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Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges

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  • Simon Benhamou

Abstract

Background: Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR). One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis. Methodology/Principal Findings: I introduce the concept of a biased random (advective-diffusive) bridge (BRB) and show that the MKDE method is a practical means to estimate UDs based on simplified (isotropically diffusive) BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection (allowed to vary between bridges) but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency. Conclusions/Significance: Biased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs), which are too complex to yield functional bridges. Relying on simplified BRBs proves to be the most reliable and easily usable way to estimate UDs from serially correlated relocations and raw activity information.

Suggested Citation

  • Simon Benhamou, 2011. "Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
  • Handle: RePEc:plo:pone00:0014592
    DOI: 10.1371/journal.pone.0014592
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    References listed on IDEAS

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    1. Devin S. Johnson & Dana L. Thomas & Jay M. Ver Hoef & Aaron Christ, 2008. "A General Framework for the Analysis of Animal Resource Selection from Telemetry Data," Biometrics, The International Biometric Society, vol. 64(3), pages 968-976, September.
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    1. Alejandro Cholaquidis & Ricardo Fraiman & Gábor Lugosi & Beatriz Pateiro-López, 2016. "Set estimation from reflected Brownian motion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 1057-1078, November.
    2. Jialin Lei & Yifei Jia & Aojie Zuo & Qing Zeng & Linlu Shi & Yan Zhou & Hong Zhang & Cai Lu & Guangchun Lei & Li Wen, 2019. "Bird Satellite Tracking Revealed Critical Protection Gaps in East Asian–Australasian Flyway," IJERPH, MDPI, vol. 16(7), pages 1-21, March.
    3. Inês Silva & Matthew Crane & Pongthep Suwanwaree & Colin Strine & Matt Goode, 2018. "Using dynamic Brownian Bridge Movement Models to identify home range size and movement patterns in king cobras," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-20, September.
    4. Nicolas Perony & Claudio J Tessone & Barbara König & Frank Schweitzer, 2012. "How Random Is Social Behaviour? Disentangling Social Complexity through the Study of a Wild House Mouse Population," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-11, November.
    5. 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.
    6. González, Tania Marisol & González-Trujillo, Juan David & Palmer, John R.B. & Pino, Joan & Armenteras, Dolors, 2017. "Movement behavior of a tropical mammal: The case of Tapirus terrestris," Ecological Modelling, Elsevier, vol. 360(C), pages 223-229.
    7. Gouvello, D.Z.M.Le & Heye, S. & Harris, L.R. & Temple-Boyer, J. & Gaspar, P. & Hart-Davis, M.G. & Louro, C. & Nel, R., 2024. "Dispersal corridors of neonate sea turtles from dominant rookeries in the Western Indian Ocean," Ecological Modelling, Elsevier, vol. 487(C).
    8. 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.

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