A spatial mark--resight model augmented with telemetry data.

Abstract:

:Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark--resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark-recapture. However, density estimation using mark-resight is difficult because the area sampled must be explicitly defined, historically using ad hoc approaches. We developed a spatial mark--resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows <100% individual identification of marked individuals. We implemented the model in a Bayesian framework, using a custom-made Metropolis-within-Gibbs Markov chain Monte Carlo algorithm. As an example, we applied this model to a mark--resight study of raccoons (Procyon lotor) on South Core Banks, a barrier island in Cape Lookout National Seashore, North Carolina, USA. We estimated a population of 186.71 +/- 14.81 individuals, which translated to a density of 8.29 +/- 0.66 individuals/km2 (mean +/- SD). The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.

journal_name

Ecology

journal_title

Ecology

authors

Sollmann R,Gardner B,Parsons AW,Stocking JJ,McClintock BT,Simons TR,Pollock KH,O'Connell AF

doi

10.1890/12-1256.1

subject

Has Abstract

pub_date

2013-03-01 00:00:00

pages

553-9

issue

3

eissn

0012-9658

issn

1939-9170

journal_volume

94

pub_type

杂志文章

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