connecting downscaled climate data to ecological modeling ncpp quantitative evaluation of...
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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
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
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
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
USGS-CSUResource forAdvanced Modeling
Catherine JarnevichTracy HolcombeColin TalbertMarian Talbert
Sunil KumarCam AldridgeTom StohlgrenDennis OjimaTom Hilinski
David KoopClaudio Silva
Petr VotavaRama Nemani
Paul Evangelista
Denis OjimaAndy HansenJoe Barsugli
David BlodgettEmily FortRobin O’MalleyShawn CarterDoug Beard
Secretarial Order 3289:DOI Climate Science Centers
Mission:To provide the best possible climate science to Department of Interior land managers
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
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.
In space and time
Vulnerability
Potential Impact
Adaptive Capacity
Sensitivity
Exposure
Resistance
Resilience
Transition
Ecological Response
Models
DOI Management Objectives/Goals
Climate data based on results of objective, quantitative evaluation
Pilot Project
Climate dataUsing 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
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
Vulnerability Assessment through Species Distribution Modeling
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
2020a2a
2050 b2a
2050a2a
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
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
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
Vulnerability Assessment through Species Distribution Modeling
Vulnerability Assessment through Species Distribution Modeling
Preliminary model analysis & decision Output routines
Input data
Preprocessing
Correlative models
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.
Preliminary model analysis & decision Output routines
Input data
Preprocessing
Correlative models
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
Visual MDS and Model OutputExample: 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
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4
Merged Data Set
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.