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Research article - Peer-reviewed, 2016

On assumptions behind estimates of abundance from counts at multiple sites

Knape, Jonas; Korner-Nievergelt, Fraenzi

Abstract

Count data of animals observed from multiple sites are commonly used to study variation in abundance across space and time. Because some individuals typically go undetected in such surveys, count data alone have traditionally been thought to not contain information about absolute abundance. In a recent paper, we showed that estimates of absolute abundance using single-visit methods with covariates (Solymos, et al. Environmetrics, 2012, 23, 197 ) can be biased arbitrarily low if the link function used for detection probability is mis-specified. Solymos & Lele (Methods in Ecology and Evolution, 2015, in press) argue that this is not a relevant issue in practice. We discuss the implications of the assumptions necessary for estimating abundance from the single-visit model and clarify and extend results in Knape & Korner-Nievergelt (Methods in Ecology and Evolution, 2015, 6, 298). We also discuss assumptions of the Dail-Madsen model. We show that for the single-visit model a partially scaled link function which covers the full range from 0 to 1 leads to the same scaling issue as the scaled link function used in Knape & Korner-Nievergelt (2015) which only covers a restricted range. We argue that there is essentially no information about absolute abundance contained in single-visit count data. Additional more direct data on detection probabilities is required to robustly estimate absolute abundances.

Keywords

detection probability; estimability; N-mixture model; occupancy model; population survey; replication; sampling

Published in

Methods in Ecology and Evolution
2016, Volume: 7, number: 2, pages: 206-209
Publisher: WILEY-BLACKWELL

    UKÄ Subject classification

    Probability Theory and Statistics
    Ecology

    Publication identifier

    DOI: https://doi.org/10.1111/2041-210X.12507

    Permanent link to this page (URI)

    https://res.slu.se/id/publ/76117