29th Annual Meeting and Symposium of the
Desert Tortoise Council, February 20-23, 2004
Abstracts

Desert Tortoise Decision Support: Landscape Analysis

Rich Inman, Frank Davenport, Paul Burgess, and Jill Heaton
University of Redlands, 1200 East Colton Avenue o Redlands, CA 92373-0999

This paper builds upon the foundation introduced and explored in the paper titled: Desert Tortoise Decision Support: Modeling Knowledge. Ecosystem Management Decision Support (EMDSTM) provides a platform for understanding desert tortoise knowledge, modeling desert tortoise habitat, and prioritizing research and data collection efforts based on the result of the model, as well as the influence of missing data and knowledge within the model. This paper will focus on the results of a landscape based desert tortoise habitat analysis, drawing upon the hierarchal model of desert tortoise knowledge presented earlier, and spatial data to illustrate the importance of identifying both gaps in current scientific knowledge and in current data. Current data may not adequately reflect current scientific understanding, yet is still used to develop spatially explicit models. Conversely, many spatial models draw upon comprehensive data, yet only incorporate partial knowledge. Unlike traditional habitat models, our model allows for the transparent exploration of differential spatial results, and thus creates the ability to identify the spatial consequences of incomplete or inexact knowledge. Model inputs are prioritized by their relative contribution to the model output, and can be mapped for uncertainty. For example, the spatial implications of incomplete or inexact knowledge of desert tortoise retreat sites can be mapped and thus more easily understood by scientists or articulated to managers. The results presented in this paper illustrate the significance of transparent models, collaborative model development, and improved spatial data compilation standards.