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LoCoH: Nonparameteric Kernel Methods for Constructing Home Ranges and Utilization Distributions

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  • Wayne M Getz
  • Scott Fortmann-Roe
  • Paul C Cross
  • Andrew J Lyons
  • Sadie J Ryan
  • Christopher C Wilmers

Abstract

Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: “fixed sphere-of-influence,” or r-LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an “adaptive sphere-of-influence,” or a-LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a), and compare them to the original “fixed-number-of-points,” or k-LoCoH (all kernels constructed from k-1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a-LoCoH is generally superior to k- and r-LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu).

Suggested Citation

  • Wayne M Getz & Scott Fortmann-Roe & Paul C Cross & Andrew J Lyons & Sadie J Ryan & Christopher C Wilmers, 2007. "LoCoH: Nonparameteric Kernel Methods for Constructing Home Ranges and Utilization Distributions," PLOS ONE, Public Library of Science, vol. 2(2), pages 1-11, February.
  • Handle: RePEc:plo:pone00:0000207
    DOI: 10.1371/journal.pone.0000207
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    Cited by:

    1. Wszola, Lyndsie S. & Simonsen, Victoria L. & Corral, Lucía & Chizinski, Christopher J. & Fontaine, Joseph J., 2019. "Simulating detection-censored movement records for home range analysis planning," Ecological Modelling, Elsevier, vol. 392(C), pages 268-278.
    2. Downs, Joni A. & Heller, Justin H. & Loraamm, Rebecca & Stein, Dana Oppenheim & McDaniel, Cassandra & Onorato, Dave, 2012. "Accuracy of home range estimators for homogeneous and inhomogeneous point patterns," Ecological Modelling, Elsevier, vol. 225(C), pages 66-73.
    3. Benhamou, Simon & Riotte-Lambert, Louise, 2012. "Beyond the Utilization Distribution: Identifying home range areas that are intensively exploited or repeatedly visited," Ecological Modelling, Elsevier, vol. 227(C), pages 112-116.
    4. Zhang, Shen & Tang, Jinjun & Wang, Haixiao & Wang, Yinhai & An, Shi, 2017. "Revealing intra-urban travel patterns and service ranges from taxi trajectories," Journal of Transport Geography, Elsevier, vol. 61(C), pages 72-86.
    5. Mathieu Pruvot & Manigandan Lejeune & Susan Kutz & Wendy Hutchins & Marco Musiani & Alessandro Massolo & Karin Orsel, 2016. "Better Alone or in Ill Company? The Effect of Migration and Inter-Species Comingling on Fascioloides magna Infection in Elk," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-16, July.

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