Evaluating the vulnerability of Wyoming's wildlife to habitat disturbance

There has recently been much debate over the validity, causes and potential impacts of an impending 'biodiversity crisis' stemming from rapidly increasing rates of extinction that likely result from anthropogenic disturbances to formerly intact landscapes (Koh et al. 2004, Wake and Vredenburg 2008). Continuation of these trends will result in natural resource managers being faced with conservation decisions relative to a large and growing number of species in the midst of rapidly changing landscapes. With limited conservation resources, it is necessary to apply strategic planning to prioritize conservation efforts (Margules and Pressey 2000).;The idea that some species are more sensitive to disturbance, and ultimately extinction, than others is not new. However, it was not until the emergence of modern population biology and, moreover, island biogeography theory (MacArthur 1967) and the growing 'extinction crisis' of late 20th century that scientists began in earnest to evaluate the forces that cause certain species to be more prone to extinction that others (McKinney 1997). Since the 1970's, such research has generated many studies examining extinction proneness, and a variety of synthetic treatments (e.g., McKinney 1997, Purvis et al. 2000, Henle et al. 2004). Most recent interest in such inquiry has been driven by conservation concerns, in hopes that the resulting insight would be useful in understanding, and thus mitigating, impacts from human disturbance, or even predicting future impacts that would allow proactive management. Despite these efforts, we still lack a unifying framework in which such information can be fruitfully applied, with the exception of small, related groups of target species under specific circumstances. Two reasons for this lack of generality are the narrow focus of most studies (e.g., restricted geographic scope or narrow taxonomic breadth of the investigation) and the often confusing, interacting nature of factors affecting extinction proneness (e.g., subtle interactions between body size and foraging strategy when examining insectivorous forest birds) (Purvis et al. 2000).;Vulnerability is the state of being susceptible to harm and, at its core, is primarily a function of exposure and sensitivity (Turner et al. 2003, Williams et al. 2008, Pacifici et al. 2015). In order for a species to be vulnerable to disturbance it must both be exposed to the disturbance and it must be sensitive to the disturbance (Fig. 1). Therefore, to accurately assess whether species are vulnerable to disturbance one must first determine whether their preferred habitats coincide with the disturbance (i.e., quantitatively evaluate exposure), and then combine the exposure assessment with an evaluation of the species sensitivity to the particular changes wrought by that type of disturbance (i.e., quantitatively evaluate sensitivity). Few previous studies have carefully assessed both factors in the same system. The advent of desktop Geographic Information Systems has increased the ability to conduct spatially explicit exposure assessments by facilitating geospatial analyses of human impacts, often through 'footprint analysis' (e.g., Leu et al. 2008, Walston et al. 2009), though such studies are limited to coarse scale overlays that do not explicitly evaluate biological sensitivities for the species in question. In contrast, studies evaluating the biological correlates of extinction proneness have generally not been spatially explicit; either evaluating taxon-wide sensitivities with no spatial reference or focusing explicitly on entire target populations.;I assessed the relative vulnerability of Wyoming's terrestrial vertebrate Species of Greatest Conservation Need (SGCN) to disturbance and/or ultimate extinction due to energy development activities. Although the focal landscape for this effort is Wyoming the methods are transferable to other systems. To accurately access vulnerability, I quantified its constituent parts, namely exposure, which is a function of species distributions relative to development, and sensitivity, which is largely a function of species biology (Fig. 1). Chapter 1 explains the development of species distribution models, and Chapter 2 combines those models with spatial estimates of energy development to quantify exposure for all SGCN (N = 156). Chapter 3 uses a meta-analysis of habitat fragmentation studies to identify and quantify predictors of sensitivity to local disturbance. Chapter 4 is a brief conclusion that combines estimates of exposure and sensitivity to rank Wyoming's SGCN according to their vulnerability to energy development.