دورية أكاديمية

Modeling ocean distributions and abundances of natural- and hatchery-origin Chinook salmon stocks with integrated genetic and tagging data.

التفاصيل البيبلوغرافية
العنوان: Modeling ocean distributions and abundances of natural- and hatchery-origin Chinook salmon stocks with integrated genetic and tagging data.
المؤلفون: Jensen AJ; School of Marine and Environmental Affairs, University of Washington, Seattle, WA, United States of America., Kelly RP; School of Marine and Environmental Affairs, University of Washington, Seattle, WA, United States of America., Satterthwaite WH; Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, CA, United States of America., Ward EJ; Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States of America., Moran P; Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States of America., Shelton AO; Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States of America.
المصدر: PeerJ [PeerJ] 2023 Nov 28; Vol. 11, pp. e16487. Date of Electronic Publication: 2023 Nov 28 (Print Publication: 2023).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: PeerJ Inc Country of Publication: United States NLM ID: 101603425 Publication Model: eCollection Cited Medium: Internet ISSN: 2167-8359 (Electronic) Linking ISSN: 21678359 NLM ISO Abbreviation: PeerJ Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Corte Madera, CA : PeerJ Inc.
مواضيع طبية MeSH: Salmon*/genetics , Oncorhynchus*, Animals ; Fisheries ; Pacific Ocean ; Endangered Species
مستخلص: Background: Considerable resources are spent to track fish movement in marine environments, often with the intent of estimating behavior, distribution, and abundance. Resulting data from these monitoring efforts, including tagging studies and genetic sampling, often can be siloed. For Pacific salmon in the Northeast Pacific Ocean, predominant data sources for fish monitoring are coded wire tags (CWTs) and genetic stock identification (GSI). Despite their complementary strengths and weaknesses in coverage and information content, the two data streams rarely have been integrated to inform Pacific salmon biology and management. Joint, or integrated, models can combine and contextualize multiple data sources in a single statistical framework to produce more robust estimates of fish populations.
Methods: We introduce and fit a comprehensive joint model that integrates data from CWT recoveries and GSI sampling to inform the marine life history of Chinook salmon stocks at spatial and temporal scales relevant to ongoing fisheries management efforts. In a departure from similar models based primarily on CWT recoveries, modeled stocks in the new framework encompass both hatchery- and natural-origin fish. We specifically model the spatial distribution and marine abundance of four distinct stocks with spawning locations in California and southern Oregon, one of which is listed under the U.S. Endangered Species Act.
Results: Using the joint model, we generated the most comprehensive estimates of marine distribution to date for all modeled Chinook salmon stocks, including historically data poor and low abundance stocks. Estimated marine distributions from the joint model were broadly similar to estimates from a simpler, CWT-only model but did suggest some differences in distribution in select seasons. Model output also included novel stock-, year-, and season-specific estimates of marine abundance. We observed and partially addressed several challenges in model convergence with the use of supplemental data sources and model constraints; similar difficulties are not unexpected with integrated modeling. We identify several options for improved data collection that could address issues in convergence and increase confidence in model estimates of abundance. We expect these model advances and results provide management-relevant biological insights, with the potential to inform future mixed-stock fisheries management efforts, as well as a foundation for more expansive and comprehensive analyses to follow.
Competing Interests: Eric. J. Ward is an Academic Editor for PeerJ. The authors declare that they have no other competing interests.
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فهرسة مساهمة: Keywords: Abundance; Chinook salmon; Coded wire tag; Distribution; Fisheries management; Genetic stock identification; Integrated state-space model; Marine life history
تواريخ الأحداث: Date Created: 20231204 Date Completed: 20231205 Latest Revision: 20231205
رمز التحديث: 20231206
مُعرف محوري في PubMed: PMC10691356
DOI: 10.7717/peerj.16487
PMID: 38047019
قاعدة البيانات: MEDLINE
الوصف
تدمد:2167-8359
DOI:10.7717/peerj.16487