An official website of the United States government
Abstract The management and conservation of tuna and other transboundary marine species have to date been limited by an incomplete understanding of the oceanographic, ecological and socioeconomic factors mediating fishery overlap and interactions, and how these factors vary across expansive, open ocean habitats. Despite advances in fisheries monitoring and biologging technology, few attempts have been made to conduct integrated ecological analyses at basin scales relevant to pelagic fisheries and the highly migratory species they target. Here, we use vessel tracking data, archival tags, observer records, and machine learning to examine inter‐ and intra‐annual variability in fisheries overlap (2013–2020) of five pelagic longline fishing fleets with North Pacific albacore tuna (Thunnus alalunga, Scombridae). Although progressive declines in catch and biomass have been observed over the past several decades, the North Pacific albacore is one of the only Pacific tuna stocks primarily targeted by pelagic longlines not currently listed as overfished or experiencing overfishing. We find that fishery overlap varies significantly across time and space as mediated by (1) differences in habitat preferences between juvenile and adult albacore; (2) variation of oceanographic features known to aggregate pelagic biomass; and (3) the different spatial niches targeted by shallow‐set and deep‐set longline fishing gear. These findings may have significant implications for stock assessment in this and other transboundary fishery systems, particularly the reliance on fishery‐dependent data to index abundance. Indeed, we argue that additional consideration of how overlap, catchability, and size selectivity parameters vary over time and space may be required to ensure the development of robust, equitable, and climate‐resilient harvest control rules.
more »
« less
Rapid approach for assessing an unregulated fishery using a series of data-limited tools
Abstract ObjectiveFisheries provide countless benefits to human populations but face many threats ranging from climate change to overfishing. Despite these threats and an increase in fishing pressure globally, most stocks remain unassessed and data limited. An abundance of data-limited assessment methods exists, but each has different data requirements, caveats, and limitations. Furthermore, developing informative model priors can be difficult when little is known about the stock, and uncertain model parameters could create misleading results about stock status. Our research illustrates an approach for rapidly creating robust initial assessments of unregulated and data-limited fisheries without the need for additional data collection. MethodsOur method uses stakeholder knowledge combined with a series of data-limited tools to identify an appropriate stock assessment method, conduct an assessment, and examine how model uncertainty influences the results. Our approach was applied to the unregulated and data-limited fishery for Crevalle Jack Caranx hippos in Florida. ResultResults suggested a steady increase in exploitation and a decline in stock biomass over time, with the stock currently overfished and undergoing overfishing. These findings highlight a need for management action to prevent continued stock depletion. ConclusionOur approach can help to streamline the initial assessment and management process for unregulated and data-limited stocks and serves as an additional tool for combating the many threats facing global fisheries.
more »
« less
- PAR ID:
- 10471970
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Marine and Coastal Fisheries
- Volume:
- 15
- Issue:
- 5
- ISSN:
- 1942-5120
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Griffith, Gary (Ed.)Abstract The stock–recruitment relationship is the basis of any stock prediction and thus fundamental for fishery management. Traditional parametric stock–recruitment models often poorly fit empirical data, nevertheless they are still the rule in fish stock assessment procedures. We here apply a multi-model approach to predict recruitment of 20 Atlantic cod (Gadus morhua) stocks as a function of adult biomass and environmental variables. We compare the traditional Ricker model with two non-parametric approaches: (i) the stochastic cusp model from catastrophe theory and (ii) multivariate simplex projections, based on attractor state-space reconstruction. We show that the performance of each model is contingent on the historical dynamics of individual stocks, and that stocks which experienced abrupt and state-dependent dynamics are best modelled using non-parametric approaches. These dynamics are pervasive in Western stocks highlighting a geographical distinction between cod stocks, which have implications for their recovery potential. Furthermore, the addition of environmental variables always improved the models’ predictive power indicating that they should be considered in stock assessment and management routines. Using our multi-model approach, we demonstrate that we should be more flexible when modelling recruitment and tailor our approaches to the dynamical properties of each individual stock.more » « less
-
null (Ed.)Translational ecology defines a collaborative effort among scientists and stakeholders to rapidly translate environmental problems into action. This approach can be applied in a fisheries management context when information needed to inform regulations is unavailable, yet conservation concerns exist. Our research uses a translational ecology framework to assess the stock status and develop research priorities for the crevalle jack (Caranx hippos) in the Florida Keys, USA, a currently unregulated species. Interview data that compiled expert fishing guide knowledge were used to develop hypotheses tested using existing fisheries-dependent datasets to check for agreement among sources and assess the consistency of observed patterns. Six hypotheses were developed concerning the status and trends of the crevalle jack population in the Florida Keys, and four of these hypotheses received clear support, with agreement between guide observations and one or more of the fisheries-dependent datasets. The results of our study outline an effective translational ecology approach for recreational fisheries management designed to rapidly recognize potential management needs as identified by fishing guides, which allows for actionable science and proactive management.more » « less
-
Abstract Sustainably managing fisheries requires regular and reliable evaluation of stock status. However, most multispecies reef fisheries around the globe tend to lack research and monitoring capacity, preventing the estimation of sustainable reference points against which stocks can be assessed. Here, combining fish biomass data for >2000 coral reefs, we estimate site-specific sustainable reference points for coral reef fisheries and use these and available catch estimates to assess the status of global coral reef fish stocks. We reveal that >50% of sites and jurisdictions with available information have stocks of conservation concern, having failed at least one fisheries sustainability benchmark. We quantify the trade-offs between biodiversity, fish length, and ecosystem functions relative to key benchmarks and highlight the ecological benefits of increasing sustainability. Our approach yields multispecies sustainable reference points for coral reef fisheries using environmental conditions, a promising means for enhancing the sustainability of the world’s coral reef fisheries.more » « less
-
Understanding population dynamics is essential for achieving sustainable and productive fisheries. However, estimating recruitment in a stock assessment model involves the challenging task of identifying a self-sustaining population, which often includes representing complex geographic structure. A review of several case studies demonstrated that alternative stock assessment models can influence estimates of recruitment. Incorporating spatial population structure and connectivity into stock assessment models changed the perception of recruit- ment events for a wide diversity of fisheries, but the degree to which estimates were impacted depended on movement rates and relative stock sizes. For multiple population components, estimates of strong recruitment events and the productivity of smaller population units were often more sensitive to connectivity assumptions. Simulation testing, conditioned on these case studies, suggested that accurately accounting for population structure, either in management unit definitions or stock assessment model structure, improved recruitment estimates. An understanding of movement dynamics improved estimation of connected sub-populations. The challenge of representing geographic structure in stock assessment emphasizes the importance of defining self- sustaining management units to justify a unit-stock assumption.more » « less
