1. CLIMATE CHANGE PLANNING FOR ALASKA’S FUTURE BIOME AND SPECIES SHIFTS

2. How will ecosystems and species shift with changing climate in Alaska? Connecting Alaska Landscapes into the Future With US Fish and Wildlife Service and other partners 2

3. What is climate change?  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 Usually refers to the complex effects of increased greenhouse gases in the atmosphere Incoming radiation from the sun gets trapped as heat

4. Why are there no exact answers?  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

5. 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

6. What can we do about climate change?  Mitigation = stopping it from happening  Energy conservation Insulation, fuel efficiency, waste reduction  Renewable energy Wind, solar, geothermal, and hydro  Carbon storage 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

7.  Forecast Planning  One Future  Scenario Planning  Multiple Futures  Scenarios overcome the tendency to predict, allowing us to see multiple possibilities for the future Scenario Planning vs. Forecasting What we know today +10% -10% Uncertainties Global Business Network (GBN) -- A member of the Monitor Group Copyright 2010 Monitor Company Group What we know today

8. 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

9. Scenarios and adaptation  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

10. 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?  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

11. SNAP climate models  Climate projections are based on global models  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

12. What data does SNAP have?  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

13. Processed data  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 2090-20992060-20692000-2009

14. Complex linked models  Shifting plants and animals (biomes and ecosystems)  Soil temperature and permafrost  Water availability  Farms and gardens  Forest fire Soil temperature at one meter depth: 1980’s, 2040’s, and 2080’s (Geophysical Institute Permafrost Lab, UAF)

15. Examples of SNAP projects  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? www.nenananewslink.com alaskarenewableenergy.org

16.  Biomes  Caribou  Alaska marmot  Trumpeter swans  Reed canary grass 16 Connecting Alaska Landscapes into the Future With US Fish and Wildlife Service and other partners

17. Project Partners

18. Goals 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 18

19. + 1 (Precipitation) 1 (Temperature) = Precipitation Temperature Mean decadal Starting: 2000-09 Future: 2030-39 2060-69 2090-99 Classification and regression trees Climate change forecasted from composite model using RandomForest TM at 5km grid MISSING! Sea level rise & Permafrost change

20. Used for Training Data Alaska Biomes Derived from Unified Ecoregions “Nowacki et al 2001” Arctic Boreal Boreal Transition North Pacific Maritime Aleutians Western Tundra 20

21. Current biomes in Alaska and western Canada http://geogratis.cgdi.gc.ca/geogratis/en/collection/detail.do?id=4361

22. Predicted biome/climate 2000-2009 Arctic AK Boreal Boreal Transition N. Pacific Maritime Aleutian Islands Western Tundra

23. Predicted biome/climate 2030-2039

24. Predicted biome/climate 2060-2069

25. Predicted biome/climate 2090-2099

26. Potential Change: Current - 2100 (Note that actual species shifts lag behind climate shifts)

27. Resiliency Red = 3 changes Orange = 2 changes Light Green = 1 change Dark Green = No Changes (refugia) 27

28. Modeling Trumpeter Swan Occurrence: Future Predictions based on Ice Free Days SNAP data and Connectivity

29. Trumpeter Swan Data (2005 Trumpeter Swan Survey, a census flown every 5 years in August) Provided by Debbie Groves via Bob Platte Tundra Swan data are not available, yet 29

30. 30 2090-2099 2060-2069 2030-2039 2000-2009

31. 2099 with nonforest + ice-free masks 31

32. ALASKA MARMOT Photo: AKNHP website

33. Known occurrences of Alaska Marmots

34. A new layer: DEM roughness

35. 2009 2099 2069 2039 Marmot distribution using climate and roughness

36. Modeling Canary Reed Grass: Future Predictions of an Invasive Species (based on Road Proximity and SNAP climatologies and Connectivity) 36

37. 2009 + roads + known occurrences 2039 2069 2099 GREEN = none YELLOW = low RED = high Reed Canary Grass potential distribution 37

38. How can we forecast climate and caribou distribution?

39. 39

40. Future Potential Caribou Range Distribution (all herds combined) 2009 2030-2039 2060-2069 2090-2099 legend: purple= winter green= summer

41. Conservation Strategies? 41

42. Lessons from species modeling… 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

43. 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?