ANDY HANSEN Montana State University

Transcription

1 ANDY HANSEN Montana State University

2 Vulnerability of Tree Species and Biome Types to Climate Change in the U.S. Northern Rocky Mountains and Yellowstone Andy Hansen, Linda Phillips, Tony Chang, Nathan Piekielek, Katie Ireland Montana State University and Penn State University NASA Applied Sciences Program (NNH10ZDA001N - BIOCLIM) GNLCC Webinar March

3 Which tree species and biome types are most vulnerable to climate change and how can management help? Studies Summarized Meta-analysis of tree species and biome climate suitability across the US Northern Rockies. Hansen, Phillips Forest Ecology and Mgt. Habitat suitability of tree species in Greater Yellowstone. Piekielek, Hansen, Chang. In Review. EcoInformatics. Climate suitability modeling for whitebark pine in Yellowstone. Chang, Hansen, Piekielek Plos ONE. Implications for management: WBP in the GYE. Hansen et al. In Review. Biol. Cons.; Ireland et al. In Prep.

4 Landscape Climate Change Vulnerability Project Principle Researchers A Hansen, C Whitlock, E Shanahan: Montana State Univ S Goetz, P Jantz: Woods Hole Research Center B Monihan, J Gross: NPS I&M Program T Olliff: NPS / Great Northern LCC F Melton: CSU Monterey Bay / NASA Ames D Theobald: Conservation Science Partners Agency Collaborators Western US NPS I&M Greater Yellowstone Network: K Legg NPS I&M Rocky Mountain Network: M Britten GYCC: V. Kelly GYCC Whitebark Pine Subcom: K Buermeyer Grand Teton National Park: D. Reinhart Yellowstone National Park: A Rodmann Rocky Mountain National Park: B Bobowski Goal: Understand and manage wildland ecosystems under climate change Study Areas Eastern US NPS I&M Appalachian Highlands Network: R Emmott NPS I&M Eastern Rivers and Mountains Network: M Marshall NPS I&M Mid-Atlantic Network: J Comiskey Delaware Water Gap National Recreational Area: R Evans, L Morelock Great Smoky Mountains National Park: J Renfro Shenandoah National Park: J Schaberl NASA Applied Sciences Program North Central Climate Sciences Center MT EPSCoR

5 Collaborative Approach to Climate Adaptation Glick et al Scanning the Conservation Horizon. John Gross, NPS Climate Scientist Ben Bobowski, Chief of Resources, Rocky Mountain National Park

6 Scientific Assessment

7 Scientific Assessment

8 Climate Envelope Modeling N. Zimmerman 2014 Identify places where future climate is projected to be suitable for a species. Latitude (Y) Longitude (X) 1. Identify where the species is present 2. Obtain climate data for these locations P pres = f (climate) Temperature Moisture 4. Project presence under future conditions 3. Statistically relate presence to climate

9 Climate Envelop Modeling Ignores Change in Disturbance / pests Competition with other species Ignores Adaptive capacity: dispersal, genetic variation, etc. Utility Climate suitability is a strong indicator of where viable populations may be able to exist. Other controlling factors can be manipulated through management. Thus, knowledge of climate suitability is a first filter for prioritizing research and management.

10 Meta-analysis for US Northern Rockies Study Rehfeldt et al Statistical modeling method Reference and future projection periods Random Forests , 2060, 2090 Scenarios / GCMs A1, B2 / Consensus of CGCM3, GFDLCM21, HADCM3 Vegetation units Biomes Crookson et al Random Forests , 2060, 2090 A1, B2 / CGCM3, GFDLCM21, HADCM3 Tree species Coops and Waring 2011 Gray & Hamann 2013 Bell et al Decision Tree Regression s, 2050 s, 2080 s Random Forests s, 2050s, 2080s Baysian Logistic Regression A1, B2 / CGCM3 Consensus of AIFI, A2, B1, B2 under CGCM, CSIRO2, HADCM3, ECHAM4, PCM A1, B2 / Average of 16 GCMs Tree species Tree species Tree species Selected based on: GNLCC or wider in extent; used comparable GCMs, scenarios, methods; grain size projection results available.

11 Future Climate Projection: Scenarios Story Line Business as usual emissions Global reductions in emissions IPCC CMIP4 (2007) A2 B1 IPCC CMIP5 (2013) RCP 8.5 RCP 4.5

12 Future Climate GYE PACE CMIP5, 8 GCM ensemble average Reference period: average Change in temperature by 2100 ( C) RCP 4.5 RCP Change in PPT (mm) by 2100 RCP 4.5 RCP (7.5%) 130 (16.3%) Context: Mean July temperature across North America since the end of the last ice age years ago varied ~5 0 C (Viau et al. 2006).

13 CMIP5, 8 GCM ensemble average, 800 m Future Climate GYE PACE Aridity Index (PET/PPT) RCP 4.5 RCP 8.5

14 Biome Types Current 2090 A2, B1, 3 GCM consensus

15 Biome Types A2, B1, 3 GCM consensus Percent of GNLCC Suitable in Climate

16 Tree Species Coops & Waring Crookston et al. Gray & Hamann Bell et al. A2 Scenario Subalpine Montane Mesic Western redcedar Western hemlock Percent of GNLCC Suitable in Climate, Reference Period to 2100

17 Change in Spatial Patterns A2 Scenario

18 Change in Spatial Patterns A2 Scenario

19 Vulnerability Assessment Based on Potential Impact Time Period Metric Units Vulnerability Ranking Current Period Area of suitable habitat Percent of study area 5: Very high (<10% of area) 4: High (10<30% of area) 3: Medium (30<50% of area) 2: Low (50<75% of area) Late century (e.g., ) Loss of reference-period suitable habitat Naturally colonizable newly suitable habitat by Newly suitable habitat by requiring assisted migration Percent loss of area from the reference period % gain in suitable habitat <=30 km from ref suitable) Percent gain in suitable habitat >30 km from ref suitable) 1: Very low (>=75% of area) 5: Very high (>75%) 4: High (>50-75%) 3: Medium (>30-50%) 2: Low (>10-30%) 1: Very low (<=10%) 0: very low gain (0<10%) -1: low gain (10<50%) -2: mod gain (50<100%) -3: large gain (100<150%) -4: very large gain (>=150%) 0: low gain (0<20%) -1: mod gain (20<100%) -2: large gain (>100%)

20 Vulnerability Assessment Based on Potential Impact Average among studies for A2 scenario

21 Habitat Suitability Modeling: Greater Yellowstone Methods Chang et al. 2014; Piekielek et al. in review Response Data 2,569 data points from FIA, GYCC, WLIS, GYRN I&M Predictor Data PRISM climate (19 variables) Monthly water balance using Thornthwaite equation (10 variables) Parent material, topography (10 variables) Random Forests Species Sagebrush spp., Juniper spp. Limber pine, Aspen, Douglas fir, Lodgepole Pine, Subalpine fir, Engleman spruce, Whitebark pine Analyses NC CSC Software for Assisted Habitat Modeling (SAHM) VisTrails package Boosted Regression Trees, Logistic Regression, Multivariate Adaptive Regression Splines, and Random Forest Model validation based on ROC for withheld data GCMs Best 9 CHIP5 GCMs WBP Suitability under 9 GCMs

22 Greater Yellowstone Douglas fir RCP 8.5 scenario N Suitable to Suitable Suitable to Unsuitable Unsuitable to suitable

23 Greater Yellowstone Juniper RCP 8.5 scenario Suitable to Suitable Suitable to Unsuitable Unsuitable to suitable

24 Greater Yellowstone Lodgepole pine RCP 8.5 scenario YNP Photo Archives Suitable to Suitable Suitable to Unsuitable Unsuitable to suitable

25 Greater Yellowstone Subalpine fir RCP 8.5 scenario Suitable to Suitable Suitable to Unsuitable Unsuitable to suitable

26 Greater Yellowstone Whitebark Pine RCP 8.5 scenario Prob. Presence > 0.42 N 2010

27 Greater Yellowstone Whitebark Pine RCP 8.5 scenario Prob. Presence > 0.42 N 2040

28 Greater Yellowstone Whitebark Pine RCP 8.5 scenario Prob. Presence > 0.42 N 2070

29 Greater Yellowstone Whitebark Pine RCP 8.5 scenario Prob. Presence > 0.42 N 2099

30 Greater Yellowstone Whitebark Pine RCP 8.5 scenario Prob. Presence > 0.42 N % Suitable Habitat RCP RCP

31 Climate Envelope Modeling Conclusions In the Northern Rockies and Yellowstone, subalpine forests are high in vulnerability to climate change and lower treeline forests are pushed substantially upslope. These results might suggest that upper and lower treeline forests are least resilient to climate change, beetles, fire. In these zones of forest decline, ecosystem services relating to snowpack, runoff, and food and habitat for other species will be reduced. Climate suitability for tree species is an important filter for prioritizing research and management. YNP Photo Archives

32 Collaborative Approach to Climate Adaptation Glick et al Scanning the Conservation Horizon. John Gross, NPS Climate Scientist Ben Bobowski, Chief of Resources, Rocky Mountain National Park

33 Informing implementation of the Greater Yellowstone Coordinating Committee s Whitebark Pine Strategy based on climate sciences MSU and UM: Andrew Hansen, Tom Olliff, Cathy Whitlock et al. GYCC WBP Subcommittee: Karl Buermeyer, Kelly McClosky, Dan Reinhart, Kristen Legg Funding: North Central Climate Sciences Center

34 Management Implications for Whitebark Pine RCP 4.5 RCP 8.5 Core Habitat. Manage to retain the species in these vitally important zones. Deteriorating Habitat. Give up? Manage towards Scenarios of Viability? Future habitat. Manage for natural colonization and assisted colonization.

35 Adaptive Management Opportunities

36 Adaptive Management Opportunities

37 Adaptive Management Opportunities

38 Informing implementation of the Greater Yellowstone Coordinating Committee s Whitebark Pine Strategy based on climate sciences MSU and UM: Andrew Hansen, Tom Olliff, Cathy Whitlock et al. GYCC WBP Subcommittee: Karl Buermeyer, Kelly McClosky, Dan Reinhart, Kristen Legg Objectives 1. Ecological forecasting under alternative IPCC climate and land use scenarios. 2. Analyzing WBP response to climate and extreme climate events over the past 15,000 years. 3. Develop spatially explicit WBP management alternatives. 4. Evaluate the management alternatives under future climate scenarios: WBP goals Ecosystem services derived from WBP Cost of implementation. 5. Draw recommendations for implementation of the GYCC WBP strategy under climate change. Funding: North Central Climate Sciences Center

39 Workshop Prospectus Vegetation Vulnerability across the Greater Yellowstone Ecosystem: Managing under Climate Change Date and Venue April 9, 2015: USGS Science Center, Bozeman, MT Objectives 1. Synthesize results from the NASA Landscape Climate Change Vulnerability Project (LCCVP)* study on climate change, ecological response, vulnerability assessment. 2. Identify management-relevant issues for vegetation in the GYE based on LCCVP, Northern Rockies Adaptation Partnership, Greater Yellowstone Coordinating Committee, and related activities. 3. Attempt to close the loop on the Climate Smart Cycle by outlining approaches for developing/evaluating/implementing/monitoring climate adaptation strategies.

40 Acknowledgements NASA Applied Sciences Program (Grant 10-BIOCLIM ) NSF EPSCoR Track-I EPS (INSTEP 3) NASA Land Cover Land Use Change Program North Central Climate Sciences Center Federal agency collaborators

41 Literature Cited Hansen, A.J. and L.B. Phillips, Which tree species and biome types are most vulnerable to climate change in the US Northern Rocky Mountains?, Forest Ecology and Management, 338: pp Chang, T., A.J. Hansen, N. Piekielek Patterns and variability of projected bioclimate habitat for Pinus albicaulis in the Greater Yellowstone Ecosystem. PLOS One. November 05, Piekielek, N., A.J. Hansen, T. Chang. In Review. Using custom scientific workflow software and GIS to inform protected area climate adaptation planning across Greater Yellowstone. EcoInformatics. Hansen, A.J., K. Ireland, K. Legg, E. Barge, M. Jenkis, M. Pillet. In Review. Can whitebark pine persist in Greater Yellowstone? Exploring Scenarios of Viability for species under deteriorating climates. Biological Conservation.