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    Bayesian multi-species N-mixture models for unmarked animal communities

    Mimnagh, Niamh and Parnell, Andrew and Prado, Estevão and Moral, Rafael de Andrade (2022) Bayesian multi-species N-mixture models for unmarked animal communities. Environmental and Ecological Statistics, 29 (4). pp. 755-778. ISSN 1352-8505

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    We propose an extension of the N-mixture model that enables the estimation of abundances of multiple species as well as the correlations between them. Our novel multi-species N-mixture model (MNM) is the first to address the estimation of both positive and negative inter-species correlations, which allows us to assess the influence of the abundance of one species on another. We provide extensions that permit the analysis of data with excess of zero counts, and relax the assumption that populations are closed through the incorporation of an autoregressive term in the abundance. Our approach provides a method of quantifying the strength of association between species’ population sizes and is of practical use to population and conservation ecologists. We evaluate the performance of the proposed models through simulation experiments in order to examine the accuracy of both model estimates and coverage rates. The results show that the MNM models produce accurate estimates of abundance, inter-species correlations and detection probabilities at a range of sample sizes. The MNM models are applied to avian point data collected as part of the North American Breeding Bird Survey between 2010 and 2019. The results reveal an increase in Bald Eagle abundance in south-eastern Alaska in the decade examined.

    Item Type: Article
    Keywords: Abundance estimation; Autoregression; BIC; Excess zeros; North American Breeding Bird Survey;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 18488
    Identification Number:
    Depositing User: Rafael de Andrade Moral
    Date Deposited: 08 May 2024 14:05
    Journal or Publication Title: Environmental and Ecological Statistics
    Publisher: Springer
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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