Blood from a stone: Performance of catch-only methods in estimating stock biomass status

Free, Christopher M.; Jensen, Olaf P.; Anderson, Sean C.; Gutiérrez, Nicolás; Kleisner, Kristin M.; Longo, Catherine; Minto, Cóilín; Osio, Giacomo Chato; Walsh, Jessica C.

doi:10.1016/j.fishres.2019.105452

Cited by 59 publications

(79 citation statements)

References 43 publications

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“…We used the COMs that had their performance tested by Free et al (2020). These included five COMs that fit a population dynamics model, and two COMs that find statistical associations using data-rich assessed stocks.…”

Section: Catch-only Models (Coms)mentioning

confidence: 99%

“…The different COMs that we fitted to our data yield different results, owing to their inherent biases due to different methods and assumptions (Free et al, 2020). To try and resolve these potential discrepancies, we combined the results of the different COMs in a superensemble model approach.…”

Section: Superensemble Modelsmentioning

confidence: 99%

“…COMS designed to estimate stock status time-series can be divided into two broad categories: mechanistic and empirical COMs (Free et al, 2020). Mechanistic COMs fit a population dynamics model to the catch data and make assumptions regarding parameter values to make up for the lack of other data.…”

Section: Introductionmentioning

confidence: 99%

“…Empirical COMs include models such as mPRM (Rosenberg et al, 2014) and zBRT (Zhou et al, 2017). COMs are not as accurate in predicting stock status as data-rich statistical catch-at-age models, but they offer a promising alternative when the absence of some data prevents a full data-rich assessment (Free et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Data-poor stock assessment of fish stocks co-exploited by commercial and recreational fisheries: applications to pike (Esox lucius) in the western Baltic Sea

Gemert

Koemle

Winkler

et al. 2021

Preprint

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Information on catch and effort of recreational angling in mixed-use fisheries (co-exploited by commercial and recreational fishers) is often scarce, preventing the application of data-rich stock assessments typically performed for industrialized commercial fisheries. Here, we show how data-poor stock assessment methods developed for marine fisheries, particularly a class of models labelled as “catch-only” models (COMs), offer a possible solution. As a case study, we use COMs to assess a northern pike stock around the German Baltic island of Rügen. We fit multiple COMs to a time-series of total pike removals, and use their outputs as explanatory variables in superensemble models. We conclude that the stock is fully exploited and currently declining. Our study highlights the potential for using COMs to determine status of previously-unassessed coastal and freshwater stocks facing recreational fishing pressure, and demonstrates how incorporating recreational removals is crucial for achieving reliable insights into the status of mixed-use stocks.

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Section: Catch-only Models (Coms)mentioning

confidence: 99%

Section: Superensemble Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Data-poor stock assessment of fish stocks co-exploited by commercial and recreational fisheries: applications to pike (Esox lucius) in the western Baltic Sea

Gemert

Koemle

Winkler

et al. 2021

Preprint

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show abstract

“…But such high resolution data is inherently expensive to acquire and is thus limited to stocks harvested by industrial or commercial fisheries, such as those cataloged in the RAM Legacy Stock Assessment database (Ricard et al, 2012). And while various data-limited approaches to stock assessment methods have been developed, they tend to produce imprecise and biased estimates of stock status relative to data-intensive methods (Free et al, 2020). As a result, the population status of species targeted purely by artisanal, recreational, and subsistence fisheries, which represent more than half of global fishing effort (Rousseau et al, 2019), are not included in stock assessments.…”

Section: Introductionmentioning

confidence: 99%

Substantial Gaps in the Current Fisheries Data Landscape

et al. 2020

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Effective management of aquatic resources, wild and farmed, has implications for the livelihoods of dependent communities, food security, and ecosystem health. Good management requires information on the status of harvested species, yet many gaps remain in our understanding of these species and systems, in particular the lack of taxonomic resolution of harvested species. To assess these gaps we compared the occurrence of landed species (freshwater and marine) from the United Nations Food and Agriculture Organization (FAO) global fisheries production database to those in the International Union for Conservation of Nature (IUCN) Red List and the RAM Legacy Stock Assessment Database, some of the largest and most comprehensive global datasets of consumed aquatic species. We also quantified the level of resolution and trends in taxonomic reporting for all landed taxa in the FAO database. Of the 1,695 consumed aquatic species or groups in the FAO database considered in this analysis, a large portion (35%) are missing from both of the other two global datasets, either IUCN or RAM, used to monitor, manage, and protect aquatic resources. Only a small number of all fished taxa reported in FAO data (150 out of 1,695; 9%) have both a stock assessment in RAM and a conservation assessment in IUCN. Furthermore, 40% of wild caught landings are not reported to the species level, limiting our ability to effectively account for the environmental impacts of wild harvest. Landings of invertebrates (44%) and landings in Asia (>75%) accounted for the majority of harvest without species specific information in 2018. Assessing the overlap of species which are both farmed and fished to broadly map possible interactions – which can help or hinder wild populations - we found 296 species, accounting for 12% of total wild landings globally, and 103 countries and territories that have overlap in the species caught in the wild and produced through aquaculture. In all, our work highlights that while fisheries management is improving in many areas there remain key gaps in data resolution that are critical for fisheries assessments and conservation of aquatic systems into the future.

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Data‐limited fishery assessment methods shed light on the exploitation history and population dynamics of Endangered Species Act‐listed Yelloweye Rockfish in Puget Sound, Washington

Min,

Cope,

Lowry

et al. 2023

Mar Coast Fish

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ObjectiveThe distinct population segment (DPS) of Yelloweye Rockfish Sebastes ruberrimus inhabiting the Puget Sound/Georgia Basin was listed under the Endangered Species Act (ESA) in 2010, and a formal recovery plan for the DPS was published by National Oceanic and Atmospheric Administration Fisheries in 2017. In this recovery plan, the biological criteria for delisting or downlisting were specified as certain levels of spawning potential ratio (SPR), a commonly used metric of equilibrium stock status for commercially exploited fishes. Although this metric can be estimated from length compositions, the combination of length data with a catch history (which was not previously available for this DPS) improves our understanding of population dynamics over time and allows us to estimate a different measure of stock status, relative (to unfished) spawning stock biomass (SSB), rather than only SPR.MethodsTo estimate relative SSB and reconstruct the historical dynamics of this DPS, we reconstructed the catch history from fisheries records, collated length data from historical and contemporary hook‐and‐line surveys, and fitted a data‐limited version of a statistical catch‐at‐age model.ResultDespite a high level of uncertainty, we estimated that Yelloweye Rockfish in Puget Sound are above 25% of unfished biomass (a reference point detailed in the recovery criteria) under the assumption of deterministic recruitment, presenting the first direct estimates of Yelloweye Rockfish population status in Puget Sound.ConclusionHowever, as informed by recent genetic studies, the DPS boundaries of ESA‐listed Yelloweye Rockfish extend from South Puget Sound to Queen Charlotte Strait in British Columbia. The Canadian portion of this population is managed separately and is currently estimated to be at 32% of unfished biomass (95% quantiles = 15%–68%). Thus, the disjunction between the biological boundaries of the population and the jurisdictional boundaries between Canada and the United States presents an additional source of uncertainty in assessing recovery that must be addressed to achieve DPS‐wide recovery goals.

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Blood from a stone: Performance of catch-only methods in estimating stock biomass status

Cited by 59 publications

References 43 publications

Data-poor stock assessment of fish stocks co-exploited by commercial and recreational fisheries: applications to pike (Esox lucius) in the western Baltic Sea

Data-poor stock assessment of fish stocks co-exploited by commercial and recreational fisheries: applications to pike (Esox lucius) in the western Baltic Sea

Substantial Gaps in the Current Fisheries Data Landscape

Data‐limited fishery assessment methods shed light on the exploitation history and population dynamics of Endangered Species Act‐listed Yelloweye Rockfish in Puget Sound, Washington

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