Best practices for defining spatial boundaries and spatial structure in stock assessment

Fisheries Research, Journal Year: 2023, Volume and Issue: 262, P. 106650 - 106650

Published: Feb. 11, 2023

The 'stock concept' in fisheries science conforms to theoretical assumptions of stock assessment models, including negligible movement across boundaries, relatively homogeneous vital rates, and extensive mixing within areas. Best practices for representing population structure involve 1) interdisciplinary identification delineate spatially discrete populations or more complex structure; 2) boundaries that are aligned with the most plausible 3) spatially-explicit sampling, fleet spatial models account heterogeneity, fishing patterns, areas; 4) routine composition sampling analysis overlapping populations; 5) simulation testing performance assessments mis-specified uncertain structure. Practical units do not accurately represent may provide sufficient information achieve fishery management objectives, so practical constraints should be addressed through iterative advances identification, delineation stocks meet unit-stock assumptions, modeling.

Language: Английский

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Spatial awareness: Good practices and pragmatic recommendations for developing spatially structured stock assessments

Fisheries Research, Journal Year: 2023, Volume and Issue: 264, P. 106703 - 106703

Published: April 7, 2023

Language: Английский

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‘Drivin' with your eyes closed’: Results from an international, blinded simulation experiment to evaluate spatial stock assessments

Fish and Fisheries, Journal Year: 2024, Volume and Issue: 25(3), P. 471 - 490

Published: March 1, 2024

Abstract Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international experiment was organized. The study design blinded to replicate uncertainty similar a real‐world stock process, data‐conditioned, high‐resolution operating model (OM) used emulate the dynamics data for Indian Ocean yellowfin tuna ( Thunnus albacares ). Six analyst groups developed both single‐region using platform their choice, then applied each simulated data. Results indicated that across all structures platforms, assessments were able adequately recreate population trends from OM. Additionally, estimate regional generally reflected true OM, particularly regions higher biomass fishing pressure. However, consistent scaling pattern emerged, where estimated scale than within given platform. Balancing parsimony complexity trade‐offs difficult, adequate in parametrizations (e.g., allowing time‐ age‐variation movement appropriate tag mixing periods) critical performance. We recommend expanded use OMs studies, ability portray realistic performance models. Moreover, increased support experiments is warranted facilitate dissemination methodology organizations.

Language: Английский

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YOLOv7-DCN-SORT: An algorithm for detecting and counting targets on Acetes fishing vessel operation

Fisheries Research, Journal Year: 2024, Volume and Issue: 274, P. 106983 - 106983

Published: March 11, 2024

Language: Английский

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Developing a collaborative Dungeness crab larval monitoring network in the Salish Sea to provide long-term, fishery-relevant data

Fisheries, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Abstract Many natural resources are managed without essential, biologically relevant data. Fisheries particularly susceptible to this reality and, thus, vulnerable environmental changes and disturbances, with both human livelihoods the health of ecological systems at stake. Here, we explore how Pacific Northwest Crab Research Group (PCRG) employs a collaborative, stakeholder-driven approach generate information needed inform data-poor, co-managed fishery, using example Dungeness crab Metacarcinus magister in northeastern Pacific’s Salish Sea. We focus on PCRG larval monitoring network as multifaceted case study, which unites tribal, state, federal governments, nongovernmental organizations, academic institutions, local communities working produce first standardized continuous data set dynamics region. Highlighting types biological collected, including spatial temporal patterns flux size, application novel fisheries management, well network’s contribution diversity educational opportunities ability leverage new research projects collaborations. The success PCRG’s ultimately highlights effectiveness cooperative, network-based addressing management challenges offers viable model for managing data-poor worldwide.

Language: Английский

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Interconnected partnerships: Mapping collaborations in Australian fisheries stock assessment

Fisheries Research, Journal Year: 2025, Volume and Issue: 282, P. 107281 - 107281

Published: Jan. 24, 2025

Language: Английский

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Synthesizing the spatial functionality of contemporary stock assessment software to identify future needs for next generation assessment platforms

Fisheries Research, Journal Year: 2024, Volume and Issue: 275, P. 107008 - 107008

Published: April 16, 2024

Language: Английский

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The MSC approach for developing harvest strategies and harvest control rules for Regional Fisheries Management Organisations (RFMOs)

Marine Policy, Journal Year: 2024, Volume and Issue: 161, P. 106004 - 106004

Published: Jan. 16, 2024

Well-designed and robust harvest strategies are a key governance tool to achieve long term sustainability of target stocks. In some fisheries, however, such as those governed by Regional Fisheries Management Organisations (RFMOs), the development adoption can be challenging. Seafood eco-labelling programs, Marine Stewardship Council (MSC), one way incentivising fisheries advocate for control rules (HCRs). Here we illustrate process through which MSC Standard was recently revised guide implementation tested using management strategy evaluation, with particular focus on RFMOs. We identify three case studies that highlight challenge HCR adoption: Indian Ocean skipjack tuna Western Central Pacific North-East Atlantic mackerel fisheries. discuss problem statement highlighted challenges present when applying previous stocks managed RFMOs, how requirements within aim overcome challenges. These provide an operational framework RFMO-managed implement 'state-of-the-art' evaluation. When applied certified new expected contribute delivering positive change respect implementing HCRs across particularly in cases where there is strong interest market benefits certification.

Language: Английский

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Climate-readiness of fishery management procedures with application to the southeast US Atlantic

ICES Journal of Marine Science, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 22, 2024

Abstract Global climate change threatens the assumption of stationarity inherent in many fisheries management decisions. This heightens importance developing strategies that are robust to future uncertainty. Management strategy evaluation (MSE) is a framework which procedures (MPs) can be developed and tested using closed-loop simulation. We explored performance various model-based empirical MPs with nonstationary projections for three commercially recreationally important fish stocks southeast US Atlantic. Using openMSE, we candidate MP across designed emulate plausible conditions, including regime shifts, nonstationarity, observation error shifts survey index. Candidate was primarily measured based on its ability maintain healthy stock biomass. Results this MSE demonstrate several may better able adapt dynamics compared traditional employ full age-structured assessments, though struggle biomass when facing artificial index shifts. Relative versus varied by climate-change scenario. These findings highlight value adaptive hold climate-ready management.

Language: Английский

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Assessing interspecific variation in life-history traits of three sympatric tropical mullets using age, growth and otolith allometry

Fisheries Research, Journal Year: 2022, Volume and Issue: 260, P. 106577 - 106577

Published: Dec. 20, 2022

Language: Английский

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