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Alternative method for assessment of southwestern Atlantic humpback whale population status

The population of humpback whales (Megaptera novaeangliae) wintering off eastern South America was exploited by commercial whaling almost to the point of extinction in the mid-twentieth century. Since cessation of whaling in the 1970s it is recovering, but the timing and level of recovery is uncerta...

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Autores principales: Bortolotto, Guilherme A., Thomas, Len, Hammond, Philip, Zerbini, Alexandre N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8598017/
https://www.ncbi.nlm.nih.gov/pubmed/34788309
http://dx.doi.org/10.1371/journal.pone.0259541
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author Bortolotto, Guilherme A.
Thomas, Len
Hammond, Philip
Zerbini, Alexandre N.
author_facet Bortolotto, Guilherme A.
Thomas, Len
Hammond, Philip
Zerbini, Alexandre N.
author_sort Bortolotto, Guilherme A.
collection PubMed
description The population of humpback whales (Megaptera novaeangliae) wintering off eastern South America was exploited by commercial whaling almost to the point of extinction in the mid-twentieth century. Since cessation of whaling in the 1970s it is recovering, but the timing and level of recovery is uncertain. We implemented a Bayesian population dynamics model describing the population’s trajectory from 1901 and projecting it to 2040 to revise a previous population status assessment that used Sampling-Importance-Resampling in a Bayesian framework. Using our alternative method for model fitting (Markov chain Monte Carlo), which is more widely accessible to ecologists, we replicate a “base case scenario” to verify the effect on model results, and introduce additional data to update the status assessment. Our approach allowed us to widen the previous informative prior on carrying capacity to better reflect scientific uncertainty around historical population levels. The updated model provided more precise estimates for population sizes over the period considered (1901–2040) and suggests that carrying capacity (K: median 22,882, mean 22,948, 95% credible interval [CI] 22,711–23,545) and minimum population size (N(1958): median 305, mean 319, 95% CI 271–444) might be lower than previously estimated (K: median 24,558, mean 25,110, 95% CI 22,791–31,118; N(1958): median 503, mean 850, 95% CI 159–3,943). However, posterior 95% credible intervals of parameters in the updated model overlap those of the previous study. Our approach provides an accessible framework for investigating the status of depleted animal populations for which information is available on historical mortality (e.g., catches) and intermittent estimates of population size and/or trend.
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spelling pubmed-85980172021-11-18 Alternative method for assessment of southwestern Atlantic humpback whale population status Bortolotto, Guilherme A. Thomas, Len Hammond, Philip Zerbini, Alexandre N. PLoS One Research Article The population of humpback whales (Megaptera novaeangliae) wintering off eastern South America was exploited by commercial whaling almost to the point of extinction in the mid-twentieth century. Since cessation of whaling in the 1970s it is recovering, but the timing and level of recovery is uncertain. We implemented a Bayesian population dynamics model describing the population’s trajectory from 1901 and projecting it to 2040 to revise a previous population status assessment that used Sampling-Importance-Resampling in a Bayesian framework. Using our alternative method for model fitting (Markov chain Monte Carlo), which is more widely accessible to ecologists, we replicate a “base case scenario” to verify the effect on model results, and introduce additional data to update the status assessment. Our approach allowed us to widen the previous informative prior on carrying capacity to better reflect scientific uncertainty around historical population levels. The updated model provided more precise estimates for population sizes over the period considered (1901–2040) and suggests that carrying capacity (K: median 22,882, mean 22,948, 95% credible interval [CI] 22,711–23,545) and minimum population size (N(1958): median 305, mean 319, 95% CI 271–444) might be lower than previously estimated (K: median 24,558, mean 25,110, 95% CI 22,791–31,118; N(1958): median 503, mean 850, 95% CI 159–3,943). However, posterior 95% credible intervals of parameters in the updated model overlap those of the previous study. Our approach provides an accessible framework for investigating the status of depleted animal populations for which information is available on historical mortality (e.g., catches) and intermittent estimates of population size and/or trend. Public Library of Science 2021-11-17 /pmc/articles/PMC8598017/ /pubmed/34788309 http://dx.doi.org/10.1371/journal.pone.0259541 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Bortolotto, Guilherme A.
Thomas, Len
Hammond, Philip
Zerbini, Alexandre N.
Alternative method for assessment of southwestern Atlantic humpback whale population status
title Alternative method for assessment of southwestern Atlantic humpback whale population status
title_full Alternative method for assessment of southwestern Atlantic humpback whale population status
title_fullStr Alternative method for assessment of southwestern Atlantic humpback whale population status
title_full_unstemmed Alternative method for assessment of southwestern Atlantic humpback whale population status
title_short Alternative method for assessment of southwestern Atlantic humpback whale population status
title_sort alternative method for assessment of southwestern atlantic humpback whale population status
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8598017/
https://www.ncbi.nlm.nih.gov/pubmed/34788309
http://dx.doi.org/10.1371/journal.pone.0259541
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