Quantifying population declines based on presence‐only records for red‐list assessments |
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Authors: | Sam S. Cruickshank Arpat Ozgul Silvia Zumbach Benedikt R. Schmidt |
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Affiliation: | 1. Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zürich, Switzerland;2. karch, Neuchatel, Switzerland |
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Abstract: | Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation. |
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Keywords: | amphibian conservation detection probability extinction risk management monitoring occupancy presence‐only data trend anfibio conservació n datos de presencia manejo monitoreo ocupació n probabilidad de detecció n riesgo de extinció n tendencia |
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