The Annals of Applied Statistics

Modelling individual migration patterns using a Bayesian nonparametric approach for capture–recapture data

Eleni Matechou and François Caron

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Abstract

We present a Bayesian nonparametric approach for modelling wildlife migration patterns using capture–recapture (CR) data. Arrival times of individuals are modelled in continuous time and assumed to be drawn from a Poisson process with unknown intensity function, which is modelled via a flexible nonparametric mixture model. The proposed CR framework allows us to estimate the following: (i) the total number of individuals that arrived at the site, (ii) their times of arrival and departure, and hence their stopover duration, and (iii) the density of arrival times, providing a smooth representation of the arrival pattern of the individuals at the site. We apply the model to data on breeding great crested newts (Triturus cristatus) and on migrating reed warblers (Acrocephalus scirpaceus). For the former, the results demonstrate the staggered arrival of individuals at the breeding ponds and suggest that males tend to arrive earlier than females. For the latter, they demonstrate the arrival of migrating flocks at the stopover site and highlight the considerable difference in stopover duration between caught and not-caught individuals.

Article information

Source
Ann. Appl. Stat. Volume 11, Number 1 (2017), 21-40.

Dates
Received: November 2015
Revised: June 2016
First available in Project Euclid: 8 April 2017

Permanent link to this document
http://projecteuclid.org/euclid.aoas/1491616870

Digital Object Identifier
doi:10.1214/16-AOAS989

Keywords
Chinese restaurant process great crested newts Poisson–Gamma process reed warblers shot-noise Cox process stopover data

Citation

Matechou, Eleni; Caron, François. Modelling individual migration patterns using a Bayesian nonparametric approach for capture–recapture data. Ann. Appl. Stat. 11 (2017), no. 1, 21--40. doi:10.1214/16-AOAS989. http://projecteuclid.org/euclid.aoas/1491616870.


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Supplemental materials

  • Supplement article. We provide details on an MCMC algorithm for the model presented in this paper, convergence diagnostics, and a comparison of results obtained using existing models for both case studies and a sensitivity analysis to prior distributions specified for several parameters.
    Digital Object Identifier: doi:10.1214/16-AOAS989SUPPA
    Supplemental files available for subscribers.
  • Code and data. The reed warbler data and code to fit the model presented in the paper to the data.
    Digital Object Identifier: doi:10.1214/16-AOAS989SUPPB
    Supplemental files available for subscribers.

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