Connecting downscaled climate data to ecological modeling

1. Connecting downscaled climate data to ecological modeling NCPP Quantitative Evaluation of Downscaling August 12-16, 2013, NCAR Foothills Laboratory, Boulder, Colorado Jeff Morisette, Marian Talbert, and many others

2. Connecting downscaled climate data to ecological modeling • It is a major focus of the USGS National Climate Change and Wildlife Science Center • It is a major focus for the North Central Climate Science Center • It is complex and difficult

3. Thanks!Questions? morisettej@usgs.gov 303-968-8986

4. Outline • Review of the Department of Interior Climate Science Centers • Vulnerability Assessments and the NCPP pilot project • Species Distribution Modeling and climate indices • A community-based integrated modeling approach • Conclusions

5. Outline • Review of the Department of Interior Climate Science Centers • Vulnerability Assessments and the NCPP pilot project • Species Distribution Modeling and climate indices • A community-based integrated modeling approach • Conclusions

6. Catherine Jarnevich Tracy Holcombe Colin Talbert Marian Talbert USGS-CSU Resource for Advanced Modeling Sunil Kumar Cam Aldridge Tom Stohlgren Dennis Ojima Tom Hilinski David Koop Claudio Silva Denis Ojima Andy Hansen Joe Barsugli David Blodgett Emily Fort Robin O’Malley Shawn Carter Doug Beard PetrVotava Rama Nemani Paul Evangelista

7. Secretarial Order 3289:DOI Climate Science Centers Mission: To provide the best possible climate science to Department of Interior land managers

12. Outline • Review of the Department of Interior Climate Science Centers • Vulnerability Assessments and the NCPP pilot project • Species Distribution Modeling and climate indices • A community-based integrated modeling approach • Conclusions

13. A framework for Vulnerability Assessment under a changing climate Glick, P., Stein, B.A., and Edelson, N.A., eds., 2011, Scanning the conservation horizon: A guide to climate change vulnerability assessment: Washington, D.C., National Wildlife Federation, 176 p.

14. In space and time

15. Resistance Sensitivity Resilience Exposure Transition Potential Impact Adaptive Capacity Vulnerability

16. Pilot Project Ecological Response Models Climate data based on results of objective, quantitative evaluation DOI Management Objectives/Goals

17. Climate data • Using acceptable global climate models, considering: • Historical and future scenarios and • Downscaling techniques • NCPP provides: • Customized climate summaries • Guidance on their use and • Evaluation of accuracy • Management Objectives/Goals • LCCs provide: • decision making context • Target species, habitat or ecosystem Ecological Response Models Conceptual Models General Characterization Models Expert Opinion Models Habitat Occupancy Models Vegetation/Habitat Response Models Physiologically Based Models Ecological Models

18. Outline • Review of the Department of Interior Climate Science Centers • Vulnerability Assessments and the NCPP pilot project • Species Distribution Modeling and climate indices • A community-based integrated modeling approach • Conclusions

19. Vulnerability Assessment through Species Distribution Modeling

20. Specific examples from impacts modeling: Mountain Pine Beetle Current conditions 2020 a2a 2020 b2a 2050 a2a 2050 b2a potential distribution extent under current climate conditions distribution increases distribution decreases Most important climate predictor was Precipitation of the warmest quarter Evangelista PH, S Kumar, TJ Stohlgren, and NE Young 2011. Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US. Forest Ecology and Management 262: 307–316 Using Maxent modeling and average of CCCMA, HadCM3, and CSIRO climate projections

21. Outstanding issues for indices • Uncertainty how does climate model and projection uncertainty propagate to indices • Multiple parameters for each indexwith little consensus or standard • Significant combinatorics problemnumber of GCM x number of downscaling techniques x number of emissions scenarios x derivative parameters

22. Outline • Review of the Department of Interior Climate Science Centers • Vulnerability Assessments and the NCPP pilot project • Species Distribution Modeling and climate indices • A community-based integrated modeling approach • Conclusions

23. Vulnerability Assessment through Species Distribution Modeling

25. Vulnerability Assessment through Species Distribution Modeling

26. Input data Preprocessing Preliminary model analysis & decision Correlative models Output routines

27. …making our modeling transparent and repeatable. Morisette et al., 2013. VisTrails SAHM: visualization and workflow management for species habitat modeling. Ecography 36: 129–135. doi: 10.1111/j.1600-0587.2012.07815.x

28. Input data Preprocessing Preliminary model analysis & decision Correlative models Output routines

29. Outstanding issues for Ecological Response Modeling • Species Distribution Modeling: we are just starting to work on: • more temporally refined modeling (for animal migration or life cycle stages) • modeling the spatial distribution of a disease or infestations of a host population; which requires some novel considerations • utilizing dynamic vegetation models as input to the species distribution models • consideration of distributional metrics • The NC CSC is working with USGS Modeling of Watershed Systems on integrating the USGS USGS Monthly Water Balance model into VisTrails • Most ecological response models involve a decision on how to extract gridded data for point observations

30. Visual MDS and Model Output Example: Resource Selection Analysis (RSF tool) courtesy of Bob Crabtree, YERC Merged Data Set 1 2 3 4 Single point ‘drilling down through’ data layers is basis for most modeling approaches Model prediction

33. Summary and Conclusion • The Department of Interior Climate Science Centers (CSCs) are working to bring the best possible climate science to land management decisions. • The North Central CSC is organized around three foundational science teams (climate, impacts, and adaptation). • Climate derivatives (or indices) are a key component to relating climate information to species vulnerability assessments through species distribution modeling. • NC CSC is focusing on species distribution modeling with predictor layers (including climate derivatives) remaining in “the cloud” accessed through machine services. • The NC CSC welcomes collaboration from the climate modeling and climate derivatives community on these issues.