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Mixture models for estimating the size of a closed population when capture rates vary among individuals

Biometrics

By:
and
DOI: 10.1111/1541-0420.00042

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Abstract

We develop a parameterization of the beta-binomial mixture that provides sensible inferences about the size of a closed population when probabilities of capture or detection vary among individuals. Three classes of mixture models (beta-binomial, logistic-normal, and latent-class) are fitted to recaptures of snowshoe hares for estimating abundance and to counts of bird species for estimating species richness. In both sets of data, rates of detection appear to vary more among individuals (animals or species) than among sampling occasions or locations. The estimates of population size and species richness are sensitive to model-specific assumptions about the latent distribution of individual rates of detection. We demonstrate using simulation experiments that conventional diagnostics for assessing model adequacy, such as deviance, cannot be relied on for selecting classes of mixture models that produce valid inferences about population size. Prior knowledge about sources of individual heterogeneity in detection rates, if available, should be used to help select among classes of mixture models that are to be used for inference.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Mixture models for estimating the size of a closed population when capture rates vary among individuals
Series title:
Biometrics
DOI:
10.1111/1541-0420.00042
Volume
59
Issue:
2
Year Published:
2003
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Biometrics
First page:
351
Last page:
364