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Modeling Population Collapse and Recovery in Herring.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Population Collapse and Recovery in Herring./
作者:	Trochta, John T.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	243 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:	Dissertations Abstracts International82-11B.
標題:	Aquatic sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28322615
ISBN:	9798728233060

Modeling Population Collapse and Recovery in Herring.
Trochta, John T.

Modeling Population Collapse and Recovery in Herring. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 243 p.

Source: Dissertations Abstracts International, Volume: 82-11, Section: B.

Thesis (Ph.D.)--University of Washington, 2021.

This item must not be sold to any third party vendors.

Population collapse in forage fish occurs both naturally and due to overfishing, and is a challenge to sustainable fisheries management. Sustained low abundance can result in prolonged fishery closures and impact the abundance of other species via predation or competition. The time taken to recover from collapse is determined by uncertain factors that control population dynamics and can widely vary between populations. Herring (Clupea spp.) are a major group of forage fishes with numerous populations throughout the Northern Hemisphere, that have sustained commercial fisheries for centuries and indigenous fishers for far longer, and support ecologically and economically valuable species including various pinnipeds, whales, seabirds, and predatory fishes. Herring populations across the world have shown varying durations of population collapse since the start of industrial fishing while hypotheses of the underlying factors have been underdetermined across and within individual populations. The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska is a modern enduring example of prolonged population collapse whose population dynamics remain largely uncertain and unpredictable despite intensive monitoring and modeling.In this dissertation, I explore and evaluate factors that potentially influence population collapse and recovery within herring. My overarching goal is to better inform the population dynamics of herring and more specifically improve the Bayesian stock assessment model of Prince William Sound herring. In Chapter 1, I conducted a meta-analysis on time series collected for 64 populations worldwide to statistically characterize population collapse and recovery in herring and model predictors of recovery times in adult biomass and recruitment. After collapse, herring populations recovered in 11 years on average, with a few populations remaining collapsed for multiple decades. Amongst populations, recovery time duration did not coincide with fishery closures, which occurred at low abundance in most Pacific herring populations but no Atlantic herring populations. Faster recovery in biomass was best associated with higher average recruitment and higher oceanographic variability in both sea surface height anomalies and sea surface temperatures.In Chapter 2, I modeled ecological factors impacting natural mortality and recruitment in Prince William Sound herring using a custom-built Bayesian age-structured stock assessment model. Support for individual factors was evaluated using multiple Bayesian model selection criteria and alternative modeling assumptions about the ecological data representing these factors. There was strongest evidence for effects on herring natural mortality from pink salmon abundance in Prince William Sound had the most broad and consistent support. Statistical support differed by the type of selection criteria, model assumptions regarding covariates, and time period modeled, resulting in generally weak evidence for most individual effects and the suggestion that results are sensitive to model flexibility.In Chapter 3, I developed a novel modeling framework and conducted a simulation study to test the usefulness of age-specific antibody, or seroprevalence, data in assessing the impact of disease-associated mortality on herring, for use in stock assessment models. Viral hemorrhagic septicemia virus (VHSV) in Prince William Sound herring is used as a case study due to its association with fish kills and well-established ecological principles for its epizootiology from extensive monitoring of VHSV in herring populations. I found that incorporating seroprevalence data within stock assessment can accurately inform infection history and disease mortality and improve population estimates. The first real application of age-specific VHSV seroprevalence is demonstrated with the Prince William Sound herring stock assessment. While motivated from VHSV in herring, these models can be easily adapted to different host populations and pathogens and I present advice for future applications of disease data within stock assessment.

ISBN: 9798728233060Subjects--Topical Terms:

3174300
Aquatic sciences.
Subjects--Index Terms:

Fisheries model

Modeling Population Collapse and Recovery in Herring.
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520 $a Population collapse in forage fish occurs both naturally and due to overfishing, and is a challenge to sustainable fisheries management. Sustained low abundance can result in prolonged fishery closures and impact the abundance of other species via predation or competition. The time taken to recover from collapse is determined by uncertain factors that control population dynamics and can widely vary between populations. Herring (Clupea spp.) are a major group of forage fishes with numerous populations throughout the Northern Hemisphere, that have sustained commercial fisheries for centuries and indigenous fishers for far longer, and support ecologically and economically valuable species including various pinnipeds, whales, seabirds, and predatory fishes. Herring populations across the world have shown varying durations of population collapse since the start of industrial fishing while hypotheses of the underlying factors have been underdetermined across and within individual populations. The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska is a modern enduring example of prolonged population collapse whose population dynamics remain largely uncertain and unpredictable despite intensive monitoring and modeling.In this dissertation, I explore and evaluate factors that potentially influence population collapse and recovery within herring. My overarching goal is to better inform the population dynamics of herring and more specifically improve the Bayesian stock assessment model of Prince William Sound herring. In Chapter 1, I conducted a meta-analysis on time series collected for 64 populations worldwide to statistically characterize population collapse and recovery in herring and model predictors of recovery times in adult biomass and recruitment. After collapse, herring populations recovered in 11 years on average, with a few populations remaining collapsed for multiple decades. Amongst populations, recovery time duration did not coincide with fishery closures, which occurred at low abundance in most Pacific herring populations but no Atlantic herring populations. Faster recovery in biomass was best associated with higher average recruitment and higher oceanographic variability in both sea surface height anomalies and sea surface temperatures.In Chapter 2, I modeled ecological factors impacting natural mortality and recruitment in Prince William Sound herring using a custom-built Bayesian age-structured stock assessment model. Support for individual factors was evaluated using multiple Bayesian model selection criteria and alternative modeling assumptions about the ecological data representing these factors. There was strongest evidence for effects on herring natural mortality from pink salmon abundance in Prince William Sound had the most broad and consistent support. Statistical support differed by the type of selection criteria, model assumptions regarding covariates, and time period modeled, resulting in generally weak evidence for most individual effects and the suggestion that results are sensitive to model flexibility.In Chapter 3, I developed a novel modeling framework and conducted a simulation study to test the usefulness of age-specific antibody, or seroprevalence, data in assessing the impact of disease-associated mortality on herring, for use in stock assessment models. Viral hemorrhagic septicemia virus (VHSV) in Prince William Sound herring is used as a case study due to its association with fish kills and well-established ecological principles for its epizootiology from extensive monitoring of VHSV in herring populations. I found that incorporating seroprevalence data within stock assessment can accurately inform infection history and disease mortality and improve population estimates. The first real application of age-specific VHSV seroprevalence is demonstrated with the Prince William Sound herring stock assessment. While motivated from VHSV in herring, these models can be easily adapted to different host populations and pathogens and I present advice for future applications of disease data within stock assessment.
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