|Home||Archived October 29, 2018||(i)|
projects > climate envelope modeling for evaluating anticipated effects of climate change on threatened and endangered species in the greater everglades
> work plan
Project Work Plan
Department of Interior USGS GE PES
Fiscal Year 2010 Study Work Plan
Study Title: Climate envelope modeling for evaluating anticipated effects of climate change on threatened and endangered species in the Greater Everglades
Overview & Objective(s): Our proposed project works toward finding solutions to problems related to long-term conservation planning in the face of the uncertainty surrounding climate change. We propose to work with resource managers to develop tools at appropriate spatial and temporal scales to assist with decision making. This project will result in both predictive ecological models and methodology for development and use of climate-based species-habitat relationships that will aid resource managers in long-term planning for sustainability of species.
To demonstrate the process and utility of our proposed approach, we will begin by focusing on the 21 threatened and endangered (T&E) terrestrial vertebrates in South Florida (Table 1). By virtue of its physical features and geography, Florida, and in particular, South Florida will be highly susceptible to climate changes, specifically with regard to already apparent sea level rise. Although methodology and developed products will be applicable to other species and regions, our initial focus is to work with partners in the southeastern region and expand the list of species of interest in that region.
For each species we will use existing information for these 21 T&E species (U.S. Fish and Wildlife Service 1999, Cox et al. 1994), augment it with up-to-date data, and identify critical limiting factors directly and indirectly influenced by climate change. This information will be provided in the form of databases, species models (including climate envelopes), maps, and a desktop application that can be used in conjunction with projections of climate change, land use, and vegetation change to examine potential impacts on T&E species and their habitats.
Recent attention to potential impacts of climate change on habitats and species has focused on development of methods and tools that not only address current habitat and landscape conditions for species, but also help resource managers to look at potential future conditions to aid in long-term planning. Key elements to our proposed work are identifying limiting factors for species with respect to their habitats, compiling and applying population and habitat models, explicitly addressing uncertainties (assumption-driven research), and developing species habitat decision support. Data collected will be useful as inputs for efforts to assess species vulnerability.
Specific Relevance to Major Unanswered Questions and Information Needs Identified:
Status: Many conservation and resource management groups have recognized the need to have an integrated, adaptive, landscape approach to conservation. To more effectively address the growing threats to fish and wildlife conservation in the 21st century, the FWS in partnership with USGS adopted a landscape approach to conservation termed Strategic Habitat Conservation. This adaptive approach links site specific actions to population and landscape sustainability through the use of biological planning, conservation design, conservation delivery, decision-based monitoring, and assumption-driven research.
The methods and tools we develop will allow resource managers to examine potential effects of climate change on species under their stewardship in the context of ecosystem and landscape planning. We will work to close the gap between managers and scientists who produce data necessary for making key decisions in the face of climate change. Locally, resource managers within South Florida (including NPS, FWS, and the South Florida Water Management District) have indicated the need to run predictive models and view model outputs on their desktop computers, the ability to adjust model parameters when assessing alternatives, and for a spatially-explicit visualization environment for comparing alternatives. The USGS Priority Ecosystem Science program provided seed funding to develop a prototype application to address the needs of resource managers. This prototype has been met with enthusiasm by the aforementioned agencies and further development should serve our need of making data, information, and model output available to resource managers.
In our effort to develop appropriate models for resource managers' needs, we will use the best and most up-to-date information and methods available. For each of the T&E species under consideration, we will develop bioclimatic models, also called 'climate envelope' models or 'niche' models. These models allow us to relate species' geographic distributions to climate factors. Determining the niche of a species allows its potential geographic range to be forecast through projection of the estimated niche boundary on a spatial domain (Drake & Bossenbroek 2009). Predicted future climate variables are used to predict future species distributions. Bioclimatic models are widely used because they can effectively predict climate-induced range shifts for large numbers of species (Beaumont et al. 2007, Jiguet et al. 2007, Lawler et al. 2006, Huntley et al. 2004, Thomas et al. 2004, Thuiller et al. 2005, Pearson et al. 2002) and provide a first step that can address issues and needs at different spatial and temporal scales. For example, Lawler et al. (2006) included land cover as a variable in their models because climate-induced changes in vegetation should be able to make more accurate future projections.
Planned Products: Through the course of the project, we plan to deliver: climate and species habitat databases (GIS and tabular); species models (including climate envelope models); graphical user interface as well as user desired plug-ins that can run as stand-alone applications; documentation of models, interface, and associated tools; species climate envelopes maps and, if available, under alternative futures.
In year one; however funding is limited. At the end of FY10, we will submit a database with life history, range, habitat associations, and vulnerability traits for each species; compiled land cover/habitat information; and results of a comparison of modeling methods (support vector machine vs. random forests) for 1 - 3 case study species. We will submit a progress report of our work for the first half of FY10.
This project will compile the most up-to-date information on the 21 T&E, non-marine, vertebrate species in South Florida using existing literature and databases and workshops of ecological experts (Year 1).
Climate data will be compiled from sources that provide reliable data at the appropriate resolution (e.g., National Climatic Data Center, Worldclim database [1 km resolution]). Climate variables used will be determined by information collected on the species and may include degree-days, temperature and precipitation averages, extremes, ranges, and seasonal averages. (Years 1&2).
Land cover/habitat information will be compiled from a variety of sources and then associations/linkages will be made among classes in the various layers (i.e., cross-walking; Year 1).
This information will form the basis for developing climate envelope models, a tool used to examine potential species range shifts under climate change scenarios. Climate envelope models are used to predict the distribution of a species in the future if it is to live in the same range of climatic conditions that it currently inhabits.
We will define climate envelopes over the entire geographic distribution and project those envelopes based on alternative futures (e.g., IPCC projection for 2100) for each species (Years 2&3).
Maps for the entire geographic range of each species will be compiled and overlaid with broad land cover layers to determine presence of suitable habitat within each grid cell. Climate data will be associated with species presence and absence at each cell and a nonparametric regression tree approach, random forest predictors (Breiman 2001), will be used to correlate climate variables with species presence/absence. Twenty percent of the presence/absence data will be withheld from the modeling to use for model validation (Years 2&3).
At the South Florida scale, climate envelopes will be combined with land cover and habitat models refined in technical workshops and used with local alternative future conditions being developed by MIT/USGS (Year 3).
Drs. Leonard Pearlstine (NPS), Steve Friedman (NPS), and Laura Brandt (FWS) will participate in workshops, data gathering, and providing guidance to this project. Matthew Supernaw (NPS) will work closely with UF/USGS programmers to implement the models.
Tasks for FY10:
Beaumont L. J., A. J. Pitman, M. Poulsen, and L. Hughes. 2007. Where will species go? Incorporating new advance in climate modelling into projections of species distributions. Global Ecology and Biogeography, 13:1369-1385.
Breiman, L., 2001. Random Forests. Machine Learning 45: 5-32.
Cox, J., Kautz, R., MacLaughlin, M. and Gilbert, T., 1994. Closing the Gaps in Florida's Wildlife Habitat Conservation System. Office of Environmental Services, Florida Game and Fresh Water Fish Commission, Tallahassee.
Drake, J.M. & J.M. Bossenbroek. 2009. Profiling ecosystem vulnerability to invasion by zebra mussels with support vector machines. Theoretical Ecology (in press).
Huntley, B. R. E. Green, Y. C. Collingham, J. K. Hill, S. G. Willis, P. J. Bartlein, W. Cramer, W. J. M. Hagemeijer, and C. J. Thomas. 2004. The performance of models relating species geographical distributions to climate is independent of trophic level. Ecology Letters, 7: 417 - 426.
Jiguet F., A. Gadot, R. Julliard, S. Newson, and D. Couvet. 2007. Climate envelope, life history traits and the resilience of birds facing global change. Global Change Biology, 13:1673-1685.
Lawler J. J., D. White, R. P. Neilson, and A. R. Blaustein. 2006. Predicting climate-induced range shifts: model differences and model reliability. Global Change Biology, 1584.
Thomas, C.D., A. Cameron, R.E. Green, M. Bakkenes, L.J. Beaumont, Y.C. Collingham, B.F.N. Erasmus, M. Ferreira de Siqueira, A. Grainger, L. Hannah, L. Hughes, B. Huntley, A.S. van Jaarsveld, G.F. Midgley, L. Miles, M.A. Ortega-Huerta, A.T. Peterson, O.L. Phillips, S.E. Williams, 2004. Extinction risk from climate change. Nature 427:145-148.
Thuiller, W., S. Lavorel, M.B. Araujo, 2005. Niche properties and geographical extent as predictors of species sensitivity to climate change. Global Ecology and Biogeography 14:347-357.
Pearson, R.G. and T.P. Dawson. 2003. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecology & Biogeography 12:361-371.
U.S. Fish and Wildlife Service. 1999. South Florida Multi-Species Recovery Plan. Atlanta, Georgia.
U.S. Department of the Interior, U.S. Geological Survey
This page is: http://sofia.usgs.gov/projects/workplans10/climateenvmodeling.html
Comments and suggestions? Contact: Heather Henkel - Webmaster
Last updated: 04 September, 2013 @ 02:09 PM(KP)
|Home||Archived October 29, 2018|