Cost-effective assessment of extinction risk with limited information
Cost-effective assessment of extinction risk with limited information
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DOI：
10.1111/1365-2664.12459
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发表时间：
2015-08-01
影响因子：
5.7
通讯作者：
McCarthy, Michael A.
中科院分区：
文献类型：
--
作者：
Bland, Lucie M.;Orme, C. David L.;McCarthy, Michael A.
以具有成本效益的方式减少全球生物多样性指标的不确定性是保护的一个中心目标。在目前世界自然保护联盟红色名录上的74000多个物种中，有六分之一的物种数据不足，导致灭绝风险估计存在相当大的不确定性。鉴于调查和红色名录评估的成本，估计数据缺乏物种的风险水平将需要大量资源。从物种特征和地理信息预测灭绝风险可以提供一种更便宜的方法来确定处于灭绝风险的数据缺乏物种的比例。我们使用双抽样理论来比较预测模型和IUCN红色名录评估的成本效益，以估计数据缺乏的陆生哺乳动物，两栖动物，爬行动物和小龙虾的风险水平。对于每个组，我们校准已知保护状态物种灭绝风险的机器学习模型，并评估其相对于实地调查的成本和可靠性，然后进行红色名录评估。我们表明，无论使用的模型类型或物种组检查，它总是更符合成本效益的模型，以确定所有物种的保护状况，并评估一小部分物种与IUCN标准（双抽样），而不是花同样的资源在实地调查和红色名录评估（单抽样）。我们估计，调查和重新评估所有数据缺乏物种目前列入世界自然保护联盟红色名录（12206种）与世界自然保护联盟的标准将花费至少3.23亿美元。双重抽样将确定数据不足物种灭绝风险比例的成本降低了68%，因为
Cost-effective reduction of uncertainty in global biodiversity indicators is a central goal of conservation. Comprising a sixth of the 74000+ species currently on the IUCN Red List, Data Deficient species contribute to considerable uncertainty in estimates of extinction risk. Estimating levels of risk in Data Deficient species will require large resources given the costs of surveys and Red List assessments. Predicting extinction risk from species traits and geographical information could provide a cheaper approach for determining the proportion of Data Deficient species at risk of extinction. We use double sampling theory to compare the cost-effectiveness of predictive models and IUCN Red List assessments for estimating risk levels in Data Deficient terrestrial mammals, amphibians, reptiles and crayfish. For each group, we calibrate machine learning models of extinction risk on species of known conservation status and assess their cost and reliability relative to field surveys followed by Red List assessments. We show that regardless of model type used or species group examined, it is always more cost-effective to determine the conservation status of all species with models and assess a small proportion of species with IUCN criteria (double sampling), rather than spend the same resources on field surveys and Red List assessments alone (single sampling). We estimate that surveying and re-assessing all Data Deficient species currently listed on the IUCN Red List (12206 species) with IUCN criteria would cost a minimum of US $323million. Double sampling reduces the cost of determining the proportion of Data Deficient species at risk of extinction by up to 68%, because