Suite of simple metrics reveals common movement syndromes across vertebrate taxa.
Suite of simple metrics reveals common movement syndromes across vertebrate taxa.
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DOI：
10.1186/s40462-017-0104-2
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发表时间：
2017
期刊：
影响因子：
4.1
通讯作者：
Getz WM
中科院分区：
文献类型：
--
作者：
Abrahms B;Seidel DP;Dougherty E;Hazen EL;Bograd SJ;Wilson AM;Weldon McNutt J;Costa DP;Blake S;Brashares JS;Getz WM
由于动物运动的实证研究是最经常的网站和物种的特定性，我们缺乏了解的一致性水平的运动模式在不同的类群，以及定量分类运动模式的框架。我们的目标是通过确定动物运动模式的统计特征在生态系统中重现的程度来解决这一差距。我们评估了一套运动指标来自GPS轨迹的13个海洋和陆地脊椎动物物种跨越三个分类类，数量级的身体大小，和运动模式（游泳，飞行，步行）。使用这些指标，我们进行了主成分分析和聚类分析，以确定个体是否组织成统计上不同的聚类。最后，为了识别和解释集群内的共性，我们将它们与计算机模拟的理想化运动综合征进行了比较，这些运动综合征代表了在各个分类群（迁移，游牧，领土和中央觅食）中观察到的相关运动特征。两个主成分解释了我们在13个物种中评估的运动指标之间的方差的70%，并用于聚类分析。分析结果显示了四个统计上不同的集群。每个理想化运动综合征的所有模拟个体被组织成单独的集群，这表明这四个集群可以用共同的运动综合征来解释。我们的研究结果提供了运动生态学中广泛的经常性模式的早期迹象，这些模式具有一致的统计特征，无论分类，体型，运动模式或环境如何。我们进一步表明，一组简单的指标可以用来分类大规模的运动模式在不同的脊椎动物类群。我们的比较方法为动物运动的量化和分类提供了一个通用框架，并促进了对运动综合症与其他生态过程之间关系的新探究。本文的在线版本（doi：10.1186/s40462-017-0104-2）包含补充材料，可供授权用户使用。
Because empirical studies of animal movement are most-often site- and species-specific, we lack understanding of the level of consistency in movement patterns across diverse taxa, as well as a framework for quantitatively classifying movement patterns. We aim to address this gap by determining the extent to which statistical signatures of animal movement patterns recur across ecological systems. We assessed a suite of movement metrics derived from GPS trajectories of thirteen marine and terrestrial vertebrate species spanning three taxonomic classes, orders of magnitude in body size, and modes of movement (swimming, flying, walking). Using these metrics, we performed a principal components analysis and cluster analysis to determine if individuals organized into statistically distinct clusters. Finally, to identify and interpret commonalities within clusters, we compared them to computer-simulated idealized movement syndromes representing suites of correlated movement traits observed across taxa (migration, nomadism, territoriality, and central place foraging). Two principal components explained 70% of the variance among the movement metrics we evaluated across the thirteen species, and were used for the cluster analysis. The resulting analysis revealed four statistically distinct clusters. All simulated individuals of each idealized movement syndrome organized into separate clusters, suggesting that the four clusters are explained by common movement syndrome. Our results offer early indication of widespread recurrent patterns in movement ecology that have consistent statistical signatures, regardless of taxon, body size, mode of movement, or environment. We further show that a simple set of metrics can be used to classify broad-scale movement patterns in disparate vertebrate taxa. Our comparative approach provides a general framework for quantifying and classifying animal movements, and facilitates new inquiries into relationships between movement syndromes and other ecological processes. The online version of this article (doi:10.1186/s40462-017-0104-2) contains supplementary material, which is available to authorized users.