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Simultaneous-count models to estimate abundance from counts of unmarked individuals with imperfect detection

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journal contribution
posted on 2019-06-01, 00:00 authored by Gerard Edward Ryan, Emily Nicholson, Jonathan C Eames, Thomas N E Gray, Robin Loveridge, Simon P Mahood, Phearun Sum, Michael A McCarthy
We developed a method to estimate population abundance from simultaneous counts of unmarked individuals over multiple sites. We considered that at each sampling occasion, individuals in a population could be detected at 1 of the survey sites or remain undetected and used either multinomial or binomial simultaneous-count models to estimate abundance, the latter being equivalent to an N-mixture model with one site. We tested model performance with simulations over a range of detection probabilities, population sizes, growth rates, number of years, sampling occasions, and sites. We then applied our method to 3 critically endangered vulture species in Cambodia to demonstrate the real-world applicability of the model and to provide the first abundance estimates for these species in Cambodia. Our new approach works best when existing methods are expected to perform poorly (i.e., few sites and large variation in abundance among sites) and if individuals may move among sites between sampling occasions. The approach performed better when there were >8 sampling occasions and net probability of detection was high (>0.5). We believe our approach will be useful in particular for simultaneous surveys at aggregation sites, such as roosts. The method complements existing approaches for estimating abundance of unmarked individuals and is the first method designed specifically for simultaneous counts.

History

Journal

Conservative biology

Volume

33

Issue

3

Pagination

697 - 708

Publisher

Wiley

Location

Chichester, Eng.

eISSN

1523-1739

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2019, Society for Conservation Biology