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Evaluation of Two Methods to Estimate and Monitor Bird Populations
BACKGROUND: Effective management depends upon accurately estimating trends in abundance of bird populations over time, and in some cases estimating abundance. Two population estimation methods, double observer (DO) and double sampling (DS), have been advocated for avian population studies and the re...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2516598/ https://www.ncbi.nlm.nih.gov/pubmed/18728775 http://dx.doi.org/10.1371/journal.pone.0003047 |
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author | Taylor, Sandra L. Pollard, Katherine S. |
author_facet | Taylor, Sandra L. Pollard, Katherine S. |
author_sort | Taylor, Sandra L. |
collection | PubMed |
description | BACKGROUND: Effective management depends upon accurately estimating trends in abundance of bird populations over time, and in some cases estimating abundance. Two population estimation methods, double observer (DO) and double sampling (DS), have been advocated for avian population studies and the relative merits and short-comings of these methods remain an area of debate. METHODOLOGY/PRINCIPAL FINDINGS: We used simulations to evaluate the performances of these two population estimation methods under a range of realistic scenarios. For three hypothetical populations with different levels of clustering, we generated DO and DS population size estimates for a range of detection probabilities and survey proportions. Population estimates for both methods were centered on the true population size for all levels of population clustering and survey proportions when detection probabilities were greater than 20%. The DO method underestimated the population at detection probabilities less than 30% whereas the DS method remained essentially unbiased. The coverage probability of 95% confidence intervals for population estimates was slightly less than the nominal level for the DS method but was substantially below the nominal level for the DO method at high detection probabilities. Differences in observer detection probabilities did not affect the accuracy and precision of population estimates of the DO method. Population estimates for the DS method remained unbiased as the proportion of units intensively surveyed changed, but the variance of the estimates decreased with increasing proportion intensively surveyed. CONCLUSIONS/SIGNIFICANCE: The DO and DS methods can be applied in many different settings and our evaluations provide important information on the performance of these two methods that can assist researchers in selecting the method most appropriate for their particular needs. |
format | Text |
id | pubmed-2516598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25165982008-08-27 Evaluation of Two Methods to Estimate and Monitor Bird Populations Taylor, Sandra L. Pollard, Katherine S. PLoS One Research Article BACKGROUND: Effective management depends upon accurately estimating trends in abundance of bird populations over time, and in some cases estimating abundance. Two population estimation methods, double observer (DO) and double sampling (DS), have been advocated for avian population studies and the relative merits and short-comings of these methods remain an area of debate. METHODOLOGY/PRINCIPAL FINDINGS: We used simulations to evaluate the performances of these two population estimation methods under a range of realistic scenarios. For three hypothetical populations with different levels of clustering, we generated DO and DS population size estimates for a range of detection probabilities and survey proportions. Population estimates for both methods were centered on the true population size for all levels of population clustering and survey proportions when detection probabilities were greater than 20%. The DO method underestimated the population at detection probabilities less than 30% whereas the DS method remained essentially unbiased. The coverage probability of 95% confidence intervals for population estimates was slightly less than the nominal level for the DS method but was substantially below the nominal level for the DO method at high detection probabilities. Differences in observer detection probabilities did not affect the accuracy and precision of population estimates of the DO method. Population estimates for the DS method remained unbiased as the proportion of units intensively surveyed changed, but the variance of the estimates decreased with increasing proportion intensively surveyed. CONCLUSIONS/SIGNIFICANCE: The DO and DS methods can be applied in many different settings and our evaluations provide important information on the performance of these two methods that can assist researchers in selecting the method most appropriate for their particular needs. Public Library of Science 2008-08-27 /pmc/articles/PMC2516598/ /pubmed/18728775 http://dx.doi.org/10.1371/journal.pone.0003047 Text en Taylor, Pollard. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Taylor, Sandra L. Pollard, Katherine S. Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title | Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title_full | Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title_fullStr | Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title_full_unstemmed | Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title_short | Evaluation of Two Methods to Estimate and Monitor Bird Populations |
title_sort | evaluation of two methods to estimate and monitor bird populations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2516598/ https://www.ncbi.nlm.nih.gov/pubmed/18728775 http://dx.doi.org/10.1371/journal.pone.0003047 |
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