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Quantifying population declines based on presence-only records for red-list assessments

机译：根据仅存在记录进行红名单评估来量化人口下降

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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.
机译：准确的趋势估算对于了解哪些物种正在减少以及哪些物种最需要采取保护行动是必要的。物种检测不完善可能导致趋势估计不可靠，因为这可能导致对下降的高估。由于许多管理决策都是基于人口趋势估计，因此这种偏差可能对保护政策产生严重影响。我们使用了一个占用模型框架来估计可检测性并计算14种瑞士两栖动物物种的全国人口趋势，这两种情况都考虑了并忽略了不完善的检测。通过将国际自然保护联盟红色名录标准应用于不同的趋势估计，我们评估了忽略不完善的检测是否会影响保护政策。所有物种的检测均不完善，并且物种间的检测差异很大，当忽略可检测性时，会导致种群下降的高估。因此，考虑不完善的检测降低了评估的14个物种中5个物种的红名单风险类别。我们证明，不考虑物种可检测性可能会对物种管理产生严重后果，并且占用模型提供了一个灵活的框架来解释观察偏差并改善对保护状况的评估。大多数历史记录固有的问题是它们包含仅存在状态数据，从中只能估计相对下降。如果养护从业人员要超越这一点，则要朝着常规记录非观测和缺勤数据的方向迈进，这将是必不可少的。

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