Spatially-explicit models for inference about density in unmarked populations

Details Spatially-explicit models for inference about density in unmarked populations Spatially-explicit models for inference about density in unmarked populations

2011-12-14

arxiv.org/abs/1112.3250v1

Statistics

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Scientific paper

Spatial capture-recapture (SCR) methods represent a major advance over traditional capture-capture methods because they yield explicit estimates of animal density instead of population size within an unknown area, and they account for heterogeneity in capture probability arising from the juxtaposition of individuals and sample locations. However, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR methods to be applied in studies of unmarked or partially-marked populations. The data required for our model are spatially-referenced counts at a collection of closely-spaced sample units such that individuals can be encountered at multiple locations. Our approach utilizes the spatial correlation in counts as information about the location of individual activity centers, which enables estimation of density and distance-related heterogeneity in detection. A simulation study demonstrated that while the posterior distribution of abundance or density is strongly skewed in small samples, the posterior mode is an accurate point estimator as long as the trap spacing is not too large relative to scale parameter of the detection function. Marking a subset of the population can lead to substantial reductions in posterior skew and increased posterior precision. We also fit the model to point count data collected on the northern parula, and obtained a density estimate of 0.38 (95% CI: 0.19, 1.64) birds/ha. Our paper challenges sampling and analytical conventions by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density---rather, spatial dependence induced by design can be informative about individual distribution and density.

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