Estimating population abundance using counts from an auxiliary population

We develop a new method for estimating population abundance for notoriously difficult to count populations. This is made possible using an easy to count auxiliary population with a known link to the target population under the framework of a layered hidden Markov model. We apply the new methods to e...

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Veröffentlicht in:Environmental and ecological statistics 2020-09, Vol.27 (3), p.509-526
Hauptverfasser: Parker, Matthew R. P., Pattison, Vivian, Cowen, Laura L. E.
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container_title Environmental and ecological statistics
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creator Parker, Matthew R. P.
Pattison, Vivian
Cowen, Laura L. E.
description We develop a new method for estimating population abundance for notoriously difficult to count populations. This is made possible using an easy to count auxiliary population with a known link to the target population under the framework of a layered hidden Markov model. We apply the new methods to estimate the breeding population of an Ancient Murrelet seabird colony, using Ancient Murrelet chicks as an auxiliary population. We compare our results to those of the established survey methodology from the Canadian Wildlife Service (CWS), which similarly shows a decrease in population over 1995 to 2006. Our methods improve upon the CWS survey methods by allowing density differences across sampling sites, and by allowing estimates to be made between CWS survey years.
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source SpringerNature Journals
subjects Abundance
Aquatic birds
Biomedical and Life Sciences
Breeding
Case studies
Chemistry and Earth Sciences
Chicks
Colonies
Computer Science
Ecology
Estimates
Estimation
Health Sciences
Life Sciences
Markov chains
Math. Appl. in Environmental Science
Medicine
Methods
Physics
Polls & surveys
Population number
Population statistics
Seabirds
Software
Statistics for Engineering
Statistics for Life Sciences
Surveying
Theoretical Ecology/Statistics
Trends
Wildlife
Wildlife conservation
title Estimating population abundance using counts from an auxiliary population
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