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ANALYSIS UNIT
CCSD, in collaboration with the Research Division and the International Center for Tropical Ecology at the University of Missouri-St. Louis (ICTE), has established an Analysis Unit, which uses biological data to answer questions that elucidate key issues in conservation biology. Using modern analytic tools, the Analysis Unit is modeling the geographic distribution of different species and identifying regions that contain high plant diversity, particularly regions that sustain high numbers of plant species with narrow geographic distributions.
To spur the formulation of testable hypotheses to guide their data analyses, CCSD scientists have developed questions such as the following:
- Identifying areas of high plant diversity: Spatial patterns of richness are central to identifying priority areas for conservation. Yet descriptions of such patterns are dependent on distribution maps, which are commonly affected by bias in biodiversity data. CCSD is using several analytical tools to distinguish taxa whose distribution appears restricted as a result of poor collection effort from taxa that are truly narrowly distributed.
- Evaluating the processes that contribute to biodiversity patterns: The conservation of biodiversity depends on the processes that determine the extinction and production of species; thus, the selection of priority areas for conservation should be informed by the study of such processes. CCSD is using data from a few plant groups to test predictions from hypotheses about the origin and maintenance of biodiversity.
- Determining how large reserve networks need to be: Identification of reserve networks for conservation is typically focused on minimizing the total area needed to represent a given number of taxa. CCSD is testing the effects of three variables on the area of reserve networks: 1) number of targeted species, 2) size of selection units, and 3) endemism of the targeted species.
- Using occupancy and abundance estimates to identify reserve networks: Reserve networks are often identified using only occurrence data and thus are likely to include populations with low probability of persistence. CCSD is using data on abundance and occupancy (portion of sites occupied across a region within the geographic range) to identify reserve networks that are resilient against temporal species turnover.
PROJECTS
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