario where summer precipitation is insufficient to compensate 

for increased evapotranspiration, 

deeper midsummer draw-down may 

be expected in lakes and ponds, but 

water levels should increase again 

with fall rains and spring melt in 

the following year. Shallow ponds 

and wet sedge meadows, which are 

dependent on direct precipitation for 

water input, would be most sensitive 

to a negative shift in water balance; 

if drier summer conditions become 

prevalent, desiccation of these wetlands may occur (Smol and Douglas 

2007).

Effects of ice wedge thawing are 

already evident on the Arctic 

Coastal Plain. A large increase in 

both area and density of degrading 

ice wedges has been observed in 

study areas near the Colville River 

Delta (Jorgenson et al. 2006). The 

accelerated thermokarst degradation, probably associated with record 

Figure 4.5. Regional differences in the distribution of surficial deposits, 

all of late Pleistocene origin, are a reflection of various past processes. 

The coastal areas are characterized by glaciomarine pebbly silt, glacial 

deposition of slightly pebbly silty sand from a northern ice sheet, and 

deposition of marine sand by marine transgression. The western portion of 

the Arctic Coastal Plain is covered by an eolian sand. The lower portion of 

the Arctic Foothills is blanketed by thick loess (silt). The upper Foothills are 

underlain by bedrock near the surface; ridges typically have rocky residual 

soils, slopes are mantled with organic-rich colluvium (accumulations of 

sediment transported downslope by gravity), and basins are filled with 

organic-rich fine-grained colluvium. From Jorgenson et al. 2009.
44

warm temperatures from 1989–1998, 

has resulted in a deepening network 

of water-filled thermokarst troughs 

and pits and drying polygon centers. 

Based on the general distribution of 

ice-rich soils, surface changes of this 

type could potentially affect 10–30% 

of arctic lowland landscapes. 

Thermokarst lakes within the 

lower latitude zone of discontinuous 

permafrost may drain as a result of 

a deepening talik that completely 

penetrates the permafrost, as 

documented on Alaska’s Seward 

Peninsula (Yoshikawa and Hinzman 

2003). On the North Slope, however, 

continuous deep permafrost would 

preclude this mechanism. In continuous permafrost environments, 

studies have concluded that the 

surface area of large lakes is either 

stable to increasing (Smith et al. 

2005, Riordan et al. 2006, Mars and 

Houseknecht 2007) or too sensitive 

to short-term variability in precipitation regime to allow detection of a 

long-term trend (Plug et al. 2008). 

Large, deep lakes are expected to 

continue to expand in surface area, 

due to shoreline erosion by winddriven waves and lake expansion 

from thermokarst. Erosion rates 

averaged 0.08 m/yr for large (>20 

ha), deep (>1.5 m) lakes at three 

study sites on the Coastal Plain west 

of the Colville River Delta (Jorgenson et al. 2003), while shorelines 

of small or shallow (≤1.5 m) lakes 

eroded at rates averaging <0.04 m/

yr. Based on extrapolation from Jorgenson et al. (2003), the increment 

in lake area due to expansion may 

comprise ~1–3% of the landscape by 

the end of the century, although this 

underestimates the effect if rates of 

lake expansion increase significantly 

due to a longer ice-free season and 

warmer water.

Most drained lake basins formed 

during a period of extensive drainage during the mid-Holocene (Jorgenson and Shur 2007) and contemporary lake drainage is uncommon. 

With expected warming, however, 

degrading ice wedges may progressively integrate into drainage 

channels with a lower base elevation 

resulting in increased frequency 

of lake-tapping (sudden drainage) 

events. Where ice-rich soils and a 

topographic gradient exist (e.g., 

adjacent to a stream or the coast), 

sequential lake tapping could occur 

(McGraw 2008).

Figure 4.6. Schematic of Arctic 

Coastal Plain landscape, current 

(above) and projected (below). The 

projected landscape illustrates 

elements likely to change as a result 

of climate warming. Figure by R. 

Mitchell/Inkworks for WildREACH 

from cited sources.

Projected

Current
45

Box 4.1. Permafrost Degradation

The susceptibility of arctic landscapes to thermokarst processes depends 

on ground ice content, and this varies according to the surficial geology 

and geomorphic setting. Ground ice may occur as segregated ice (smaller 

stuctures interspersed within the permafrost) or massive bodies such as ice 

wedges, and the relative abundance of 

each type affects how the surface will 

respond to warming, at both the landscape scale and over distances of a few 

meters. On the Arctic Coastal Plain, 

mean segregated ice volume in the 

upper 2 m ranged from 45% in inactive 

sand dunes to 71% in alluvial-marine 

deposits (Jorgenson et al. 1998, 2003). 

The mean volume of ice wedges in the 

upper 2 m varied from less than 1% in 

ice-poor margins of lakes to a high of 

33% in ice-rich lake centers (Jorgenson 

and Shur 2007). Understanding how 

the type and amount of ground ice varies across the landscape is essential to 

forecasting how habitats may change 

in response to warming temperatures. 

Ice wedges, with top surfaces located just 30-40 cm beneath the surface, 

are particularly sensitive to warming air temperatures (Jorgenson et al. 

2006). Melting of the tundra surface results in varying amounts of ground 

settlement, with ice wedges melting faster than the intervening polygon 

centers. The subsiding surface overlying the melting ice wedges forms 

water-filled troughs with deeper pools at the intersections (see photos). 

As the trough system develops and deepens, a steeper drainage gradient 

redistributes water from broad polygon centers into narrow, deep troughs. 

The landscape may shift from a more uniform mesic state to one of alternating patches of dry polygon centers and flooded troughs. In settings 

with sufficient topographic gradient, which occur commonly in the transitions from upland ridges to lake basins and floodplains, deepening troughs 

can develop into a drainage network that promotes runoff, lowers the 

water table, and results in more widespread drying. In contrast to the upland setting, ice wedge degradation in topographic basins will create more 

capacity for water storage but should have little effect on water levels.

Left: Aerial view of polygonal pools 

formed by ice wedge degradation 

west of the Colville River Delta. 

Below: Ground level view of the 

same location. Both photos by M.T. 

Jorgenson.

Above: This polygonal terrain is 

located in the Niguanak Lowlands 

on the coastal plain of the Arctic 

National Wildlife Refuge. The 

bright green polygon troughs are 

associated with the reticulatepatterned network of subterranean 

ice wedges. The wet troughs support 

lush sedge vegetation, in contrast to 

the drier polygon centers. Photo by 

M.T. Jorgenson.
46

have little effect on surface hydrology. Under drying conditions, little 

change is expected.

The colluvium-mantled hillsides are 

likely to be very sensitive to climate 

warming. The soils on colluvium, 

typical of mid- to lower slopes, tend 

to be highly organic, saturated, 

and have abundant ice wedges and 

segregated ice near the permafrost 

table. Because the active layer is underlain by ice-rich permafrost, thaw 

slumps are likely to become abundant on the sloping surfaces (Gooseff 

et al. 2009). The slumping will create 

new thaw lakes, expose new soil 

to plant colonization, and increase 

sediment transport in runoff (Figure 

4.7). Gullies are likely to become 

common where water flow through 

ice wedge networks causes the 

ground surface to collapse. The gullies then contribute to channelization 

of flow and drying of lakes and intervening ridges. In some areas, water 

tracks may deepen without deeper 

gully formation but still serve to 

channel suprapermafrost groundwater flow. On very gentle slopes, ice 

wedges are likely to degrade without 

prominent gully formation.

Landscapes characterized by the 

presence of extremely ice-rich loess 

(yedoma) of late Pleistocene origin 

are highly sensitive to warming and 

have the potential for drastic change. 

Figure 4.7. Schematic of Arctic 

Foothills landscape, current (above) 

and projected (below). The projected 

landscape illustrates elements likely 

to change as a result of climate 

warming. Figure by R. Mitchell/

Inkworks for WildREACH from 

cited sources.

Current

Projected

Arctic Foothills

The upland ecosystems of the Arctic 

Foothills have three major distinctive geomorphic environments: 1) 

rocky residual soils on ridges, 2) 

gentle slopes mantled with ice- and 

organic-rich colluvium (material 

deposited at slope-bottom by gravity) over bedrock, and 3) Pleistocene 

loess on the lower Foothills (Figure 

4.7). Response of each Foothills terrain condition is discussed separately below. 

The rocky residual soils are welldrained, have deep active layers, and 

are relatively thaw stable. Rocky 

ridges probably will undergo little 

geomorphic change under a warmer 

and wetter climate. The soils will 

remain well drained and thaw stable. 

The active layer will likely increase 

and taliks may develop on some 

south-facing slopes, but this will 
47

Floodplains

Floodplains are active geomorphic 

environments because of sedimentation caused by flooding, erosion 

caused by channel migration, and 

deposition of wind-blown sand from 

barren river bars (Figure 4.8). The 

varying flooding regime creates a 

sequence of deposits that include 

massive or crossbedded sand in the 

active channel; rippled interbedded sands and fine-grained material (fines) with distinctive detrital 

organics that are the remains of peat 

banks eroded upstream; layered 

fines caused by vertical accretion 

of silts during overbank flooding; 

layered organics and silts created by 

the accumulation of organic matter 

between infrequent flooding events; 

and massive organics that accumulate on higher floodplains that are 

rarely flooded (Shur and Jorgenson 

Figure 4.8. Schematic of arctic 

floodplain landscape, current 

(above) and projected (below). The 

projected landscape illustrates 

elements likely to change as a result 

of climate warming. Figure by R. 

Mitchell/Inkworks for WildREACH 

from cited sources.

Yedoma is abundant across the lower 

foothills and may occupy roughly 

20% of the overall foothills landscape 

(Carter 1988). In this type of terrain, 

masses of ice can extend to depths of 

up to 30 m (Carter 1988). Along the 

lower Colville River, the yedoma has 

only 0.5–1 m of soil covering 10–25 

m of ice. Because of the massive ice, 

deep thermokarst lakes are common on this terrain. The degraded 

yedoma landscape of the Seward 

Peninsula may provide a good analog 

of how the arctic landscape could be 

altered by widespread ice degradation. First, thermokarst develops 

in the network of shallow Holocene 

ice wedges near the surface of the 

permafrost. Next, the thermokarst 

troughs and pits expand into thermokarst ponds and lakes that thaw 

into the underlying massive ice. Finally, expansion of the thermokarst 

lakes and drainage networks causes 

the lakes to drain, forming a thaw 

lake plain—this process, however, is 

likely to take hundreds to thousands 

of years.

Current

Projected
48

1998). During floodplain evolution, 

the deposits are modified by the aggradation of segregated and wedge 

ice, which deforms the surface, 

affects water runoff, and increases 

the susceptibility of older terrain to 

thermokarst. These deposits support 

a successional sequence of ecotypes 

from river to riverine barrens, tall 

shrub, low shrub, dwarf shrub, 

and wet sedge meadows. Riverine ecosystems are not abundant, 

comprising ~8% of the Coastal Plain 

and ~4% of the Foothills. They are 

highly productive ecosystems, however, serving as conduits of water, 

sediments, and nutrients, and are 

used by a wide range of species.

Riverine ecosystems could respond 

to climate change in a variety of 

ways depending on the amount of 

warming and the balance between 

evapotranspiration and precipitation. 

In response to warming, permafrost 

aggradation will be retarded in the 

barren portions of active floodplains, 

and degradation will be accelerated on the inactive and abandoned 

floodplains. Ice wedges formed in 

the later stages of floodplain development will degrade, thus lowering the water table and instigating 

formation of drainage networks that 

will accelerate drainage of riverine 

lakes. The consequences of altered 

precipitation (amount, seasonality, 

and frequency of extreme events), 

discharge, flooding, sedimentation, 

and erosion are more uncertain. 

Many of these processes are more 

sensitive to extreme events rather 

than to average conditions. A scenario of increased precipitation will be 

accompanied by increased flooding, 

sedimentation, and erosion. This, in 

turn, should favor more productive 

early successional ecosystems. In 

contrast, decreased runoff associated with drying during midsummer 

may lead to increased channel stability and increased shrub growth on 

the stabilized active floodplain.

Floodplain lakes include oxbow and 

thaw lakes. These lakes are important to fish and bird species and 

play an important role in trapping 

sediments and the biogeochemical processing of water before it is 

discharged to the ocean. Fish access, 

as well as nutrient status, is related 

to the degree of connectivity with 

river systems, the duration of which 

can vary from constant (all summer) 

to a transitory connection limited to 

high-water events (especially spring 

flood). For example, when flow from 

upstream snow melt begins before 

the onset of melt downstream, ice 

dams may spread water over vast 

areas in arctic river deltas, reconnecting and recharging lakes. In 

the MacKenzie River Delta, the 

degree to which lakes are connected 

depends on their distance from the 

nearest active channel and elevation. 

During low-water years, associated 

with decreased ice-dam flooding, 

lakes greater than 4 m above sea 

level are not recharged or connected 

to riverine source waters (Lesack 

and Marsh 2007). If changes in 

freeze-thaw cycles cause years with 

little ice-damming to become more 

frequent, these lakes may dry, sediment transport to river deltas may 

increase, and biogeochemistry of 

river water discharged to the ocean 

may be altered. 

Above: A male Wilson’s warbler (Wilsonia pusilla) singing during the 

breeding season. Songbird species may move into expanded shrub habitats 

if active arctic floodplains stabilize in drier summers. Photo by Ted Swem, 

USFWS. Below: The floodplain of the Katakturuk River in the Arctic 

National Wildlife Refuge shows the effects of past flooding and erosion 

events on the vegetation community. USFWS photo.
49

Historically, tundra fires have been 

rare on the North Slope, with only 

10 known occurrences north of 69°N 

from 1956 to 2007 (Racine and Jandt 

2008). In the fall of 2007, however, 

coinciding with an anomalously 

warm and dry season, a 1,000 km2

area burned between the Itkillik and 

Nanushuk rivers in the central Arctic Foothills; this is the largest North 

Slope fire on record (Racine and 

Jandt 2008). This event underscores 

the potential for more frequent, 

larger tundra fires under a climate 

scenario of warmer, drier summers. 

A severe fire reduces surface albedo 

and combusts the insulating surface 

organic layer, increasing soil thermal conductivity and heat flow into 

the ground (Yoshikawa et al. 2002). 

Post-fire soil moisture increases in 

the short term (Liljedahl et al. 2007), 

which also increases soil thermal 

conductivity and promotes warming. 

Soil warming is accompanied by at 

least a temporary thickening of the 

active layer and, if the soils are icerich, can stimulate thermokarst. In 

some settings, long-term change in 

active layer thickness and a change 

in vegetation community (decreased 

moss cover and increased shrub 

cover) ensues, reinforcing a shift 

toward warmer, drier near-surface 

soils (Yoshikawa et al. 2002). On 

the Seward Peninsula, active layer 

thickness diminished to pre-fire 

levels within a few decades on flatter 

terrain, but a thickened active layer 

persisted on steeper slopes (Racine 

et al. 2004). The post-fire warming 

and drying on slopes promoted a 

shift to willow shrub vegetation on 

the steeper slopes, but tussock sedge 

recovered well on the poorly drained 

sites. Sphagnum moss and lichen 

failed to recover after 24 years, except for Sphagnum in a wet meadow 

site (Racine et al. 2004). 

Fire Regime

The Anaktuvuk Fire ignited on July 16, 2007, and burned until early 

October. This MODIS satellite image was obtained on September 

25, 2007, and the red dots indicate areas still burning on that date 

(NASA, http://earthobservatory.nasa.gov/NaturalHazards/view.

php?id=19139&oldid=14550).

Fire frequency on the Seward 

Peninsula is greater than that on 

the North Slope (Racine and Jandt 

2008). The two regions are similar, 

however, with respect to frequency 

of lightning strikes (http://geology.

com/articles/lightning-map.shtml, 

retrieved April 2009) and vegetation. 

Differing soil moisture, therefore, 

most likely accounts for the difference in fire frequency. In Barrow, 

under near-average summer conditions, polygon rims and troughs 

remained >80% saturated after late 

June (Liljedahl et al. 2009). The water table on tussock tundra hillsides 

in the upper Kuparuk River watershed typically remains within 10 

cm of the ground surface (Hinzman 

et. al. 1993), whereas soils at 10 cm 

depth at a Seward Peninsula tussock site declined to ~40% saturated 

after the spring peak (Liljedahl 

et al. 2007). Predicting the future 

North Slope fire regime, therefore, 

is closely linked with projection of 

summer water balance.
50

Current Vegetation Communities

The North Slope of Alaska comprises less than 3% of the circumpolar arctic region mapped by the 

CAVM Team (2003) but contains 

26% of the area classified as sedge, 

moss, dwarf-shrub wetland, primarily on the Coastal Plain, and 24% of 

the area classified as tussock-sedge, 

dwarf-shrub, moss tundra, mostly 

in the Foothills (Figure 4.9). EcoreVegetation

Figure 4.9 (left). Vegetation of arctic 

Alaska based on the Circumpolar 

Arctic Vegetation Map (CAVM 

2003). Map by FWS, based on 

CAVM data. Available online at 

http://data.arcticatlas.org/geodata/

circumpolar/cavm/.

gional differences in vegetation reflect differences in climate, topography, and parent material (Table 4.1, 

Figure 4.9, 4.10, Appendix 2). 

The Coastal Plain landscape is 

a mosaic of low-lying lacustrine 

(lake-related) basins separated by 

intervening higher terrain. Lacustrine ecosystems include deep (>1.5 

m) lakes, shallow (<1.5 m) lakes 

and ponds, lacustrine grass marsh 

(dominated by Arctophila fulva

in water >0.3 m deep), lacustrine 

sedge marsh (Carex aquatilis and 

Eriophorum angustifolium in water 

0.1–0.3 m deep), and lacustrine 

wet sedge tundra (C. aquatilis, E. 

angustifolium, forbs and mosses 

in water <0.1 m deep). The older, 

higher terrain between basins also 

supports lowland wet sedge tundra 

in swales, lowland moist sedge-shrub 

tundra on lower slopes, and upland 

tussock tundra on upper slopes and 

gentle ridges. Prostrate willows and 

Dryas (a small flowering shrub) 

occur on moist sedge-shrub tundra, 

but typically comprise <35% cover. 

Upland Shrubby 

 Tussock

Upland Low Shrub 

Birch-willow 

Upland 

Tussock 

Upland Moist 

Sedge-shrub 

 

Low Moist 

Sedge-shrub 

Other 

Arctic Foothills 

7 %

8 %

 Low Moist 

Sedge-shrub 

 Low Wet 

Sedge-shrub 

Lowland Lake 

Upland Tussock 

Coastal Water 

Other 

Arctic Coastal Plain 

23%

20%

14%

14%

12%

17%

28%

20%

19%

14%

10%

35%

25%

10%

15%

Upland Shrubby Tussock Tundra 

Upland Low Shrub Birch-willow Tundra 

Upland Tussock Tundra 

Upland Moist Sedge-shrub Tundra 

Lowland Moist Sedge-shrub Tundra Other 

Lowland Wet Sedge-shrub Tundra 

Lowland Lake 

Coastal Water 

Alpine Noncarbonate Dwarf Shrub Tundra 

Alpine Noncarbonate Barrens 

Alpine

 Noncarbonate 

Dwarf Shrub 

Upland Low 

Shrub BirchUpland Shrubby willow 

Tussock 

Alpine 

Noncarbonate 

Barrens 

Upland Moist 

Sedge-shrub 

Other 

Brooks Range 

10%

Figure 4.10. Distribution of ecotypes among ecoregions of the North Slope, after Jorgenson and Heiner 2003.
51

Uplands in the Foothills are characterized by shrub-dominated vegetation. Dominant ecotypes include 

upland Dryas and ericaceous dwarf 

shrub on dry rocky ridges, upland 

low birch-willow shrub (Betula 

nana, Salix. planifolia, S. glauca) 

on better drained soils, upland 

shrubby tussock tundra (B. nana, S. 

planifolia, E. vaginatum) and upland tussock tundra (E. vaginatum) 

on saturated organic-rich soils, and 

upland moist sedge-shrub tundra 

(C. bigelowii, D. integrifolia) on 

circum-alkaline soils. Less common 

are lowland wet sedge tundra and 

lowland low birch-willow shrub in 

swales, toe-slopes, and basins. 

Upland tall alder shrub occurs on 

mid- to upper slopes of the Brooks 

Range but is <1% of the landscape. 

Tall alder-willow shrub occurs in 

riverine settings in both the Foothills 

and the Brooks Range, but is <0.1% 

of the landscape in either ecoregion.

Ecotype Coastal Plain Foothills

Brooks 

Range

North Slope 

(total area)

Area 

(km2

)

% Area 

(km2)

% Area 

(km2)

% Area 

(km2)

%

Coastal Barrens 507.7 0.9 9.5 0.0 0.0 0.0 517.2 0.2

Coastal Wet Sedge Tundra 1253.8 2.3 40.9 0.0 0.0 0.0 1294.7 0.6

Coastal Water 6741.6 12.1 301.4 0.3 0.0 0.0 7043.0 3.4

Coastal Grass and Dwarf Shrub Tundra 1320.0 2.4 79.2 0.1 0.0 0.0 1399.2 0.7

Riverine Barrens 548.4 1.0 921.1 1.0 228.3 0.4 1697.8 0.8

Riverine Willow Shrub Tundra 75.9 0.1 920.9 1.0 146.9 0.3 1143.7 0.5

Riverine Moist Sedge-Shrub Tundra 1374.4 2.5 2948.2 3.1 579.5 1.0 4902.1 2.3

Riverine Wet Sedge Tundra 951.3 1.7 914.4 1.0 135.3 0.2 2000.9 1.0

Riverine Waters 554.2 1.0 610.9 0.6 132.1 0.2 1297.2 0.6

Riverine Dryas Dwarf Shrub Tundra 0.0 0.0 4.8 0.0 270.2 0.5 275.0 0.1

Riverine Spruce Forest 0.0 0.0 0.0 0.0 1.8 0.0 1.8 0.0

Lowland Wet Sedge Tundra 11239.0 20.2 3511.4 3.7 643.6 1.1 15394.0 7.4

Lowland Lake 7983.2 14.4 1665.3 1.7 246.3 0.4 9894.9 4.7

Lowland Moist Sedge-Shrub Tundra 12671.0 22.8 6923.7 7.2 0.0 0.0 19595.5 9.4

Lowland Low Birch-Willow Shrub 683.2 1.2 1293.7 1.4 297.6 0.5 2274.6 1.1

Lowland Spruce Forest 0.0 0.0 0.0 0.0 11.5 0.0 11.5 0.0

Upland Tussock Tundra 7480.6 13.5 9682.7 10.1 0.0 0.0 17163.7 8.2

Upland Dryas Dwarf Shrub Tundra 891.5 1.6 551.7 0.6 1089.5 1.9 2532.9 1.2

Upland Shrubby Tussock Tundra 17.6 0.0 33469.3 34.9 10448.6 18.2 43938.2 21.0

Upland Low Shrub Birch-Willow Tundra 1199.5 2.2 23831.6 24.9 11357.8 19.8 36390.4 17.4

Upland Moist Sedge-Shrub Tundra 18.1 0.0 7869.5 8.2 5621.5 9.8 13510.1 6.5

Upland Tall Alder Shrub 0.0 0.0 0.0 0.0 211.8 0.4 211.8 0.1

Upland Spruce Forest 0.0 0.0 0.4 0.0 41.2 0.1 41.6 0.0

Alpine Glaciers 0.0 0.0 0.0 0.0 198.6 0.3 198.6 0.1

Alpine Non-carbonate Barrens 0.0 0.0 62.7 0.1 8133.0 14.2 8195.8 3.9

Alpine Carbonate Barrens 0.0 0.0 0.0 0.0 103.2 0.2 103.2 0.0

Alpine Mafic Barrens 0.0 0.0 0.0 0.0 103.1 0.2 103.1 0.0

Alpine Non-carbonate Dwarf Shrub Tundra 0.0 0.0 51.5 0.1 16060.3 28.0 16112.0 7.7

Alpine Carbonate Dwarf Shrub Tundra 0.0 0.0 0.0 0.0 129.5 0.2 129.5 0.1

Alpine Mafic Dwarf Shrub Tundra 0.0 0.0 0.0 0.0 185.4 0.3 185.4 0.1

Riverine Alder-Willow Shrub 0.0 0.0 0.0 0.0 2.0 0.0 2.0 0.0

Cloud, Snow, and Ice 5.4 0.0 123.7 0.1 1071.7 1.9 1200.8 0.6

Total 55516.4 26.6 95788.7 45.9 57450.1 27.5 208762.5 100

Table 4.1 Distribution of ecotypes1 among ecoregions of the North Slope. More abundant (>5% of area) 

ecotypes are highlighted in bright yellow. 

1. Source: Jorgenson and Heiner (2003).
52

Projected Changes in Vegetation 

Communities

Treeline

The Arctic Climate Impact Assessment (ACIA 2005, p. 332) predicted 

very likely replacement of tundra 

by forest, and some continent-scale 

biome shift models predict that a 

taiga environment will replace North 

Slope tundra by the year 2100 (Gonzalez et al. 2005). Although northward shift of the spruce treeline has 

been observed (Lloyd et al. 2002), 

modeling studies focused on the 

Alaska forest-tundra ecotone predict 

that a shift from upland tundra 

to spruce forest (5% tree cover) 

would take >150 years (Chapin and 

Starfield 1997, Rupp et al. 2000a). 

Furthermore, the position of the 

Brooks Range coincides with the 

latitudinal treeline and is expected 

to pose a significant topographic 

barrier to forest establishment on 

the Alaska North Slope (Rupp et al. 

2000b). Conversion of North Slope 

tundra to spruce forest is therefore 

considered an unlikely scenario 

within the century time frame.

Patches of balsam poplar forest occur in scattered locations across the 

northern Brooks Range and Foothills, in floodplain settings with yearround groundwater flow (Bockheim 

et al. 2003). They also occur in numerous small patches on floodplains 

and hillsides in northwestern Alaska 

where mean annual air temperatures are -6 to -8 °C (Jorgenson et al. 

2004). Because these trees release 

highly mobile wind-dispersed seeds 

and are adapted to growing on welldrained, early successional habitats, 

balsam poplar should be able to 

rapidly advance down floodplains 

across arctic Alaska in response to 

warming temperatures.

Shrub Expansion

Shrubs can have dramatic effects on 

local microclimates and may provide 

a positive feedback that contributes 

to global warming (Sturm et al. 

2001, Pomeroy et al. 2006). Shrubs 

trap snow and can increase winter 

soil temperatures, and the snow 

cover change can affect the timing 

and magnitude of all surface energy 

balance components during the melt 

and increase runoff late in the snowmelt period (Liston et al. 2002).

Within the Brooks Range and Foothills, an expansion of shrub tundra 

into areas formerly dominated by 

sedge is evident over the time scale 

of a half century. Increased abundance of alder, willow, and dwarf 

birch is detectable via comparison 

of historical oblique aerial photos 

(1940s) with modern photography 

(Sturm et al. 2001, Stow et al. 2004, 

Tape et al. 2006). The study sites 

are located in the Brooks Range and 

Arctic Foothills, primarily in the 

Colville River watershed. Expansion 

of alder is most conspicuous in the 

photographs, but field observations 

confirm that willow and shrub birch 

cover has increased as well. These 

results pertain mainly to hill slopes 

and valley bottoms. 

Vegetation on the broad interfluve 

areas of the Foothills is primarily tussock-shrub tundra, with the 

tussock-forming sedge Eriophorum vaginatum codominant with 

low shrubs, principally dwarf birch 

Betula nana and willow Salix pulchra. Plot experiments conducted 

at Toolik Field Station suggest that 

relative cover and canopy height 

of shrubs (principally B. nana) will 

increase under conditions of warmer 

summer temperatures and deeper 

A systematic comparison of photos of Alaska’s North Slope taken in 

the mid-20th century with recent photos of the same locations reveals an 

increase in shrub vegetation over time (Sturm et al. 2001). In 2002, alder 

shrubs cover more of the landscape along the Nimiuktuk River, a tributary 

of the western Noatak River, compared to conditions in 1950. The vegetation 

of the western Brooks Range and North Slope appears to be responding 

to changes in climate, with implications for surface energy exchange and 

carbon flux. Photos courtesy of Ken Tape.

6 July 1950

27 July 2002
53

snow (Wahren et al. 2005). These 

results are consistent with increased 

shrub and graminoid height and 

cover after artificial warming at 10 

other international experimental 

tundra biome sites (Walker et al. 

2006). Increased birch cover could 

promote fire spread, because shrub 

birch is relatively flammable compared with other shrubs and graminoids (Higuera et al. 2008).

Remote sensing methods, most 

notably the normalized difference 

vegetation index (NDVI) have also 

been used to assess vegetation 

trends in the Arctic. NDVI values 

are a measure of “greenness” and 

correlate well with above-ground 

plant biomass. Retrospective studies 

show an increase in NDVI in arctic 

Alaska over the periods 1981–2001 

(Jia et al. 2003) and 1990–1999 (Stow 

et al. 2004). Increasing NDVI values 

could reflect increased shrub cover 

and stature, but this interpretation 

is not straightforward. A 22-year 

record analyzed by Verbyla (2008) 

demonstrated a significant positive 

trend in the annual maximum NDVI 

on the Arctic Coastal Plain and 

Arctic Foothills, with no significant 

trend in the Brooks Range. Increasing biomass on the Arctic Coastal 

Plain is not likely to be associated 

with shrub increase, as shrubs 

constitute a very low proportion of 

the cover. The only available study 

from the Coastal Plain based on 

field measurements (Jorgenson and 

Buchholtz 2003) reported a small but 

significant decline in non-vascular 

plant cover, but no significant change 

in vascular plant cover or shrub 

height in plot studies covering the 

period 1984–2002. On the wet and 

lowland moist sedge tundra of the 

Arctic Coastal Plain, therefore, the 

increasing NDVI values reported by 

Verbyla (2008) might be indicative of 

more robust graminoid growth. Anecdotal evidence of shrub invasion in 

this ecoregion includes the establishment of alders (Alnus spp.) on polygon rims in the Colville River Delta 

(M.T. Jorgenson, ABR Inc., personal 

communication; see image page 37). 

There is no strong evidence, however, for widespread shrub expansion 

on the Arctic Coastal Plain.

Paludification

Paludification refers to the process 

of establishment of peat-forming 

plant communities on both dry lands 

and in bodies of water (bog formation from water-body infilling may 

be considered a distinct process, 

terrestrialization, but here we refer 

to all bog formation as “paludification”). Klinger (1990) proposed that 

mosses such as Sphagnum play a 

key role in driving this successional 

process. Initially, according to this 

hypothesis, organic acids released 

by moss cause mortality of fine roots 

in vascular plants, setting in motion 

a shift in plant species composition, 

with an increasingly acidic and mossdominated bog as the stable climax 

community. In the boreal and arctic 

environment, conditions created 

by Sphagnum normally produce 

a positive feedback that enhances 

paludification by providing cooler, 

increasingly acidic soils leading to 

increased peat formation, a thinner active layer, and permafrost 

aggradation (Auerbach et al. 1997). 

Extrinsic disturbance that results in 

drier soils and/or higher alkalinity 

leads to conditions less favorable for 

Sphagnum growth (Spatt and Miller 

1981).

Present-day acidic tussock tundra 

that dominates the Arctic Foothills 

may have evolved from arid grassforb communities that were prevalent during the late Pleistocene, 

through paludification in the warmer, moist Holocene environment 

(Walker et al. 2001). Tussock tundra 

communities are characterized by 

plants that are relatively unpalatable 

to herbivores, with high concentrations of toxic secondary compounds, 

and thus offer less favorable habitat for herbivores. Conversion of 

Figure 4.11. Thermokarst pits on 

the Hulahula Lowlands, Arctic 

National Wildlife Refuge. Orange 

coloration on trough margins are 

patches of Sphagnum moss. Photo by 

M.T. Jorgenson.
54

Phenology

Growth and photosynthetic activity commences almost immediately 

after snowmelt exposes plants in 

spring and the ground thaws. Data 

collected as part of the International 

Tundra Experiment (ITEX) suggest that experimental warming of 

tundra can produce “small to moderate” advance in green-up (Arft et 

al. 1999). Similarly, NDVI data from 

northeast Alaska spanning 12 years 

(Figure 4.12) shows that in warmer 

years (1990s), green-up is advanced 

approximately two weeks on the 

Coastal Plain. Peak greenness occurs in mid-July regardless of mean 

temperature, but biomass averages 

higher in the warmer years. Absent 

other influences, warming air temperatures are projected to advance 

spring thaw an average of 8–11 days 

by the end of the century, and as 

indicted by the ITEX results, may 

advance the onset of annual plant 

growth and development. Deepening 

of the snowpack and greater cloud 

cover in spring, however, could offset 

the effect of increased air temperature, slowing snow ablation and possibly delaying onset of green-up. 

Senescence in plants is a highly 

regulated, species-specific process 

controlled by both endogenous (e.g., 

nutrient drain, plant hormones) and 

exogenous (e.g., photoperiod, temperature) factors (Kelly et al. 1988). 

The potential impacts of increased 

temperature on plant senescence 

are not well understood. Indeed, 

experimental warming of tundra has 

produced conflicting results. The 

ITEX experiment reported little effect on timing of senescence, indicating that photoperiod might play a 

more important role in late-season 

phenology (Arft et al. 1999). In 

contrast, an experiment in northeast 

Greenland using an alternate warming technique showed that warmer 

temperatures postponed the onset of 

senescence (Marchand et al. 2004). 

In further contrast, NDVI data from 

northeast Alaska indicated that the 

decline in senescence began earlier 

in the warmer years (Figure 4.12). 

Given the conflicting evidence and 

the complexity surrounding onset 

and control of plant senescence, it 

cannot be assumed that warmer fall 

temperatures will extend the period 

of greenness. Figure 4.12. Median normalized difference vegetation index (NDVI) within 

the late July concentrated use area of satellite-collared adult females from 

the Porcupine caribou herd in the 1980s (1985–1989) compared to the 1990s 

(1990–2001). Source: Brad Griffith, USGS, Alaska Cooperative Wildlife 

Research Unit, unpublished data.

shallow water and sedge tundra on 

the Arctic Coastal Plain to acidic 

bog habitats would have profound 

ecological implications, given that 

acidification impedes nutrient availability, lowers productivity, and 

creates favorable conditions for 

slower-growing sedges and heath 

shrubs (Szumigalski and Bayley 

1997, Thormann and Bayley 1997).

In the northern hemisphere, Sphagnum reaches peak abundance in the 

climate zone featuring 630–1,300 mm 

annual precipitation and -2°C to -6°C 

MAAT (Gajewski et al. 2001), both 

warmer and wetter than current 

conditions in arctic Alaska. In contrast to the Arctic, wet drained lake 

basins in the warmer environment of 

the Seward Peninsula (MAAT of -6 

°C) are characterized by vegetation 

co-dominated by sedges and Sphagnum moss (Jorgenson et al. 2004). If 

the Seward Peninsula coastal climate 

is a reasonable analog for the future 

climate of the Coastal Plain, we 

may expect increased abundance of 

Sphagnum in the Arctic and potential conversion of wet sedge tundra 

to bog meadow (M.T. Jorgenson, 

ABR Inc., personal communication). The rate at which peatlands 

might develop on the Coastal Plain is 

unknown. Holocene peatland formation in northern Canada developed 

over a period >1,000 years (Kuhry 

et al. 1992), but Sphagnum has been 

observed to fill thermokarst pits 

(Figure 4.11) on the Arctic Coastal 

Plain over the past half century 

(M.T. Jorgenson, ABR Inc., personal 

communication).
55

Contaminants generated throughout the globe are deposited across 

the arctic landscape through atmospheric deposition and ocean 

currents, in addition to local sources. 

Climate change may increase both 

transport and mobilization of these 

contaminants to fish, wildlife, and 

their habitats. For example, climate 

change may increase contaminant 

mobilization from previously contained sources. Coastal erosion and 

sea level rise may breach or erode 

sewage lagoons, landfills, dumps, 

tailing ponds, drilling mud pits, and 

oil-contaminated soils (AMAP 2003), 

releasing contaminants into the 

nearshore environment. Shoreline 

fuel delivery, storage, and pipeline systems may also be damaged 

or destroyed; in 2007, Newtok, 

Alaska, lost its barge landing and 

a 1,000-gallon fuel tank in a storm 

(CCAAG 2008). Increased discharge 

from large river systems and the 

associated increases in sediment 

transport also will bring additional 

contaminant mobilization. For example, mercury concentrations were 

positively correlated with river flow 

and were greatest during spring 

freshets and high flow events in the 

Mackenzie River Delta (Leitch et al. 

2007); increased mercury concentrations may in part reflect increased 

surface inundation and bank erosion. 

Contaminants currently contained 

within glacial ice, multi-year sea ice, 

and permafrost, including persistent 

organic pollutants and mercury, will 

almost certainly be mobilized to 

aquatic ecosystems as these systems melt. Additionally, long-range 

atmospheric transport will continue 

to be a source of contaminants to the 

Arctic. 

Increased number or intensity 

of fires could result in additional 

mercury inputs to the arctic tundra. Turetsky et al. (2006) evaluated climate-related changes in fire 

incidence and associated mercury 

emissions. They found that mercury 

formerly sequestered in cold, wet 

peat soils is released to the environment during fires in Canadian boreal 

forests and present a growing threat 

to sensitive aquatic habitats and 

northern food chains as the climate 

warms. Estimates of circumboreal 

mercury emissions presented in 

this study are 15-fold greater than 

estimates that did not account for 

mercury stored in peat soils.

Weidinmeyer and Friedli (2007) 

estimated mercury emissions from 

wildfires in Alaska and the lower 48 

states to average 44 metric tons per 

year from 2002–2006. This amount 

is roughly equivalent to 30% of the 

total mercury emissions permitted 

by the U.S. Environmental Protection Agency in 2002. While emissions due to fire were quite variable 

in Alaska, it is notable that in 2004 

fire-related mercury emissions in 

Alaska (32 metric tons) exceeded 

the combined total amount from the 

lower 48 states (23 metric tons). In 

2005, mercury emissions from fires 

in Alaska (22 metric tons) were only 

slightly lower than the total for the 

other states (28 metric tons). 

Mercury concentrations in fish have 

been shown to increase following 

fires in Alberta, Canada, both by 

increasing mercury inputs and by 

restructuring food webs; top predators switched from invertebrate prey 

to smaller fish (Kelly et al. 2006). 

Collectively, these studies suggest 

that these fire-related mercury 

emissions will continue, assuming 

fire incidence remains constant or 

increases with a warming climate. If 

wetland area increases as predicted 

by some climate models, the area 

available for methylation of mercury 

will also increase. Increased mercury mobilization and methylation will 

cause mercury levels in all trophic 

levels to increase; already, mercury 

is a major contaminant of concern 

for arctic biota. 

Contaminants

Top: The Anaktuvuk Fire of 2007 was by far the largest fire ever recorded 

north of the Brooks Range. Photo courtesy Arctic Long Term Ecological 

Research program. 

Bottom: Debris from a dump at the abandoned military site at Nuvagapak 

Point in the Arctic National Wildlife Refuge. Coastal erosion is exposing 

buried industrial and household waste. USFWS photo.
56

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59

Caribou (Rangifer tarandus) foraging near Toolik Field Station; the animals’ ability to access vegetation under 

snow is key to their overwinter survival. Photo by Øivind Tøien.
60

Chapter 5

Climate Effects on 

Fish and Wildlife

In the previous chapter, 

important physical and 

biological agents that will alter 

arctic habitats in response to 

climate change were described. 

In this chapter, we explore 

likely pathways by which fish 

and wildlife populations will be 

affected. 
61

The WildREACH workshop participants worked in breakout sessions 

(see Appendices 3–5) to consider 

the mechanisms by which climaterelated changes in habitat would 

affect fish and wildlife. Workshop 

participants acknowledged the immense uncertainty associated with 

climate projections and the manner 

in which physical and ecological 

systems will respond to an altered 

thermal regime. Against this background, participants were cautious 

to avoid poorly supported predictions regarding fish and wildlife 

response. For each taxonomic group 

of wildlife (i.e., birds, fish, and 

mammals) graphic and narrative 

conceptual models were developed 

that represent hypotheses linking 

climate change, habitat change, and 

biological effects. It is important 

to recognize that these models are 

intended as hypotheses to be tested 

through observation and experiment, rather than evidence-based 

conclusions.

The models are not intended as an 

exhaustive catalog of all possible 

effects; rather they represent a 

selection based on our judgment of 

both plausibility and magnitude of 

effect. We focus attention on changes 

associated with physical processes 

and vegetation change. Trophic 

interactions are considered at the 

community and system level, but an 

assessment of other multi-species 

interactions is largely deferred. We 

acknowledge that climate change 

is likely to result in novel species 

assemblages accompanied by altered 

competitive interactions, predatorprey relationships, and parasite-host 

relationships. Predicting the nature 

of these changes was considered too 

speculative at this stage. 

Hydrologic Process Models

Hydrologic processes are found to 

be a critical link between climate 

change and habitat suitability. Issues 

of water balance, precipitation, and 

surface water distribution were of 

paramount concern for all species 

groups. Two simple conceptual models are presented (summer [Figure 

5.1] and winter [Figure 5.2]), outlining pathways by which changes in 

air temperature and precipitation 

regime will affect aspects of surface 

hydrology most relevant to fish 

and wildlife habitat. These models 

provide the foundation for the taxonspecific models that follow later in 

this section. Summer and winter 

seasons are considered separately 

since winter constitutes most of 

the year in the Arctic, yet the short 

summer growing season is critical to 

reproduction and body condition for 

most species. 

Summer Processes

1. Evapotranspiration is the primary means by which surface and 

soil water loss occurs and thus is 

a key factor in controlling arctic 

hydrology (Kane 1997, Bowling et 

al. 2003). There is evidence that 

portions of the Coastal Plain are 

! Thermokarst

Local redistribution of water and new 

drainage networks (Arctic Coastal 

Plain); lake drainage in some regions

New drainage networks and drying 

interfluves (Arctic Foothills) ! Lake area 

! TEMPERATURE

! Evapotranspiration ! Active layer depth

Summer: Temperature, precipitation, and surface hydrology

! water temperature !"glacial input

! PRECIPITATION

!"soil moisture and 

surface storage

1 2

3 4

5

Figure 5.1. Conceptual model illustrating the effects of increased summer air temperature and precipitation on 

aspects of surface hydrology relevant to habitat change. Gray text boxes identify climate drivers, blue boxes identify 

physical processes, and white boxes represent habitat effects.

Introduction
62

already experiencing increasingly 

drier conditions as precipitation 

fails to compensate for evapotranspiration (Hinzman et al. 2005). 

While increasing temperatures will 

promote evapotranspiration, it is 

important to recognize that the actual rate of evapotranspiration can 

be either water- or energy-limited. 

If projected increases in summer 

precipitation do not compensate 

for increased evapotranspiration, 

then summer drying will occur 

earlier and to a greater degree 

than currently. Fall evapotranspiration tends to be limited by available 

energy, as well as by the onset of 

plant senescence. Soil saturation and surface water storage at 

the onset of winter is sensitive to 

changes in rainfall, which tends to 

occur in late summer and fall.

2. Warmer soil temperatures and 

earlier onset of active layer thaw 

will increase the depth of seasonal 

thaw. As active layer thickness 

increases, the soil storage capacity 

will increase and water may percolate downward, resulting in drying 

at the surface. Streamflow records 

from gauges in the Canadian 

Northwest Territories and portions 

of the Yukon River show increases 

in baseflow during winter, which 

has been attributed to permafrost degradation (St. Jacques 

and Sauchyn 2009, Walvoord and 

Striegl 2007). In the Foothills, a 

longer warm season may prolong 

the time available for soil moisture 

to move down gradient and into 

drainage networks. This may lead 

to drying of shallow soils in late 

summer and early fall, while baseflow increases due to additional 

shallow groundwater flow. Fall and 

winter drainage may be less important on the Coastal Plain because 

soil moisture distribution is largely 

determined by microtopography. 

Deepening of the active layer and 

subsequent redistribution of water, 

however, should reduce surface 

storage (e.g., lower lake levels) and 

produce drier near-surface soils.

3. A warming climate combined with 

increased snow cover is expected 

to have a significant impact on the 

annual heat budget of arctic lakes 

(for review see Schindler and Smol 

2006). Increased snow cover will 

insulate lakes and result in thinner 

ice. Thinner lake ice will melt faster 

in spring, leading to earlier ice-out 

and earlier seasonal rise in water 

temperature. There is a paucity 

of long-term temperature records 

for arctic lakes and streams, but 

what data are available suggest 

a warming trend. Toolik Lake, 

located within the Foothills, shows 

a 3°C warming of the epilimnion 

(upper layer of lake) from 1975 to 

1992 (O’Brien et al. 1997). Warming 

of water in the Arctic is not limited 

to lakes, as large rivers, such as the 

Lena River in Siberia, also show a 

warming trend (Yang et al. 2002). 

Milner et al. (1997) reported that 

daily maximum temperatures in 

a tundra stream reached as high 

as 21°C, although the maximum 

monthly temperature was 13.5°C. 

If these data are representative, it 

suggests that water temperature in 

arctic Alaska lakes and streams is 

highly sensitive to climate change. 

4. As the rate of ice loss continues to 

increase for Brooks Range glaciers 

(Nolan et al. 2006), these glaciers 

are expected to disappear in the 

next 100–200 years (Weller et al. 

2007). Initially the magnitude and 

temporal extent of glacial runoff 

will increase, leading to increased 

sediment delivery to deltaic mud 

flats and the ocean and greater 

connectivity to floodplain lakes. 

When ice loss reaches the point at 

which meltwater outflow decreases 

or ceases, glacial-fed systems will 

show reduced flow rates, lower 

turbidity, and altered water quality. 

These changes will be particularly 

important in the eastern portion 

of the North Slope where glaciers 

exert strong controls over flow regime, habitat suitability, and formation of coastal deltas. 

5. Recent observations in arctic 

Alaska suggest that permafrost is 

warming (Romanovsky and Osterkamp 1997, Osterkamp and Jorgenson 2006, Clow 2008) and that 

warming temperatures can accelerate thermokarst processes at mean 

annual ground temperatures well 

below 0°C (Jorgenson et al. 2006). 

Permafrost temperatures are likely 

to continue to increase under the 

expected scenario of increasing 

air temperature and precipitation. 

This in turn will likely accelerate the formation of thermokarst 

features. Types of thermokarst 

features and ecological implications 

of permafrost degradation will vary 

depending on location, landscape 

position, soils, hydrology, and 

amounts and types of ice (Jorgen-
63

son and Osterkamp 2005). In areas 

with little topographic relief, such 

as portions of the Coastal Plain, ice 

wedge degradation can produce 

water-filled pits and troughs that 

drain water from flooded polygon 

centers (Jorgenson et al. 2006). 

Where topographic gradients are 

large enough to allow for rapid 

drainage, suprapermafrost groundwater flow can deepen the active 

layer and produce features known 

as water tracks (Jorgenson et al. 

2008). Similarly, thermokarst gullies can form when surface water 

becomes channelized, deepens the 

active layer, and thaws ice-rich 

permafrost (Jorgenson et al. 2008). 

Thermokarst lakes, common across 

the western portion of the Coastal 

Plain, will also respond to a warming climate. Lakes can undergo 

lateral expansion by the process 

of thermal and mechanical erosion 

(Jorgenson and Shur 2007, Jorgenson et al. 2008). As permafrost 

warms and begins to degrade, lake 

area will likely increase as shorelines become more susceptible to 

erosion.

Winter Processes 

1. Snow acts as an insulator between 

relatively warm soil and cold air 

throughout the winter. Temperature records from the Kuparuk 

River basin show that snow cover 

attenuates average winter air temperature by 34–47% and diurnal 

air temperatures by 40–96% (Taras 

et al. 2002). Where snow is deep, 

soil temperatures are warmer, and, 

in extreme cases, deep snowdrifts 

can prevent soils from freezing 

(Sturm et al. 2005). Using a model 

developed for the Kuparuk basin, 

↑ Thaw–freeze cycles

↑ TEMPERATURE

↑ End-of-winter soil and 

subnivian temperatures

↑ Rain on snow events

Winter: Temperature and precipitation

↑ PRECIPITATION

↑ End-of-winter SWE Changes in snow 

structure

Advance in first day 

above freezing

1

2 3 4 4

4

Taras et al. (2002) estimated that 

increasing snow depth by 15 cm 

would increase temperatures at 

the soil/snow interface by 0.5–3°C. 

It follows that warmer winter air 

temperatures in combination with 

increased snow depth will likely 

produce warmer soil and subnivean 

(air layer between the snow and 

the soil surface) temperatures.

2. Increased snowpack depth will 

likely produce higher snow water 

equivalent (SWE) values.

3. Control of timing and duration of 

snowmelt is complex. In general, 

snowmelt is advanced in warm, 

wet springs and delayed under cool 

and dry conditions (Zhang et al. 

2001). Therefore, under a scenario 

of warming air temperatures it is 

possible that spring melt will occur 

earlier in the year. Snow cover 

records from Barrow suggest that 

the snowmelt date is becoming increasing variable and has advanced 

by 10 days since 1941 (Hinzman et 

al. 2005), suggesting that a shift to 

an earlier onset of spring is already 

occurring. 

4. On the North Slope, mid-winter 

freeze-thaw cycles and rain-onsnow events can occur but are rare 

(Kane et al. 2000). Warmer temperatures during winter could result in 

more frequent thaw-freeze cycles 

and rain-on-snow events. If these 

icing events become increasingly 

common, the snowpack will become 

denser and grain size will increase. 

Such a change would likely have 

profound consequences for a number of mammals.

Figure 5.2. Conceptual model illustrating the effects of increased winter air temperature and precipitation on 

aspects of surface hydrology relevant to habitat change. Gray text boxes identify climate drivers and blue boxes 

identify physical processes.
64

Over 200 species of birds have been 

observed on the North Slope, but 

many are of casual occurrence. Over 

90 species (Table 5.1) regularly use 

terrestrial and freshwater habitats 

for nesting, brood rearing, and fall 

staging. Nearly all are migratory, 

occupying the region for some portion of the summer season (May to 

September). A few species, including 

rock and willow ptarmigan, common 

raven, snowy owl, and American 

dipper (Johnson and Herter 1989), 

are known to occur on a year-round 

basis. 

The avifauna of arctic Alaska is 

dominated numerically by waterfowl 

and shorebirds that are dependent 

on a variety of wetland habitat 

types distributed broadly across the 

Coastal Plain. All of the waterfowl 

(21 species), loons (4 species), grebes 

(1 species), and gulls/terns (4 species) that regularly occur in arctic 

Alaska are dependent on open-water 

habitats for foraging, brood rearing, 

and/or molting (Bergman et al. 1977, 

USFWS 1993). Shorebirds (25 species) vary in their breeding habitat 

preference, with some species using 

moist upland tundra and others dependent on aquatic or semi-aquatic 

habitats (Cotter and Andres 2000, 

Troy 2000, Brown et al. 2007). While 

wetland-dependent species are most 

prevalent on the Coastal Plain, the 

diversity of perching birds is greatest in the Brooks Range and Foothills, where shrub-associated species 

with taiga affinities reach the northern limits of their ranges (Johnson 

and Herter 1989, Poole 2005).

Many species of waterfowl and 

shorebirds use coastal habitats 

(mainland beaches, river deltas, 

protected lagoons and their shorelines, and barrier islands) for brood 

rearing, molt, and staging prior to 

fall migration (Connors et al. 1979, 

Connors et al. 1981, Johnson and 

Richardson 1982, Connors 1984, 

Gill et al. 1985, Johnson et al. 1993, 

Fischer and Larned 2003). Mainland and barrier-island beaches are 

used by high densities of staging 

shorebirds (e.g., red and red-necked 

phalaropes), likely attracted by 

marine invertebrates concentrated 

by wind-driven water currents (Connors et al. 1979). Barrier islands are 

used by nesting common eiders to 

the virtual exclusion of other habitats (Johnson and Herter 1989, Dau 

and Larned 2007). Coastal wet sedge 

(also known as arctic salt marsh) is 

used preferentially by many broodrearing and post-breeding waterfowl 

and shorebirds, particularly brant 

and snow geese (Johnson 2000, 

Sedinger and Stickney 2000). Riverdelta mudflats provide important 

pre-migration habitat for shorebirds 

(Connors et al. 1979, Andres 1994, 

Alaska Shorebird Group 2008). Lake 

basins breached by coastal erosion 

may provide especially favorable 

staging habitat for post-breeding 

shorebirds (Audrey Taylor, University of Alaska, unpublished data).

Several waterfowl species perform 

a post-breeding molt migration to 

specific North Slope sites at which 

they complete wing molt, remaining 

flightless for several weeks. Notably, 

tens of thousands of geese of four 

species converge on the large lake 

area north of Teshekpuk Lake each 

year from breeding areas in northern and western Alaska, arctic Russia, and Canada (King and Hodges 

1979, Derksen et al. 1979). Similarly, 

large numbers of long-tailed ducks 

use nearshore waters of Beaufort 

Sea coastal lagoons for molting 

(Johnson and Richardson 1981, 

Johnson 1985).

Diets vary among species groups, 

but many arctic birds rely heavily on invertebrate prey. Of the 94 

species listed in Table 5.1, 37 species (39%) are entirely dependent 

on invertebrate prey, and 72 species 

(77%) rely at least to some degree on 

invertebrates. Insects are a particularly important component of the 

diet for juveniles of widely divergent 

taxonomic groups, ranging from 

dabbling ducks to sparrows. Herbivorous species are few but include 

geese and ptarmigans, which are 

of special management significance 

because of their importance to subsistence and sport hunters. Piscivory 

is also uncommon, with loons and 

terns the most prominent examples. 

Twelve species rely significantly on 

bird and mammal prey, including 

hawks, falcons, eagles, owls, jaegers, 

and gulls.

Predation is a major cause of nest 

failure among arctic-breeding waterfowl and shorebirds (Day 1998, Troy 

2000, Sovada et al. 2001, Meltofte et 

al. 2007), likely influencing productivity and population sizes for some 

species, particularly colonial nesters. 

Arctic foxes are the most important 

predator of bird eggs and young 

(Day 1998, Burgess 2000, Troy 2000, 

Birds
65

Bety et al. 2001), and they also take 

adults of some species. Other important predators include glaucous 

gulls, jaegers, common ravens, and 

brown bears (Day 1998, Troy 2000, 

Bety et al. 2002, NRC 2003). Foxes, 

gulls, and jaegers rely heavily on 

microtine rodents (lemmings and 

voles), and predation on tundranesting birds appears to be inversely 

related to the abundance of mammalian prey (Day 1998, Bety et al. 2001, 

2002, ACIA 2005: 301, Meltofte et al. 

2007).

Common Name Scientific Name Diet1

Habitat Associations2

Wetlands Shrubs Coastal

LakeEmergent MarshWet SedgeMoist SedgeShrubTallLowBarrensWet SedgeWater

 Waterfowl

Tundra Swan Cygnus columbianus H 3 3 3 3 2

Greater White-fronted 

Goose

Anser albifrons H 3 3 3 2 2

Snow Goose Chen caerulescens H 2 2 2

Brant Branta bernicla H 3 3 3 3 3 2

Canada Goose Branta canadensis H 2 2 2 3

American Wigeon Anas americana H, I 2 2 2 2

Mallard Anas platyrhynchos H, I 2 2

Northern Shoveler Anas clypeata H, I 2 2 2 2

Northern Pintail Anas acuta H, I 2 3 3 3 2 2

Green-winged Teal Anas crecca H, I 2 2 2 2

Greater Scaup Aythya marila H, I 2 2 2 2

Lesser Scaup Aythya affinis I 2

Steller’s Eider Polysticta stelleri I 2 2 3

Spectacled Eider Somateria fischeri H, I 3 3 3 2 2

King Eider Somateria spectabilis H, I 2 3 3 2 2 2

Common Eider Somateria mollisima I 2 3 2

Harlequin Duck Histrionicus histrionicus I 2 2

Surf Scoter Melanitta perspicillata I 2

White-winged Scoter Melanitta fusca I 2 3

Long-tailed Duck Clangula hyemalis H, I 3 3 3 2 2 2 3

Red-breasted Merganser3 Mergus serrator I, P

 Grouse

Willow Ptarmigan Lagopus lagopus H 3 3 2 2

Rock Ptarmigan Lagopus muta H 3 3 2

 Loons 

Red-throated Loon Gavia stellata P 3 3 3 2 2

Pacific Loon Gavia pacifica P, I 3 3 3 2 2 2

Common Loon Gavia immer P 2

Yellow-billed Loon Gavia adamsii P 3 2 2

 Grebes

Red-necked Grebe3 Podiceps grisegena P, I

Table 5.1. Bird species occurring regularly in terrestrial 

and freshwater habitats of arctic Alaska (Johnson and 

Herter 1989) classified by diet (Poole 2005) and habitat 

association (The Nature Conservancy [TNC] and ABR, Inc., 

unpublished data).

Continued next page
66

Common Name Scientific Name Diet1

Habitat Associations2

Wetlands Shrubs Coastal

LakeEmergent MarshWet SedgeMoist SedgeShrubTallLowBarrensWet SedgeWater

 Hawks, Eagles, Falcons

Northern Harrier3 Circus cyaneus C

Rough-legged Hawk3 Buteo lagopus C

Golden Eagle3 Aquila chrysaetos C

Merlin4 Falco columbarius C

Gyrfalcon3 Falco rusticolus C

Peregrine Falcon3 Falco peregrinus C

 Cranes

Sandhill Crane3 Grus canadensis H, I, C

 Shorebirds

Black-bellied Plover Pluvialis squatarola I 3 3 2

American Golden-Plover Pluvialsi dominica I 3 3 2

Semipalmated Plover Charadrius semipalmatus I 2

Spotted Sandpiper4 Actitis macularius I

Wandering Tattler3 Tringa incana I

Upland Sandpiper3 Bartramia longicauda I

Whimbrel Numenius phaeopus I, F 2

Bar-tailed Godwit Limosa lapponica I, F 3 2 3

Ruddy Turnstone Arenaria interpres I 2 2 2 3 2

Surfbird3 Aphriza virgata I

Red Knot Calidris canutus I, H 2 2 3

Sanderling Calidris alba I 2 3

Semipalmated Sandpiper Calidris pusilla I 3 3 3 2

Western Sandpiper Calidris mauri I 3 3

Least Sandpiper Calidris minutilla I 2 2 2 2

White-rumped Sandpiper Calidris fuscicollis I 3 3 2

Baird’s Sandpiper Calidris bairdii I 2 3 2 3

Pectoral Sandpiper Calidris melanotos I 2 3 3 2 2

Dunlin Calidris alpina I 3 3 2 2

Stilt Sandpiper Calidris himantopus I 3 3 2

Buff-breasted Sandpiper Tryngites subruficollis I 2 3 3 2

Long-billed Dowitcher Limnodromus scolopaceus I 2 3 3 2 2

Wilson’s Snipe Gallinago delicata H, I 2 3 2 2

Table 5.1. Continued

1. Diet categories: H=herbivore (shoots, leaves), F=herbivore (fruit), S=herbivore (seeds), 

I=invertebrates, C=carnivore (mammals/birds), P=piscivore, A=anthropogenic.

2. Habitat associations: 2=medium, 3=high, based on review of habitat use by 89 species (TNC/

ABR). Only habitat use indices of 2 and 3 are reported, regardless of data quality. Alpine, Dwarf 

Shrub, Forested, Bluff and Riverine Water habitats are not presented here because few species 

exhibited medium or high use of these habitats. Some TNC/ABR habitats are combined here: 

Emergent Marsh includes both Lacustrine Marsh and Riverine Marsh categories presented in 

TNC/ABR; Wet Sedge includes Lowland Wet Sedge Tundra and Riverine Wet Sedge Tundra 

categories; Moist Sedge-Shrub includes Upland Moist Sedge-Shrub Tundra, Lowland Moist 

Sedge-Shrub Tundra, and Riverine Moist Sedge-Shrub Tundra categories; Tall Shrubs includes 

Upland Tall Alder Shrub and Riverine Tall Alder-Willow Shrub categories; and Low Shrubs 

includes Upland Low Birch-Willow Shrub Tundra, Upland Shrubby Tussock Tundra, Lowland 

Low Birch-Willow Shrub, and Riverine Low Willow-Shrub Tundra categories. 

3. Species reviewed in TNC/ABR, but none have index ≥ 2 for habitats presented in this table.

4. Species not reviewed in TNC/ABR. 
67

Common Name Scientific Name Diet1

Habitat Associations2

Wetlands Shrubs Coastal

LakeEmergent MarshWet SedgeMoist SedgeShrubTallLowBarrensWet SedgeWater

 Shorebirds, continued

Red-necked Phalarope Phalaropus lobatus I 3 2 3 3 2

Red Phalarope Phalaropus fulicarius I 2 3 3 2

 Gulls and Terns

Glaucous Gull Larus hyperboreus C, P, A 3 2 2 2 3 3

Mew Gull4 Larus canus C, P, A, I

Sabine’s Gull Xema sabini H, I, P 3 3 3 2 3 3 2

Arctic Tern Sterna paradisaea I, P 2 2 2 3 3 2

 Jaegers

Pomarine Jaeger Stercorarius pomarinus C 2 2

Parasitic Jaeger Stercorarius parasiticus C 3 2

Long-tailed Jaeger Stercorarius longicaudus C, I 3 3

 Owls

Snowy Owl3 Bubo scandiacus C

Short-eared Owl Asio flammeus C 2

 Perching Birds

Say’s Phoebe4 Sayornis saya I

Horned Lark4 Eremophila alpestris I, S

Cliff Swallow4 Petrochelidon pyrrhonota I

Common Raven3 Corvus corax H,C,P,A

Gray-headed Chickadee4 Poecile cincta I, S

American Dipper3 Cinclus mexicanus I, P

Arctic Warbler4 Phylloscopus borealis I

Bluethroat Luscinia svecica I 2 3

Northern Wheatear3 Oenanthe oenanthe H, I

Gray-cheeked Thrush Catharus minimus I, F 3 3

American Robin4 Turdus migratorius I, F

Eastern Yellow Wagtail Motacilla tschutschensis I 2 3

American Pipit3 Anthus rubescens I

Northern Shrike Lanius excubitor I, C 3 3

Yellow Warbler4 Dendroica petechia I

Wilson’s Warbler4 Wilsonia pusilla I

American Tree Sparrow Spizella arborea I 3 3

Savannah Sparrow Passerculus sandwichensis I, S 3

Fox Sparrow Passerella iliaca I 3 3

White-crowned Sparrow Zonotrichia leucophrys I, S 3 2

Lapland Longspur Calcarius lapponicus I, S 3 3 2 2

Smith’s Longspur Calcarius pictus I, S 3 2 3

Snow Bunting Plectrophenax nivalis I, S 3 3

Common Redpoll Carduelis flammea I, S 2 3

Hoary Redpoll Carduelis hornemanni I, S 2 3

Table 5.1. Continued
68

Effects of Climate Change on Birds of 

Arctic Alaska

Many bird species characteristic of 

high latitudes have broad circumpolar distributions. Within Alaska, 

the breeding range of some tundraassociated species extends along the 

Chukchi Sea coast and as far south 

as the Yukon-Kuskokwim Delta (e.g., 

tundra swan, common eider, blackbellied plover, bar-tailed godwit, and 

western sandpiper). Other species 

are widely distributed across Alaska, 

including alpine areas and wetlands 

in the boreal forest zone (e.g., Pacific 

loon, long-tailed duck, American 

golden plover, arctic tern, and 

Lapland longspur). Considering only 

the Alaska portion of their range, 

populations of several species are 

concentrated in the Arctic. These include: yellow-billed loon, snow goose, 

king eider, spectacled eider, Steller’s 

eider, red phalarope, stilt sandpiper, ruddy turnstone, red knot, 

white-rumped sandpiper, pectoral 

sandpiper, buff-breasted sandpiper, 

long-billed dowitcher, glaucous gull, 

pomarine jaeger, snowy owl, and 

Smith’s longspur (Poole 2005). While 

arctic Alaska may serve as a refugium for species with more southerly 

distributions, these arctic specialists 

are likely the most vulnerable to 

climate warming.

The potential for warmer summers 

and delayed freeze-up would likely 

improve reproductive success for 

some bird species. For example, 

there is evidence that shorebird 

chick growth and survival is constrained by cold weather conditions 

(Soloviev et al. 2006), thus a warming climate could increase productivity in these species. A longer openwater season should also improve 

fledging success for species like 

red-throated loons, for which early 

freezing temperatures are a significant source of juvenile mortality 

(Dickson 1993).

If warmer summers result in drying of wetlands, however, species 

that rely on shallow water and wet 

meadow habitats could be profoundly affected. A long-term drying 

trend would likely lead to changes in 

vegetation community composition 

and productivity of invertebrates, 

affecting herbivorous species as 

well as those dependent on arthropods. Widespread paludification 

(expansion of bogs and peat-forming 

environments, see page 53) could 

reduce habitat quality for wetlanddependent species across the Arctic 

Coastal Plain. Shrub expansion 

on the North Slope, if it results in 

displacement of open moist and 

wet sedge tundra habitats, would 

similarly reduce habitat quality and 

availability. 

Increased temperatures and longer 

open-water and growing seasons are 

likely to increase primary and secondary productivity in aquatic and 

semi-aquatic systems, thus increasing food abundance for invertebratedependent species and herbivores. 

Changes in seasonal patterns of food 

availability and quality, however, 

could be detrimental if birds cannot adjust migration, breeding, and 

molting schedules to optimize exploitation of food resources. This could 

result in a “trophic mismatch,” in 

which the seasonal timing of life cycle events is out of phase with that of 

critical food resources (Coppack and 

Both 2002). At present, the timing of 

breeding activities for many species 

of arctic birds appears closely linked 

to peak insect emergence (Hurd and 

Pitelka 1954, Holmes 1966, MacLean 

1980). If birds are unable to respond 

to climate-mediated changes in these 

peak events, breeding success and 

population size will likely be affected 

(Both et al. 2006, Moller et al. 2008, 

Tulp and Schekkerman 2008). Similarly, changes in plant phenology and 

increased plant growth may reduce 

the availability of high-quality forage 

for geese. This could reduce gosling 

growth and survival (Dickey et al. 

2008) and restrict nutrient uptake 

among molting geese (Schmutz et al. 

unpublished). 

The presence or absence of fish in 

arctic lakes heavily influences the invertebrate community (Stross et al. 

1980) and, therefore, prey availability for aquatic birds. Changes in flow 

regimes that prevent fish from entering lakes would be detrimental to 

piscivores, but reduced competition 

for invertebrate prey will likely benefit other bird species. Additionally, 

in northern Alaska, species diversity 

of soil invertebrates increases substantially along a climatic gradient 

away from the colder coastal zone 

(MacLean 1975), suggesting that 

longer summer seasons will result 

in range shifts and changes in the 

composition of the soil invertebrate 

fauna. The potential effects of such 

changes on birds are unclear and 

would depend on their ability to 

exploit these new resources.
69

Changes in coastal habitats will 

affect availability of bird habitat. 

Coastal erosion, accompanied by 

lake-breaching and salinization 

of adjacent low-lying areas, may 

result in changes in vegetation that 

influence habitat suitability differentially for birds (Flint et al. 2008). 

Increased stream sediment loads 

may result from increasing drainage 

basin surface temperatures (Syvitski 

2002) and thermokarst-associated 

bank erosion (Walsh et al. 2005); the 

persistence of deltaic mud-flat habitat is dependent on the balance of 

deposition rate and inundation from 

sea level rise.

Climate warming may affect the relationship between arctic birds and 

their predators in several ways. Population cycles of lemmings and other 

small rodents affect productivity of 

waterfowl and shorebirds because 

these bird species (especially at egg 

and chick stages) serve as alternate 

prey when rodent populations are 

low (Bety et al. 2001, 2002, ACIA 

2005: 301). The inverse relationship between lemming abundance 

and nest success is less apparent on 

the North Slope than the Eurasian 

Arctic (Day 1998). Nevertheless, 

climate-related changes in rodent 

population cycles (Ims and Fuglei 

2005, Kausrud et al. 2008) could 

indirectly influence bird productivity 

and abundance. 

Warming may lead to further 

increases in human economic activity (e.g., increased shipping and 

offshore oil development), and this 

activity may further influence abundance or distribution of predators. 

Arctic foxes, glaucous gulls, common 

ravens, and brown bears tend to 

concentrate in areas of human activity on the North Slope (Day 1998, 

NRC 2003). Increased development 

could increase localized densities 

of predators, although populationlevel effects on birds are unknown 

and could likely be at least partially 

mitigated (Liebezeit et al. in press). 

Further increases in human economic activity may also result in 

increased industrial contamination, 

including oil spills. 

Finally, there is anecdotal evidence 

that red foxes may be increasing in number on the North Slope 

and documentation of competition 

between the arctic fox and the larger 

red fox, with the latter dominating 

(Pamperin et al. 2006). The effect 

on breeding birds of increasing red 

fox numbers and their potential 

exclusion of arctic foxes is unclear. 

Red foxes would likely occur at 

lower densities during the breeding 

season, but they are more capable of 

killing or chasing off large adult waterfowl that often succeed at defending nests and deterring predation 

attempts by the smaller arctic fox.

A red fox (Vulpes vulpes) carrying a spectacled eider (Somateria 

fischeri) near Prudhoe Bay, Alaska. Climate warming may allow red fox 

populations to expand in arctic Alaska. Photo by Bryan Collver, BryLyn 

Collver Art.
70

Conceptual Models: Potential Climatemediated Impacts to Arctic Birds

Four conceptual models were developed describing potential climatemediated habitat changes on North 

Slope birds. Narratives describing 

elements of each model are presented below.

Abundance and Distribution of 

Surface Water (Figure 5.3)

1. Aquatic and semi-aquatic habitats 

of the North Slope support large 

numbers of birds, both herbivores 

and invertebrate-dependent species (Bergman et al. 1977, Derksen 

et al. 1981, Martin and Moitoret 

1981, Meehan and Jennings 1988, 

USFWS 1993, TERA 1994). 

Persistently dry summer conditions could result in conversion 

of aquatic marsh and wet sedge 

meadow to moist sedge meadow, 

and moist sedge meadow to tussock 

tundra. Widespread loss of aquatic 

and semi-aquatic habitat across the 

Arctic Coastal Plain would likely 

decrease invertebrate productivity and availability. This alteration 

would represent a loss of habitat 

quantity and quality, leading to 

changes in bird distributions as 

well as decreases in productivity 

and abundance, with populationlevel effects possible for some 

species.

Above: A male Steller’s eider (Polysticta stelleri) near Barrow; the species is listed as threatened under the 

Endangered Species Act. Photo by Ted Swem, USFWS. 

Below: Long-billed dowitchers (Limnodromus scolopaceus) at Prudhoe Bay, Alaska, flocking in August prior to 

migration. Photo by Bryan Collver, BryLyn Collver Art.
71

2. Permafrost degradation in polygonal terrain will continue to drive 

local redistribution of surface water from shallow polygon centers 

to deeper polygon troughs. Loss 

of productivity in drying polygon 

centers would likely be offset by 

increased primary and secondary 

productivity of expanding thermokarst pits, including higher biomass 

of aquatic insects (MacLean 1980, 

Martin 1983). Habitat heterogeneity characteristic of thermokarst 

terrain has been linked to higher 

local-scale nest density for species 

such as American golden plover, 

semipalmated sandpiper, and rednecked phalarope (Troy 2000) and 

higher general use by some waterfowl such as greater white-fronted 

goose (Troy 1991). It is unclear, 

however, whether landscape-wide 

acceleration of thermokarst would 

be a net benefit to these or other 

species. 

3. The formation of new drainage 

networks could cause increased 

lake drainage in some landscapes, 

resulting in a loss of open-water 

habitats. Depending on the extent 

to which this occurs, it could affect 

the distribution, productivity, and 

abundance of species such as loons, 

terns, and some diving ducks. Lake 

drainage can also result in the 

development of productive drained 

lake-basin complex wetlands 

Local redistribution of water

and new drainage networks

(Arctic Coastal Plain).

New drainage networks,

drying inferfluves (Arctic

Foothills)

↑ Lake area

↑ Drying of polygon

centers

↓ Water table, drying

of intervening ridges

Lake drainage ↑ Drying of saturated soils and

shallow wetlands

Abundance and distribution of surface water: BIRDS

Δ soil moisture and

surface storage

Minor effect

↓ Invertebrate productivity

and availability

↓ Productivity and abundance;

∆ in distribution of some

shorebirds (e.g. red phalarope,

pectoral sandpiper) and

waterfowl.

↑ 1° and 2° (invertebrate)

productivity in thermokarst

pits

↑ Productivity and abundance;

∆ in distribution of some

shorebirds (e.g. red-necked

phalarope), geese and dabbling

ducks.

↑ Water in thermokarst

pits and troughs

↓ Minor effect Large openwater bodies↑ Drained-lake

basin-complex

wetlands

↓ Productivity and abundance;

∆ in distribution of loons, terns

and some diving ducks.

↑ Productivity and abundance;

∆ in distribution of phalaropes,

some shorebirds and some

waterfowl (e.g. geese, dabbling

ducks)

1 2 3 4 5

with stands of water sedge Carex 

aquatilus and emergent pendant 

grass Arctophila fulva. Emergent 

Carex and Arctophila stands have 

high primary productivity (Alexander et al. 1980) and support high 

densities of aquatic invertebrates 

(Bergman et al. 1977). Arctophila

wetlands are preferred habitat 

for Pacific and red-throated loons, 

tundra swans, black brant, northern pintails, long-tailed ducks, 

white-winged scoters, king eiders, 

and both red and red-necked phalaropes (Derksen et al. 1981, Troy 

1988), and are also important to 

threatened spectacled and Steller’s 

eiders (Quakenbush et al. 1995, 

USFWS 1996).

4. In the Foothills ecoregion, development of new drainage networks 

and drying of intervening ridges 

may result in transition from 

tussock tundra to dwarf birch 

vegetation. The effects on birds of 

such a transition are uncertain and 

perhaps minor. 

5. Large, deep lakes unaffected by 

new drainage networks are expected to continue expanding due to 

thermokarst and shoreline erosion 

by wind-driven waves. This will 

likely affect only a small portion 

of the Coastal Plain landscape and 

will have only minor effects on bird 

distribution and abundance. 

Figure 5.3. Conceptual model of 

how changes in abundance and 

distribution of surface water could 

impact birds. Blue text boxes 

identify physical drivers, green 

boxes identify habitat effects, and 

white boxes summarize biological 

implications of habitat change. 
72

Above: Location of the Teshekpuk 

Lake Special Area (orange outline) 

and area used by concentrations of 

molting geese (green outline). Map 

by USFWS from Bureau of Land 

Management data. 

Below: Brant (Branta bernicla) are 

exclusively high arctic breeders 

that depend on particular coastal 

vegetation communities to feed 

young goslings. Following breeding, 

brant congregate at specific areas 

such as Teshekpuk Lake where 

they molt in large flocks before fall 

migration. Photo by Stephanie 

Clemens, USFWS.

Box 5.1 Avian Population Response to Ecological 

Change Along the Arctic Coastal Plain

The Teshekpuk Lake Special Area (TLSA), northeast of Teshekpuk 

Lake in the National Petroleum Reserve–Alaska, represents one of 

the most important goose molting habitats in the circumpolar arctic 

(Flint et al. 2008). To understand how variability in the physical environment may manifest 

biological change, the U.S. Geological Survey 

(USGS) investigated the extent to which goose 

distribution has changed over time, whether 

such change was a consequence of habitat 

change, and what physical and biological processes were responsible. Managers need this 

understanding to better predict future distributions of molting geese, thereby improving 

land management decisions.

The USGS analyzed survey data collected by 

the U.S. Fish and Wildlife Service since 1976 

and discovered that goose distribution has 

changed. In particular, black brant shifted from 

inland lakes to coastal habitats while greater 

white-fronted geese concurrently increased 

in numbers. The change in distribution could 

either have been related to habitat change or 

interspecific competition could have forced 

brant to use suboptimal habitats. Examination 

of a time-series of aerial imagery confirmed 

that high rates of coastal erosion combined 

with periodic storm surges have led to saltwater intrusion into freshwater habitats, and the 

associated changes in salinity may have altered 

foraging conditions for geese in the coastal 

zone (Jones et al. 2009). 

The results from multiple lines of inquiry suggested that the change in distribution has not 

been detrimental to brant. There was no difference in body condition between birds molting 

in traditional inland habitats compared to those 

molting along the coast. Moreover, body condition appears to have improved in recent years 

compared with birds measured in the 1980s. 

Analyzing forage plant species across a range 

of habitats within the TLSA revealed that salttolerant plant species, most commonly found 

along the coast, tended to have higher nitrogen 

content than species sampled along inland 

lakes, an indicator of higher nutritional quality. 

Interestingly, in the warmer year (2006) plant 

productivity was higher in terms of net biomass, but nutrient quality 

was lower in terms of percent nitrogen and the carbon-to-nitrogen 

ratio. 

These results demonstrate the difficulty in predicting how climate 

change may impact habitat and wildlife. On the surface, a change in 

distribution from historical molting grounds seems troubling. However, changes in goose distribution at TLSA that are correlated with 

climate change suggest that geese have shifted habitats in response 

to improving conditions along the coast. This redistribution of birds 

from inland lakes likely reduced interspecific competition, resulting in 

overall improvements in body condition across all habitats. We anticipate further shifts in wildlife distributions and changes in plant forage 

species productivity and nutrient composition as warming patterns 

continue to alter the landscape. 

Alaska
73

Vegetation Community Changes 

(Figure 5.4)

1. Increased shrub abundance could 

have variable effects, depending on 

the landscape setting. Increased 

abundance of tall shrubs in riparian 

or hillslope settings would permit 

range expansion and increased 

abundance of a variety of songbirds 

with affinities for tall shrub. At 

present, tall shrub habitat is exceedingly scarce (<1% of the landscape), and thus an increase would 

have the net effect of increasing 

regional biodiversity. Conversion of 

tussock tundra to shrubby tussock 

tundra in the Foothills and Coastal 

Plain, particularly in the form of 

increased stature and density of 

dwarf birch (Betula spp.), would 

have uncertain consequences for 

bird distribution and abundance. 

Broad-scale expansion of shrub 

communities at the expense of wet 

sedge tundra and moist sedgeshrub tundra on the Coastal Plain 

would reduce habitat availability for a broad suite of wetlandadapted species (Table 5.1). The 

threshold at which shorebird and 

waterfowl production would be reduced, however, and the likelihood 

of reaching that threshold are not 

well understood.

2. The extent to which paludification 

may impact bird populations and 

distribution depends on the rate at 

which this process may occur and 

the degree to which diminished 

primary productivity influences the 

availability of invertebrate prey. 

Acidification may reduce diversity 

and biomass of aquatic invertebrates (Hendrey et al. 1976).

3. Only a few species of birds are 

herbivorous during the summer 

season. For herbivorous geese, 

forage quality rather than quantity 

is thought to be limiting, and forage quality affects gosling growth 

rates and subsequent survival 

(Lindholm et al. 1994, Sedinger et 

al. 1995). Preliminary studies near 

Teshekpuk Lake (Schmutz et al. 

unpublished) suggest that warmer 

temperatures during the growing 

season result in greater plant biomass but diminished forage quality. 

There is evidence suggesting that 

reduced gosling size in years of 

higher spring temperatures may be 

attributed to a mismatch between 

hatching dates of goslings and 

timing of the peak forage quality 

(Dickey et al. 2008).

Changes in plant phenology; ↑ 1°

productivity and plant biomass 

↑ Productivity and abundance; 

∆ in distribution of some 

passerines, ptarmigan.

Vegetation community changes: BIRDS

↓ Habitat for 

water-dependent 

species

↑ Habitat for 

shrub-associated 

species.

↓ 1° and 2°

(invertebrate) 

productivity in 

shallow wetlands

↓ Productivity and abundance, ∆ in 

distribution of phalaropes, some 

shorebirds and some waterfowl

↑ Paludification

↓ Habitat for 

most species

↑ Forage quantity ↓ Forage quality Timing mismatch 

between emergence of 

high-quality forage and 

herbivore life history

Minor effect

↓ Egg and young production, 

fledging success, fledgling survival; 

↓ Body condition during molt, postmolt and pre-migration among 

herbivores

Increased shrub abundance

1 2 3

Figure 5.4. Conceptual model of how vegetation community changes could impact birds. Blue text boxes identify 

physical drivers, green boxes identify habitat effects, and white boxes summarize biological implications of habitat 

change. 
74

Invertebrate Community Changes 

(Figure 5.5)

1. The timing of insect emergence 

is closely related to the timing 

of snowmelt, and might advance 

with warmer spring temperatures 

(Høye and Forchhammer 2008, 

Tulp and Schekkerman 2008). If 

warming alters the timing and patterns of insect emergence and peak 

abundance, and birds are unable 

to compensate for these changes, 

“trophic mismatches” may result. 

If birds cannot alter their migration and breeding schedules 

accordingly, nest success, fledgling 

survival, and pre-migration body 

condition will likely decline. 

Beyond short-term phenological response to changing climate, 

seasonality may have profound 

long-term consequences for the 

distribution and abundance of 

arctic arthropods. Multi-year life 

cycles occur in many arctic invertebrates (MacLean 1980, Chernov 

1985) and the prevalence of multiyear life cycles results in a large 

standing biomass of larval invertebrates available to predators 

throughout the summer season. A 

shift to shorter, even annual, life 

cycles could substantially influence the larval biomass available to 

birds during portions of the breeding season, although the relationship is complex (MacLean 1980). A 

decrease in availability of benthic 

invertebrate larvae could affect 

brood-rearing waterfowl and premigration body condition of shorebirds, perhaps resulting in reduced 

juvenile survival among both, with 

subsequent declines in recruitment 

and, ultimately, population size.

2. Other things equal, warmer 

temperatures and longer growing 

seasons should result in increased 

productivity of soil and aquatic 

invertebrates. Increases in production associated with increased 

temperatures, permafrost degradation, and longer open-water and 

growing seasons may initially lead 

to increased primary and secondary productivity in both pelagic and 

benthic habitats. If birds are able 

to exploit these increases in prey 

abundance, the result should be improved habitat quality that would 

translate into increased productivity and abundance, and perhaps 

higher densities and expanded 

distributions among shorebirds and 

invertebrate-dependent waterfowl 

and passerines. Increased nutrient 

input into lakes, however, may lead 

to eutrophication which would decrease light penetration and could 

ultimately lead to a decline in benthic primary production (Vadeboncoeur et al. 2003). This decline may 

translate into decreased benthic 

invertebrate biomass/production 

↑ Productivity and abundance: ∆

in distribution of phalaropes, 

some shorebirds and some 

waterfowl

↓ Invertebrate productivity and 

availability – meadows and 

polygons

↓ Productivity and abundance: 

∆ in distribution of phalaropes, 

some shorebirds and some 

waterfowl

↑ Drying of saturated soils, 

shallow wetlands and 

polygon centers

Invertebrate community changes: BIRDS

↓ Habitat for some invertebratedependent species

↑ Invertebrate productivity

↓ Multi-year invertebrate life cycles

Trophic mismatch for invertebratedependent species

↓ Biomass, end-of-season 

benthic invertebrate larva 

↓ Fledging success, fledgling 

survival; ↓ Body condition 

during molt, post-molt and premigration

↑ Water in thermokarst 

pits/ troughs

↑ Habitat some invertebratedependent birds

↓ Body condition during molt, postmolt and pre-migration among 

invertebrate-dependent species

Local redistribution of water and new 

drainage networks (Arctic Coastal Plain 

and Arctic Foothills).

Δ soil moisture and 

surface storage ↑ Growing season and 

warmer water temperatures

1

2

3

Figure 5.5. Conceptual model of how 

invertebrate community changes 

may impact birds. Blue text boxes 

identify physical drivers, green 

boxes identify habitat effects, and 

white boxes summarize biological 

implications of habitat change. 
75

and/or a change in benthic invertebrate community composition that 

may negatively impact both birds 

and fish.

3. If warming results in broadscale drying of moist and shallow 

wet habitats, a decline in soil and 

aquatic invertebrates would be 

expected across the North Slope. 

This would reduce habitat quality 

and availability for all shorebirds 

and most waterfowl, with associated decreases in productivity and 

abundance as well as changes in 

distributions for many species.

Coastal Processes and Habitats 

(Figure 5.6)

1. A warming Arctic may cause 

a number of changes in barrier 

islands of the Beaufort and Chukchi seas. Potential changes include 

reduced size, increased rates of migration and erosion, and a greater 

likelihood of overwashing and 

breaching by storm surges. Most 

of the 2,000–3,000 common eiders 

that breed along the Beaufort and 

Chukchi sea coasts (Johnson and 

Herter 1989, Dau and Larned 2007) 

nest on coastal barrier islands, 

and loss of this specialized habitat 

would likely lead to substantial 

reduction in this population. More 

frequent or severe overwash events 

would reduce nest success through 

direct egg mortality, as well as 

diminished nesting habitat suitability, due to removal of sheltering 

driftwood, detritus, and vegetation 

clumps (Dau and Larned 2007).

Loss or major reduction of barrier 

islands would likely cause changes 

in nearshore temperature and 

salinity regimes, perhaps reducing 

invertebrate abundance and, therefore, the quality of foraging habitat 

for species such as long-tailed 

ducks. Loss of barrier islands 

would also reduce shoreline foraging habitat for shorebirds such as 

phalaropes because their planktonic prey frequently becomes concentrated along island water lines. 

2. The increase in coastal erosion 

projected over the next century is 

not expected to result in a significant loss of terrestrial habitats 

along much of the coast; however, 

the potential loss of 8% or more 

of the goose molting area north of 

Teshekpuk Lake could have significant consequences for the tens of 

thousands of geese that molt there 

annually.

3. Climate-induced changes in 

coastal processes could potentially affect other coastal habitats, 

including coastal wet sedge tundra, 

salt-killed tundra, and delta mud 

flats. Coastal wet sedge and deltaic 

mud flats currently are sparsely 

distributed but important habitats, 

and any loss would be considered 

detrimental to waterfowl and 

shorebirds. Salt-killed tundra is 

of low value as nesting habitat 

because of limited plant cover so an 

increase of this type at the expense 

of more productive habitat would 

be detrimental. The total area affected, however, is expected to be 

relatively minor on a regional scale.

Figure 5.6. Conceptual model of how changes in coastal processes and habitats could impact birds. Blue text boxes 

identify physical drivers and white boxes summarize biological implications of habitat changes.

↓ Barrier islands and protected 

lagoons

↓ Terrestrial habitats 

along coastline

∆ Delta mudflats Δ Salt-killed 

tundra 

Δ Saline mud flats and 

coastal wet sedge tundra 

Coastal processes and habitats: BIRDS

∆ Shorebird premigration staging 

habitat 

↓ Nesting habitat for common eiders.

↓ Foraging and/or molting habitat for 

waterfowl, loons, gulls, terns, and some 

shorebirds.

Δ Habitat quality and quantity Δ Minor effect

for brood-rearing brant, postbreeding waterfowl and 

shorebirds.

↓ Foraging, nesting, broodrearing and staging habitats 

for some waterfowl and 

shorebirds.

1 2 3

Opposing influences create uncertainty regarding direction of 

change for mudflats, coastal wet sedge tundra, and salt-killed 

tundra
76

Fish Aquatic Habitats of the North Slope of 

Alaska

Aquatic habitats on the North Slope 

are characterized by low average 

temperatures, low prey densities, 

short open water periods each year, 

and limited overwintering areas. 

Many fish populations are reliant on 

seasonal movements among habitats 

(Craig 1989). North Slope streams 

can be categorized by ecoregion, 

size, and origin (Craig and McCart 

1975, Craig 1989). Mountain streams 

originate in the Brooks Range and 

Arctic Foothills, are prevalent east 

of the Colville River, and are characterized by glacial and clear water 

systems of variable size, with flows 

derived mostly from springs and 

surface runoff (Craig and McCart 

1975). These streams are typically 

cooler and have higher discharges 

than other waterbodies in the region 

and typically freeze to the bottom 

in winter, with only spring areas 

and deep pools containing liquid 

water in the winter (Craig 1989). As 

the largest mountain stream and 

the largest drainage on the North 

Slope, the Colville River intercepts 

smaller mountain streams across the 

western Brooks Range. West and 

north of the Colville, most streams 

originate on the Coastal Plain. These 

Coastal Plain streams are typically 

smaller, warmer, and slower-moving, 

and many do not contain liquid 

water in winter (Craig 1989); the 

larger of these drainages, however, 

contain liquid water in deep pools 

and springs throughout the year 

(Morris et al. 2006). Many Coastal 

Plain streams meander through 

lake networks with their discharges 

dependent on surface runoff. These 

systems also include the smaller tundra streams that typically occur as 

tributaries across the Coastal Plain.

Lakes across the North Slope can 

also be categorized as mountain 

lakes or Coastal Plain lakes, based 

on ecoregion, size, and origin 

(Hobbie 1973). Mountain lakes are 

uncommon, occupying only 1.7% of 

the Foothills and 0.4% of the Brooks 

Range ecoregions (Jorgenson and 

Heiner 2003) and are typically of 

glacial origin, formed by moraines, 

scour, or deposited ice blocks (kettle 

lakes; Hobbie 1973). Many of these 

lakes are large and deep with 

recharge associated with surface 

runoff and groundwater sources. 

Because of their depth, most of these 

lakes do not freeze to the bottom. 

Coastal Plain lakes are abundant, 

occupying approximately 14% of the 

Coastal Plain ecoregion (Jorgenson 

and Heiner 2003). The area they 

encompass is considered to be the 

second largest lake district in Alaska 

(Arp and Jones 2008). Many Coastal 

Plain lakes are derived from thermokarst processes (Hobbie 1973) 

and are relatively shallow (<9 m), 

including Teshekpuk Lake, the largest lake on the North Slope (NRC 

2003). Smaller and shallower (<2 m) 

lakes typically freeze to the bottom 

and only contain liquid water during 

the warm season. Coastal Plain lakes 

are dependent on surface runoff for 

recharge and are subject to substantial evaporative loss during summer (Miller et al. 1980). Although 

landlocked lakes are present on the 

Coastal Plain, many lake systems 

are seasonally linked by shallow 

streams, forming complex networks 

of connected habitats.

Marine and estuarine environments 

on the North Slope are no less 

extreme than freshwater habitats. 

Many areas of the North Slope coast 

are characterized by barrier islands 

that form shallow lagoon systems 

and by large river deltas, both of 

which provide important fish habitat 

(NRC 2003). During summer and 

depending on prevailing winds, 

topography, and nearshore currents, 

freshwater flows from North Slope 

rivers mix with coastal waters to 

produce a narrow nearshore band 

of relatively warm, brackish water 

(Craig 1984). During winter when 

freshwater input is minimal, nearshore water may become hypersaline due to concentrated salts from 

ice formation, and the temperature 

of under-ice water can reach -2°C or 

colder (Griffiths et al. 1977). These 

cold waters are not suitable habitat 

for anadromous or freshwater fish. 

Tidal fluctuations are on the order of 

20 cm and do not play a major role in 

mixing and exchange between brackish and marine waters (Griffiths et 

al. 1977). 
77

Species

Life 

History 

Strategy1

Habitat Use2

Open-water Season Ice-cover Season

Streams Lakes Coastal 

Water

Streams Lakes

Large

Small

Deep

Shallow

Near-shore

Ocean

Large

Small

Deep

Least Cisco

A X X X X X

R X X

Arctic Cisco A X X X X

Round Whitefish R X X X X X X

Broad Whitefish A X X X X X

Humpback 

Whitefish A X X X X X X

Lake Trout R X X

Arctic Char R X X

Dolly Varden

A X X X X X X

R X X X X

Pink Salmon A X X X X

Chum Salmon A X X X X

Arctic Grayling R X X X X X X X

Ninespine 

Stickleback

A X X X X X X X X

R X X X X X X X X

1. Life history strategies: A=Anadromous, R=Resident. Least cisco, Dolly 

Varden, and ninespine stickleback have populations in both categories.

2. Habitat Definitions: Large streams have sufficient flow to allow instream 

(springs and deep areas) and estuarine (river delta) overwintering 

habitat. Small streams have insufficient flow to develop estuarine 

habitats, but some of these streams may provide instream overwintering 

habitat in the form of springs and deep pools. Deep lakes do not freeze to 

the bottom allowing year-round use by fish. Shallow lakes do not provide 

overwintering habitat but may be used by fish during the open water 

season if there is access. Coastal water (near-shore) is marine water that 

is somewhat warmer and of lower salinity than the ocean in summer, due 

to freshwater inflow during the open water period; these habitats take on 

fully marine characteristics of salinity and temperature during winter, 

which precludes their use by freshwater or anadromous species during 

that season. Coastal water (ocean) is fully marine habitat that does 

not allow overwintering of any salmonid species because of low water 

temperature.

Table 5.2. Generalized life 

history and seasonal habitat 

use by common North Slope 

freshwater and anadromous 

fish.

Freshwater Resident and Anadromous 

Fish of the North Slope of Alaska

Species in the family Salmonidae 

are perhaps the most diverse group 

of fishes that use North Slope 

freshwater habitats. They include 

lake trout (Salvelinus namaycush) 

and Arctic char (S. alpinus), which 

live exclusively in freshwater lake 

systems (Morrow 1980, Reist et al. 

1997). Arctic grayling (Thymallus 

arcticus) and round whitefish (Prosopium cylindraceum) live in lakes 

and rivers and are rarely encountered in coastal waters. Most Dolly 

Varden (S. malma) populations 

are anadromous, while others are 

resident and live entirely in freshwater. Similarly, both anadromous and 

freshwater resident populations of 

least cisco (Coregonus sardinella) 

occur on the North Slope (Seigle 

2003, Moulton et al. 1997). Broad 

whitefish (C. nasus) and humpback 

whitefish (C. pidschian) populations 

are typically anadromous, although 

freshwater populations may exist in 

certain lakes or in upstream reaches 

of the Colville River (Craig 1989). 

Arctic cisco (C. autumnalis) encountered on the North Slope of Alaska 

are entirely anadromous and return 

to the Mackenzie River in northern 

Canada to spawn (Fechhelm et al. 

2007). Chum salmon (Oncorhynchus 

keta), pink salmon (O. gorbuscha), 

and other Pacific salmon species 

occur in low numbers in nearshore 

coastal waters of the Beaufort Sea 

each summer (Stephenson 2005). 

Small numbers of spawning chum 

and pink salmon are regularly observed in the Colville River and occasionally observed in other streams 

as well. Aside from chum salmon 

in the Colville River, it is not clear 

whether Pacific salmon observed in 

North Slope rivers are members of 

self-sustaining populations or strays 

from populations in drainages of the 

Chukchi Sea or farther south. 

A number of non-salmonid fishes of 

several families have also adapted to 

aquatic habitats on the North Slope. 

Ninespine stickleback (Pungitius 

pungitius) populations can be either 

resident or anadromous (Morrow 

1980). They are found in freshwater 

and nearshore habitats across the 

North Slope, and they play a critical 

role in the food webs of piscivorous 

birds (Poole 2005) and fish. Burbot 

(Lota lota) are common in stream 

and lake habitats of the western 

North Slope (Morris 2003), but 

they are rarely captured in coastal 

waters. Alaska blackfish (Dallia pectoralis), northern pike (Esox lucius), 

slimy sculpin (Cottus cognatus), and 

longnose sucker (Catostomus catostomus) are also found in freshwater 

habitats of the western North Slope. 

Habitat use for a subset of fish species is summarized in Table 5.2.
78

Effects of Climate Change on Fish of 

Arctic Alaska

The Intergovernmental Panel on Climate Change (IPCC) and the Arctic 

Climate Impact Assessment (ACIA) 

both identified the Arctic as an area 

where climate change effects will be 

observed most readily (IPCC 2007, 

ACIA 2005). Furthermore, aquatic 

systems within the region are expected to act as key indicators of the 

timing, rate, intensity, and effects of 

the change. Fish response to climate 

change is difficult to quantify due to 

the lack of basic biological information and the incomplete understanding of climate effects on ecological 

processes of freshwater systems 

(ACIA 2005). There is little doubt, 

however, that a changing climate has 

the potential for widespread consequences for the physical, chemical, 

and biological processes that are key 

components of fish habitat in arctic 

Alaska (Reist et al. 2006a). Reduced 

flow and increased air temperatures 

that cause higher water temperatures may also have direct effects 

on individual fitness and population 

resilience (Svenning and Gullestad 

2002).

A warming climate is likely to 

increase ecosystem productivity, 

resulting in increased biomass and 

yields of many species (Reist et al. 

2006b). The magnitude of change in 

ecosystem productivity and biomass 

will depend on local conditions and 

population tolerances. Freshwater 

resident fish in lakes may show increased production in comparison to 

those populations in flowing water. 

Increased productivity in nearshore 

areas could boost returns of anadromous fish. However, increased productivity in freshwater and estuarine 

systems could be offset if water 

temperatures rise past optima. 

Higher than optimum water temperatures could result in decreased 

biomass and yield, leading to altered 

rates and locations of colonization, 

extinction, competition, and productivity (Tonn 1990). Increasing temperatures will have a direct effect on 

available habitats, including populations reliant on colder water below 

the thermocline in lakes (Reist et al. 

2006a). Increased air temperature 

and duration of the ice-free season 

may promote thermal stratification 

in lakes that currently remain unstratifed due to wind-mixing, short 

ice-free season, and low air temperatures. Over the past 40 years, 

presence and strength of late summer thermal stratification in several large deep lakes in the Brooks 

Range has increased dramatically 

(G. Burkart, National Park Service, 

personal communication). Juvenile 

fish constrained to the warm epilimnion (surface layer) may experience 

lower growth rates because greater 

food availability may not compensate for higher metabolic rate, while 

adult fish seeking thermal refuge in 

the hypolimnion (deep layer) may 

experience anoxic conditions due to 

the increae in pelagic productivity in 

the warmer surface waters. 

Longer term changes may also lead 

to a disturbance of synchronized 

environmental cues, such as photoperiod and water temperature, 

which may drive major life history 

actions, including gonadal maturation and fertilization success (Reist 

et al. 2006a). Changes in groundwater flows may affect the type and 

amount of instream sediment and 

substrate, alter chemical composition, and change the temperature 

of the water, leading to increased 

physiological stress for populations 

not adapted to these new conditions. Changes to the physical and 

chemical properties of water may 

reduce incubation success and the 

availability of overwintering habitat. 

In addition, groundwater can alter 

the timing, extent, and duration of 

ice cover, which may lead to changes 

in habitat structure. Changes in 

both groundwater and precipitation 

runoff may affect the flow regimes 

of rivers and streams and disrupt 

the migration patterns of freshwater 

and anadromous fish (Prowse et al. 

2006). An increase in sea level and 

coastal erosion may also disrupt traditional migration patterns or make 

current habitats unavailable (ACIA 

2005).

Dolly Varden char (Salvelinus malma malma) in arctic Alaska can be found 

in both anadromous and resident populations. Photo by Fred DeCicco, 

Alaska Department of Fish and Game. 
79

Access to Spawning and 

Overwintering Habitats

Periods of low stream flow and low 

water levels in lakes could have 

significant effects on migratory patterns of many fish populations (Reist 

et al. 2006a, 2006b). Sufficient flows 

during particular seasons are critical 

to fish movements and also reduce 

stranding events (Power et al. 1999). 

The degree to which changes in water balance impact fish will depend 

in part on the type of watershed 

they occupy and the time of year. 

Anadromous and many freshwater 

resident fish populations on the 

North Slope are highly migratory 

and are reliant on corridors with sufficient discharges to complete their 

annual life cycle. While anadromous 

populations move between freshwater and marine environments (Craig 

1989), freshwater residents move 

among individual lakes and streams, 

as well as within lake and stream 

systems (Morris 2003). During the 

spring freshet (water flow resulting 

from sudden rain or melting snow), 

anadromous populations move from 

overwintering areas in freshwater 

to summer feeding areas in marine water. These populations then 

leave marine waters in late summer 

and ascend rivers to spawn and 

overwinter. Freshwater residents 

that spawn in the spring are also 

dependent on the freshet when they 

move from overwintering areas to 

spawning areas. After spawning, 

they move to summer feeding areas, 

and in late summer and fall return 

to overwintering areas. Freshwater 

residents that spawn in the fall move 

directly from overwintering to feeding areas in the spring, and in late 

summer and fall return to spawning 

and overwintering areas. Because 

the freshet is driven by snowmelt, 

sufficient flows during spring are 

expected to be available for fish to 

move to preferred habitats, regardless of their life history strategy.

Key impacts could occur in late 

summer and early fall, however, 

when warmer air temperatures and 

increased evapotranspiration reduce 

the amount of water stored at the 

surface, causing a drying effect that 

may limit access to spawning and 

overwintering habitats. Even in 

those areas where stream baseflow 

is likely to increase or be maintained 

(Kane 1997), hot, dry summers could 

result in at least a temporary loss of 

connectivity. For example, Deegan 

and Peterson (1992) described a case 

in the summer of 1990 where water 

levels in the upper Kuparuk River 

were low, many riffles were nearly 

dry, and many of the deeper pools 

were isolated. A similar instance 

was noted in the upper John River 

near Anaktuvuk Pass in the Brooks 

Range (G. Burkart, National Park 

Service, personal communication). 

Arctic grayling in several areas of 

the stream became stranded, and 

only after a heavy rain event in 

September were water levels high 

enough to allow these fish to migrate 

to overwintering areas. If similar 

circumstances become more common across the North Slope, fish 

may be delayed in their migrations, 

and they may not be able to access 

spawning or overwintering areas 

prior to freeze-up, with direct mortality likely. 

Increased Water Temperatures

Periods of low stream flow and low 

water levels in lakes could also have 

significant effects on the temperature regimes of the habitats required 

by many fish populations (Reist et al. 

2006a). Fish seek out habitats with 

water temperatures that fall within 

their thermal preference (Coutant 

1987). These habitat areas can be 

dispersed, and the availability of 

water at the preferred temperatures 

limit seasonal and spatial fish distribution. As such, water temperatures 

influence migration patterns (Svenning and Gullestad 2002), can pose a 

barrier to movement, and influence 

the availability of pathways to access 

preferred habitats (Coutant 1987). 

Water temperature also affects 

physiological processes, including 

growth, gonadal maturation, and 

egg incubation, as well as population 

productivity and survival (Reist et 

al. 2006a). Warmer waters may also 

increase the prevalence of diseases 

and parasites (Reist et al. 2006b) and 

increase the uptake and toxicity of 

contaminants (Schiedek et al. 2007).

If streams 

on the North 

Slope become 

shallower, fish 

may be unable to 

access seasonal 

habitats such as 

overwintering 

areas. Photo 

by Larry 

Hinzman.
80

Conceptual Model: Effects of 

Changed Surface Hydrology and 

Water Temperature

We developed a conceptual model 

describing potential effects of 

changed surface hydrology and water temperature on North Slope fish 

(Figure 5.7). Narratives describing 

elements of the model are presented 

below.

1. As soil moisture and surface storage change, baseflow in mountain 

streams during summer and fall 

will likely increase and may be sufficient to maintain the physical connections among required habitats 

within a watershed; if increased 

precipitation is insufficient to compensate for increased evapotranspiration, however, loss of connectivity is probable. Moreover, surface 

flow may also be controlled by thaw 

depth beneath the channel, and a 

deeper active layer may allow more 

underground flow and drying at 

the surface. Water levels in mountain lakes may decrease, but should 

remain sufficient in most cases to 

support populations of lake trout 

and Arctic char. In settings where 

fish move between deeper overwintering lakes and productive shallow 

lakes for summer foraging, however, a loss of connectivity could 

result in reduced food availability 

or stranding.

A shift from surface storage to 

soil storage of water could lower 

water levels in coastal streams 

and lakes and reduce connectivity 

among these waterbodies. Species 

that rely on these connections to 

access critical habitats, such as 

broad whitefish, least cisco, Arctic 

grayling, and ninespine stickleback 

(Moulton 2007), may be forced into 

less preferred habitats (Wrona et 

al. 2006). A lack of connectivity 

between streams and their deltas may also affect the amount of 

overwintering habitat available and 

the timing of annual migrations for 

resident species. For anadromous 

species, the loss of connectivity 

may restrict access to spawning 

and overwintering areas as fish 

return from summer feeding in 

estuarine and marine waters.

Sequential lake drainage where

topographic gradients are great

enough to allow for drainage

Temperature and surface hydrology: FISH

Loss of summer foraging

habitat resulting in reduced

growth rates and productivity.

Little direct

impact to fish.

Loss of connectivity;

drying of streams.

impedes migration and ↑

stranding.

When ice loss reaches the point where

input to streams decreases, this will

change flow regimes and water quality

of glacial streams.

↑ baseflow for

streams in the

Arctic Foothills

(i.e., Mountain

steams)

Little impact to fish if

baseflow maintains

waterbody connectivity

(see text).

Δ soil moisture and

surface storage

↓ availability of thermal refugia during summer (e.g., deeper

and thermoclines in lakes and reduced areas of cold water in

streams) and ↑ strength and prevalence of thermoclines.

Physiological impacts to fish including increased metabolism,

change in productivity (short term ↑ followed by long-term ↓),

and direct mortality, incidence of parasites/disease.

Local redistribution

of water and new

drainage networks

(Arctic Coastal Plain)

New drainage

networks and

drying interfluves

(Arctic Foothills)

Δ water Δ glacial input ↑ Lake area

temperature

Pits and troughs intercept

suprapermafrost water

and reduce baseflow

1

2 3 4 5

↓ surface flow

for streams in

the Arctic

Coastal Plain

Loss of connectivity

between Coastal

streams and lakes

impedes migration and

↑ stranding.

Figure 5.7. Conceptual model describing potential effects on changes in surface hydrology and water temperature 

on North Slope fish. Blue text boxes identify physical drivers, green boxes identify habitat effects, and white boxes 

summarize biological implications of habitat change.
81

2. Increased water temperatures in 

late summer may prevent fish from 

reaching spawning and overwintering areas after summer feeding. 

The magnitude of temperature 

change and loss of thermal refugia 

will differ among stream systems, 

with those systems fed by springs 

or glaciers (see element 3) likely 

having cooler water that will allow normal fish movements. Fish 

inhabiting mountain lakes, such as 

lake trout and Arctic char, may be 

confined to deeper waters as water 

temperatures increase (Reist et 

al. 2006c), and may be restricted 

from moving into shallow areas 

and summer feeding areas along 

the shoreline. Migratory fish that 

use Coastal Plain streams and 

lakes may be the most affected by 

increases in water temperatures. 

Although migratory fish may be 

able to find suitable temperatures 

in deep portions of these waterbodies, warmer temperatures at the 

surface may interfere with emigration. Also, warmer temperatures in 

streams may constrain movements 

and result in fish becoming stranded in isolated pockets of cooler 

water (Power 1999). Increased 

water temperatures could lead 

to higher metabolism and higher 

productivity, but will likely result in 

long term decreases in yield (Tonn 

1990). Consistently high temperatures could also lead to direct 

mortality.

3. Migratory fish rely on sufficient 

late summer discharge to reach 

spawning and overwintering 

habitats. Glacial stream systems 

and the fish that use them are 

likely to be significantly impacted 

by a warming climate. As the rate 

of ice loss continues to increase 

for Brooks Range glaciers (Nolan et al. 2006), these glaciers are 

expected to disappear in the next 

100–200 years (Weller et al. 2007). 

When ice loss reaches the point at 

which meltwater input decreases, 

sufficient discharge may not be 

available to allow Dolly Varden 

and other species that use glacial 

systems to complete their migrations from summer feeding areas 

to spawning and overwintering 

habitats. The decrease in amount of 

meltwater may also change turbidity and other water quality characteristics to which these populations 

have adapted.

4. As air temperatures increase, 

the distribution of surface water 

on the Coastal Plain is likely to 

change due to both local redistribution of water and formation of 

new drainage networks (McGraw 

2008). Newly formed pits and 

troughs can intercept subsurface 

flows, decreasing baseflow into 

streams and reducing connectivity 

among streams and lakes. Where 

topographic gradients are large 

enough, new drainage networks 

may form, resulting in the loss of 

connectivity among previously used 

corridors, potentially disrupting 

migration.

5. Increased thermokarst along 

lakeshores will cause soils to slump 

into the lakes (Prowse et al. 2006), 

expanding lake surface area and 

increasing the amount of shoreline 

habitat. Provided that lake expansion does not result in breaching 

of the lake margins, this will result 

in a slight increase in fish habitat 

availability.

Ublutuoch River during spring breakup (above) and mid-summer (below). 

Strong seasonal variation in flow regime is a characteristic of Coastal 

Plain streams that could be accentuated by climate change. Photo by 

Richard Kemnitz, Bureau of Land Management.
82

Twenty-eight species of terrestrial 

mammals live in arctic Alaska from 

the crest of the Brooks Range north 

to the Beaufort Sea (Bee and Hall 

1956, Wilson and Ruff 1999, Table 

5.3). Polar bears are usually classified as marine mammals, but, 

because they use terrestrial habitats 

for birthing dens and scavenging 

carcasses, they are included here. 

Some arctic species are restricted 

to very narrow ecological niches, 

using only one type of tundra and/

or a very specific diet; others have 

broad niches, using a wide variety 

of habitats and/or foods. Species 

vary in their geographic distributions from those that are endemic 

to northern Alaska, to those found 

worldwide throughout the northern 

hemisphere (Table 5.3). For many 

broadly distributed species, arctic 

Alaska includes the northern limit of 

their geographic range. 

Terrestrial 

Mammals

Niche breadth (number of habitats/types of food): 1=few; 2=moderate; 3=many. 

Geographic range: 1=endemic, arctic/west Alaska; 2=arctic Alaska/Canada; 3=Alaska/

northern Canada; 4=circumpolar arctic; 5=Alaska through west or south U.S.; 

6=circumpolar-boreal north to mid-latitudes; 7=most of northern hemisphere; N=northern 

extent of range. Species are grouped as in Tables 5.4, 5.5. Scientific names and ecological 

information from Wilson and Ruff (1999) and Wilson and Reeder (2005). Geographic 

distribution and other ecological information summarized from MacDonald and Cook (2008) 

and the IUCN Red List 2008 (www.iucnredlist.org).

1. Both species have been recorded on the North Slope. The range of L. othus evidently has 

contracted from the North Slope in the past century; L. americanus is known to occur today 

along the Colville River. Despite some taxomonic uncertainty, L. othus appears to be a distinct 

species (Waltari and Cook 2005).

2. Polar bears use terrestrial habitats for natal dens and scavenging carcasses.

Common name Scientific name Habitats (niche breadth) Range

Red-backed vole Myodes rutilus Forest + tundra (3) 6 

Singing vole Microtus miurus Tundra dry shrub (2) 3 N

Tundra vole Microtus oeconomus Tundra taiga moist graminods (3) 6 

Collared lemming Dicrostonyx groenlandicus Arctic tundra shrub (1) 2 

Brown lemming Lemmus trimucronatus Arctic+ subarctic graminoids (2) 4 

Snowshoe hare1 Lepus americanus Forest + tundra (3) 5 N

Alaskan hare1 Lepus othus Tundra (1) 1 N 

Porcupine Erethizon dorsatum Forest + tundra (3) 5 N

Arctic ground squirrel Spermophilus parryii Forest, tundra, meadows (3) 3 N

Alaska marmot Marmota broweri Tundra alpine rocks (1) 1 N

Dall’s sheep Ovis dalli Arctic+subarctic alpine rocks (1) 3 N

Caribou Rangifer tarandus Tundra + open woodlands (3) 6

Muskox Ovibos moschatus Tundra graminoid + shrub (2) 2

Moose Alces americanus Forest + tundra shrub (3) 6 

Barren-ground shrew Sorex ugyunak Tundra graminoid+shrub (2) 2

Tundra shrew Sorex tundrensis Forest+tundra graminoid shrub (3) 5

Dusky shrew Sorex monticolus Forest+tundra wet areas (3) 5 N

Alaska tiny shrew Sorex yukonicus Forest, riparian shrub (3) 2

Least weasel Mustela nivalis Forest, prairies, tundra (3) 6

Ermine Mustela erminea Forest, meadows, tundra (3) 6

Mink Neovison vison Streams, lakes, marshes (2) 5 N

Arctic fox Vulpes lagopus Arctic tundra and coasts (2) 4

Red fox Vulpes vulpes Forests, deserts, tundra (3) 7

River otter Lontra canadensis Rivers + lakes: fish (2) 5 N 

Wolverine Gulo gulo Forests, taiga, tundra (3) 6

Wolf Canis lupus Forests, tundra: ungulates (2) 7

Grizzly bear Ursus arctos Forests, taiga, tundra, deserts (3) 6

Polar bear2 Ursus maritimus Arctic sea ice: ice seals (1) 4

Table 5.3. Species, habitats, and geographic range of mammals found in arctic Alaska, north of the 

Brooks Range mountains. 
83

Arctic mammals can be grouped 

by diet, body size, winter survival 

strategies, and reproductive strategies (Table 5.4). Arctic mammals eat 

plants (herbivores), other animals 

(carnivores), or a mixed diet of 

plants and animals (omnivores). Terrestrial mammals range in size from 

the 10-g tundra shrew to the 600-kg 

polar bear. Arctic mammals can be 

classified as small (<0.1 kg), medium 

(0.5–10 kg), large (50–90 kg), or very 

large (>150 kg), based on the average mass of adult females (Wilson 

and Ruff 1999).

Group Common name

Group characteristics

Body size and diet Winter strategy Reproductive strategy

H1

Red backed vole

Small herbivores

<0.1 kg

Subnivian (active 

beneath snow)

Store food

Altricial offspring

Short gestation, lactation, 

parental care

Multiple medium to 

large litters

Singing vole

Tundra vole

Collared lemming

Brown lemming

H2a

Snowshoe hare Medium-sized 

herbivores 

0.5–10 kg

Active

Precocial offspring

Short to long gestation, 

lactation, parental care

Single & multiple small to 

large litters

Alaskan hare

Porcupine

H2b

Arctic ground squirrel Medium-sized 

herbivores

0.5–10 kg

Dormant in den 

(hibernation)

Fatten before denning

Use body reserves

Altricial offspring

Short to medium gestation, 

short lactation, social groups

Single small to medium litters Alaska marmot

H3

Dall sheep Large/very large 

herbivores 

(ungulates)

50–200 kg

Active

Adapted to cold & 

less food

Use body reserves

Precocial offspring

Long gestation, lactation, 

parental care

Single birth of 1–2 offspring

Caribou

Muskox

Moose

C1

Barren-ground shrew

Small carnivores

<0.1 kg

Active and/or 

subnivean

Altricial offspring

Short gestation & lactation; 

short to medium care

Single/multiple medium to 

large litters

Delayed implantation in 

mustelids (weasels)

Tundra shrew

Dusky shrew

Least weasel

Ermine

C2

Mink

Medium/large 

carnivores

0.5–45 kg

Active

Adapted to cold

Altricial offspring

Short to medium gestation & 

 lactation; short to long care

Single small to large litters

Arctic fox

Red fox

River otter

Wolverine

Lynx

Wolf

C3 

Grizzly bear Very large 

carnivores/omnivores

>200 kg

Dormant in den

Fatten before denning

Use body reserves

Altricial offspring

Delayed implantation, medium 

gestation, very long lactation 

& care

Single small litters

Polar bear

Reproductive strategies play an 

important role in the fitness of arctic 

mammals (Table 5.4). Most arctic 

mammals are blind, naked, and 

helpless (altricial) at birth and need 

shelter and parental care that can 

last from a few weeks to ≥2 years. 

In contrast, some medium-sized herbivores (e.g., hares and porcupines) 

and large ungulates (e.g., caribou, 

Dall sheep, muskoxen, and moose) 

produce more mature (precocial) 

offspring. All young mammals 

obtain their initial nutrition from 

milk produced by their mothers, and 

Table 5.4. Arctic mammals grouped by body size, diet, and life history strategies. 

Ecological information summarized from Wilson and Ruff (1999) and various authors from IUCN Red 

List 2008 (www.iucnredlist.org). 
84

lactation is a major energetic cost 

for reproductive females (Vaughan 

et al. 2000, Persson 2005). The length 

of gestation, lactation, and parental 

care ranges from a few weeks to ≥2 

years (Wilson and Ruff 1999). Most 

arctic mammals reproduce once per 

year, and litter sizes vary from 1 to 

>20. Some small and medium-sized 

mammals (e.g., shrews, lemmings, 

voles, snowshoe hares, and least 

weasels) can have >2 litters per 

year. In contrast, some very large 

herbivores and carnivores, e.g., muskoxen and grizzly bears, have few 

offspring at intervals of 2 or more 

years (Wilson and Ruff 1999).

Unlike most birds that are present 

in the Arctic only during the brief 

summer season, most mammals remain year-round. Therefore, winter 

survival strategies are critical (Table 

5.4). Arctic mammals survive the 

long winter by:

1. adapting to cold temperatures 

and low food availability and living 

in the arctic landscape year-round 

(surface active); 

2. storing food and remaining active 

in winter beneath insulating snow 

cover (subnivean); or 

3. putting on large fat reserves and 

spending the winter in dens in true 

hibernation or a torpid (dormant) 

state (Blix 2005). 

Group Mammals Winter season needs Growing season needs

H1 Microtines (lemmings 

and voles) 

Access to stored food

Hoar frost layer

Snow for insulation

Natal nests

Abundant green forage

Food to store for winter

Natal and post natal nests

Runways + escape cover

H2a Hares and porcupines

Winter forage

Shelter for offspring

Escape cover

Abundant green forage

Shelter for offspring

Escape cover

H2b Ground squirrels and 

marmots

Winter dens

Snow for insulation

Abundant green forage

Burrows for escape/sleep

Large pre-winter body reserves

H3 

Large ungulates (sheep, 

caribou, muskoxen, 

moose)

Adequate winter forage

Escape terrain (sheep)

Soft shallow snow

Abundant green forage

Escape terrain (sheep, moose)

Pre-winter body reserves

C1 Shrews and small 

mustelids (weasels)

Invertebrate/microtine prey

Natal nests

Snow for insulation

Invertebrate/microtine prey

Nests

C2 Medium/large mustelids, 

foxes, lynx, wolves

Winter prey or carcasses

Natal and/or permanent dens

Summer prey or carcasses

Dens/shelter

C3 Bears Natal and/or winter dens

Adequate snow for insulation

Access to food

Large pre-winter body 

reserves

Even species that typically migrate, 

such as caribou, move only short distances relative to most birds and are 

therefore exposed to severe winter 

conditions, requiring specific adaptations to cold and resource shortages.

The previously identified mammal 

groups (Table 5.4) also vary with 

respect to their habitat and physiological requirements for survival and 

reproduction (Table 5.5). Identification of these essential elements is a 

useful starting point for developing 

hypotheses regarding species’ vulnerability to climate-related habitat 

change. During the short growing 

season, mammals must have access 

to adequate food to replace body 

reserves lost the previous winter 

and depleted during pregnancy and 

lactation. They must also accumulate body fat to survive the coming 

winter. In winter, mammals must 

conserve energy, access stored food 

or fat reserves, and find appropriate 

shelter. Females that are pregnant 

and lactate during the winter season 

require additional body reserves and 

natal nests or dens to shelter helpless offspring. 

Table 5.5. Seasonal requirements of arctic mammals. 
85

Effects of Climate Change on Mammals 

of Arctic Alaska

Climate change will have different 

effects on arctic mammals in different seasons. Winter is the dominant 

season in the Arctic, lasting for 

8–9 months of the year. Although 

temperatures below 0°C and snow 

can occur any time of the year, these 

conditions generally exist from 

September through May. As a result 

of climate change, temperatures and 

precipitation are expected to increase, primarily in winter. Warmer 

winter temperatures will likely 

affect amounts of precipitation, the 

density and hardness of snow, and 

will likely increase the frequency of 

rain-on-snow or “icing” events. 

The growing season in the Arctic occurs from early to mid-June through 

early to mid-August. Although this is 

a relatively short period in the annual cycle, the growing season is key to 

survival. Herbivores and omnivores 

depend on the high digestibility and 

nutritional value of green plants 

to replace body reserves used up 

during the long winter, to meet the 

demands of pregnancy and lactation, 

and to fatten before the next long 

winter season. Several species, like 

muskoxen, do not breed until body 

mass reaches a minimum threshold 

(White et. al 1997).

Conceptual Models: Changes in Winter 

and Growing-season Conditions 

Two conceptual models were developed summarizing potential effects 

of changing conditions on arctic 

mammals during winter and during 

the short growing season (Figures 

5.8, 5.9). We assumed a scenario of 

increasing temperatures and precipitation, primarily in winter (Walsh 

et. al 2008, IPCC 2007). Numbered 

elements within the model are described more fully below.

Winter 

1. Warmer temperatures in winter 

will likely result in an increase in 

thaw-freeze cycles and the number of rain-on-snow (icing) events. 

Denser, harder snow and the formation of ice layers within the snow 

pack or at ground level will reduce 

accessibility to forage and increase 

energetic costs for ungulates and 

other mammals active throughout 

the winter. A severe icing event in 

October 2003 resulted in the deaths 

of thousands of muskoxen on 

Banks Island (Grenfell and Putkonen 2008). Ice layers and changes in snow structure may cause the 

loss of nests and runways and could 

decrease access to stored food used 

by subnivean herbivores. The effect of ice layers on the transportation of oxygen and carbon dioxide 

through snow is unknown, but this 

may be important for denning and 

subnivean mammals.

Figure 5.8. Conceptual model 

illustrating possible effects of 

changing conditions during the 

winter season (September–May) on 

arctic mammals. Blue text boxes 

identify physical drivers, green 

boxes identify habitat effects, and 

white boxes summarize biological 

implications of habitat change.
86

2. Deeper, harder snow will be 

energetically costly to ungulates 

and possibly some predators who 

must travel through snow or dig 

through snow to find food. Deeper 

snow could benefit some species, 

however. For example, deeper snow 

would provide additional insulation 

for denning and subnivean mammals and might create additional 

denning habitat for polar bears. 

The insulative effect of deeper 

snow will also increase winter soil 

temperatures, potentially enhancing microbial activity and nutrient 

availability for plants (see Growing 

Season below).

3. Warmer winter temperatures 

and a shorter snow season would 

result in the early emergence of 

some plants. This would provide 

early green forage and reduced 

energetic costs for some ungulates 

and possibly other species, but this 

shift could also disrupt the seasonal 

synchrony between herbivores and 

the plants upon which they feed. 

Emerging plant species have higher forage quality than do plants at 

later phenological stages (Jorgenson et al. 2002). Herbivores such 

as caribou migrate to calving areas 

and give birth when tussock sedges 

are emerging. Earlier emergence 

may result in forage of lesser quality being available during calving 

and peak lactation when nutritional 

demands reach a yearly maximum 

(Griffith et al. 2002).

4. Warmer temperatures will result 

in a shorter snow season and 

reduced snow extent in late winter. 

Earlier breakup and flooding may 

affect subnivean mammals and 

mammals in winter dens. Warmer 

temperatures will likely result in 

early emergence from winter dens 

and the subsequent death of altricial neonatal offspring like bear 

cubs, canid (wolves, foxes) pups, 

and young rodents. 

Growing Season 

1. Improved nutrient availability, 

as a result of warmer winter soil 

temperatures, could increase overall primary productivity/for age 

availability, but also may contribute 

to a shift toward a more shrubby 

environment (Sturm et al. 2005), 

with divergent effects on mammal 

populations (see below). 

2. With a longer, warmer growing 

season, plant biomass will likely 

increase, providing more forage for 

large and small herbivores, including lemmings, voles, squirrels, and 

large ungulates. In experiments, 

cool overcast summers were accompanied by lower productivity 

of grasses and forbs (Lenart et al. 

2002, Rachlow and Bowyer 1998), 

but a long-term trend toward 

warmer and drier conditions may 

result in a shift to increased shrub 

cover. Shrubby tundra and boreal 

forests are expanding northward 

Figure 5.9. Conceptual model 

illustrating possible effects of 

changing conditions during the 

growing season (June–August) 

on arctic mammals. Blue text box 

identifies physical drivers, green 

boxes identify habitat effects, and 

white boxes summarize biological 

implications of habitat change.
87

and up mountain slopes (Sturm et 

al. 2001, Danby and Hik 2007). If 

wet graminoid tundra is replaced 

by drier shrubbier tundra, singing 

voles, collared lemmings, snowshoe 

hares, porcupines, barren ground 

shrews, and moose could benefit, 

and brown lemmings, tundra voles, 

and tundra and dusky shrews may 

not. The diversity of arctic-adapted 

species will likely decline if some 

arctic habitats disappear, but 

overall diversity may increase as 

additional species shift their ranges 

northward. 

3. Warmer temperatures and a 

longer growing season will likely 

increase the abundance of invertebrates, parasites, and disease organisms that could potentially negatively affect all arctic mammals. 

For example, life cycles of protostrongylid nematodes (Umingmakstrongylus pallikuukensis in 

muskoxen and Paralaphostrongylus odocoilei and P. stilesi in Dall’s 

sheep) shorten as temperatures 

warm and the frost-free season 

lengthens, increasing the incidence 

of disease (Kutz et al. 2004, Jenkins 

et al. 2006). Increases in biting 

insects like bot and warble flies will 

likely cause stress and declines in 

body condition in caribou and other 

species (Thomas and Kilaan 1990). 

If drier summer conditions prevail, 

soil invertebrate communities will 

change; shrews would likely benefit 

if there were an overall increase in 

invertebrate abundance. 

Above: A group of muskoxen (Ovibos moschatus) on the North Slope. Although the species was extirpated from 

Alaska in the late 19th century, it was successfully reintroduced in the 20th century. Photo by Richard Flanders.

Below: A Dall’s sheep ram (Ovis dalli) in the Brooks Range. Photo by Ken Whitten.
88

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Chapter 6

Working Groups’ Summaries: 

Common Themes and 

Research Gaps 

This chapter synthesizes the 

discussions of the WildREACH 

working groups for birds, fish, 

and mammals. 
95

The working groups were multidisciplinary groups of scientists and 

multi-organization groups of managers (see Appendix 5). The working 

groups’ findings are organized into 

four sections:

Integrated Research and Monitoring. All working groups emphasized the importance of interdisciplinary studies and recognized that 

collaboration between geophysical 

and biological specialists is paramount. 

Common Themes Across Species 

Groups. Specific information gaps 

varied among species groups, but 

most fell into four crosscutting 

themes: 1) changes in precipitation 

and hydrology; 2) changes in vegetation communities and phenology; 3) changes in abundance and 

timing of invertebrate emergence; 

and 4) coastal dynamics.

Fish and Wildlife Ecology Data. All 

working groups emphasized that 

information available on life history, habitat requirements, distribution, abundance, and demography is inadequate for many arctic 

species. More complete information 

on basic life history is needed to 

refine hypotheses and improve 

our predictions regarding species’ 

response to environmental change.

Focal Species in the Context of Climate Change. All working groups 

developed a preliminary list of focal 

species perceived to be sensitive 

indicators of climate change. 

Above: Image of the Arctic 

National Wildlife Refuge and 

the Beaufort Sea acquired 

by the Multi-angle Imaging 

SpectroRadiometer’s nadir 

(vertical-viewing) camera on 

August 16, 2000, during Terra 

orbit 3532. The area represented 

by the image is approximately 

380 km x 540 km. Image Credit: 

NASA/GSFC/LaRC/JPL, MISR 

Team.

Below: Arctic grayling 

(Thymallus arcticus) have highly 

variable life history strategies 

depending on location. Some 

populations are highly migratory 

while others are relatively 

sedentary. Wikimedia Commons 

photo.
96

We cannot accurately predict the effects of climate change on organisms 

without sufficient information about 

the underlying biological and physical processes that drive terrestrial 

and aquatic ecosystem functions 

(Wrona et al. 2006). Acquiring this 

understanding will require additional effort in three complementary 

areas:

1. Long-term monitoring of physical 

and biological parameters;

2. Field observations and focused 

process studies to clarify the mechanisms by which environmental 

variables influence fish and wildlife 

populations; and

3. Interdisciplinary synthesis modeling.

This approach is consistent with that 

proposed by Vörösmarty et al. (2000) 

in their assessment of the needs for 

developing a synthetic understanding of the arctic hydrologic cycle. 

The strong linkages and feedbacks 

between climate, permafrost, hydrology, and habitat conditions highlight 

the critical need for comprehensive, 

cross-disciplinary monitoring and 

research programs. Integrated longterm data sets from representative 

locations are needed to test hypotheses regarding the mechanisms by 

which climate affects habitat conditions and to parameterize models of 

landscape change. Similarly, moving 

toward more specific predictions 

regarding specific fish and wildlife 

responses to habitat change will require both long-term monitoring and 

focused research approaches. 

Long-term data sets are particularly 

scarce in Alaska, where organized 

scientific programs are recent, and 

access to remote areas is difficult 

and expensive. Initial investment 

should be placed in “rescue” and assembly of legacy data to be used for 

retrospective analyses. These data 

sets may be limited by resolution 

and spatial scale; however, they may 

provide valuable insights into:

1. the extent, spatial scale, and intensity of monitoring efforts necessary 

to develop efficient and relevant 

approaches for long-term data collection and modeling needs,

2. mechanisms of change and their 

relative importance to fish and 

wildlife populations, and

3. additional gaps in data not addressed during this workshop.

Future approaches should include 

establishment of integrated longterm data sets at multiple scales. 

Satellite-based remote sensing approaches are essential for assessing 

attributes such as snow cover, greenup, and surface water on a regional 

scale. Processing and archiving 

these data sets in a readily usable 

form will require multi-agency coordination. At an intermediate scale 

(e.g., watershed), high-resolution 

satellite or aircraft-mounted sensors 

can provide elevation data for digital 

elevation models or detailed stream 

and landcover mapping. These remote sensing efforts combined with 

spatial and retrospective analyses 

will better inform planning efforts 

for costly long-term monitoring and 

process studies conducted on the 

ground. Cost considerations will 

likely limit ground-based efforts to 

relatively few sites, thus careful site 

selection will be important.

Multidisciplinary monitoring programs, integrated with research, 

will provide the best opportunity 

for developing a mechanistic understanding of climate-related habitat 

change. In this framework, intensive 

in situ research and monitoring 

would be scaled up to the landscape 

and regional level through modeling 

informed by remote sensing technologies. Monitoring and research 

should include replication across 

dominant environmental or ecological gradients using a distributed 

network of sites that are sampled at 

a lower intensity.

There are some existing long-term 

monitoring efforts on the North 

Slope of Alaska, which provide a 

limited foundation and baseline data 

for an integrative approach to longterm monitoring of fish, wildlife, and 

key environmental variables. For 

example, existing facilities at Toolik 

Lake and Barrow should serve as 

“flagship observatories” (Shaver et 

al. 2004) around which a research 

and monitoring program could be 

built. An essential element of an 

observatory is a sustained observational time series consisting of measurements of a core set of environmental variables. The Arctic Long 

Term Ecological Research (LTER) 

site at Toolik Lake provides the best 

example of integrated monitoring 

in northern Alaska (http://ecosystems.mbl.edu/ARC/Datatable.html, 

retrieved April 10, 2009), but data 

pertaining to higher trophic-level organisms are largely absent from the 

existing program, with the exception 

of freshwater fish. Suitable models 

for integration of fish and wildlife 

Need for 

Integrated 

Research and 

Monitoring
97

monitoring with environmental data 

exist, however, at sites such as Zackenburg Research Station, northeast 

Greenland (Meltofte et al. 2008). 

The National Park Service’s Arctic 

Network Inventory and Monitoring Program provides an example 

that emphasizes the use of fish and 

wildlife as “vital sign” indicators 

of ecosystem function (http://science.nature.nps.gov/im/units/arcn/, 

retrieved 10 April 2009). These 

existing programs provide useful 

models, but data collection at the 

temporal and spatial scale necessary 

to effectively address climate change 

issues will require implementation 

of monitoring at multiple sites, and 

strong collaboration among federal, 

state and local agencies, academic 

institutions, conservation organizations, and private industry.

Much of the uncertainty in projecting future habitat conditions stems 

from an insufficient understanding of arctic hydrologic systems. 

In the Arctic, the thermal and 

hydrologic regimes are uniquely 

linked through changes in the active 

layer (the ground layer that experiences seasonal freeze and thaw), so 

coordinated study of the coupling 

between permafrost dynamics, soil 

moisture, and ecological systems is 

fundamental to predicting the extent 

and magnitude of habitat change. 

High priority must be placed on 

establishing a distributed network 

of watershed-based study sites to 

collect data essential to improved 

synthesis modeling of environmental 

change. A proposed set of measurements for hydrological study sites 

(modified from Vörösmarty et al. 

2000) is provided in Box 6.1. Some of 

these parameters have been measured in the Kuparuk River watershed, beginning as early as 1985. We 

recommend establishing a long-term 

hydrological observatory within the 

Kuparuk River watershed and at 

least two additional watersheds to 

better represent variability across 

the North Slope. Data obtained at 

hydrologic observatories will be 

instrumental in creating predictive 

models that will help land managers better understand and manage 

fish and wildlife habitat in a rapidly 

changing climate.

Because climate modelling forms 

the basis for projections of habitat 

change, continued effort to improve 

the reliability of down-scaled climate 

models is crucial, and would likely 

benefit from an expanded network of 

Box 6.1. Examples of the coordinated set of measurements 

that might be made at an arctic hydrologic observatory study 

site. After Vörösmarty et al. (2000). 

Hydrologic and other geophysical measurements

• Precipitation amount (year round)

• Evapotranspiration and sublimation

• Solar flux and surface energy measurements

• Snow pack

• Snow redistribution

• Snow melt

• Soil thermal properties and their variation

- Temperature profiles

- Active layer depth

- Permafrost temperature

- Thermal conductivity

• Infiltration on frozen and unfrozen soils

• Soil moisture

• Runoff flow paths

• Stream and large river discharge

• High-resolution and accurate digital elevation models

• Distribution of surface waters, including seasonal flooding and 

connectivity between lakes and rivers

• Timing of freeze-thaw cycles

Biological and biogeochemical measurements

• Precipitation chemistry

• Vegetation surveys (ecotype maps and community composition)

• Soil mapping, including ice content

• Monitoring of vegetation, soil, and groundwater chemistry

• Physical, chemical, and biological parameters in stream, river, 

and lake ecosystems

• Isotope and other tracers for discharge entering the Arctic Ocean

meteorological stations with coordinated data storage and analysis. 

In considering climate effects, we 

are constrained to some degree by 

the ways in which we aggregate 

data. Projections of future climate 

conditions tend to focus on metrics 

describing annual or seasonal averages. While practical and often useful, evaluation of potential climate 

change effects based solely on average conditions overlooks the importance of extreme events on fish and 

wildlife populations. For instance, 

events such as rain-on-snow in 

winter (which have killed thousands 

of muskoxen and caribou) and major 

floods in summer (which have killed 

dozens of muskoxen, and likely caribou and moose) have a potential to 

devastate populations if they occur 

with increased frequency. Greater 

attention must be paid to modeling 

variability in climate conditions. 

Similarly, conditions during the seasonal transition periods (spring thaw, 

freeze-up) can be more critical for 

fish and wildlife populations than the 

relatively stable mid-winter or summer periods. Greater consideration 

of the key issues related to seasonal 

transitions is warranted.
98

Although climate change effects will 

differ among species and among 

taxonomic groups, a common set of 

environmental drivers and processes 

will affect habitat suitability for a 

broad suite of species. Four major 

themes emerge as relevant to a 

diversity of fish and wildlife species 

groups:

1. Hydrologic processes, including 

precipitation, water balance, and 

distribution of surface water;

2. Vegetation, including community 

composition and phenology;

3. Invertebrates (primarily aquatic 

or semi-aquatic forms), including 

productivity and phenology; and

4. Coastal dynamics, including the 

interacting effects of erosion, 

sedimentation, stream discharge, 

inundation, and plant successional 

processes.

Within these four general areas, 

there are specific needs for improving understanding of the physical 

processes that drive habitat change 

and the associated ecological responses, summarized in Table 6.1 

and further elaborated below.

Hydrologic Processes: Precipitation, 

Water Balance, and Distribution of 

Surface Water

Understanding water balance and 

partitioning of water among habitat 

units is a key issue, with important 

direct and indirect implications 

across all fish and wildlife taxa. The 

changes associated with the proCommon 

Themes Across 

Species Groups

jected wetter and warmer winter 

environment will have important 

implications for resident mammals (see below) but minimal direct 

consequences to birds because 

most are migratory and absent in 

winter. For arctic fish populations, 

overwintering habitat availability 

is currently limiting, and a warmer, 

wetter winter environment would 

most likely relax that constraint. 

The consequences of a hypothetical 

summer drying regime, however, are 

perceived as a greater threat to fish 

and birds. High priority is assigned 

to addressing the following questions:

• How reliable are the projections 

for increasing precipitation and 

evapotranspirtion?

• How will the annual precipitation 

input on the Coastal Plain and 

Foothills be allocated between winter (snow pack) and summer?

• How will changes in precipitation, 

evapotranspiration, and active 

layer depth alter summer surface 

water availability in shallow-water 

and mesic/wet tundra habitats?

• How will changing patterns of seasonal runoff affect stream flow? 

• What is the contribution of 

groundwater in various systems, 

and is it sufficient to maintain yearround flow? 

• Will drought conditions and changes in drainage patterns decrease 

water body connectivity?

Lakes may be susceptible to draining as a result of newly developed 

thermokarst drainage networks, 

thus:

• Which Coastal Plain lakes are 

susceptible to draining and on what 

time scale?

Increasing temperatures and precipitation in winter will affect food 

acquisition and energy balance of 

non-denning and subnivean mammals. For mammals, the quantity 

and nature of winter precipitation 

is of paramount interest, with a 

particular focus on the following 

questions:

• What are expected changes in 

snowpack characteristics (depth, 

density, presence of ice layers) and 

how might these vary on a regional 

and local scale?

• How much change will occur in 

the timing of snow melt and snow 

onset?

• How will the frequency of rainon-snow and severe winter storm 

events change?

A collared lemming (Dicrostonyx groenlandicus) in a subnivean runway. 

Lemmings spend the majority of the year in subnivean spaces, and the 

characteristics of the snowpack are likely to be critical to their survival and 

reproduction. Photo by Jean-Louis Klein and Marie-Luce Hubert. 
99

Vegetation Community Change

Changes in vegetation have important implications for several ecosystem processes. Vegetation exerts an 

important influence on soil moisture 

and temperature, active layer thickness, and permafrost stability, and 

vice versa. Changes in both plant 

phenology and the relative abundance of forage species will affect 

the palatability, nutritional quality, 

and quantity of available food for 

herbivores (primarily mammals in 

arctic Alaska). Changes in primary 

productivity will directly affect the 

carrying capacity of habitat for 

aquatic and terrestrial herbivores, 

and indirectly affect higher trophic 

levels. Vegetation is a primary component of habitat structure, which 

may affect suitability for some species independent of trophic effects. 

Vegetation change will affect fish 

indirectly, primarily through exTable 6.1. Pathways by which climate-influenced habitat change could influence arctic fish and wildlife, 

categorized by major themes. 

Theme Habitat Change Pathway Affected Species 

Groups

Water: Precipitation, water 

balance, and distribution of 

surface water

Lake drainage due to development of new drainage networks Birds, Fish

Drying of shallow-water and mesid/wet tundra habitats Birds

Changes in flow regimes, as influenced by water source Fish

Drought-related loss of connectivity between water bodies Fish

Change in snowpack characteristics, e.g., depth and density Mammals

Change in the length and timing of the snow season Fish, Mammals

Change in the frequency and timing of extreme events, i.e., rainon-snow events and major winter storms Mammals

Changes in aquatic trophic systems, including potential shift 

from benthic to pelagic production in lakes Birds, Fish

Vegetation: Seasonality and 

community composition

Change in plant phenology, accompanied by change in the timing 

of forage nutritional quality Birds, Mammals

Change in plant community composition: 

−Change in forage quantity and quality, at community level Birds, Mammals

−Shrub expansion Birds, Mammals

−Paludification and consequences for both herbivore and 

detritus-based trophic systems Birds

Increased primary productivity of terrestrial vegetation and 

export of nutrients into aquatic systems Fish

Change in riparian vegetation, as influenced by flow regime and 

frequency/severity of flooding Birds, Fish, Mammals

Invertebrates: Phenology and 

abundance

Change in productivity, abundance, and seasonality of life cycles 

for aquatic and semi-aquatic invertebrates Birds, Fish

Change in timing of emergence and abundance of biting insects, 

parasites, and disease vectors Mammals

Coastal Dynamics: Interactions 

of coastal erosion/deposition, 

river discharge, sedimentation, 

inundation, succession

Degradation of barrier island systems and alterations to physical/chemical environment of lagoons Birds, Fish

Increased fog/clouds and subsequent effects on evapotranspiration, snow melt, and plant phenology Birds, Mammals

Change in availability of coastal habitats, specifically coastal wet 

sedge and deltaic mud flats Birds, Mammals

Change in availability of deep-channel habitat in major river 

deltas Fish

port of terrestrial productivity into 

the aquatic system in the form of 

leaves and insects. This input could 

increase with increased floodplain 

shrub growth, with potential implications for invertebrate community 

composition and productivity. Shoreline stability and water temperature 

is also influenced by the vegetation 

adjacent to water bodies. For birds 

and mammals, the influence of 

changing vegetation communities is 

more direct, with the following issues considered highest priority:

• How will changes in temperature 

and precipitation affect plant 

community composition, including changes in habitat structure 

and nutritional quality of available 

forage (i.e., digestibility, nutrient 

content)?

• What is the expected rate of shrub 

increase, and how will this vary by 

species/growth form (low vs. tall 

shrub) and ecoregion? 
100

• How will changes in the length 

and timing of the growing season 

influence plant phenology, including seasonal changes in nutritional 

quality?

• What is the likelihood of widespread conversion from sedge 

and sedge-shrub meadow to bog 

meadow (paludification), and how 

would this affect herbivore and 

detritus-based trophic systems?

• How will changes in the seasonality of stream discharge and occurrence of flood events influence 

development of riparian vegetation 

communities? 

Invertebrate Populations: Temperature 

and Seasonality Influences

Most species of birds and fish in 

arctic Alaska are predators of 

aquatic and semi-aquatic macroinvertebrates (e.g., insects, crustaceans, gastropods) and are therefore 

vulnerable to changes in productivity, abundance, and seasonality of life 

cycle stages. This is an exceptionally 

poorly studied aspect of arctic ecology, and experimental research and 

monitoring efforts to address the 

following areas are a high priority:

• How does earlier spring thaw 

affect timing of invertebrate life 

cycle events and peak availability 

to predators?

• How does temperature affect 

growth and development of aquatic 

insects?

• What climate-related changes are 

likely in community composition of 

macroinvertebrates in stream, lake, 

and saturated soil environments?

• How will changes in the distribution and quality of surface waters 

and shifts from pelagic to benthic 

productivity in deep lakes affect 

availability of macroinvertebrates 

to fish and wildlife? 

For most mammals, invertebrates 

are more important in their role as 

parasites and vectors of disease, 

rather than prey. Related priority 

questions include:

• How will warming and changing seasonality affect abundance 

and peak activity periods of biting 

insects, and what are the bioenergetic consequences for caribou?

• How will warming and changing 

seasonality affect the prevalence of 

parasites and disease vectors (e.g., 

nematode parasites of muskoxen 

and Dall’s sheep)? 

Coastal Dynamics

Loss of summer sea ice, increased 

coastal erosion, rising sea level, 

warmer ocean waters, changing 

seasonality of river discharge, and 

altered sedimentation rates interact 

to affect coastal habitats. Coastal 

lagoons of the Beaufort and Chukchi 

seas are important summer feeding habitat and migration corridors 

for birds and fish, while deltas and 

coastal wet sedge tundra are important foraging habitats for shorebirds 

and waterfowl. Although coastal 

habitats are dynamic by nature, climate change may cause directional 

change that alters the availability 

of some habitats. Related priority 

questions include:

• Will higher water temperatures, 

sea level rise, and retreat of summer sea ice cause degradation of 

the barrier island systems of the 

Beaufort and Chukchi seas?

• Will alluvial deltas continue to 

build or will rising sea levels outpace potential increases in sedimentation rates?

• How quickly will shoreline retreat 

result in newly breached lake 

basins? 

• To what extent will coastal erosion, in combination with sea level 

rise, cause salinization of low-lying 

coastal areas?

• Will coastal wet sedge meadows 

establish at a rate equal to loss of 

this habitat through erosion and 

inundation?

A longer ice-free season will strongly influence climate in the coastal 

zone. A longer open water season 

may increase the prevalence of fog, 

which will have a cooling effect in 

spring while a warming effect in fall. 

• Will increased fogginess/cloudiness exert a negative or positive 

feedback effect on air temperature 

in the coastal zone? What would be 

the expected spatial extent of this 

effect?

The USFWS has determined 

that listing the yellow-billed loon 

(Gavia adamsii) as a threatened or 

endangered species is warranted 

under the Endangered Species 

Act, but that listing is precluded 

by other higher priority species. 

The “warranted but precluded” 

finding was published in the Federal 

Register on March 25, 2009. The 

yellow-billed loon is now designated 

as a candidate species. Photo by Ted 

Swem, USFWS.
101

With the exception of a few wellstudied species, such as caribou, our 

knowledge of life history, habitat 

requirements, distribution, abundance, and demography is incomplete or poor for most arctic species; 

additional basic biological data are 

needed for all but the most general 

forecasts regarding species response 

to a warming climate. Because the 

region is remote, basic knowledge of 

status and distribution is often inadequate, as illustrated in the following 

examples:

• Little is known about the distribution and natural history of the 

Alaska marmot, an alpine-adapted 

species that has a limited and disjunct population.

• The Alaska Tiny Shrew is a newly 

described species (discovered 

in 1997) with only a few dozen 

specimens collected to date, two of 

which are from the North Slope.

Fish and 

Wildlife 

Ecology

• Spawning and overwintering areas 

are known for some populations of 

Dolly Varden in the eastern North 

Slope and broad whitefish in the 

Teshekpuk Lake region, but the 

extent of inter-drainage movement 

and the habitats used at different 

life stages for these and other species are poorly known.

• Little is known about the factors 

that limit Pacific salmon populations on the North Slope and the 

potential for range expansion into 

arctic waters.

• Knowledge of bird distribution is 

heavily biased toward the coastal 

areas, with very sparse data from 

the Foothills and northern Brooks 

Range, particularly west of the 

Dalton Highway.

• Habitat models that reliably 

predict bird species occurrence 

and/or abundance on the basis of 

measurable habitat parameters are 

lacking.

Alaska marmots (Marmota broweri) are endemic to mountains north of the Yukon River (Gunderson et al. 2009); 

evidence suggests that these highly social animals hibernate in groups. Photo by Jake Schaas, Toolik Field Station.
102

Cost constraints and practicality 

argue for conducting biological and 

life history investigations on focal 

species or related species groups, 

chosen on the basis of criteria that 

includes consideration of climate 

impacts; this topic is explored below.

Because species respond individualistically to climate drivers, it is 

expected that novel assemblages of 

species will arise. Given the difficulty 

inherent in predicting the composition of new species assemblages, 

consideration of interspecific interactions is largely deferred, except 

at the broad level of trophic dynamics. In specific instances, however, 

observed changes in other arctic 

regions suggest promising avenues 

for investigation:

• In most portions of the Arctic, 

lemming populations exhibit 

strong cyclicity, but observations in Eurasia over the past few 

decades indicate that lemming 

cycles are becoming less regular 

and of lesser amplitude (Ims and 

Fuglei 2005, Kausrud et al. 2008). 

A breakdown in the cyclicity of 

population highs could influence 

nutrient cycling, plant community 

composition, avian and mammalian 

predator population dynamics, 

and productivity of shorebirds and 

waterfowl. It is not known whether 

lemming population dynamics in 

arctic Alaska are similar to those 

reported from Eurasia.

• The Fennoscandian population 

of arctic fox is considered endangered (Angerbjörn et al. 2008). 

Competition with red fox, along 

with the influence of warming on 

prey (lemming) availability, has 

been suggested as contributing to 

the non-recovery of this arctic fox 

population (Frafjord 2003, Killengreen et al. 2006). Anecdotal 

evidence from northern Alaska 

documents interspecific competition (Pamperin et al. 2006) but is 

insufficient to demonstrate broadscale displacement of the arctic 

fox. The relative abundance of the 

two species may be a useful early 

indicator of a climate related shift 

in predator-prey dynamics.

The arctic fox (Vulpes lagopus), found across the circumpolar Arctic, is an important predator of small mammals 

and birds in summer and ranges out onto the sea ice in winter. Photo by Ken Whitten.
103

Developing a better understanding of the physical processes that 

influence ecosystem function is an 

essential foundation for managing 

fish and wildlife populations affected 

by climate change. Basic biological information, however, such as 

seasonal habitat requirements, is 

deficient for many species. Understanding the response of arctic 

fish and wildlife to climate change 

requires improved understanding of 

physical and ecological processes, as 

well as enhanced knowledge of natural history and population ecology of 

arctic species. 

Practical considerations dictate that 

resource management agencies 

choose a subset of species to actively 

study and manage—traditionally, 

those species whose numbers have 

or will decline without management 

intervention or which have significant public recreational or commercial value. Choosing these “focal 

species” is a challenging task, best 

undertaken in a structured fashion 

based on objective criteria. In the 

context of the Fish and Wildlife 

Service’s “Strategic Habitat Conservation” approach, it has been suggested that these criteria reflect the 

importance of the species relative to 

its ecological significance, management significance, legal mandates, 

and feasibility of implementing 

long-term, landscape-based adaptive 

management.

Choosing Focal 

Species in the 

Context of 

Climate Change

Above: Both species of phalarope found in northern Alaska —red phalaropes (Phalaropus fulicarius) and rednecked phalaropes (Phalaropus lobatus)—may be good indicator species for climate change effects. Photo by 

Stephanie Clemens, USFWS.

Below: This polar bear (Ursus maritimus) ranged about 125 miles inland along the Dalton Highway in October 

2002 before returning to the coast. Photo by Richard Flanders.
104

Climate change adds complexity to 

the process of selecting focal species. 

While existing lists (e.g., endangered species listing, NatureServe 

heritage ranking, International 

Union for Conservation of Nature 

[IUCN] Red List) reflect population 

response to past events, consideration of climate change forces us 

to consider a future in which over 

40% of species are at risk of extinction globally (IPCC 2007), and the 

arctic tundra region may experience up to 74% turnover in species 

assemblage (Lawler et al. 2009). 

Intrinsic life history traits that may 

be associated with greater extinction 

risk in a changing climate may be 

incorporated into a ranking process 

(Foden et al. 2008). An example of an 

application of this approach to arctic 

terrestrial mammals is provided in 

Box 6.2. While a valuable first step, 

this approach does not incorporate 

specific projections of habitat change 

on a local or regional scale. 

The uncertainties surrounding scenarios of climate-associated habitat 

change exacerbate the difficulties in 

choosing appropriate focal species 

for conservation planning. Our approach has been to develop hypotheses regarding projected habitat 

change in the form of conceptual 

models (Chapter 5). For each model, 

we have proposed reasonably foreseeable fish and wildlife responses. 

Here, we propose monitoring priorities based on selection of species/

parameters believed to be sensitive indicators of the hypothesized 

habitat changes (Table 6.2). The 

resulting list includes both common 

and rare species—some that would 

benefit from a warming climate and 

some for which negative effects are 

postulated. In this framework, focal 

species are selected, at least in part, 

on the basis of their perceived value 

as tests of specific models of habitat 

change. This list should be considered preliminary and should be 

refined through a further structured 

decision-making process. A second 

additional criterion to consider when 

refining selection of focal species 

is the timescale on which different 

processes of change occur. Some 

processes will alter habitats relatively quickly, while others operate 

on much longer timescales (Table 

6.3). As the priority list develops, it 

may be necessary to add or remove species. The process must be 

undertaken in full awareness that 

initial projections of future habitat 

condition may be inaccurate (thus 

understanding of species’ vulnerability limited), but this should not 

deter us from initiating biological 

monitoring. As data are collected 

and synthesized, conceptual models 

can be adjusted to reflect changes 

in our understanding or changes in 

processes and species/environmental 

responses.

A common eider (Somateria mollisima) sits on her nest on a barrier island. 

Common eiders breed colonially, and females commonly return to their 

natal islands. Current evidence suggests that the existing system of barrier 

islands in northern Alaska may deteriorate or diminish in a relatively 

short time frame. Photo by James Zelenak, USFWS.
105

Box 6.2. Ranking arctic terrestrial mammals by resilience to climate change

Effects of climate change on terrestrial mammals of the Arctic depend 

on the individual species’ relative vulnerability or resistance to change 

(resilience). Resilience is a function of geographic distribution and niche 

breadth. Mammals that have a broad 

geographic range, are habitat generalists, and/or eat a variety of foods are more 

likely to survive changing environmental 

conditions than those that are highly specialized for the current arctic environment 

and are found only in the circumpolar 

north or in northern Alaska. For example, 

an endemic species like Alaska marmots 

that occurs only in northern and central 

Alaska is more likely to be adversely affected by climate change than red-backed 

voles, which live throughout Alaska and 

northern Canada. Arctic-adapted species 

like polar bears, muskoxen, and arctic 

foxes are more vulnerable to warming 

temperatures than species like grizzly bears and red foxes that are found 

throughout the northern hemisphere in a 

variety of habitats (see Table 5.3). Montane species (e.g., Alaska marmots, Dall’s 

sheep) may be particularly vulnerable to 

changes occurring along elevational gradients that essentially shrink their available 

habitat. 

In contrast, species like moose that are 

broadly distributed and have recently 

expanded their distribution into the Arctic 

likely have an advantage as temperatures 

warm. We estimated relative resilience 

scores for representative species living in 

the Alaskan arctic based on geographic 

range, niche breadth, population status, 

and life-history strategies (Table). Our results suggest that polar bears and Alaska 

marmots are likely to be most vulnerable 

to expected changes in climate.

Arctic mammals sorted by their relative 

vulnerability to climate change. An index 

of relative resilience was calculated 

from world-wide geographic range 

(Table 5.3), breadth of ecological niche 

(Table 5.3), status under the Endangered Species Act and IUCN Red List 

(1=threatened, 2=of least concern) and life history strategies (1=low 

reproducing carnivores [bears], 2=low reproducing herbivores [ungulates 

and porcupines], 3=moderate reproducing carnivores [shrews, mustelids, 

canids, felids] and herbivores [squirrels], and 4=high reproducing 

herbivores [microtines and hares]). Polar bears were the only species 

considered threatened; wolverines are listed as “near threatened” under 

IUCN criteria, but Alaska populations are not threatened. 

Group Species

Index of 

potential 

resilience

C3 Polar bear7

H2b Alaska marmot7

H3 Dall sheep8

C1 Barren-ground shrew9

H1 Collared lemming9

H2a Alaskan hare9

H3 Muskox 9

C2 Arctic fox 11

H1 Singing vole 11

H2b Arctic ground squirrel 11

C2 Mink 12

C2 River otter 12

C2 Lynx 12

C3 Grizzly bear 12

H1 Brown lemming 12

H2a Porcupine 12

H3 Moose 12

C1 Tundra shrew 13

C1 Dusky shrew 13

H3 Caribou 13

C2 Least weasel 14

C2 Ermine 14

C2 Wolverine 14

H2a Snowshoe hare 14

C2 Red fox 15

C2 Wolf 15

H1 Red backed vole 15

H1 Tundra vole 15

Less resilient More resilient
106

Species or 

Species Group

Parameter to 

Measure

Projected Change in 

Habitat

Positive 

or 

Negative 

Effect

Rationale for Response to Projected 

Habitat Change

Birds

Yellow-billed loon Distribution, 

fledging success

Changes in fish 

availability, lake 

drainage

+ or - Warming lakes could increase 

productivity, but loss of connectivity 

could inhibit fish migration

Pacific loon Fledging success Increased productivity 

in warmer lakes +

Warming could improve availability 

of macroinvertebrates fed to chicks; 

longer ice-free season allows more 

time to fledge

Red phalarope, 

pectoral 

sandpiper

Abundance, 

distribution

Drying of wet 

sedge meadow - Loss of preferred foraging habitat and/

or decreased food availability

Red-necked 

phalarope

Abundance, 

distribution

Drying of wet sedge 

meadow, increased 

thermorkarst

+ or -

Loss of preferred foraging habitat in 

lowlands (drying of wet sedge meadow), but increased thermokarst could 

allow expansion into upland areas

Geese (black 

brant, greater 

white-fronted)

Gosling growth rates Change in plant 

phenology - Growth rates are sensitive to forage 

quality during the fledging period

Shorebirds

Timing of arrival and 

nesting; 

chick growth and 

survival

Change in timing of 

aquatic insect life cycle 

stages -

Potential trophic mismatch if timing of 

shorebird migration and nesting does 

not match temperature-regulated timing of insect abundance

Perching birds 

(sparrows. warblers, etc.)

Abundance, 

distribution Increased shrubbiness +

Shrub-associated species will expand 

their range and local abundance as 

shrubs increase

Common eider Abundance, 

nest success

Loss of barrier islands, 

increased storms -

Reduced availability of gravel islands 

limits nesting habitat and/or increased 

frequency of storm overwash increases nest loss 

Long-tailed duck

Abundance and 

distribution during 

molt stage

Change in lagoon 

systems - Loss of barrier islands reduces availability of habitat for resting and 

disrupts trophic system of lagoons

Fish

Arctic grayling

Growth rate, 

productivity, age at 

maturity, withindrainage distribution

Increased water 

temperature 

(associated with 

availability of food)

+ (until 

upper 

lethal 

temperature is 

reached)

Sensitive, ubiquitous

Broad whitefish 

Growth rate, productivity, age of maturity, within-drainage 

distribution

Increased water temperature; loss of waterbody connectivity - Fish passage will depend on 

connectivity between lakes, small 

streams, and other habitats

Dolly Varden Population estimates

Increased water 

temperature; habitat 

fragmentation - High site fidelity; specific habitat 

requirements

All salmon Regional distribution Increased water 

temperature + Assume that expansion of range would 

have a positive effect

Arctic char and 

lake trout Regional distribution

Changes in water 

quality and increasing 

temperatures - Perhaps narrow range of temperature 

tolerance

Aquatic insects/

invertebrates

Species abundance and 

composition

Changes in water 

quality; changes in pH 

(resulting from acidification of terrestrial 

habitats) 

 + or - Rapid changes in response to 

environmental changes; easily 

sampled

Table 6.2. Proposed indicators of climate change effects on fish and wildlife.

Continued next page
107

Species or 

Species Group

Parameter to 

Measure

Projected Change in 

Habitat

Positive 

or 

Negative 

Effect

Rationale for Response to Projected 

Habitat Change

Mammals

Polar bear Use of onshore 

habitats/denning 

Loss of summer sea ice 

and principle prey - Shift in distribution, decline in 

abundance are likely to occur as sea 

ice disappears 

Alaska marmot Distribution, 

life history Loss of alpine habitats - Limited distribution; little is known 

about this endemic species that has a 

limited and disjunct population

Dall’s sheep Trends in abundance, 

distribution

Loss of alpine habitats; 

more rain-on-snow 

events, deeper snow, 

warmer summers

- Higher energetic costs, more parasites 

and diseases, changes in plant phenology and communities 

Muskox Trends in abundance, 

distribution

More rain-on-snow 

events, deeper snow, 

warmer summers, 

more shrubs

-

Arctic-adapted species lives in arctic 

Alaska year-round. Less access to 

winter forage, higher energetic costs, 

more diseases and parasites may 

offset positive aspects of increasing 

summer biomass

Caribou Trends in abundance, 

distribution

More rain-on-snow 

events, deeper snow, 

warmer summers, 

fewer lichens, changes 

in plant phenology and 

community structure

-

Less access to winter forage, loss of 

lichens from increased fire or competition with other vegetation, timing of 

migration uncoupled from optimal 

foraging, more insect harassment, 

parasites, and diseases, and increased 

energetic costs may offset positive 

aspects of increases summer biomass

Lemmings and 

barren ground 

shrews 

Distribution and 

relative trend 

Changes in distribution 

and population cycles + or -

Arctic-adapted species likely to be affected by changes in food and shelter; 

important in food webs; little known 

about barren ground shrews (may be 

difficult to study)

Arctic fox Distribution and 

relative trend 

Changes in abundance 

and distribution -

Arctic-adapted carnivore; possible competition with red foxes and disappearance of sea ice may affect distribution 

and abundance; important predator 

of birds.

Table 6.2. Continued

Timeline Process

Annual to decadal

Erosion, construction, and migration of barrier islands

Ecosystem phenology and productivity

Expansion of lake shorelines (due to erosion)

Thermokarst, pond formation, and gully formation

Decadal to century

Change in fire regime

Change in species composition

Change in length of ice-free season

Change in sea-surface temperatures

Lake tapping

Shrub advance

Century to millennial

Formation of a thaw lake plain

Loss of continuous permafrost

Stabilization of drained lake basin

Re-establishment of polygonal terrain

Unknown

(decadal to millennial)

Paludification

Table 6.3. Relative timeline of climate-driven processes of change.
108

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An arctic ground squirrel (Spermophilus parryii) emerges from his burrow in spring after hibernating for more 

than six months underground. Photo by Øivind Tøien.
110

Chapter 7

Conclusions and 

Recommendations

Land and resource managers 

know that climate change will 

strongly affect the future 

landscape of America’s 

Arctic. Under a mid-range 

carbon emissions scenario, 

mean annual air temperature 

for the North Slope is projected 

to rise ~7°C by the end of the 

century, and precipitation is 

projected to increase by up to 

50% in coastal areas. Despite 

the expected increase in precipitation, warmer summers are 

expected to result in significant 

drying.
111

Arctic aquatic and terrestrial 

habitats are shaped by the complex 

interactions among climate, soils, 

permafrost, hydrology, and vegetation. Arctic habitats are among the 

most sensitive to warming because 

of the pivotal role played by permafrost, which can only persist at low 

temperature. Some arctic-adapted 

species will respond to habitat 

change through range shifts, but 

other species may be vulnerable to 

extirpation from the North Slope if 

suitable refugia are not available.

Climate change requires that managers of arctic species and landscapes anticipate the future condition of habitats and populations, 

but they cannot do this at present 

because too little is known about the 

linkages between climate, habitat, 

and organisms. Global Circulation 

Models, down-scaled to the North 

Slope region, are beginning to paint 

a clearer picture of the magnitude of 

climate change that may be expected 

within the century; these projections, however, are subject to large 

uncertainty. Our ability to translate 

climate change projections into 

specific forecasts of habitat condition 

is currently rudimentary. Indeed, it 

is not yet possible to link climate scenarios to fish and wildlife population 

status with the level of confidence 

needed to support development and 

implementation of conservation 

plans.

The WildREACH workshop and 

related discussions have identified 

important scientific priorities and 

activities required to improve our 

ability to forecast—and thus 

respond to—climate change effects 

on arctic fish and wildlife. 

The Porcupine caribou herd (Rangifer tarandus) crosses the 1002 area of the Arctic National 

Wildlife Refuge. Photo by Chuck Young, USFWS.

A male spectacled eider (Somateria fischeri) near Barrow; the species is 

listed as threatened under the Endangered Species Act. Photo by Ted Swem, 

USFWS.
112

1. Precipitation, Water Balance, and 

Distribution of Surface Water 

a. How reliable are the projections 

for increasing precipitation and 

evapotranspiration?

b. How will the annual precipitation input on the Coastal Plain 

and Foothills be allocated between 

winter (snow pack) and summer?

c. How will changes in precipitation, 

evapotranspiration, and active 

layer depth alter summer surface 

water availability in shallow-water 

and mesic/wet tundra habitats?

d. How will changing patterns of 

seasonal runoff affect stream flow?

e. What is the contribution of 

groundwater in various systems, 

and is it sufficient to maintain yearround flow? 

f. Will drought conditions and changes in drainage patterns decrease 

water body connectivity?

g. Which Coastal Plain lakes are susceptible to tapping (rapid drainage) 

and on what time scale?

h. What are the expected changes in 

snowpack characteristics (depth, 

density, presence of ice layers), and 

how might these vary on a regional 

and local scale?

i. How much change will occur in 

the timing of snow melt and snow 

onset?

j. How will the frequency of rainon-snow and severe winter storm 

events change?

Workshop participants identified 

important information gaps in our 

understanding of climate change 

effects on birds, mammals, and fish 

populations. The specific gaps varied 

among species groups, but most 

fell into four cross-cutting thematic areas and underlying research 

questions (see Chapter 6 for more 

details):

Scientific 

Priorities

A pectoral sandpiper (Calidris melanotos) near Barrow. Photo by Ted 

Swem, USFWS.
113

2. Vegetation Community Composition 

and Phenology

a. How will changes in the length 

and timing of the growing season 

influence plant phenology, including seasonal changes in nutritional 

quality?

b. How will plant species composition shift in response to long-term 

climate change, and what are the 

implications for habitat structure 

and quality of the prevalent available forage (i.e., digestibility, nutrient content)?

c. What is the time scale of expected 

shrub increase, and how will this 

vary by species/growth form (low 

vs. tall shrub) and ecoregion? 

d. What is the likelihood of widespread conversion from sedge 

and sedge-shrub meadow to bog 

meadow (paludification) and how 

would this affect herbivore and 

detritus-based trophic systems?

e. How will changes in the seasonality of stream discharge and occurrence of flood events influence 

development of riparian vegetation 

communities? 

3. Abundance and Phenology of 

Invertebrates

a. How does earlier spring thaw affect timing of life cycle events and 

peak availability to predators?

b. How does temperature affect 

growth and development of aquatic 

insects?

c. What climate-related changes are 

likely in community composition of 

macroinvertebrates in stream, lake, 

and saturated soil environments?

d. How will changes in the distribution and quality of surface waters 

and shifts from pelagic to benthic 

productivity in deep lakes affect 

availability of macroinvertebrates 

to fish and wildlife? 

e. How will warming and changing seasonality affect abundance 

and peak activity periods of biting 

insects, and what are the bioenergetic consequences for caribou in 

particular?

f. How will warming and changing 

seasonality affect the prevalence of 

parasites and disease vectors (e.g., 

nematode parasites of muskoxen 

and Dall’s sheep)? 

4. Coastal Dynamics 

a. Will higher water temperatures, 

sea level rise, and retreat of summer sea ice cause degradation of 

the barrier island systems of the 

Beaufort and Chukchi seas?

b. Will alluvial deltas continue to 

build or will rising sea levels outpace potential increases in sedimentation rates?

c. How quickly will shoreline retreat 

result in newly breached lake 

basins? 

d. To what extent will coastal erosion, in combination with sea level 

rise, cause salinization of low-lying 

coastal areas?

e. Will coastal wet sedge meadows 

establish at a rate equal to loss of 

this habitat through erosion and 

inundation?

f. Will increased fogginess/cloudiness exert a negative or positive 

feedback effect on air temperature 

in the coastal zone? What is the expected spatial extent of this effect?

Relevant to all of the four major 

themes above, the study and modeling of hydrologic processes emerged 

as critical to understanding habitat 

change. Furthermore, hydrologic 

data and models are needed by a 

broad constituency of user groups, 

including engineers and infrastructure planners. 

Ptarmigan (Lagopus sp.) are 

nomadic in winter, moving in flocks 

from one sheltered slope or patch of 

food to another from November to 

March. Photo by Øivind Tøien.
114

The scientific priorities previously 

listed should be addressed by activities including: monitoring of physical and biological parameters; field 

observations and focused research 

activities designed to clarify the 

mechanisms by which environmental 

variables influence fish and wildlife 

populations; and development and 

refinement of arctic process models 

that integrate physical and biological 

parameters. More specific research 

activity recommendations are detailed below.

Hydrologic Research

Hydrologic data are sparse for the 

North Slope, principally due to the 

cost of acquisition. Recognizing that 

cost sharing among agencies and 

others is necessary, we recommend 

four initiatives in this area:

1. Establishment of at least three 

long-term observatories on the 

North Slope to collect integrated 

hydrologic, climate, and geophysical data. The central mission of 

these observatories should be to 

develop an understanding of the 

response of permafrost (active 

layer dynamics), hydrologic, and 

ecological systems to changes in 

thermal regime. To ensure applicability to fish and wildlife biology, 

water budgets should be estimated 

for key ecotypes.

2. Intensive observations at the 

observatory sites should be supplemented by instrumentation (e.g., 

meteorology, radiation, stream discharge, soil moisture) at dispersed 

sites arrayed across important 

environmental gradients.

3. Modeling that dynamically 

couples soil thermal and hydrologic 

regimes, and biological systems at 

appropriate spatial and temporal 

scales.

4. Centralized data storage and interpretation for the mutual benefit 

of multiple end-users.

Development of Habitat Change 

Models

We recommend immediate attention 

to developing habitat change models, 

focusing initially on processes that 

are ongoing and occurring on a short 

(decadal) time scale. Priority topics 

include:

•Coastal processes (e.g., erosion, 

storm surge, deposition, succession);

•Seasonality (e.g., plant phenology, 

animal migration, life stages of 

aquatic invertebrates); 

•Shrub advance; 

•Fire regime (as a function of interactions among climate, permafrost, 

and vegetation); and

•Thermokarst effects on surface 

water and lake drainage.

Selection of Indicator Species and 

Parameters

Deficiencies in our knowledge of 

basic natural history and ecology of 

arctic species currently hinder our 

ability to assess responses to climate 

change. We suggest choosing focal 

species that reflect sensitivity to 

hypothesized climate change effects. 

The WildREACH working groups 

made progress toward this goal, but 

we recommend additional work in 

this area. Specifically, the Service 

should engage the U.S. Geological Survey (USGS) and others in a 

structured decision-making process 

to refine the selection of indicator 

species/parameters as components 

of a long-term climate monitoring 

program. Upon reaching consensus, 

management agencies should seek 

stable funding for monitoring these 

species/attributes.

Recommended 

Research 

Activities

A flock of long-tailed ducks (Clangula hyemalis) migrating along the coast 

near Barrow. Photo by Ted Swem, USFWS.
115

Climate change is transformative. 

The challenge of conserving fish 

and wildlife populations in the face 

of climate change already exceeds 

the capacity of any single entity. The 

scale and scope of climate change 

demands change in the way that 

resource agencies do business—we 

must pool already constrained human and financial resources. The 

future of conservation lies in landscape approaches that are developed 

and implemented with other federal, 

state, and non-governmental organization (NGO) partners. We recognize 

that there is no overarching business 

model that fits all agencies’ mandates, but there is ample common 

ground for agencies and NGOs to 

engage in collaborative conservation. Conservation partnerships will 

provide efficiencies through strategic targeting of financial resources 

and provide an opportunity to codevelop an adaptive, landscape-level 

response. 

Since the WildREACH workshop, 

the Service has promoted conservation partnerships across landscapes 

that align with Bird Conservation 

Regions (BCRs). These Landscape 

Conservation Regions (LCRs) will 

be supported by Landscape Conservation Cooperatives (LCCs) 

that house the technical expertise 

from multiple partners to address 

the science needs of each LCR. The 

Service has designated America’s 

Arctic as Alaska’s first LCR, affirming the high priority to be placed 

on developing partnerships and 

research plans and implementing 

conservation for the Arctic LCR. 

The Arctic LCR will be supported by 

the Northern Alaska LCC located 

in Fairbanks. The Northern Alaska 

LCC will work with USGS, through 

its National Climate Change and 

Wildlife Science Center and/or 

Regional Climate Science Hub, 

and other partners to establish the 

technical and organizational capacity 

to address the science needs of the 

Arctic LCR. 

Engaging in the broad scope of 

scientific inquiry recommended by 

workshop participants will reAgency 

Coordination 

and 

Collaboration 

quire financial commitment from a 

coalition of organizations and the 

formation of teams of specialists 

representing multiple disciplines. 

Toward those ends, the U.S. Fish 

and Wildlife Service is committed to 

improving communication and collaboration with the arctic research 

community. The Service will:

1. Work with the National Science 

Foundation (NSF) to define priorities for basic and applied research 

programs targeted toward climate 

research relevant to resource management agencies; 

2. Seek opportunities to collaborate with academic institutions to 

frame grant proposals in ways that 

address the priorities of fish and 

wildlife managers; 

3. Participate in planning and implementation of the interagency Study 

of Environmental Arctic Change 

(SEARCH) Program to ensure 

inclusion of research relevant to 

resource management agencies;

4. Work with arctic science program 

managers in the research agencies 

(e.g., National Science Foundation, 

USGS, National Oceanic and Atmospheric Administration) to identify 

funding sources to address priority 

questions; and

5. Promote a collaborative approach 

to acquire, process, archive, and 

disseminate essential satellitebased remote sensing data products (e.g., snow cover, green-up, 

and surface water) needed for 

regional-scale monitoring.

The Service is currently working 

with other federal and state managers to develop mechanisms to 

facilitate coordinated interagency 

planning, budget implementation, 

and data-sharing on a statewide 

basis via the Climate Change 

Roundtable. The State of Alaska’s 

Governor’s subcabinet (http://www.

climatechange.alaska.gov/) is also 

working to identify priority tasks 

to address mitigation and adaptation within the context of social and 

economic factors. As we designate 

LCRs and build the LCCs that support them, resource management 

agencies, research institutions, and 

NGOs must implement interagency 
116

Candle ice (small, icicle-shaped pieces of lake ice) is rapidly blown to shore on a lake on the Ikpikpuk Delta in July, 

crumpling the soft lake margin. It took only 4–5 minutes for the ice to come ashore. Photo by Leslie Pierce (TREC 

2005), courtesy of ARCUS.

agreements that commit resources 

to coordinated long-term research 

and monitoring, biological planning, 

and conservation design and delivery.

Climate change presents an unprecedented challenge to managers 

of arctic natural resources. The 

complexity with which interacting 

systems may respond to changing climate forces us to accept an 

uncomfortable level of uncertainty, 

and the time scales of change are 

long relative to the normal management cycle. We have the opportunity 

and obligation, however, to lay the 

foundation of information needed to 

inform future management decisions. The WildREACH workshop 

was successful in identifying priority information gaps and activities 

needed to provide the basis for 

adaptive management of arctic fish 

and wildlife resources. Adopting 

these recommendations will greatly 

strengthen our capacity to form 

anticipatory responses to climaterelated habitat change, and will 

help us identify the most promising 

strategies to protect arctic fish and 

wildlife populations.
117

Climate Data Sets

Temperature and precipitation 

projections were based on the 

downscaled General Circulation 

Model (GCM) output distributed 

by the University of Alaska Scenarios Network for Alaska Planning 

(SNAP; http://www.snap.uaf.edu/

about), based on the work of Walsh 

et al. (2008). Output from each model 

contains spatially explicit mean 

temperature (°C) and total precipitation (mm) grids for every month of 

every year for 120 years (1980–2099) 

for the entire state of Alaska. These 

data were downloaded to the Department of Atmospheric Sciences 

at the University of Illinois from 

the World Climate Research Programme (WCRP ) Coupled Model 

Intercomparison Project phase 3 

(CMIP3) multi-model dataset. The 

five models used were:

• ECHAM5/MPI from the Max 

Planck Institute for Meteorology in 

Germany;

• GFDL-CM2.1 produced by the 

National Oceanic and Atmospheric 

Administration (NOAA) Geophysical Fluid Dynamics Laboratory, a 

unit of the Department of Commerce, in the U.S.;

• MIROC3.2MedRes produced 

by the Center for Climate System Research at the University 

of Tokyo, the National Institute 

for Environmental Studies, and 

the Frontier Research Center for 

Global Change, a unit of the Japan 

Agency for Marine-Earth Science 

and Technology (JAMSTEC), in 

Japan;

• UKMO-HadCM3 produced by the 

Hadley Centre for Climate Prediction and Research and the Met 

Office in the U.K.; and

• CGCM3.1 produced by the Canadian Centre for Climate Modelling 

and Analysis in Canada.

More documentation on each model 

is available at the CMIP3 website 

(http://www-pcmdi.llnl.gov/ipcc/model_documentation/ipcc_model_documentation.php). Walsh et al. (2008) 

objectively evaluated 15 models over 

Alaska—the above five models were 

ranked highest and provided output 

that most closely matched actual 

Alaska climate data for the years 

1958–2000 (SNAP; http://www.snap.

uaf.edu/about). The best performing models in that analysis tend to 

be the models that project the most 

change in climate. Limiting the 

analysis to only the best performing 

models is one approach to narrowing the uncertainty of the projected 

climate change (Walsh et al. 2008). 

Each model run is based on the 

Intergovernmental Panel on Climate Change (IPCC) A1B greenhouse gas emission scenario (IPCC 

2007), which assumes fast economic 

growth, an eventual decline in global 

population, development of more 

efficient technology, and the continued use of fossil fuels for some, but 

not all, energy sources. The A1B 

scenario is considered a “middleof-the-road” scenario among those 

presented by the IPCC. The A1B, 

B1 (slow greenhouse gas increase), 

and A2 (more rapid greenhouse gas 

increase) scenarios differ little by 

mid-century but diverge by 2100. 

The projected climate changes 

are generally proportional to the 

respective increases of greenhouse 

gas concentrations, so the B1 and 

A2 changes of climate can be scaled 

to the A1B changes. The projections used in this report are derived 

from a composite of the five model 

outputs. 

Baseline temperature and precipitation data were derived from the 

Parameter-Elevation Regression on 

Independent Slopes Model (PRISM) 

dataset created by the PRISM 

Group (Oregon State University, 

www.prism.oregonstate.edu). These 

data consist of 12 gridded mean 

maximum temperature, mean 

minimum temperature, and total 

precipitation files at 2-km resolution, 

one for each month averaged over 

1961–1990 for the state of Alaska. 

This dataset was created using observation data from weather stations 

across Alaska and spatially interpolated over intervening areas using 

weighted regression incorporating 

elevation and terrain effects on climate (Daly et al. 2002, Simpson et al. 

2005). Walsh et al. (2008) calculated 

GCM baseline values for each of 

the five selected models using mean 

monthly outputs for 1961–1990. They 

then calculated differences between 

projected GCM values and baseline 

GCM values for each year and created “anomaly grids” representing 

these differences. The anomaly grids 

were added to the PRISM baseline 

to create fine-scale (2-km) grids for 

monthly mean temperature and precipitation projections out to 2099.

Appendix 1: 

Methods for 

Climate 

Projections
118

Temperature and Precipitation 

Projections

The Nature Conservancy calculated the projected decadal mean 

for each month of the year, for 

both temperature and precipitation. Monthly values were averaged 

(for temperature) or summed (for 

precipitation) across months to yield 

seasonal and annual values. Midcentury and end-of-century intervals 

were selected to represent projected 

change. Mid-century (2051–2060) 

and end-of-century (2091–2100) 

grids were generated by calculating 

the differences between projected 

values from the PRISM baseline 

value (temperature) or the percent 

change from the PRISM baseline 

value (precipitation). A spatial mean 

was then calculated to produce the 

summaries by ecoregion. For this 

document, summer is defined as 

June through September and winter 

as October through May.

Freeze-Up, Thaw, and the Frost-Free 

Season Projections

The Wilderness Society generated 

data for onset of freeze-up, thaw, 

and length of frost-free season. Data 

were analyzed using the open source 

application R (R Development Core 

Team 2005) and ArcGIS 9.3 (ESRI, 

Redlands, California). Climate data 

were monthly means and totals, but 

freeze-up and spring thaw dates are 

often variable within days; therefore, 

a ramp function was used to linearly 

interpolate the day of freeze-up and 

thaw for the 1980–2099 composite 

(Euskirchen et al. 2007). A 12 x 120 

matrix (12 months, 120 years) of 

spatial mean values was developed 

and assumed to represent the value 

for the 15th day of that month. The 

slope between these values was calculated and added to each progressive day beyond the 15th until the 15th

of the next month was reached. This 

procedure was repeated for each 

month. For the purposes of these 

analyses, freeze-up was defined as 

the first day of the year when the 

interpolated value fell below 0°C, 

and thaw was defined as the first 

day above 0°C. The number of days 

between these two dates was defined 

as the frost-free season, calculated 

for all 120 years and plotted over 

time. Rate of change over time was 

calculated using a linear regression. 

This analysis is not indicative of the 

actual dates of freeze-up and thaw 

or the natural variability surrounding them (e.g., several freezing 

and unfreezing events may occur), 

however, it does give an indication 

of how much these actual dates may 

be delayed or advanced under each 

scenario of climate change.
119

Potential Evapotranspiration and Water 

Availability Projections

The Wildness Society calculated 

potential evapotranspiration (PET) 

for each of the three North Slope 

ecoregions using a modified version of the Priestly-Taylor method 

adapted to a monthly time step using 

energy balance equations from Allen 

et al. (1998). The two time slices used 

for PET projections are different 

than those used for temperature 

and precipitation and are centered 

around 2035–2044 and 2075–2084. 

Climate variable inputs included 

mean monthly temperature (Tmean), 

mean monthly minimum temperature, (Tmin), mean monthly maximum 

temperature (Tmax), and percent 

cloud cover. Spatial averages for 

each ecoregion were derived from 

the baseline PRISM dataset for each 

ecoregion. Mean monthly minimum 

and maximum temperature grids 

were created by subtracting the 

corresponding PRISM Tmean grids 

from the projected Tmean grids to 

obtain monthly anomalies from the 

baseline PRISM climatology. These 

anomaly grids were then added to 

the PRISM Tmax temperature grids 

and subtracted from the PRISM Tmin

grids to create 12 projected Tmax and 

12 projected Tmin temperature grids 

for the two time periods. For months 

with mean temperatures below 0°C, 

PET is assumed to be zero. Mean 

cloudiness, as percent sky cover, for 

each ecoregion was estimated using 

station data available at the Alaska 

Climate Research Center (ACRC) 

website (http://climate.gi.alaska.edu/

Climate/index.html) and assumed 

to remain constant throughout 

future projections. Additional inputs 

included ordinal date and latitude. 

The 15th of January served as an 

initial ordinal date and progressed 

through the year at a 30-day time 

step. For example, the ordinal date 

used for the month of February 

was the 45th, and for August it was 

the 225th. The latitude coordinates 

used for the Arctic Coastal Plain, 

Arctic Foothills, and Brooks Range 

were 70.37°N, 69.42°N, and 68.80°N, 

respectively.

Growing season months (Tmean >0°C) 

used for the Coastal Plain and Foothills analysis remained consistent 

throughout future projections, spanning the months of June through 

September. The growing season in 

the Brooks Range expanded, however, from the historical June–August 

to include September by 2035–2044 

and May by 2075–2084.

Sparse cloud cover data made it 

necessary to interpolate regional 

values. Cloud cover data for the 

Coastal Plain are averages of ACRC 

weather station data from Barrow 

and Barter Island (the only stations 

available for the region). Values for 

the Brooks Range are assumed to 

be the same as those measured in 

Bettles (the closest high-altitude 

station available). Because none of 

the weather stations located within 

the Arctic Foothills contained cloud 

cover measurements, cloud cover 

data for this ecoregion is represented by an average of value from 

Barrow, Barter Island, and Bettles.

Monthly estimates of PET were subtracted from total monthly precipitation (P) values for each time period 

to estimate changes in the mean 

growing season water balance (PPET) for each ecoregion over time. 

These analyses were restricted to 

months with average temperatures 

exceeding 0°C and did not include 

the additional days expected to contribute to a longer growing season as 

determined by the separate frostfree season regression analyses.

Literature Cited 

Allen RG, Perieira LS, Raes D, 

Smith M. 1998. Crop evaptranspiration: Guidelines for computing 

crop water requirements. FAO 

Irrigation and Drainage Paper 56, 

Rome, Italy. 

Daly, C, Gibson WP, Taylor GH, 

Johnson GL, Pasteris P. 2002. A 

knowledge-based approach to the 

statistical mapping of climate. Clim 

Res 22: 99-113.

Euskirchen ES, McGuire AD, 

Chapin FS. 2007. Energy feedbacks of northern high-latitude 

ecosystems to the climate system 

due to reduced snow cover during 20th century warming. Global 

Change Biol 13: 2425-2438.

Simpson JJ, Hufford GL, Daly 

C, Berg JS, Fleming MD. 2005. 

Comparing maps of mean monthly 

surface temperature and precipitation for Alaska and adjacent areas 

of Canada produced by two different methods. Arctic 58: 137-161.

Walsh JE, Chapman WL, Romanovsky V. 2008. Global climate 

model performance over Alaska 

and Greenland. J. Climate 21:6156-

6174.
120

Class Description

Alpine Ecotypes

Alpine Glaciers Perennially frozen snow and ice at high elevations in the Brooks Range, typically on northfacing slopes. 

Alpine Non-carbonate 

Barrens

Barren (<5% plant cover) to partially vegetated (5–30%) areas on non-carbonate bedrock and 

talus slopes above treeline in the Brooks Range. Bedrock includes felsic intrusive (e.g., granite, 

granodiorite), non-carbonate metamorphic (e.g., slate, schist), and non-carbonated sedimentary 

(e.g., conglomerate, sandstone, shale) rocks that generally have low calcium and sodium and 

high aluminum concentrations that lead to acidic soils. Soils are rocky, excessively drained, lacking in surface organic accumulations, and strongly acidic (pH <5.5). At high elevations, common 

species include Geum glaciale, Saxifraga bronchialis, S. flagellaris, S. nivalis, S. eschscholtzii,

and crustose and fruticose lichens. Lower elevations have species similar to Alpine Non-carbonate Dwarf Shrub Tundra. 

Alpine Carbonate 

Barrens

Barren (<5% plant cover) to partially vegetated (5–30%) areas on carbonate bedrock and talus 

slopes above treeline in the Brooks Range. Bedrock includes both sedimentary (limestone, dolostone) and metamorphic (marble) carbonate rocks. Soils are rocky, excessively drained, lacking 

in surface organics, and alkaline (pH >7.3). Common pioneering plants include Dryas integrifolia, D. octopetala, Saxifraga oppositifolia, Potentilla uniflora, Oxytropis nigrescens, O. arctica, 

and Carex rupestris.

Alpine Mafic Barrens

Barren areas on intermediate, mafic, and ultramafic plutonic rocks above treeline in the Brooks 

Range that typically have dark-colored mineral assemblages with abundant iron and magnesium. Soils are rocky, excessively drained, lacking in surface organic accumulations, and are 

neutral to alkaline. Some areas have high levels of trace metals. Areas usually are devoid of 

vegetation. 

Alpine Non-carbonate 

Dwarf Shrub Tundra 

Areas on noncarbonate bedrock and talus slopes above treeline in the Brooks Range with dwarf 

shrub vegetation. Soils are rocky, excessively drained, have very thin surface organic accumulations, and are strongly acidic. Vegetation is dominated by dwarf shrubs including Dryas 

octopetala (mostly south slopes), Salix phlebophylla, S. arctica, Loiseleuria procumbens, Diapensia lapponica, Arctostaphylos alpina, Empetrum nigrum, Vaccinium uliginosum, and Cassiope tetragona (north slopes). Other species include Carex podocarpa, C. bigelowii, Hierochloe 

alpina, Cladina mitis, C. rangiferina, and Rhizocarpon geographicum. 

Alpine Carbonate 

Dwarf Shrub Tundra 

Areas on carbonate bedrock and talus slopes above treeline in the Brooks Range with dwarf 

shrub vegetation. Soils are rocky, excessively drained, rich in humus, and alkaline. Vegetation 

is dominated by dwarf shrubs including Dryas integrifolia (mostly south slopes), D. octopetala, 

Cassiope tetragona (north slopes), Salix arctica, and Arctostaphylos alpina. Other species 

include Carex rupestris, C. bigelowii, Saxifraga oppositifolia, Potentilla uniflora, Oxytropis 

nigrescens, O. arctica, Nephroma arcticum, Rhytidium rugosum, Flavocetraria cucullata, and

Thamnolia vermicularis.

Alpine Mafic 

Dwarf Shrub Tundra

Areas on intermediate, mafic, and ultramafic plutonic rocks above treeline in the Brooks Range 

with dwarf shrub vegetation. Rocks have dark-colored mineral assemblages with abundant iron 

and magnesium. Soils are rocky, excessively drained, lacking in surface organic accumulations, 

and are neutral to alkaline. Some areas have high levels of trace metals. Vegetation is poorly described for this type but it probably is similar to that described for Alpine Non-carbonate Dwarf 

Shrub Tundra.

Terrestrial habitat types adapted from the ecotypes described by Jorgenson and Heiner (2003) are described in 

Table A2.1. The distribution of ecotypes is depicted in Figure A2.1. 

Appendix 2:

Description and 

Distribution of 

Northern Alaska 

Ecotypes 

Table A2.1. Description of terrestrial habitat types found in northern Alaska. From Jorgenson and Heiner (2003).

Continued page 122
121

Figure A2.1. Distribution of ecotypes in northern Alaska (Jorgenson and Heiner 2003).
122

Class Description

Upland Ecotypes

Upland Spruce Forest

Upland areas on mid- to upper slopes on weathered bedrock, colluvium, and glacial till with vegetation dominated by needleleaf trees. Soils are loamy to rocky, well-drained, have moderately 

thick organic horizons, are acidic, and may or may not have permafrost. This late-successional 

forest is dominated by an open to closed canopy of Picea glauca, but can include minor amounts 

of Betula papyrifera and P. mariana. Understory plants include Alnus crispa, Vaccinium 

vitis-idaea, Ledum groenlandicum, Empetrum nigrum, Rosa acicularis, Cornus canadensis, 

Shepherdia canadensis, Spiraea beauverdiana, Linnaea borealis, Calamagrostis canadensis, 

Hylocomium splendens, and Pleurozium schreberi.

Upland Birch-AspenSpruce Forest

Upland areas on mid- to upper slopes on weathered bedrock, colluvium, and glacial till with vegetation co-dominated by broadleaf and needleleaf trees. Soils are well-drained, have thin organic 

horizons, are moderately acidic, and usually lack permafrost. This mid-successional mixed forest 

is dominated by an open to closed canopy of Betula papyrifera, Populus tremuloides, and Picea 

glauca. Understory plants include Alnus crispa, Salix glauca, Vaccinium vitis-idaea, Ledum 

groenlandicum, Rosa acicularis, Cornus canadensis, Shepherdia canadensis, Linnaea borealis, Calamagrostis canadensis, and feathermosses.

Upland Birch-Aspen 

Forest

Upland areas on mid- to upper slopes on weathered bedrock, colluvium, and glacial till with 

vegetation dominated by broadleaf deciduous trees. Soils are loamy to rocky, well-drained, have 

thin organic horizons, are acidic, and usually lack permafrost. The mid-successional forest is 

dominated by an open to closed canopy of Betula papyrifera and Populus tremuloides. Understory plants include Alnus crispa, Salix glauca, Vaccinium vitis-idaea, Ledum groenlandicum, 

Rosa acicularis, Cornus canadensis, Shepherdia canadensis, Spiraea beauverdiana, Linnaea 

borealis, Calamagrostis canadensis, and feathermosses.

Upland Tall Alder Shrub

Upland areas on mid- to upper slopes on weathered bedrock, colluvium, and glacial till with 

vegetation dominated by tall shrubs. Soils are loamy to rocky, well-drained, have thin organic 

horizons, are acidic, and usually lack permafrost. Vegetation is dominated by an open to closed 

canopy of Alnus crispa, although Salix pulchra, Salix glauca, and Betula glandulosa occasionally are abundant. Understory species include Vaccinium uliginosum, Vaccinium vitis-idaea, 

Betula nana, B. glandulosa, Ledum groenlandicum, Empetrum nigrum, Equisetum arvense, 

Spiraea beauverdiana, Calamagrostis canadensis, and Petasites frigidus. Mosses include 

Sphagnum spp., Hylocomium splendens, and Dicranum spp.

Upland Low BirchWillow Shrub Tundra

Upland areas on mid- to upper slopes on weathered bedrock, colluvium, and glacial till with 

vegetation dominated by low shrubs. Soils are loamy to rocky, well-drained, have moderately 

thick organic horizons, are acidic, and usually have permafrost. Vegetation has an open to closed 

canopy of Betula nana and/or Salix pulchra. Other species include Salix glauca, Vaccinium 

uliginosum, V. vitis-idaea, Ledum decumbens, Empetrum nigrum, Arctostaphylos alpina, 

Dryas octopetala, D. integrifolia, Salix reticulata, Equisetum arvense, Carex bigelowii, and the 

mosses and lichens Hylocomium splendens, Tomentypnum nitens, Sphagnum spp., Aulacomnium palustre, Dicranum spp., Cladina rangiferina, and Flavocetraria cucullata. 

Upland Dryas Dwarf 

Shrub Tundra

Upland windswept ridges and upper slopes on weathered bedrock, colluvium, inactive sand 

dunes, and coastal plain deposits with vegetation dominated by dwarf shrubs. Soils are welldrained, loamy to rocky, have thin organic horizons, and are circumneutral to acidic. Common 

dwarf shrubs include Dryas octopetala (mostly south slopes), D. integrifolia, Salix phlebophylla, S. arctica, S. reticulata, Loiseleuria procumbens, Diapensia lapponica, Arctostaphylos 

alpina, Empetrum nigrum, Vaccinium uliginosum, Ledum decumbens, and Cassiope tetragona (north slopes). Other common species include Carex bigelowii, C. scirpoidea, Arctagrostis 

latifolia, Equisetum variegatum, Tomentypnum nitens, Hylocomium splendens, and Cladina 

stellaris.

Upland Shrubby 

Tussock Tundra

Gently sloping uplands and ridges on loess and colluvium over bedrock and glacial till, primarily within the Brooks Foothills (>120 m elevation), with vegetation co-dominated by tussockforming sedges and low shrubs. Soils are somewhat poorly drained, loamy, have moderately 

thick surface organics, are acidic, and are underlain by ice-rich permafrost. The open low shrub 

canopy of Betula nana and Salix pulchra usually overtop the Eriophorum vaginatum tussocks. 

Other dominant plants include E. angustifolium, Carex bigelowii, Ledum decumbens, Vaccinium vitis-idaea, V. uliginosum, Rubus chamaemorus, Hylocomium splendens, Sphagnum 

spp., Aulacomnium palustre, Cladina rangiferina, C. arbuscula, C. mitis, and Flavocetraria 

cucullata.

Upland Tussock Tundra

Gently sloping uplands and ridges on loess, colluvium, and coastal plain deposits, primarily within the Beaufort Coastal Plain (<120 m elevation), with vegetation dominated by tussock-forming 

sedges. Soils are moist, somewhat poorly drained, loamy, and have moderately thick surface 

organics, are circumneutral to acidic, and are underlain by ice-rich permafrost. Vegetation is 

dominated by Eriophorum vaginatum. On circumneutral soils, Carex bigelowii, Dryas integrifolia, Salix pulchra, Cassiope tetragona, S. reticulata, Tomentypnum nitens, and Hylocomium 

splendens are common. On acidic soils, dominant plants include E. angustifolium, Betula nana, 

Salix pulchra, Ledum decumbens, Vaccinium vitis-idaea, Rubus chamaemorus, Hylocomium 

splendens, Sphagnum spp., Aulacomnium palustre, and Cladina rangiferina.

Table A2.1. Continued
123

Class Description

Upland Moist SedgeShrub Tundra

Upland ridges and upper slopes on weathered bedrock, loess-mantled bedrock, colluvium, and 

glacial till, with vegetation co-dominated by sedges and low and dwarf shrubs. Soils are loamy 

to rocky, somewhat poorly drained, have moderately thick surface organics, and are alkaline to 

acidic depending on substratum. On acidic soils more common in the upper foothills and mountains, dominant plants include Betula nana, Salix pulchra, Carex aquatilis, Eriophorum angustifolium, and Sphagnum spp. On circumneutral to alkaline soils more common on the coastal 

plain and lower foothills, dominant plants include Salix lanata richardsonii, Dryas integrifolia, 

S. reticulata, Arctostaphylos rubra, Rhododendron lapponicum, Equisetum arvense, Carex 

bigelowii, Tomentypnum nitens, and Thamnolia vermicularis.

Lowland Ecotypes

Lowland Spruce 

Forest

Low-lying flats and gentle slopes on colluvium and abandoned floodplains with vegetation 

dominated by needleleaf forests. Soils are wet, somewhat poorly drained, have moderately thick 

surface organics, are acidic, and usually are underlain by permafrost. The open tree canopy 

(usually 5–10 m high) is dominated by Picea mariana, although P. glauca, Larix laricina, and

Betula papyrifera occasionally can be present in small amounts. In the wettest areas the trees 

can be very stunted. Common understory plants include Salix pulchra, Betula nana, Vaccinium 

uliginosum, Ledum groenlandicum, Potentilla fruticosa, Rubus chamaemorus, Equisetum 

arvense, and Carex bigelowii. Mosses and lichens include Sphagnum spp., Hylocomium splendens, Pleurozium schreberi, Cladonia spp., Nephroma spp., Cetraria spp., and Peltigera spp.

Lowland Low BirchWillow Shrub Tundra

Low-lying flats and lower slopes on drained lake basins, abandoned floodplains, colluvium, 

and coastal plain deposits with vegetation dominated by low shrubs. Soils typically are poorly 

drained, loamy, have moderately thick surface organics, are acidic, and are underlain by permafrost. The open to closed low shrub canopy is dominated by Salix pulchra and Betula nana. 

On acidic soils other common species include Ledum decumbens, Vaccinium uliginosum, V. 

vitis-idaea, Empetrum nigrum, Petasites frigidus, Rubus chamaemorus, Eriophorum angustifolium, Carex aquatilis, Calamagrostis canadensis, and Sphagnum spp. On circumneutral 

to alkaline soils, Salix lanata richardsonii, S. reticulata, Dryas integrifolia, Arctostaphylos 

rubra, Equisetum arvense, Eriophorum angustifolium, and Carex aquatilis are common.

Lowland Moist SedgeShrub Tundra

Low-lying flats and gentle slopes on drained lake basins, abandoned floodplains, colluvium, and 

coastal plain deposits, particularly on the Beaufort Coastal Plain, with vegetation co-dominated 

by sedges and low or dwarf shrubs. Soils are saturated at intermediate depths (>15 cm), loamy 

with moderately thick surface organics, are circumneutral to alkaline, and are underlain by icerich permafrost. Sites generally are free of surface water during summer. Vegetation is dominated by Carex aquatilis, C. bigelowii, Eriophorum angustifolium, and Dryas integrifolia. Other 

common species include Salix lanata richardsonii, S. pulchra, S. reticulata, Tomentypnum 

nitens, and Hylocomium splendens. Acidic vegetation could not be adequately differentiated 

from non-acidic vegetation on the Beaufort Coastal Plain.

Lowland Wet Sedge 

Tundra

Low-lying flats and drainages on drained lake basins, abandoned floodplains, colluvium, and 

coastal plain deposits, particularly on the Beaufort Coastal Plain, with vegetation dominated 

by sedges. Soils are poorly drained, have moderately thick to thick (10–50 cm) surface organics over silt loam, usually circumneutral, and are underlain by ice-rich permafrost. Ice wedge 

development in older landscapes creates distinctive low-centered polygons. The surface generally is flooded during early summer (depth <0.3 m) and drains later, but soils remain saturated 

≥15 cm from the surface throughout the growing season. Vegetation is dominated by Carex 

aquatilis and Eriophorum angustifolium, while willows, including Salix lanata richardsonii 

and S. pulchra, often are present but usually not co-dominant. Other common species include 

Dryas integrifolia, S. reticulata, C. bigelowii, and Equisetum scirpoides on higher microsites 

and polygon rims.

Lowland Lake

Shallow (<1.5 m) ponds and deep (≥1.5 m) lakes resulting from thawing of ice-rich permafrost, 

primarily on the coastal plain and distal portions of abandoned floodplains. In shallow ponds, 

water freezes to the bottom during winter, thaws by early to mid-June, and is warmer than 

water in deep lakes. In deep lakes, water does not freeze to the bottom during winter in deeper 

portions of the lake. Sediments are loamy to sandy. These lakes lack riverine influences (flooding), but they may have distinct outlets or connections to rivers.

Continued next page 
124

Class Description

Lacustrine Ecotypes

Lacustrine Barrens (not 

mapped)

Barren or partially vegetated (<30% cover) areas on newly exposed sediments in recently 

drained lake basins. The surface form generally is nonpatterned due to the lack of ice wedge 

development. Soils are saturated to well-drained, sandy to loamy, lack surface organics, and are 

alkaline. Typical colonizers are Arctophila fulva, Carex aquatilis, Dupontia fisheri, Scorpidium 

scorpioides, and Calliergon spp. on wet sites and Poa alpigena, Senecio congestus, Salix ovalifolia, and Salix arctica on drier sites.

Lacustrine Marsh (not 

mapped)

Shallow (<1 m), permanent waterbodies with emergent aquatic sedges and grasses. Water and 

bottom sediments freeze completely during winter, but the ice melts in early June. The sediments range from sands to organics (10–50 cm deep) overlying silt loam. In deeper water (30–

100 cm), Arctophila fulva can form sparse to dense stands and is the predominant vegetation. In 

shallower (<30 cm) water, Carex aquatilis and Eriophorum angustifolium are dominant, and 

Utricularia vulgaris is common. This ecosystem type is important to waterbirds but could not 

be mapped separately and is included in both Lowland Lakes and Lowland Wet Sedge Tundra. 

Riverine Ecotypes

Riverine Spruce 

Forest

Flat areas on inactive floodplains subject to infrequent flooding with vegetation dominated by 

needleleaf trees. The late-successional forest has an open to closed tree canopy dominated by 

Picea glauca. Soils are well-drained, loamy to gravelly, have moderately thick surface organics, 

and are acidic. The understory is dominated by Alnus crispa, Vaccinium uliginosum, V. vitisidaea, Arctostaphylos rubra, Cornus canadensis, Viburnum edule, Rosa acicularis, Mertensia 

paniculata, and feathermosses (Hylocomium splendens, Rhytidiadelphus triquetrus, and

Pleurozium schreberi).

Riverine SpruceBalsam Poplar Forest

Flat areas on inactive floodplains subject to infrequent flooding with mixed forests co-dominated 

by needleleaf and broadleaf trees. The mid-successional forests have an open to closed tree 

canopy dominated by Picea glauca and Populus balsamifera. Soils are well-drained, loamy to 

gravelly, have moderately thick surface organics, and are circumneutral to acidic. The understory is dominated by Alnus crispa, Vaccinium uliginosum, V. vitis-idaea, Arctostaphylos rubra, 

Cornus canadensis, Viburnum edule, Rosa acicularis, Equisetum arvense, Epilobium angustifolium, Calamagrostis canadensis, and feathermosses (Hylocomium splendens, Rhytidiadelphus triquetrus, and Pleurozium schreberi).

Riverine Balsam 

Poplar Forest

Flat areas on inactive floodplains subject to infrequent flooding and that have vegetation dominated by broadleaf forests. Soils are well-drained, loamy to gravelly, have thin surface organics, 

and are circumneutral. The mid-successional forest has an open to closed canopy dominated 

by Populus balsamifera or occasionally Betula papyrifera. The understory has Alnus crispa, 

Rosa acicularis, Equisetum arvense, Epilobium angustifolium, Hedysarum alpinum, Calamagrostis canadensis, Galium boreale, and Rhytidiadelphus triquetrus.

Riverine Tall AlderWillow Shrub

Flat areas on active floodplains subject to frequent flooding that have vegetation dominated by 

tall shrubs in the boreal region. Soils are well-drained, loamy to gravelly, have very thin surface 

organics, and are circumneutral. The early succession community has an open to closed tall 

shrub canopy dominated by Salix alaxensis, S. arbusculoides, S. monticola, and Alnus crispa. 

The understory is dominated by Vaccinium uliginosum, Artemisia tilesii, Calamagrostis canadensis, Petasites frigidus, and Equisetum arvense. Mosses and lichens are not abundant.

Riverine Low Willow 

Shrub Tundra

Flat to gently sloping areas on active and inactive floodplains in arctic regions subject to variable flooding frequency and that have vegetation dominated by tall and low shrubs. On the 

narrow zone close to the river, soils are frequently flooded, well-drained, lack organic accumulations, and have vegetation dominated by open tall (>1.5 m) Salix alaxensis, S. arbusculoides, 

and S. glauca. Alnus crispa is uncommon. In the understory, Equisetum arvense, Astragalus 

alpinus, Aster sibericus, and Festuca rubra are common. On inactive floodplains, where soils 

have interbedded organic layers and are seasonally saturated, Salix lanata richardsonii and S. 

pulchra are dominant. Common understory species include Salix reticulata, Arctostaphylos rubra, Dryas integrifolia, Arctagrostis latifolia, Equisetum spp., legumes, Tomentypnum nitens,

and other mosses.

Riverine Dryas Dwarf 

Shrub Tundra

Flat areas on inactive floodplains subject to infrequent flooding and that have vegetation 

dominated by dwarf shrubs. Soils are well-drained, sandy to rocky, have thin surface organics, 

are alkaline, and are underlain by ice-poor permafrost. The dwarf shrub Dryas integrifolia is 

dominant, and Salix reticulata, S. lanata richardsonii, Carex bigelowii, Arctagrostis latifolia, 

Astragalus spp., Oxytropis deflexa, and Equisetum scirpoides are common. Tomentypnum 

nitens and Distichium capillaceum are common mosses.

Riverine Moist SedgeShrub Tundra

Flat areas on inactive floodplains subject to infrequent flooding and that have vegetation codominated by sedges and low and/or dwarf shrubs. Soils are moderately well-drained, loamy, 

have moderately thick surface organics, are circumneutral and underlain by ice-rich permafrost. 

Vegetation is dominated by Carex aquatilis and Eriophorum angustifolium with Dryas integrifolia, Salix lanata richardsonii, S. reticulata, and Carex bigelowii, Equisetum spp., Tomenthypnum nitens, and Campylium stellatum as common associates. 

Table A2.1. Continued
125

Class Description

Riverine Wet Sedge 

Tundra

Flat areas on active and inactive floodplains subject to frequent or infrequent flooding and that 

have vegetation dominated by sedges. Soils are poorly drained, loamy with moderately thick 

to thick surface organics, are circumneutral to alkaline, and are underlain by ice-rich permafrost. Surface forms vary from nonpatterned to low-relief, low-centered polygons; the latter are 

indicative of progressive ice wedge development. Vegetation is dominated by Carex aquatilis 

and Eriophorum angustifolium, although occasionally the willow Salix lanata richardsonii

is a co-dominant. Other species include Dupontia fisheri, Equisetum variegatum, Pedicularis 

sudetica, Campylium stellatum, Scorpidium scorpioides, and Limprichtia revolvens.

Riverine Marsh 

(not mapped)

Shallow waterbodies (0.1–1.0 m) on active and inactive floodplains subject to occasional flooding with vegetation dominated by emergent aquatic grasses and sedges. Due to shallow water 

depths, the water freezes to the bottom in the winter, and the ice melts by early June. Arctophila fulva usually is found in deeper water while Carex aquatilis is usually found in very shallow 

water. Hippuris vulgaris occasionally is present.

Riverine Barrens

Barren or partially vegetated (<30% cover) areas on active river channel deposits associated 

with meandering or braided rivers. Frequent sedimentation and scouring restricts establishment and growth of vegetation. Soils are poorly to excessively drained, sandy to gravelly, lack 

surface organics, are alkaline, and usually have ice-poor permafrost in arctic regions and lack 

permafrost is boreal regions. Typical pioneer plants include Salix alaxensis, Deschampsia caespitosa, Chrysanthemum bipinnatum, Epilobium latifolium, Artemisia arctica, Festuca rubra, 

Arctagrostis latifolia, and Trisetum spicatum. 

Riverine Waters

Permanently flooded channels of freshwater rivers and streams, and lakes on inactive floodplains that are subject to occasional flooding. Some stream water flows throughout the year. 

Peak flooding generally occurs during spring breakup, and the lowest water levels occur during 

mid-summer. Riverbed materials can be either sand or gravel. Shallow (<1.5 m) or deep lakes 

usually are associated with old river channels, point bars, and meander scrolls, although some 

result from thawing of ice-rich permafrost on large floodplains. Some may have connecting 

channels that flood during high water. Shorelines usually are smooth (lack polygonization).

Coastal Ecotypes

Coastal Grass and Dwarf 

Shrub Tundra

Low-lying, salt-affected areas along the coast with vegetation dominated by either grasses 

or dwarf shrubs. Soils are well-drained, slightly saline, and alkaline. This class includes three 

vegetation types. On active dunes and beaches, vegetation includes Elymus arenarius, Chrysanthemum bipinnatum, Puccinellia spp., Artemisia tilesii, and Salix ovalifolia. Well-drained 

inactive tidal flats dominated by dwarf shrub vegetation have S. ovalifolia, Stellaria humifusa, 

E. arenarius, Deschampsia caespitosa, Dupontia fisheri, Carex subspathacea, and A. tilesii. 

Inactive dunes along the Chukchi Sea with slightly saline sandy soils have dwarf shrub vegetation dominated by Empetrum nigrum, S. ovalifolia, E. arenarius, Lathyrus maritimus, C. 

bipinnatum, and lichens. Substantial areas of this mapped class would have been more accurately mapped as Lowland Moist Sedge-Shrub Tundra but could not be adequately differentiated spectrally or by modeling.

Coastal Wet Sedge 

Tundra

Low-lying, salt-affected areas on tidal flats, deltas, and muddy beaches along the coast that are 

frequently flooded and have vegetation dominated by sedges. The surface is nonpatterned. Soils 

are poorly drained, clayey to loamy, usually lack surface organics, and are brackish and alkaline. 

The soils are underlain by ice-poor permafrost. Vegetation is dominated by Carex subspathacea, 

Carex ursina, and Puccinellia phryganodes, with Dupontia fisheri, Puccinellia andersonii, 

Cochlearia officinalis, and Stellaria humifusa also common. Non-vascular plants usually are 

absent. Substantial areas of Lowland Wet Sedge Tundra are included in these mapped areas but 

could not be adequately differentiated.

Coastal Barrens

Barren or partially vegetated, low-lying, salt-affected areas on tidal flats, deltas, and muddy 

beaches along the coast that are frequently flooded. Soils are poorly drained, clayey to loamy, 

usually lack surface organics, and are brackish and acidic to alkaline. The soils are underlain 

by ice-poor permafrost. Common colonizing plants include Deschampsia caespitosa, Elymus 

arenarius, Salix ovalifolia, and Stellaria humifusa in well-drained areas, and Puccinellia phryganodes, Dupontia fisheri, and Carex subspathacea in wetter areas. This class also includes 

tundra that has been killed by saltwater intrusions from storm surges and is being colonized 

by salt-tolerant plants. Newly deposited sediments typically are found on top of a thick organic 

horizon. These areas have low pH, high salinity, and shallow thaw depths. Common colonizing 

plants include Puccinellia phryganodes, Stellaria humifusa, Cochlearia officinalis, and Salix 

ovalifolia. 

Coastal Water

Shallow (~<2 m) estuaries, lagoons, embayments, and tidal ponds along the coast of the Beaufort and Chukchi seas. Winds, tides, river discharge, and icing create dynamic changes in physical and chemical characteristics. Salinity ranges widely from nearly fresh near rivers to saline in 

unprotected areas. Tidal ranges normally are small (<0.2 m) along the Beaufort and moderate 

(0.5–1 m) along the Chukchi seas, but storm surges produced by winds may raise sea level as 

much as 2–3 m. Bottom sediments are mostly unconsolidated mud and sand. The ice-free period 

extends from July until October. Winter freezing generally begins in late September.

Continued next page 
126

Class Description

Other Ecotypes

Marine Water 

(not mapped)

Deep (~>2 m) marine waters of the Beaufort and Chukchi seas outside of lagoons and barrier 

islands. Ice coverage is highly variable from permanent pack ice to seasonally ice free areas. 

Small areas of Marine Water are included in Coastal Water for mapping purposes.

Human Modified Barren or partially vegetated areas resulting from human disturbance. As mapped, the humanmodified areas are predominantly roads, pads, and mine pits and overburden.

Cloud, Snow, and Ice

Areas with clouds, snow, and ice. The Clouds and Ice Class was combined with the Shadow 

classes for the final map. Most of the original shadow classes in the input maps in the Brooks 

Range were recoded to alpine classes based on modeling. Remaining shadow areas are primarily due to clouds in the Brooks Foothills. Aufeis on rivers was classified as Riverine Barrens to 

avoid creation of a separate Riverine Ice class.

Table A2.1. Continued
127

Wildlife Response to Environmental Arctic Change (WildREACH): 

Predicting Future Habitats of Arctic Alaska 

17–18 November 2008 

Westmark Hotel, Fairbanks, Alaska 

Day 1: Monday, 17 November 2008 

Registration: 7:30 a.m.–9:30 a.m. 

7:30 a.m. Arrival and Coffee Service 

Plenary Session Held in Gold Room 

8:00 a.m. Welcome 

Geoffrey Haskett, Regional Director, U.S. Fish and Wildlife Service 

8:10 a.m. Introductions 

Philip Martin, U.S. Fish and Wildlife Service 

8:30 a.m. Workshop Goals and Structure 

Philip Martin, U.S. Fish and Wildlife Service 

8:50 a.m. Observed Climate Change in Northern Alaska 

Martha Shulski, University of Alaska Fairbanks 

9:05 a.m. Projected Climate of Northern Alaska 

Peter Larsen, The Nature Conservancy 

9:20 a.m. Coastal Processes 

David Atkinson, University of Alaska Fairbanks 

9:35 a.m. Permafrost and Active Layer Dynamics 

Vladimir Romanovsky, University of Alaska Fairbanks 

9:55 a.m. Permafrost-Influenced Geomorphic Processes 

Torre Jorgenson, ABR Environmental Services, Inc. 

10:15 a.m. Plenary Discussion/Q&A 

10:30 a.m. Break 

10:50 a.m. Vegetation Change 

Eugenie Euskirchen, University of Alaska Fairbanks 

11:05 a.m. Hydrologic Processes 

Amy Tidwell, University of Alaska Fairbanks 

11:20 a.m. Hydrology Panel—Predicting Change 

Snow: Matthew Sturm, Cold Regions Research and Engineering 

 Laboratory 

Water Balance: Doug Kane, University of Alaska Fairbanks 

Feedbacks: Larry Hinzman, University of Alaska Fairbanks 

 Anna Liljedahl, University of Alaska Fairbanks 

11:50 a.m. Plenary Discussion/Q&A 

12:30 p.m. Lunch (on your own) 

1:30 p.m. Integration – Potential Ecosystem Pathways 

Torre Jorgenson, ABR Environmental Services, Inc. 

1:50 p.m. Charge to Working Groups 

Philip Martin, U.S. Fish and Wildlife Service 

2:00 p.m. Working Groups Breakout Session I 

Working Groups will be presented with scenarios of climate and landscape 

change that would affect landscape-scale habitat availability, e.g., broad 

scale conversion from one habitat type to another. What species (or species 

attributes) would be sensitive indicators of the hypothesized changes? 

3:30 p.m. Break 

4:00 p.m. Return to Plenary Session: Working Group Reports 

Bird Working Group 

Fish Working Group 

Mammal Working Group 

Managers Working Group 

5:00 p.m. Summary of Day’s Discussion; Plans for Day 2 

5:15 p.m. Adjourn 

5:30 p.m. Reception and Poster Session (light food and cash bar) 

All participants are encouraged to bring a poster that describes synthesis research, data, and modeling needs within their area of interest, or relevant 

research findings from integrated projects. 

Appendix 3:

WildREACH 

Workshop 

Agenda
128

Day 2: Tuesday, 18 November 2008 

8:00 a.m. Arrival and Coffee Service 

8:15 a.m. Review of Day 1 Discussion, Day 2 Goal, Workshop Products 

8:25 a.m. Trophic Systems: Herbivores 

Brad Griffith, University of Alaska Fairbanks 

8:40 a.m. Trophic Systems: Aquatic 

Mark Wipfli, University of Alaska Fairbanks 

8:55 a.m. Charge to Working Groups 

Philip Martin, U.S. Fish and Wildlife Service 

9:10 a.m. Working Groups Breakout Session II 

Climate-associated processes may lead to changes in habitat suitability 

which cannot easily be equated with change in availability. Examples 

include: changes in water temperature that affect physiological processes 

of fish, enhanced food availability due to increased primary and secondary productivity, changing seasonality that results in asynchrony between 

optimal food availability and critical life history phases. Based on the 

scenarios of climate change outlined in the previous Breakout, what are the 

most important mechanisms by which climate would affect habitat suitability? Express the relationships and mechanisms in the format of “box-andarrow” conceptual models. 

11:15 a.m. Return to Plenary Session: Report of Working Groups 

Bird Working Group 

Fish Working Group 

Mammal Working Group 

Managers Working Group 

12:00 p.m. Lunch (on your own) 

1:00 p.m. Return to Plenary Session 

1:15 p.m. Bayesian Network Modeling 

Erik Beever, U.S. Geological Survey 

1:30 p.m. Empirical Temperature Downscaling: Improving Thermal 

Information Detail 

David Atkinson, University of Alaska Fairbanks 

1:45 p.m. Charge to Working Groups 

Philip Martin, U.S. Fish and Wildlife Service 

2:00 p.m. Working Groups Breakout Session III 

Focusing on the conceptual models identified in the previous breakout 

session, what are the key areas where reducing uncertainty in physical 

process models would enhance our ability to predict habitat change? What 

would we most like modelers and researchers in other disciplines to work 

on? 

4:00 p.m. Return to Plenary Session: Report of Working Groups 

Bird Working Group 

Fish Working Group 

Mammal Working Group 

Managers Working Group 

4:30 p.m. Identify Areas of Commonality Among Working Groups 

Panel Discussion: Working Group Leaders, Workshop Participants 

5:00 p.m. Summary, Discussion, and Next Steps 

Philip Martin, U.S. Fish and Wildlife Service 

5:15 p.m. Workshop Adjourns 

Day 3: Wednesday, 19 November 2008 

U.S. Fish and Wildlife Service Conference Room, Federal Building 

9:00 a.m. Invited Writing Group 

U.S. Fish and Wildlife Service Staff & invited Workshop Participants 

Synthesis of Key Results and Themes from Workshop 

The third day is intended for a small group of participants who are willing to 

make a substantial commitment to drafting and reviewing the final document from this workshop. If you are interested in participating, please 

contact Philip Martin at 907-456-0325 or philip_martin@fws.gov. 

12:00 p.m. Adjourn 
129

Jeff Adams

Assessment and Monitoring

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0218

Fax: 907-456-0454

Jeff_Adams@fws.gov

Stephen M. Arthur

Division of Wildlife Conservation

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7336

Fax: 907-452-6410

steve.arthur@alaska.gov

David E. Atkinson

International Arctic Research 

Center

University of Alaska Fairbanks

930 Koyukuk Drive, Room 313

PO Box 757340

Fairbanks, AK 99775-7340

Phone: 907-474-1126

Fax: 907-474-2643

datkinson@iarc.uaf.edu

Scott D. Ayers

School of Fisheries and Ocean Sciences

University of Alaska Fairbanks

PO Box 757220

Fairbanks, AK 99775-7220

Phone: 907-474-2486

scottdayers@gmail.com

Michael Baffrey

Office of the Secretary

U.S. Department of the Interior

1689 C Street, Suite 100

Anchorage, AK 99501

Phone: 907-271-4399

Fax: 907-271-4102

michael_baffrey@ios.doi.gov

Earl Becker

Division of Wildlife Conservation

Alaska Department of Fish and 

Game

333 Raspberry Road

Anchorage, AK 99518-1599

Phone: 907-267-2407

Fax: 907-267-2433

earl.becker@alaska.gov

Erik A. Beever

Alaska Science Center

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508-4626

Phone: 907-786-7085

Fax: 907-786-7150

ebeever@usgs.gov

Appendix 4:

WildREACH 

Workshop 

Participants

Mark Bertram

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0446

mark_bertram@fws.gov

Erica Betts

University of Alaska Fairbanks

869 Landon Lane

Fairbanks, AK 99709

Phone: 404-317-5312

betts.erica@gmail.com

Dixie Birch

U.S. Fish and Wildlife Service

1011 East Tudor Road

Anchorage, AK

Phone: 907-786-3523

dixie_birch@fws.gov

Karen Bollinger

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0427

Fax: 907-456-0208

karen_bollinger@fws.gov

Bonnie Borba

Commercial Fisheries

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7260

Fax: 907-459-7271

bonnie.borba@alaska.gov

Alan W. Brackney

Arctic National Wildlife Refuge

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-456-0450

Fax: 907-456-0428

alan_brackney@fws.gov

Scott Brainerd

Division of Wildlife Conservation

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7261

Fax: 907-459-7332

scott.brainerd@alaska.gov

Rena Bryan

International Arctic Research 

Center

University of Alaska Fairbanks

PO Box 757340

Fairbanks, AK 99775

Phone: 907-474-1556

rbryan@iarc.uaf.edu
130

Greta Burkart

Arctic Network Inventory and 

Monitoring Program

National Park Service

4175 Geist Road

Fairbanks, AK 99709-3420

Phone: 907-455-0669

Fax: 907-455-0601

greta_burkart@nps.gov

Kristina R. Creek

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709

Phone: 907-474-1600

Fax: 907-474-1604

creek@arcus.org

Cathy Curby

Arctic National Wildlife Refuge

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99709

Phone: 907-456-0500

cathy_curby@fws.gov

David Daum

Fishery Resource Office

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0290

Fax: 907-456-0454

david_daum@fws.gov

Tony DeGange

Alaska Science Center

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508-4626

Phone: 907-786-7046

Fax: 907-786-7021

tdegange@usgs.gov

Laurel Devaney

Fairbanks Fisheries Resource Office

U.S. Fish and Wildlife Service

101 12th Avenue, Room 222

Fairbanks, AK 99701

Phone: 907-456-0558

Fax: 907-456-0454

laurel_devaney@fws.gov

Eugenie Euskirchen

Institute of Arctic Biology

University of Alaska Fairbanks

311 Irving Building I

Fairbanks, AK 99775

Phone: 907-474-1958

ffese@uaf.edu

Judy Fahnestock

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709

Phone: 907-474-1600

Fax: 907-474-1604

judy@arcus.org

Craig L. Fleener

Division of Subsistence

Alaska Department of Fish and 

Game

1255 W 8th Street

PO BOX 115526

Juneau, AK 99802-5526

Phone: 907-465-4147

Fax: 907-465-2066

craig.fleener@alaska.gov

Brad Griffith

Alaska Cooperative Fish and Wildlife Research Unit

University of Alaska Fairbanks

PO Box 757020

Fairbanks, AK 99775-7020

Phone: 907-474-5067

Fax: 907-474-7872

ffdbg@uaf.edu

Julie Griswold

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

julie@arcus.org

Guido Grosse

Geophysical Institute

University of Alaska Fairbanks

903 Koyukuk Drive

Fairbanks, AK 99775

Phone: 907-474-7548

ggrosse@gi.alaska.edu

Raymond Hander

U.S. Fish and Wildlife Service

101 12th Avenue, Room 110

Fairbanks, AK 99701-6267

Phone: 907-456-0402

Fax: 907-456-0454

ray_hander@fws.gov

Melanie Hans

U.S. Fish and Wildlife Service

101 Front Street

Galena, AK 99741

Phone: 907-656-1231

melanie_hans@fws.gov

Geoffrey Haskett

Alaska Regional Office

U.S. Fish and Wildlife Service

1011 East Tudor Road

Anchorage, AK 99503

Phone: 907-786-3542

Fax: 907-786-3495

Geoff_Haskett@fws.gov

Larry D. Hinzman

International Arctic Research 

Center

University of Alaska Fairbanks

930 Koyukuk Drive

PO Box 757335

Fairbanks, AK 99775-7340

Phone: 907-474-7331

Fax: 907-474-1578

lhinzman@iarc.uaf.edu

Leslie Holland-Bartels

Alaska Science Center

U.S. Geological Survey

4230 University Drive, Suite 201

Anchorage, AK 99508-4664

Phone: 907-786-7000

Fax: 907-786-7150

leslie_holland-bartels@usgs.gov

Birte M. Horn-Hanssen

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

birte@arcus.org

Judy Jacobs

U.S. Fish and Wildlife Service

1011 E. Tudor Road

Anchorage, AK 99503

Phone: 907-786-3472

judy_jacobs@fws.gov

Jennifer Jenkins

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK

Phone: 907-456-0327

jennifer_jenkins@fws.gov

Tim Jennings

U.S. Fish and Wildlife Service

1011 East Tudor Road

Anchorage, AK 99503

Phone: 907-786-3505

timothy_jennings@fws.gov

Danielle Jerry

U.S. Fish and Wildlife Service

1011 East Tudor Road

Anchorage, AK 99503

Phone: 907-786-3335

Fax: 907-786-3901

Danielle_Jerry@fws.gov
131

Benjamin Jones

Alaska Science Center

U.S. Geological Survey

4230 University Drive, Suite 201

Anchorage, AK 99508-4650

Phone: 907-786-7033

Fax: 907-786-7036

bjones@usgs.gov

Janet C. Jorgenson

Arctic National Wildlife Refuge

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-456-0216

Fax: 907-456-0428

janet_jorgenson@fws.gov

M. Torre Jorgenson

ABR, Inc.—Environmental 

Research and Services

PO Box 80410

Fairbanks, AK 99709

Phone: 907-455-6777

Fax: 907-455-6374

tjorgenson@abrinc.com

Douglas L. Kane

Water and Environmental Research 

Center

University of Alaska Fairbanks

PO Box 755860

Fairbanks, AK 99775-5860

Phone: 907-474-7808

Fax: 907-474-7041

ffdlk@uaf.edu

Lon Kelly

Northern Field Office

Bureau of Land Management

1150 University Avenue

Fairbanks, AK 99709

Phone: 907-474-2368

Fax: 907-474-2280

lon_kelly@ak.blm.gov

Steve Kendall

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-456-0303

Fax: 907-456-0428

Steve_Kendall@fws.gov

David R. Klein

Institute of Arctic Biology

University of Alaska Fairbanks

PO Box 757020

Fairbanks, AK 99775-7020

Phone: 907-474-6674

Fax: 907-474-6967

ffdrk@uaf.edu

Richard B. Lanctot

Migratory Bird Management

U.S. Fish and Wildlife Service

1011 East Tudor Road, MS 201

Anchorage, AK 99503-6199

Phone: 907-786-3609

Fax: 907-786-3641

richard_lanctot@fws.gov

Peter H. Larsen

The Nature Conservancy

715 L Street, Suite 100

Anchorage, AK 99501

Phone: 907-276-3133, ext 113

Fax: 907-276-2584

plarsen@tnc.org

Brian E. Lawhead

ABR, Inc.—Environmental 

Research and Services

PO Box 80410

Fairbanks, AK 99708

Phone: 907-455-6777

Fax: 907-455-6781

lawhead@abrinc.com

Jim P. Lawler

National Park Service

4175 Geist Road

Fairbanks, AK 99709-3420

Phone: 907-455-0624

Fax: 907-455-0601

jim_lawler@nps.gov

Anna K. Liljedahl

International Arctic Research 

Center

University of Alaska Fairbanks

PO Box 757340

Fairbanks, AK 99775

Phone: 907-474-1951

ftakl@uaf.edu

Mark Lisac

U.S. Fish and Wildlife Service

PO Box 270

Dillingham, AK

Phone: 907-842-1063

mark_lisac@fws.gov

Wendy M. Loya

The Wilderness Society

705 Christensen Drive

Anchorage, AK 99501

wendy_loya@tws.org

Edward J. Mallek

Waterfowl Management

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0341

ed_mallek@fws.gov

Joseph Margraf

Alaska Cooperative Fish and 

Wildlife Research Unit

University of Alaska Fairbanks

PO Box 757020

Fairbanks, AK 99775-7020

Phone: 907-474-7661

Fax: 907-474-6716

ffjfm1@uaf.edu

Philip D. Martin

Ecological Services Fairbanks

U.S. Fish and Wildlife Service

101 12th Avenue, Room 110

Fairbanks, AK 99701

Phone: 907-456-0325

Fax: 907-456-0208

philip_martin@fws.gov

Angela Matz

Northern Alaska Ecological Services

U.S. Fish and Wildlife Service

101 12th Avenue, Room 110

Fairbanks, AK 99701

Phone: 907-456-0442

Fax: 907-456-0208

angela_matz@fws.gov

A. David McGuire

Alaska Cooperative Fish and 

Wildlife Research Unit

University of Alaska Fairbanks

214 Irving Building I

Fairbanks, AK 99775

Phone: 907-474-6242

Fax: 907-474-7872

ffadm@uaf.edu

Neil Mochnacz

Arctic Science Division, Central and 

Arctic Region

Fisheries and Oceans Canada

501 University Crescent

Winnipeg, MB R3T 2N6

Canada

Phone: 204-984-3147

Fax: 204-984-2403

Neil.Mochnacz@DFO-MPO.GC.CA

William Morris

Habitat Division

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7282

Fax: 907-459-7303

william.morris@alaska.gov

Larry Moulton

MJM Research

1012 Shoreland Drive

Lopez Island, WA 98261

Phone: 360-468-4821

lmoulton@rockisland.com
132

Karen Murphy

U.S. Fish and Wildlife Service

1011 E Tudor Road

Anchorage, AK 99503

Phone: 907-786-3501

Fax: 907-786-3501

karen_a_murphy@fws.gov

Stephen M. Murphy

ABR, Inc.—Environmental 

Research and Services

PO Box 80410

Fairbanks, AK 99708

Phone: 907-455-6777

Fax: 907-455-6781

smurphy@abrinc.com

Matt Nolan

Institute of Northern Engineering

University of Alaska Fairbanks

455 Duckering Bldg

PO Box 755910

Fairbanks, AK 99775-5910

Phone: 907-474-2467

Fax: 907-474-7979

matt.nolan@uaf.edu

Alvin Ott

Habitat Division

Department of Fish and Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7279

Fax: 907-459-7303

E-Mail: al.ott@alaska.gov

Ronnie Owens

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

ronnie@arcus.org

Tom Paragi

Division of Wildlife Conservation

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701

Phone: 907-459-7327

Fax: 907-452-6410

tom_paragi@fishgame.state.ak.us

Lincoln Parrett

Division of Wildlife Conservation

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1551

Phone: 907-459-7366

Fax: 907-459-7332

lincoln.parrett@alaska.gov

David Payer

Arctic National Wildlife Refuge

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-455-1830

Fax: 907-456-0428

david_payer@fws.gov

John F. Payne

North Slope Science Initiative

Bureau of Land Management

222 West 7th Avenue, #13

Anchorage, AK 99513-7599

Phone: 907-271-3431

Fax: 907-271-4596

jpayne@ak.blm.gov

B. Zeb Polly

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

zeb@arcus.org

Alex Prichard

ABR, Inc.—Environmental 

Research and Services

PO Box 80410

Fairbanks, AK 99708

Phone: 907-455-6777

aprichard@abrinc.com

Mary Rabe

Alaska Department of Fish and 

Game

PO Box 115526

Juneau, AK 99811

Phone: 907-465-6195

mary.rabe@alaska.gov

Kumi Rattenbury

National Park Service

4175 Geist Road

Fairbanks, AK 99709-3420

Phone: 907-455-0673

Fax: 907-455-0601

Kumi_Rattenbury@nps.gov

Deborah Rocque

Fairbanks Field Office

U.S. Fish and Wildlife Service

101 12th Avenue, Room 110

Fairbanks, AK 99701

Phone: 907-456-0272

Fax: 907-456-0208

deborah_rocque@fws.gov

Nora Rojek

Endangered Species Program

U.S. Fish and Wildlife Service 

101 12th Avenue, Room 110

Fairbanks, AK 99701

Phone: 907-456-0276

Fax: 907-456-0208

nora_rojek@fws.gov

Vladimir E. Romanovsky

Geophysical Institute

University of Alaska Fairbanks

PO Box 757320

Fairbanks, AK 99775-7320

Phone: 907-474-7459

Fax: 907-474-7290

ffver@uaf.edu

Diane M. Sanzone

Environmental Studies Group

BP Exploration (Alaska), Inc.

900 East Benson Boulevard

PO Box 196612

Anchorage, AK 99519-6612

Phone: 907-564-4857

Fax: 907-564-5020

Diane.Sanzone@BP.com

Brendan Scanlon

Sport Fish Division

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7268

brendan.scanlon@alaska.gov

Joel Schmutz

Alaska Science Center

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508-4626

Phone: 907-786-7186

Fax: 907-786-7021

jschmutz@usgs.gov

Robert W. Schneider

Northern Field Office

Bureau of Land Management

1150 University Avenue

Fairbanks, AK 99709

Phone: 907-474-2302

Fax: 907-474-2282

bob_schneider@ak.blm.gov

Stan Senner

Alaska State Office

National Audubon Society

715 L Street, Suite 200

Anchorage, AK 99501

Phone: 907-276-7034

Fax: 907-276-5069

ssenner@audubon.org
133

Mark B. Shasby

Alaska Science Center

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508-4650

Phone: 907-786-7065

Fax: 907-786-7150

shasby@usgs.gov

Richard Shideler

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701

Phone: 907-459-7283

Fax: 907-456-3091

dick.shideler@alaska.gov

Reija S. Shnoro

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

reija@arcus.org

Martha Shulski

Alaska Climate Research Center

University of Alaska Fairbanks

903 Koyukuk Drive

Fairbanks, AK 99775

Phone: 907-474-7885

martha@climate.gi.alaska.edu

Trey Simmons

National Park Service

4175 Geist Road

Fairbanks, AK 99709-3420

Phone: 907-455-0666

Trey_Simmons@nps.gov

LaVerne Smith

U.S. Fish and Wildlife Service

1011 East Tudor Road, MS361

Anchorage, AK 99503

Phone: 907-786-3544

Fax: 907-786-3848

laverne_smith@fws.gov

Melanie Smith

Audubon Alaska

441 W 5th Avenue, Suite 300

Anchorage, AK

Phone: 907-276-7034

masmith@audubon.org

Neesha Stellrecht

U.S. Fish and Wildlife Service

101 12th Avenue, Room 222

Fairbanks, AK 99701

Phone: 907-456-0297

Fax: 907-456-0208

neesha_stellrecht@fws.gov

Charla Sterne

U.S. Fish and Wildlife Service

1011 East Tudor Road, Stop 331

Anchorage, AK 99503

Phone: 907-786-3471

charla_sterne@fws.gov

Matthew Sturm

Cold Regions Research and 

Engineering Laboratory - Alaska

PO Box 35170

Fort Wainwright, AK 99703-0170

Phone: 907-361-5183

Fax: 907-353-5142

msturm@crrel.usace.army.mil

Eric J. Taylor

National Wildlife Refuge System

U.S. Fish and Wildlife Service

1011 East Tudor Road, MS 221

Anchorage, AK 99503-6199

Phone: 907-786-3846

Fax: 907-786-3905

eric_taylor@fws.gov

Amy Tidwell

Institute of Northern Engineering

University of Alaska Fairbanks

PO Box 755860

Fairbanks, AK 99775-5860

Phone: 907-474-2783

Fax: 907-474-7979

a.tidwell@uaf.edu

Declan Troy

Troy Ecological Research Associates 

2322 E 16th Avenue

Anchorage, AK 99508-2905

Phone: 907-276-3436

declan.troy@acsalaska.net

Tim Viavant

Alaska Department of Fish and 

Game

1300 College Road

Fairbanks, AK 99701-1599

Phone: 907-459-7266

Fax: 907-456-2259

tim.viavant@alaska.gov

Cashell Villa

Arctic National Wildlife Refuge

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-456-0275

cashell_villa@fws.gov

Douglas Vincent-Lang

Sport Fish Division

Alaska Department of Fish and 

Game

333 Raspberry Road

Anchorage, AK 99518-1599

Phone: 907-267-2339

douglas.vincent-lang@alaska.gov

Wendy K. Warnick

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-450-1600

Fax: 907-474-1604

warnick@arcus.org

Tara Wertz

Ecological Services

U.S. Fish and Wildlife Service

101 12th Avenue, Room 236

Fairbanks, AK 99701

Phone: 907-456-0444

Tara_Wertz@fws.gov

Matthew Whitman

Northern Field Office

Bureau of Land Management

1150 University Avenue

Fairbanks, AK 99709

Phone: 907-474-2249

Fax: 907-474-2280

Matthew_Whitman@blm.gov

Helen V. Wiggins

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

helen@arcus.org

Robert A. Winfree

Alaska Regional Office

National Park Service

240 W 5th Avenue, Office 521

Anchorage, AK 99501

Phone: 907-644-3516

Fax: 907-644-3816

robert_winfree@nps.gov

Mark Wipfli

Alaska Cooperative Fish and Wildlife Research Unit

University of Alaska Fairbanks

PO Box 757020

Fairbanks, AK 99775-7020

Phone: 907-474-6654

Fax: 907-474-6716

Mark.Wipfli@uaf.edu

Eve Witten

The Nature Conservancy

715 L Street, Suite 100

Anchorage, AK 99501

Phone: 907-276-3153

Fax: 907-276-2584

ewitten@tnc.org
134

David A. Yokel

Arctic Field Office

Bureau of Land Management

1150 University Avenue

Fairbanks, AK 99709

Phone: 907-474-2314

Fax: 907-474-2282

dave_yokel@blm.gov

Alison D. York

Arctic Research Consortium of the 

U.S.

3535 College Road, Suite 101

Fairbanks, AK 99709-3710

Phone: 907-474-1600

Fax: 907-474-1604

york@arcus.org

Steve Zack

North America Program

Wildlife Conservation Society

718 SW Alder Street, Suite 210

Portland, OR 97205

Phone: 503-241-3743

szack@wcs.org

James Zelenak

U.S. Fish and Wildlife Service

101 12th Avenue, Room 110

Fairbanks, AK 99701

Phone: 907-456-0354

Fax: 907-456-0208

jim_zelenak@fws.gov

Chris Zimmerman

Alaska Science Center

U.S. Geological Survey

4210 University Drive

Anchorage, AK 99508-4626

Phone: 907-786-7071

Fax: 907-786-7150

czimmerman@usgs.gov

Other Contributors

Jonathan Benstead

Department of Biological Sciences

University of Alabama

PO Box 870206

Tuscaloosa, AL 35487

Phone: 205-348-9034

Fax: 205-348-1403

jbenstead@bama.ua.edu

Stephanie M. Clemens

mountainphacelia@yahoo.com

Fred DeCicco

Fairbanks, AK

freddecicco@gmail.com

Linda Deegan

The Ecosystems Center

Marine Biological Laboratory

7 MBL Street

Starr 337

Woods Hole, MA 02543

Phone: 508-289-7487

Fax: 508-457-1548

ldeegan@mbl.edu

Vadim Fedorov

Institute of Arctic Biology

University of Alaska Fairbanks

PO Box 757000

Fairbanks, AK 99775

Phone: 907-474-1533

E-Mail: fnvf@uaf.edu

Richard Flanders

Fairbanks, AK

richardflanders@compuserve.com

Marie-Luce Hubert

Jean-Louis Klein 

http://www.klein-hubert-photo.com

Russ Mitchell

Inkworks

2324 Waterford Road

Fairbanks, AK 99709

Phone: 907-455-6378

Fax: 907-455-4740

inkworks@gci.net

Mitch Osborne

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99709

Phone: 907-456-0209

mitch_osborne@fws.gov

James D. Reist

Arctic Fish Ecology and Assessment 

Research Section

Fisheries and Oceans Canada

501 University Crescent

Winnipeg, MB R3T 2N6

Canada

Phone: 204-983-5032

Fax: 204-984-2403

Jim.Reist@dfo-mpo.gc.ca

Ted Swem

U.S. Fish and Wildlife Service

101 12th Avenue

Fairbanks, AK 99701

Phone: 907-456-0441

ted_swem@fws.gov

Ken Tape

Institute of Arctic Biology 

University of Alaska Fairbanks

PO Box 80425

Fairbanks, AK 99708

Phone: 907-374-9000

Fax: 907-353-5142

fnkdt@uaf.edu

Øivind Tøien

Institute of Arctic Biology

University of Alaska Fairbanks

PO Box 757000

Fairbanks, AK 99775

Phone: 907-474-6843

oivind.toien@uaf.edu

John E. Walsh

International Arctic Research 

Center

University of Alaska Fairbanks

PO Box 757340

Fairbanks, AK 99775-7340

Phone: 907-474-2677

Fax: 907-474-2643

jwalsh@iarc.uaf.edu

Ken Whitten

Fairbanks, AK

whitten@gci.net
135

Appendix 5:

Working Group

Charges and 

Members

Working Group Breakout Session Charges

Sideboards and Assumptions

Geographic Scope: The geographic scope includes terrestrial and freshwater ecosystems from the crest of the Brooks Range northward. The boundary with the marine system is recognized as fuzzy; coastal processes are 

acknowledged to affect terrestrial and freshwater systems and vice versa. 

Processes that affect nearshore coastal environments may be considered for 

those species that cross ecosystem boundaries. 

Priority Issues: It is recognized that climate change may influence organisms in multiple and complex ways. We intend to focus the discussion 

primarily on the following climate change effects:

•Change in relative abundance and distribution of habitat types on the landscape.

•Change in structural (including plant community structure) or physical 

characteristics of habitat.

•Change in trophic systems, including primary and secondary productivity, 

phenology, and forage/prey availability.

The importance of other potential effects of climate change—such as competitive interactions, invasive species, prevalence of disease, and contaminants—are recognized but are of secondary priority for this workshop.

Working Group Breakout Session I (Monday afternoon)

The goals of this session are to:

•Identify species or species groups that are expected to be sensitive indicators of the changes hypothesized in the climate scenarios and ecosystem 

pathway models.

•For each species, develop hypotheses regarding positive or negative 

response to changes in the availability of habitat, based on knowledge of 

species’ life histories and habitat requirements.

•For each species, identify specific parameters (e.g., distribution, abundance, demography, body condition, growth rate, etc.) that would be affected.

Groups should focus on landscape-level changes in habitat availability. 

Species should be selected for their value as indicators of climate change. 

Groups should NOT feel constrained to only those species or parameters 

that are easily measured. This breakout session is an opportunity for discussion on any and all species in the region that will be affected by climate 

change. Later in the workshop, we will consider feasibility issues when 

prioritizing the research and modeling needs that arise from the breakout 

group sessions. 

Working Group Breakout Session II (Tuesday morning)

The goal of this session is to refine draft conceptual models of climate effects 

on species, including processes that are not captured by habitat change models. Each working group will be presented with models drafted as a result 

of the scoping meetings. Groups are encouraged to consider “reasonable 

worst-case scenarios,” i.e., scenarios that are within the expected range of 

potential change AND would have the greatest magnitude effects, thus most 

detectable. For example:

•Birds: Trophic system shifts for consumers of invertebrates, coastal habitat 

availability.

•Mammals: Forage quantity and quality in summer, snow conditions, forage 

availability in winter.

•Fish: Stream system flow regimes, availability of river delta overwintering 

habitat.
136

Fish Working Group

Jeff Adams (leader) U.S. Fish and Wildlife Service

Jennifer Jenkins (recorder) U.S. Fish and Wildlife Service

David Atkinson University of Alaska

Bonnie Borba Alaska Department of Fish and Game

Guido Grosse University of Alaska Fairbanks

Douglas Kane University of Alaska Fairbanks

Anna Liljedahl (Monday) University of Alaska Fairbanks

Joseph Margraf University of Alaska Fairbanks

Neil Mochnacz Fisheries and Oceans Canada

William Morris Alaska Department of Fish and Game

Larry Moulton MJM Research

Matt Nolan University of Alaska Fairbanks

Amanda Rosenberger University of Alaska Fairbanks

T. Scott Rupp University of Alaska Fairbanks

Brendan Scanlon Alaska Department of Fish and Game

Rod Simmons U.S. Fish and Wildlife Service

Tim Viavant Alaska Department of Fish and Game

Matthew Whitman Bureau of Land Management

Mark Wipfli University of Alaska Fairbanks

Chris Zimmerman U.S. Geological Survey

Kristina Creek ARCUS Staff

Working Group Breakout Session III (Tuesday afternoon)

The goal of this final breakout session is to review the products from the 

first two breakout sessions and identify the most critical gaps in data and 

modeling needed to predict future habitats of arctic Alaska. Gaps could be of 

at least two types:

•Models have not been constructed.

•Models exist but are not supported by adequate data.

Identified gaps should focus on the underlying ecological and physical 

processes that may affect species in all three groups of interest (birds, fish, 

and mammals). The goal is to go beyond identification of data gaps for arctic 

species biology and refine our thinking of what is needed to gain predictive 

ability of the system-level physical processes and ecosystem functions.

Breakout session results will form the core content for a five-year strategic 

plan that identifies the priority research, modeling, and synthesis activities 

needed to predict climate-related impacts to fish and wildlife populations in 

the Arctic. 
137

Birds Working Group

Philip Martin (leader) U.S. Fish and Wildlife Service

James Zelenak (recorder) U.S. Fish and Wildlife Service

Alan Brackney U.S. Fish and Wildlife Service

Syndonia Bret-Harte University of Alaska Fairbanks

Steve Kendall U.S. Fish and Wildlife Service

Richard Lanctot U.S. Fish and Wildlife Service

Peter Larsen The Nature Conservancy

A. David McGuire University of Alaska Fairbanks

Vladimir Romanovsky University of Alaska Fairbanks

Joel Schmutz U.S. Geological Survey

Stan Senner National Audubon Society

Eric Taylor U.S. Fish and Wildlife Service

Amy Tidwell University of Alaska Fairbanks

Declan Troy Troy Ecological Research

Steve Zack Wildlife Conservation Society

Judy Fahnestock ARCUS Staff

Mammals Working Group

David Payer (leader) U.S. Fish and Wildlife Service

Tara Wertz (recorder) U.S. Fish and Wildlife Service

Stephen Arthur Alaska Department of Fish and Game

Erik Beever U.S. Geological Survey

Scott Brainerd Alaska Department of Fish and Game

Eugenie Euskirchen University of Alaska Fairbanks

Brad Griffith University of Alaska Fairbanks

Larry Hinzman University of Alaska Fairbanks

David Klein University of Alaska Fairbanks

Brian Lawhead ABR, Inc.

Anna Liljedahl (Tuesday) University of Alaska Fairbanks

Stephen Murphy ABR, Inc.

Tom Paragi Alaska Department of Fish and Game

Lincoln Parrett Alaska Department of Fish and Game

Alex Prichard ABR, Inc.

Richard Shideler Alaska Department of Fish and Game

Martha Shulski University of Alaska Fairbanks

Matthew Sturm Cold Regions Research and Engineering Lab

David Yokel Bureau of Land Management

Alison York ARCUS Staff
138

Managers Working Group

Deborah Rocque (leader) U.S. Fish and Wildlife Service

Michael Baffrey U.S. Department of the Interior

Dixie Birch U.S. Fish and Wildlife Service

Tony DeGange U.S. Geological Survey

Geoffrey Haskett U.S. Fish and Wildlife Service

Leslie Holland-Bartels U.S. Geological Survey

Tim Jennings U.S. Fish and Wildlife Service

Lon Kelly Bureau of Land Management

Dennis Lassuy U.S. Fish and Wildlife Service

John Payne North Slope Science Initiative

Mark Shasby U.S. Geological Survey

Robert Schneider Bureau of Land Management

LaVerne Smith U.S. Fish and Wildlife Service

Douglas Vincent-Lang Alaska Department of Fish and Game

Robert Winfree National Park Service

Helen Wiggins ARCUS Staff