Biodiversity and Scale: Determinants of Species Richness in Great Smoky Mountains National Park

There is a great need for simple yet flexible and biologically meaningful ways of classifying landscapes using readily available data for the purposes of inventorying and monitoring biodiversity. In this paper we describe a strategy developed for the All Taxa Biodiversity Inventory (ATBI) in Great Smoky Mountains National Park (NC and TN, USA) that establishes an objective and iterative approach to assessing and understanding patterns of biological diversity. Our strategy begins with the selection of ecologically important and available environmental factors. For the ATBI, we selected variables based on energy flux, temperature, and moisture. We show how to classify and combine these variables into a single classification scheme of “ecological zipcodes” that efficiently represents the combined environmental distribution of these factors. We also present a method for clustering samples of a landscape survey to account for both fine-grained and coarse-grained variation in species distributions. Finally, we show how studies can be iteratively designed to incorporate additional variables such as soil chemistry and disturbance, either as continuous variables or as contrasts for direct hypothesis testing using the ecological zipcodes. By translating a complex landscape into a simple yet biologically relevant