Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska

We used a mechanistic movement model within a Bayesian framework to estimate survival, abundance, and rate of increase for a population of humpback whales ( Megaptera novaeangliae ) subject to a long-term photographic capture–recapture effort in southeastern Alaska, USA (SEAK). Multiple competing mo...

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Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Hendrix, A.N., Straley, J., Gabriele, C.M., Gende, S.M.
Other Authors: Chen, Yong
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2012
Subjects:
Online Access:http://dx.doi.org/10.1139/f2012-101
http://www.nrcresearchpress.com/doi/full-xml/10.1139/f2012-101
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spelling crcansciencepubl:10.1139/f2012-101 2024-05-19T07:41:45+00:00 Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska Hendrix, A.N. Straley, J. Gabriele, C.M. Gende, S.M. Chen, Yong 2012 http://dx.doi.org/10.1139/f2012-101 http://www.nrcresearchpress.com/doi/full-xml/10.1139/f2012-101 http://www.nrcresearchpress.com/doi/pdf/10.1139/f2012-101 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 69, issue 11, page 1783-1797 ISSN 0706-652X 1205-7533 journal-article 2012 crcansciencepubl https://doi.org/10.1139/f2012-101 2024-05-02T06:51:26Z We used a mechanistic movement model within a Bayesian framework to estimate survival, abundance, and rate of increase for a population of humpback whales ( Megaptera novaeangliae ) subject to a long-term photographic capture–recapture effort in southeastern Alaska, USA (SEAK). Multiple competing models were fitted that differed in movement, recapture rates, and observation error using deviance information criterion. The median annual survival probability in the selected model was 0.996 (95% central probability interval (CrI): 0.984, 0.999), which is among the highest reported for this species. Movement among areas was temporally dynamic, although whales exhibited high area fidelity (probability of returning to same area of ≥0.75) throughout the study. Median abundance was 1585 whales in 2008 (95% CrI: 1455, 1644). Incorporating an abundance estimate of 393 (95% confidence interval: 331, 455) whales from 1986, the median rate of increase was 5.1% (95% CrI: 4.4%, 5.9%). Although applied here to cetaceans in SEAK, the framework provides a flexible approach for estimating mortality and movement in populations that move among sampling areas. Article in Journal/Newspaper Humpback Whale Megaptera novaeangliae Alaska Canadian Science Publishing Canadian Journal of Fisheries and Aquatic Sciences 69 11 1783 1797
institution Open Polar
collection Canadian Science Publishing
op_collection_id crcansciencepubl
language English
description We used a mechanistic movement model within a Bayesian framework to estimate survival, abundance, and rate of increase for a population of humpback whales ( Megaptera novaeangliae ) subject to a long-term photographic capture–recapture effort in southeastern Alaska, USA (SEAK). Multiple competing models were fitted that differed in movement, recapture rates, and observation error using deviance information criterion. The median annual survival probability in the selected model was 0.996 (95% central probability interval (CrI): 0.984, 0.999), which is among the highest reported for this species. Movement among areas was temporally dynamic, although whales exhibited high area fidelity (probability of returning to same area of ≥0.75) throughout the study. Median abundance was 1585 whales in 2008 (95% CrI: 1455, 1644). Incorporating an abundance estimate of 393 (95% confidence interval: 331, 455) whales from 1986, the median rate of increase was 5.1% (95% CrI: 4.4%, 5.9%). Although applied here to cetaceans in SEAK, the framework provides a flexible approach for estimating mortality and movement in populations that move among sampling areas.
author2 Chen, Yong
format Article in Journal/Newspaper
author Hendrix, A.N.
Straley, J.
Gabriele, C.M.
Gende, S.M.
spellingShingle Hendrix, A.N.
Straley, J.
Gabriele, C.M.
Gende, S.M.
Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
author_facet Hendrix, A.N.
Straley, J.
Gabriele, C.M.
Gende, S.M.
author_sort Hendrix, A.N.
title Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
title_short Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
title_full Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
title_fullStr Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
title_full_unstemmed Bayesian estimation of humpback whale ( Megaptera novaeangliae) population abundance and movement patterns in southeastern Alaska
title_sort bayesian estimation of humpback whale ( megaptera novaeangliae) population abundance and movement patterns in southeastern alaska
publisher Canadian Science Publishing
publishDate 2012
url http://dx.doi.org/10.1139/f2012-101
http://www.nrcresearchpress.com/doi/full-xml/10.1139/f2012-101
http://www.nrcresearchpress.com/doi/pdf/10.1139/f2012-101
genre Humpback Whale
Megaptera novaeangliae
Alaska
genre_facet Humpback Whale
Megaptera novaeangliae
Alaska
op_source Canadian Journal of Fisheries and Aquatic Sciences
volume 69, issue 11, page 1783-1797
ISSN 0706-652X 1205-7533
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/f2012-101
container_title Canadian Journal of Fisheries and Aquatic Sciences
container_volume 69
container_issue 11
container_start_page 1783
op_container_end_page 1797
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