CLIMATE CHANGE PLANNING FOR
ALASKA’S FUTURE
BIOME AND SPECIES SHIFTS
Connecting Alaska
Landscapes into the Future
With US Fish and Wildlife Service and other partners
How will ecosystems
and species shift
with changing
climate in Alaska?
2
What is climate change?
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 Usually refers to the complex effects of
increased greenhouse gases in the
atmosphere
 Incoming radiation from the sun gets
trapped as heat
Because ocean currents and air currents
control climate, warming in one part of
the globe may cause cooling elsewhere
Heat increases evaporation and
transpiration, so clouds and rainfall also
change
Why are there no exact answers?

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Other factors besides greenhouse
gases affect climate, e.g volcanoes,
solar variation, and ocean currents
Weather varies from day to day
Climate varies over cycles of years,
centuries, and millennia
Water vapor also traps heat, and
climate in turn effects how much
water vapor is in the atmosphere
We don’t know exactly how much
carbon will be released, because
this depends on global development
and international cooperation
http://geology.com/news/labels/Global-Warming.html
How do we know it’s happening?

Measurements
 Average
yearly temperatures
 Precipitation
 Atmospheric gases

Models
 Past
and present trends
 Linking oceans, atmosphere,
and energy from the sun
What can we do about climate change?

Mitigation = stopping it from happening

Energy conservation


Renewable energy


Wind, solar, geothermal, and hydro
Carbon storage


Insulation, fuel efficiency, waste reduction
Trees, oceans, and soils can all store carbon
and keep greenhouse gases out of the
atmosphere
Adaptation = dealing with the effects that
are already occurring


Reactive: as each crisis happens
Proactive: planning ahead
Wind turbines at Selawik AK
http://www.avec.org/galleries/Selawik/Selawik_WindTurbi
nes.jpg
Scenario Planning vs. Forecasting

Scenarios overcome the tendency to predict, allowing us to see multiple possibilities for the future

Forecast Planning

-10%
One Future
+10%
What we know today
Global Business Network (GBN) -- A member of the Monitor Group


Scenario Planning
Multiple Futures
Uncertainties
What we know today
Copyright 2010 Monitor Company Group
Scenarios: “what if” stories

Everyday choices are based on scenarios
 Applying
for a job
 Deciding what to wear
 Buying a lottery ticket

Examining scenarios
 What
are possible outcomes?
 What is the likelihood of each outcome?
 How much do we want to avoid the bad outcomes?
 How desirable are the good outcomes?
 How do we balance time and costs against risks?
http://mareeconway.com/blog
Scenarios and adaptation

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Plan for several potential
futures, not just one
Consider human choices
and political changes
Account for uncertainty
When the future is
uncertain, resiliency is
important
Communicate and
collaborate
http://mareeconway.com/blog
http://www.geog.mcgill.ca/faculty/peterson/susfut/resilienc
e/rLandscape.html
SNAP scenarios

What is most important to Alaskans and
other Arctic partners?
What changes are most likely?
 What changes will have the greatest impact?
 What are we best able to predict?
 How can we adapt to those changes?
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Scenarios are linked to SNAP models
Climate models
 Models of how people use land and resources
 Other models linked to climate and human
behavior

www.snap.uaf.edu
SNAP climate models
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Climate projections are based on global models
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Three possible scenarios of greenhouse gas emissions
Different models of how the ocean and atmosphere may respond
SNAP selected the models that were most accurate in the far
north
We scaled down the model to account for local features such
as mountains and coastlines
Global Circulation Model (ECHAM5) Figure 1A from Frankenberg et al., Science,
Sept. 11, 2009
What data does SNAP have?
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Temperature
Precipitation (rain and snow)
Every month of every year from
1900 to 2100 (historical +
projected)
5 models, 3 emission scenarios
Available as maps, graphs, charts,
raw data
On line, downloadable, in Google
Earth, or in printable formats
Projected January
temperatures, 1980 and 2099
Processed data
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
Raw data on temperature and precipitation can be
linked to other models to create more useful
products
Examples include thaw dates, freeze-up dates,
season length, soil temperature, and water
availability
Days between
spring thaw
and autumn
freeze-up
2000-2009
2060-2069
2090-2099
Complex linked models
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Shifting plants and animals (biomes and ecosystems)
Soil temperature and permafrost
Water availability
Farms and gardens
Soil temperature at one meter depth:
Forest fire
1980’s, 2040’s, and 2080’s (Geophysical
Institute Permafrost Lab, UAF)
Examples of SNAP projects
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alaskarenewableenergy.org
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www.nenananewslink.com
How will climate change affect
Alaska’s National Parks?
Will farmers near Fairbanks be able
to plant new crops?
Will plant and animals species shift?
Will hydroelectric dams have enough
water?
Can we expect more forest fires?
Can tour companies plan for more
summer visitors?
Connecting Alaska
Landscapes into the Future
With US Fish and Wildlife Service and other partners
 Biomes
 Caribou
 Alaska marmot
 Trumpeter swans
 Reed canary grass
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Project Partners
Goals
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Identify lands and waters in
Alaska that likely serve as
landscape-level migration
corridors currently and into the
future given climate change
Identify conservation strategies
with our partners that will help
maintain landscape-level
connectivity
Climate change forecasted from composite model
using RandomForestTM at 5km grid
Precipitation
Temperature
MISSING! Sea level rise & Permafrost change
Mean decadal
Starting:
2000-09
Future:
2030-39
2060-69
2090-99
Classification and regression trees
1 (Precipitation)
+
1 (Temperature)
=
Used for Training Data
Alaska Biomes
Derived from Unified Ecoregions
“Nowacki et al 2001”
Arctic
Boreal
Boreal Transition
Western
Tundra
North Pacific
Maritime
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Current biomes in Alaska and western Canada
http://geogratis.cgdi.gc.ca/geogratis/en/collection/detail.do?id=4361
Predicted biome/climate 2000-2009
Arctic
AK Boreal
Western
Tundra
Boreal Transition
N. Pacific Maritime
Aleutian Islands
Predicted biome/climate 2030-2039
Predicted biome/climate 2060-2069
Predicted biome/climate 2090-2099
Potential Change: Current - 2100
(Note that actual species shifts lag behind climate shifts)
Resiliency
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Red = 3
changes
Orange = 2
changes
Light Green = 1
change
Dark Green =
No Changes
(refugia)
Modeling Trumpeter Swan Occurrence:
Future Predictions based on Ice Free Days
SNAP data and Connectivity
Trumpeter Swan Data
(2005 Trumpeter Swan Survey,
a census flown every 5 years in August)
Provided by Debbie Groves via Bob Platte
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Tundra Swan data
are not available, yet
2000-2009
30
2060-2069
2030-2039
2090-2099
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2099 with nonforest +
ice-free masks
ALASKA
MARMOT
Photo: AKNHP website
Known occurrences of Alaska Marmots
A new layer: DEM roughness
Marmot distribution using climate and roughness
2009
2069
2039
2099
Modeling Canary Reed Grass:
Future Predictions of an Invasive Species
(based on Road Proximity and SNAP climatologies
and Connectivity)
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Reed Canary Grass potential distribution
2039
2009 + roads + known
occurrences
GREEN = none
YELLOW = low
RED = high
2069
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2099
How can we forecast climate
and caribou distribution?
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Future Potential Caribou Range Distribution
(all herds combined)
legend:
purple= winter
green= summer
2009
2060-2069
2030-2039
2090-2099
Conservation Strategies?
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Lessons from species modeling…
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Creation of climatic niche is possible to suggest trends but
must be done thoughtfully and acknowledge limitations
Even simple models of distribution shifts require more data
than we have readily available

Classic connectivity models are scale- and species-dependent

Invasive plant spread likely to accelerate
Recommendations:
Better modeling
• More species
• More data inputs
• Scenario analysis
Delineation and monitoring
• Refugia
• Regions of extreme change
Anticipatory adaptation
• Assisted migration?
• New protected areas?
• New protected species?