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异质景观中的动物运动:识别有利可图的地点和同质化运动周期。

Animal movements in heterogeneous landscapes: identifying profitable places and homogeneous movement bouts.

作者信息

Barraquand Frédéric, Benhamou Simon

机构信息

Centre d'Ecologie Fonctionnelle et Evolutive, CNRS Montpellier, France.

出版信息

Ecology. 2008 Dec;89(12):3336-48. doi: 10.1890/08-0162.1.

Abstract

Because of the heterogeneity of natural landscapes, animals have to move through various types of areas that are more or less suitable with respect to their current needs. The locations of the profitable places actually used, which may be only a subset of the whole set of suitable areas available, are usually unknown, but can be inferred from movement analysis by assuming that these places correspond to the limited areas where the animals spend more time than elsewhere. Identifying these intensively used areas makes it possible, through subsequent analyses, to address both how they are distributed with respect to key habitat features, and the underlying behavioral mechanisms used to find these areas and capitalize on such habitats. We critically reviewed the few previously published methods to detect changes in movement behavior likely to occur when an animal enters a profitable place. As all of them appeared to be too narrowly tuned to specific situations, we designed a new, easy-to-use method based on the time spent in the vicinity of successive path locations. We used computer simulations to show that our method is both quite general and robust to noisy data.

摘要

由于自然景观的异质性,动物不得不穿越各种类型的区域,这些区域或多或少符合它们当前的需求。实际利用的有利可图之地的位置,可能只是所有可用适宜区域的一个子集,通常是未知的,但可以通过运动分析推断出来,假设这些地方对应于动物比其他地方花费更多时间的有限区域。识别这些密集使用的区域使得通过后续分析,既能解决它们相对于关键栖息地特征是如何分布的,又能解决用于找到这些区域并利用此类栖息地的潜在行为机制。我们批判性地回顾了之前发表的几种用于检测动物进入有利可图之地时可能发生的运动行为变化的方法。由于所有这些方法似乎都过于针对特定情况进行调整,我们设计了一种基于在连续路径位置附近花费的时间的新的、易于使用的方法。我们使用计算机模拟表明,我们的方法既相当通用,又对噪声数据具有鲁棒性。

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