Estima de una población de corzo mediante modelos de capturarecaptura clásicos y espacialmente explícitos

J. Jiménez, Carlos Rodríguez, Á. Moreno
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引用次数: 3

Abstract

Modern wildlife conservation and management requires accurate methods for population census and monitoring. In this work, we estimated the roe deer population (Capreolus capreolus) of Quintos de Mora (Toledo, Spain) in two close areas: one open and other fenced. For roe deer population estimates we used capture-recapture models and photo-identification of males by camera traps on feeding points by summer 2012. We used both a classic non-spatially explicit and a spatially explicit (SECR) capture-recapture models. Maximum-likelihood estimations MLE and Bayesian approaches were used in both cases. In the open area, deer estimates varied between 0.50 ± 0.14 (SECR approach) and 1.04 ± 0.14 (classic Bayesian approach) individuals per square kilometer, whereas in the fenced area between 7.58 ± 0.34 (classical Bayesian approach) and 11.25 ± 3.05 (SECR MLE approach) individuals per square kilometer. Finally we compared our estimations with direct counts. Although our estimates resulted consistent we recommend the use of SECR approaches for avoiding sampling area misspecifications.
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使用经典和空间显式捕获模型估计狍种群
现代野生动物保护和管理需要精确的人口普查和监测方法。在这项工作中,我们估计了Quintos de Mora(托莱多,西班牙)两个封闭区域的狍种群(Capreolus Capreolus):一个开放区域和一个围栏区域。2012年夏季,我们采用捕捉-再捕获模型和在喂食点设置相机陷阱,对雄性狍进行照片识别。我们使用了经典的非空间显式和空间显式(SECR)捕获-再捕获模型。在这两种情况下都使用了最大似然估计MLE和贝叶斯方法。在开放区域,鹿的估计值在每平方公里0.50±0.14 (SECR方法)和1.04±0.14(经典贝叶斯方法)之间,而在围栏区域,鹿的估计值在每平方公里7.58±0.34(经典贝叶斯方法)和11.25±3.05 (SECR MLE方法)之间。最后,我们将我们的估计与直接计数进行了比较。虽然我们的估计结果一致,但我们建议使用SECR方法来避免采样区域的错误规范。
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