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利用动态布朗桥运动模型来识别眼镜王蛇的家域大小和运动模式。

Using dynamic Brownian Bridge Movement Models to identify home range size and movement patterns in king cobras.

机构信息

School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.

School of Biology, Suranaree University of Technology, Nakhon Ratchasima, Thailand.

出版信息

PLoS One. 2018 Sep 18;13(9):e0203449. doi: 10.1371/journal.pone.0203449. eCollection 2018.

Abstract

Home range estimators are a critical component for understanding animal spatial ecology. The choice of home range estimator in spatial ecology studies can significantly influence management and conservation actions, as different methods lead to vastly different interpretations of movement patterns, habitat selection, as well as home range requirements. Reptile studies in particular have struggled to reach a consensus on the appropriate home range estimators to use, and species with cryptic behavior make home range assessment difficult. We applied dynamic Brownian Bridge Movement Models (dBBMMs) to radio-telemetry data from Ophiophagus hannah, a wide-ranging snake species. We used two focal individuals at different life stages (one juvenile male and one adult male) and sought to identify whether the method would accurately represent both their home range and movement patterns. To assess the suitability of dBBMMs, we compared this novel method with traditional home range estimation methods: minimum convex polygons (MCP) and Kernel density estimators (KDE). Both KDE and MCP incorporated higher levels of Type I and Type II errors, which would lead to biases in our understanding of this species space-use and habitat selection. Although these methods identified some general spatial-temporal patterns, dBBMMs were more efficient at detecting movement corridors and accurately representing long-term shelters sites, showing an improvement over methods traditionally favored in reptile studies. The additional flexibility of the dBBMM approach in providing insight into movement patterns can help further improve conservation and management actions. Additionally, our results suggest that dBBMMs may be more widely applicable in studies that rely on VHF telemetry and not limited to studies employing GPS tags.

摘要

家域估计器是理解动物空间生态学的关键组成部分。在家域生态学研究中选择家域估计器的方法会极大地影响管理和保护行动,因为不同的方法会导致对运动模式、栖息地选择以及家域需求的解释大不相同。特别是爬行动物研究在选择适当的家域估计器方面一直存在争议,而行为隐秘的物种使得家域评估变得困难。我们将动态布朗桥运动模型(dBBMM)应用于 Ophiophagus hannah 的无线电遥测数据,这是一种分布广泛的蛇类。我们使用了两个不同生命阶段的焦点个体(一个幼年雄性和一个成年雄性),并试图确定该方法是否能准确代表它们的家域和运动模式。为了评估 dBBMM 的适用性,我们将这种新方法与传统的家域估计方法:最小凸多边形(MCP)和核密度估计器(KDE)进行了比较。KDE 和 MCP 都包含了更高水平的 I 型和 II 型错误,这将导致我们对该物种空间利用和栖息地选择的理解产生偏差。尽管这些方法确定了一些一般的时空模式,但 dBBMM 更有效地检测运动走廊,并准确地代表长期庇护所,这表明它比传统上在爬行动物研究中使用的方法有所改进。dBBMM 方法在提供运动模式洞察力方面的额外灵活性可以帮助进一步改进保护和管理行动。此外,我们的结果表明,dBBMM 可能更广泛地适用于依赖甚高频(VHF)遥测的研究,而不仅仅限于使用 GPS 标签的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ca2/6143228/335c8d02366c/pone.0203449.g001.jpg

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