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线截抽样法在估计群居动物密度中的应用:灵长类动物的经验教训。

Selection of line-transect methods for estimating the density of group-living animals: lessons from the primates.

机构信息

Centre for Ecology, Law and Policy, Environment Department, University of York, Heslington, York, United Kingdom.

出版信息

Am J Primatol. 2008 May;70(5):452-62. doi: 10.1002/ajp.20516. Epub 2008 Jan 31.

Abstract

We review the four major contemporary methods for estimating density of group-living animals from line-transect sampling: perpendicular modelling of group centers, perpendicular modelling of center of measurable individuals, strip transects and animal-observer distance. The efficacy of each method is evaluated to produce a simple selection guide. We review the literature and use field data from the Udzungwa Mountains, Tanzania. The review is relevant to all group-living animals; however, examples are drawn from the primates. Perpendicular methods have better mathematical justification than non-perpendicular methods. For perpendicular methods using detection function models, it is preferable to measure group location using center of measurable individuals, as group centers are hard to estimate. The assumptions of detection function models are often broken in poor visibility habitats or with unhabituated animals. Alternatively strip transects may be used where there are reliable data on group spread and/or visibility. Strip transects are also the most practical, along with the animal-observer method; however, the latter lacks mathematical justification. We conclude that there are arguments for continued use of all four methods. In certain situations the use of raw encounter rates may also be considered. The appropriate method is determined by minimizing bias and considering time, resources and field conditions.

摘要

我们回顾了四种从样线截距抽样中估算群居动物密度的现代主流方法

群体中心的垂线建模、可测个体中心的垂线建模、样带截距和动物-观察者距离。每种方法的有效性都经过了评估,以生成一个简单的选择指南。我们回顾了文献,并使用了来自坦桑尼亚乌宗圭山脉的野外数据。该综述与所有群居动物都相关,但例子取自灵长类动物。垂直方法比非垂直方法具有更好的数学依据。对于使用检测函数模型的垂直方法,最好使用可测个体的中心来测量群体位置,因为群体中心很难估计。检测函数模型的假设在能见度差的栖息地或不熟悉的动物中经常被打破。或者,在有可靠的群体扩散和/或可见性数据的情况下,可以使用样带截距。样带截距和动物-观察者方法也是最实用的,但后者缺乏数学依据。我们的结论是,这四种方法都有继续使用的理由。在某些情况下,也可以考虑使用原始的遭遇率。适当的方法是通过最小化偏差并考虑时间、资源和现场条件来确定的。

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