Indices of movement behaviour: conceptual background, effects of scale and location errors
Indices of movement behaviour: conceptual background, effects of scale and location errors
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DOI：
10.1590/s1984-46702010000500002
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发表时间：
2010-10-01
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影响因子：
--
通讯作者：
Cerqueira, Rui
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作者：
Almeida, Paulo J. A. L.;Vieira, Marcus V.;Cerqueira, Rui
新兴运动理论的一个基本步骤是描述运动路径，并确定其最近和最终的驱动因素。用于描述和分析运动路径的最常见的特征是其曲折度，并且在不同的理论或经验背景下已经提出了各种曲折度指数。在这里，我们回顾了五个运动指数之间的概念差异及其偏差，由于位置误差，样本大小和规模依赖性：栖息地使用强度（IU），分形D，MSD（均方距离），直线度（ST）和弯曲度（SI）。栖息地使用强度和ST是直接计算的，但ST实际上是定向搜索和弹道运动的无偏估计。分形D不太容易计算，它代表了覆盖平面的倾向指数，而IU是三者中唯一完全经验的。这三个指标可以用来识别路径的不同阶段，它们的路径曲折度是路径的无量纲特征，主要取决于路径形状，而不是测量单位。弯曲度的概念不同于BENHAMOU（2004）的弯曲度中隐含的概念，其中假设特定的随机行走运动模型，并且扩散距离是路径长度和转向角的函数，需要将它们包含在弯曲度的度量中。MSD应被用作随机行走路径的诊断工具，而不是曲折指数。由于位置误差、样本大小和规模的偏差在指数之间以及所隐含的弯曲度概念之间存在差异。在选择最合适的指数时，必须考虑这些差异。
A fundamental step in the emerging Movement Theory is the description of movement paths, and the identification of its proximate and ultimate drivers. The most common characteristic used to describe and analyze movement paths is its tortuosity, and a variety of tortuosity indices have been proposed in different theoretical or empirical contexts. Here we review conceptual differences between five movement indices and their bias due to locations errors, sample sizes and scale-dependency: Intensity of Habitat use (IU), Fractal D, MSD (Mean Squared Distance), Straightness (ST), and Sinuosity (SI). Intensity of Habitat use and ST are straightforward to compute, but ST is actually an unbiased estimator of oriented search and ballistic movements. Fractal D is less straightforward to compute and represents an index of propensity to cover the plane, whereas IU is the only completely empirical of the three. These three indices could be used to identify different phases of path, and their path tortuosity is a dimensionless feature of the path, depending mostly on path shape, not on the unit of measurement. This concept of tortuosity differs from a concept implied in the sinuosity of BENHAMOU (2004), where a specific random walk movement model is assumed, and diffusion distance is a function of path length and turning angles, requiring their inclusion in a measure of sinuosity. MSD should be used as a diagnostic tool of random walk paths rather than an index of tortuosity. Bias due to location errors, sample size and scale, differs between the indices, as well as the concept of tortuosity implied. These differences must be considered when choosing the most appropriate index.