Meeting Abstract

102.4  Tuesday, Jan. 7 08:45  Fractal dimension of landscape features drives activity of terrestrial ectotherms SEARS, MW*; LEVY, O; ANGILLETTA, MJ; Clemson Univ.; Arizona St. Univ.; Arizona St. Univ. sears3@clemson.edu

Understanding the ecological responses to global climate change represents one of the greatest challenges of the 21st century. To forecast these responses, we must develop computer-intensive models that leverage detailed climatic and biological data to predict the future distributions of species. Current approaches to ecological forecasting have focused on driving factors of geographic distributions such as climate, topography, and land use. In particular, mechanistic models have successfully integrated principles of biophysical ecology with GIS. While this approach is quite powerful, integrating behavior and physiology to predict the potential for organismal activities—a central component of many mechanistic models—remains challenging. The problem is worsened by the mismatch between the scales on which these models consider climate and geography versus the scale at which organisms experience environmental heterogeneity. Here, we extend a framework that explicitly incorporates fine-scale processes to predict the activity, dispersal, and energetics of animals. Initial findings suggest that either increased elevational relief or increased fractal dimension of a landscape will increase the potential duration of activity. To examine the robustness of this result, we generated randomly configured landscapes that differ in elevational range, percent vegetation, and the fractal dimensions of elevation and vegetation. With these artificial landscapes, we will use an individual-based model to predict spatial and temporal patterns of activity, not just the potential for activity. We will then examine whether these factors can be used to correct estimates of activity on a flat surface that can then be applied to mechanistic models of species’ distributions.