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引用次数: 11
摘要
活动范围是衡量鱼类和野生动物空间利用模式的基本尺度。核密度估计(Kernel density estimation, KDE)是应用最广泛的home range估计器,尽管它的性能很差。在本文中,我们认为KDE不适合用于home range估计,因为它假设基于欧几里得的空间使用情况。由于动物空间使用模式表现出基于网络的运动特征,我们开发了一个基于网络的家园距离估计器。首先,我们使用Delaunay三角剖分(DT)从一组动物点位置近似出一个旅行路径网络。然后,我们调整KDE来估计家庭范围作为该网络的函数。初步结果表明,使用DT进行基于网络的家庭范围估计有可能改善生态学家测量动物空间利用模式的方式。
Network-based Home Range Analysis Using Delaunay Triangulation
The home range is the fundamental measurement of fish and wildlife space-use patterns. Kernel density estimation (KDE) is the most widely applied home range estimator, although its poor performance has recently been documented. In this paper, we suggest that KDE is inappropriate for home range estimation, because it assumes Euclidean-based space usage. Because animal space-use patterns show characteristics of network-based movement, we develop a network-based home range estimator. First, we use Delaunay triangulation (DT) to approximate a network of travel paths from a set of animal point locations. Then, we adapt KDE to estimate home ranges as a function of that network. Preliminary results suggest that network-based home range estimation using DT has the potential to improve the way ecologists measure animal space-use patterns.