Abstract Detail

Ecological Section

Aitken, M. [1], Shultz, Leila M. [2], Roberts, D.W. [2].

Modeling distributions of rare plants in the eastern Great Basin.

This study developed field-validated site and landscape level predictive models for identification of potential habitat for rare and endemic plants in the eastern Great Basin. Four species were chosen to include a range of environmental variability and plant communities. In the first phase of this study, herbarium records of known occurrences were used to locate initial sample sites. The geographic coordinates, environmental attributes and vegetation data collected at each site were used to develop two predictive models for each species: a field key and a probability-of-occurrence map. The field key was developed from environmental attribute and associated species data collected at the sites and employed data only available in the field. Predictive maps were developed by using a geographic information system (GIS) containing slope, elevation, aspect, soils, and geologic data. Tree-classifier software was used to generate dichotomous field keys and the maps of occurrence probabilities. Predictions from both models were then field validated during the second phase of the study, and final models were developed through an iterative process, where data collected during the field validation were then incorporated into subsequent predictive models. Using cross-validated models, we predicted presence accurately even though presence data were often less than 10% of the total data set. These models identified potential habitat by combining elevation, slope, aspect, rock type, and geologic process into habitat models for each species.

1 - U.S. Forest Service, Forestry and Range Science Laboratory, La Grande, Oregon, 97850, USA
2 - Utah State University, Department of Forest, Range, and Wildlife Sciences, Logan, Utah, 84322-5230

Keywords:
endemic
predictive model
classification tree
biogeography.

Presentation Type: Poster
Session: 32-26
Location: Special Event Center (Cliff Lodge)
Date: Tuesday, August 3rd, 2004
Time: 12:30 PM
Abstract ID:127