PARENT SESSION
Oral Session # 36: Rare, Threatened, and Endangered Species I: Plants.
Presiding: H Balbach
Tuesday, August 5. 1:30 PM to 5:00 PM, SITCC Meeting Room 204.
Modeling the potential distribution of rare plants in Wyoming.
Fertig, Walter*,1, 2, Thurston, Robert2, Reiners, William2, 1 Grand Staircase-Escalante National Monument, Kanab, UT, USA2 University of Wyoming, Laramie, WY
ABSTRACT- Predictive modeling of plant distributions rests on the assumption that correlations exist between the presence/absence of a species and selected climate, topographic, substrate, and land cover variables. Once these underlying patterns are determined, maps can be created in GIS that identify all areas that meet the specific conditions for a given species. Such maps can be used to prioritize areas for field surveys of rare plants or assist decision makers in project clearance activities. Using classification tree analysis, we developed correlational models for 44 Wyoming plant species listed as BLM Sensitive or Threatened or Endangered under the Endangered Species Act. Presence/absence of each species was the response variable in the models and was derived from location records of the Wyoming Natural Diversity Database and Rocky Mountain Herbarium. Environmental variables, including total monthly precipitation, average monthly air temperature, monthly shortwave radiation, number of wet days, growing degree-days, local topographic relief, bedrock and surficial geology, soils, elevation, and land cover, were used as predictors. Location data were randomly subdivided into model-building and validation data sets to test the classification success of the final models. We found that the distribution of rare species in Wyoming was most strongly correlated with specific bedrock and soil types, but was also influenced by topographic relief, land cover, and various monthly precipitation and temperature values. Overall, our models were conservative in the area predicted for these species and typically had low commission error rates. The distribution maps produced by correlational modeling did an excellent job of identifying areas where rare species are unlikely to occur and did a good job of highlighting areas of potential habitat that warrant additional on-the-ground survey.
Key words: rare plants, modeling, Wyoming, BLM