USING LIDAR TO ENHANCE DISTRIBUTION MODELS FOR THE DUNES SAGEBRUSH LIZARD (SCELOPORUS ARENICOLUS) IN TEXAS, USA
Academic Article
Overview
Research
Additional Document Info
View All
Overview
abstract
Mapping species distributions and habitat suitability guides policy decisions and conservation. Over the last few decades, multiple expert-derived, qualitative species occurrence and habitat availability maps have been developed in response to increasing conservation attention on the Dunes Sagebrush Lizard (Sceloporus arenicolus). Management and conservation decisions, however, necessitate development of a more structured, quantitative approach, based on the known occurrences of S. arenicolus and its habitat requirements. Thus, the goal of our work was to develop a continuous species distribution model for S. arenicolus in Texas. We used Generalized Linear (GLM) and Generalized Additive (GAM) models to predict areas where conditions were appropriate, using land cover covariates as well as rugosity covariates derived from Airborne Light Detection and Ranging (LiDAR), for S. arenicolus occurrence within its known Texas range. The best fitting GLM model indicated higher mean maximum rugosity and lower percentage cover of Shinnery Oak (Quercus havardii) increased the mean predicted probability of occurrence for S. arenicolus. Using the best-fitting model, we also predicted probability of occurrence via a GAM that included a spatial effect, which indicated that greater proximity to identified S. arenicolus presences increased the predicted probability of occurrence. Our species distribution maps can be used to inform the listing determination and support future conservation actions by identifying suitable areas for S. arenicolus, helping prioritize areas for future S. arenicolus surveys, and determining areas for high-value conservation or management actions.
