An Assessment of Visual Encounter Surveys for an Elusive Species - The Dunes Sagebrush Lizard (Sceloporus arenicolus)
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The Dunes Sagebrush Lizard (Sceloporus arenicolus - DSL) is a highly cryptic, habitat specialist that shows a preference for environments comprised of large wind-blown sand dune complexes and dense arrays of shinnery oak (Quercus harvardii). This species occupies a narrow range in the Monahans Sandhills of Texas and the Mescalero Sands of New Mexico and like many habitat specialists, they are sensitive to disturbances within their environment. Conservation of this species relies upon precise assessments of the occurrence, abundance, and the trends in both metrics for this lizard. The standard method for detecting the DSL, visual encounter surveys (VES), was utilized to estimate the probability of detection, across sites that had varying degrees of reported suitability. Three separate VES methodologies were analyzed: 1) plot size: 200m x 200m; survey duration: 15 minutes, 2) plot size: 400m x 400m; survey duration: 60 minutes, and 3) plot size: 200m x 200m; survey duration: 30 minutes. The probability of detection, for S. arenicolus, was compared to two more commonly detected species, Uta stansburiana and Aspidoscelis marmoratus. The minimum number of surveys, needed to reliably detect these species, was then calculated from detection estimates. A total of 1,135 individual lizards were recorded, 12 of which were S. arenicolus. The mean detection probability for U. stansburiana = 0.38, followed by A. marmoratus = 0.28, and finally the DSL = 0.13 to 0.19. Less surveys were needed to be 95% confident that a lizard was detected, if that lizard had a higher probability of detection. Results of the study indicated that while VES may be suitable for many common species of lizards, it may not be the most efficient method for accurately determining presence of rarer species of lizards (i.e., the DSL). This could indicate that a more intensive survey methodology (i.e., pitfall traps) may be needed when trying to make reliable occupancy or abundance estimates.