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. USGS-CSU R esource for A dvanced M odeling Catherine Jarnevich Tracy Holcombe Colin Talbert Marian Talbert Sunil Kumar Cam Aldridge Tom Stohlgren Dennis Ojima Tom Hilinski David Koop Claudio Silva Petr Votava Rama Nemani Paul Evangelista Denis Ojima Andy Hansen Joe Barsugli David Blodgett Emily Fort Robin O’Malley Shawn Carter Doug Beard

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. Vulnerability Potential Impact Adaptive Capacity Sensitivity Exposure Resistance Resilience Transition

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

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 Conceptual Models General Characterization Models Expert Opinion Models Ecological Response 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 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 2020 b2a Current conditions 2020 a2a 2050 b2a 2050 a2a potential distribution extent under current climate conditions distribution increases distribution decreases Most important climate predictor was Precipitation of the warmest quarter 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 index with little consensus or standard Significant combinatorics problem number 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

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

27. 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 …making our modeling transparent and repeatable.

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

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 Single point ‘drilling down through’ data layers is basis for most modeling approaches Model prediction 1 2 3 4 Merged Data Set

33. Summary and Conclusion 1.The Department of Interior Climate Science Centers (CSCs) are working to bring the best possible climate science to land management decisions. 2.The North Central CSC is organized around three foundational science teams (climate, impacts, and adaptation). 3.Climate derivatives (or indices) are a key component to relating climate information to species vulnerability assessments through species distribution modeling. 4.NC CSC is focusing on species distribution modeling with predictor layers (including climate derivatives) remaining in “the cloud” accessed through machine services. 5.The NC CSC welcomes collaboration from the climate modeling and climate derivatives community on these issues.