Calengei C, Dufour A B
UMR CNRS 5558, Laboratoire de biométrie, Université Claude Bernard Lyon 1, 69622 Villeurbanne Cedex, France.
Ecology. 2006 Sep;87(9):2349-55. doi: 10.1890/0012-9658(2006)87[2349:eosrfa]2.0.co;2.
The development of methods to analyze habitat selection when resources are defined by several categories (e.g., vegetation types) is a topical issue in radio-tracking studies. The White and Garrott statistic, an extension of the widely used test of Neu et al., can be used to determine whether habitat selection is significant. As well, Manly's selection ratio, a particularly useful measure of resource selectivity by resource users, allows detection of the most strongly selected habitat types. However, when both the number of animals and types of habitat are large, the biologist often has to deal with an excessively large number of measures. In this paper we present a new method, the eigenanalysis of selection ratios, that generalizes these two common methods within the framework of eigenanalyses. This method undertakes an additive linear partitioning of the White and Garrott statistic, so that the difference between habitat use and availability is maximized on the first factorial axes. The eigenanalysis of selection ratios is therefore optimal in habitat selection studies. Although we primarily consider the case where the habitat availability is the same for all animals (design II), we also extend this analysis to the case where the habitat availability varies from one animal to another (design III). An application of this method is provided using radio-tracking data collected on 17 squirrels in five habitat types. The results indicate variability in habitat selection, with two groups of animals displaying two patterns of preference. This difference between the two groups is explained by the patch structure of the study area. Because this method is mainly exploratory, and therefore does not rely on any distributional assumption, we recommend its use in studies of habitat selection.
在资源由多个类别（如植被类型）定义的情况下，分析栖息地选择方法的发展是无线电跟踪研究中的一个热门问题。怀特和加罗特统计量是广泛使用的纽等人检验的扩展，可用于确定栖息地选择是否显著。此外，曼利选择比率是资源使用者对资源选择性的一种特别有用的度量，能够检测出被选择程度最高的栖息地类型。然而，当动物数量和栖息地类型都很多时，生物学家常常不得不处理大量的度量指标。在本文中，我们提出了一种新方法——选择比率的特征分析，它在特征分析框架内对这两种常用方法进行了推广。该方法对怀特和加罗特统计量进行加法线性划分，以便在第一个因子轴上使栖息地利用与可利用性之间的差异最大化。因此，选择比率的特征分析在栖息地选择研究中是最优的。虽然我们主要考虑所有动物的栖息地可利用性相同的情况（设计II），但我们也将此分析扩展到栖息地可利用性因动物而异的情况（设计III）。使用在五种栖息地类型中收集的17只松鼠的无线电跟踪数据给出了该方法的一个应用。结果表明栖息地选择存在变异性，两组动物表现出两种偏好模式。两组之间的这种差异是由研究区域的斑块结构所解释的。由于该方法主要是探索性的，因此不依赖于任何分布假设，我们建议在栖息地选择研究中使用它。
