Evaluation of the prediction skill of stock assessment using hindcasting

Kell, Laurence T.; Kimoto, Ai; Kitakado, Toshihide

doi:10.1016/j.fishres.2016.05.017

Cited by 23 publications

(14 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In other cases, such as IOTC albacore, likelihood weighting was not possible due to issues with data (different sample sizes for length frequencies). Similar issues arise with the Akaike information criterion (AIC), since it cannot be used to choose between models (or assign weights) whenever models are conditioned on different sets of data, which occurs whenever OMs are expected to represent uncertainty arising from conflicting or unreliable data sources (Kell, Kimoto, & Kitakado, 2016).…”

Section: Common Issues In Conditioning Selecting and Weighting Of Om Across The Trfmosmentioning

confidence: 99%

Operating model design in tuna Regional Fishery Management Organizations: Current practice, issues and implications

Sharma¹,

Levontin

Kitakado

et al. 2020

Fish and Fisheries

Self Cite

View full text Add to dashboard Cite

The five Regional Fishery Management Organizations dedicated to tunas (tRFMOs) are all either developing or implementing Management Strategy Evaluations (MSEs) to provide advice for the stocks under their competencies. Providing a comparative overview will help tRFMOs to learn from one another and to collaborate on common solutions and may also help to more clearly define the challenges of building decision support tools in contexts of large scientific uncertainty and where management requires cooperation across multiple stakeholders characterized by unequal power and divergent interests. For example, our overview showed that in most cases, a grid‐based design with an emphasis on structural uncertainty has been adopted. However, uncertainties such as sampling errors and non‐stationarity of important ecological processes, which are of potentially equal significance for demonstrating robustness of management procedures, were not considered. This paper identifies key issues for operating model (OM) design that challenges the tRFMOs, compares how these challenges are being met, summarizes what lessons have been learned and suggests a way forward. Although the current approach of using assessment models as the basis for OM design is a reasonable starting point, improvements should be made to the conditioning of OMs, especially with respect to enabling the inclusion of other important processes and uncertainties that are difficult to account for in stock assessments but that can crucially affect the robustness of advice. Attempts should also be made to improve documentation and communication of uncertainties that are included and those that are excluded from consideration in the process.

show abstract

Section: Common Issues In Conditioning Selecting and Weighting Of Om Across The Trfmosmentioning

confidence: 99%

Operating model design in tuna Regional Fishery Management Organizations: Current practice, issues and implications

Sharma¹,

Levontin

Kitakado

et al. 2020

Fish and Fisheries

Self Cite

View full text Add to dashboard Cite

show abstract

“…They also can be used for a quantitative evaluation of the effect of F for recovering depleted fisheries [30,32,33]. In other framework, this knowledge has been used to examine changes of biomass, recruitment, and harvest rate, based on the catch data transformed into size composition data, in a similar way as [34][35][36].…”

Section: Discussionmentioning

confidence: 99%

Assessing the Exploitation Strategies of the Shrimp Fishery in the Gulf of California

RamÃÂrez-Villalobos¹,

ChÃ¡vez²

2020

Fish Aquac J

View full text Add to dashboard Cite

Shrimp is the most valuable fisheries resource in Mexico, representing almost 40% of the total production landed, with total revenue of more than US $ 132 million per year. Shrimp fishery provides with more than 30,000 direct and indirect jobs. Three peneid shrimp species, blue, brown, and white shrimp of the southern Gulf of California, are exploited near to their maximum capacity, and they account for >95% of the wild stock of the Pacific coast. In the current fishery, the age of first capture is the overexploiting juveniles; therefore, increasing the age of the first capture from four to five months is recommended. The stocks were evaluated with a simulation model. Two fishing scenarios were tested: the maximum sustainable yield (MSY) and the MSY/fisher. As it is not possible to address particular exploitation policies for each species, the recommended exploitation strategies are based on combined species. It was concluded that, for the MSY scenario, 12,000 fishing days per season would fulfill most of the requirements; in the second case (MSY/fisher), reducing the current number of boats to 530 would achieve the required goal.

show abstract

“…Having identified the serious potential risks of assessment misspecification, a priority for future research is the development of suitable diagnostic tools. Current approaches include analysis of retrospective patterns and residual analysis (Carvalho, Punt, Chang, Maunder, & Piner, 2017;Hurtado-Ferro et al, 2015;Legault, 2009) and predictive skill (Brooks & Legault, 2015;Kell, Kimoto, & Kitakado, 2016). Currently, under investigation is the development of methods that compare the data observed after an assessment was conducted with the posterior predictive data of the assessment to detect persistent model misspecification (e.g.…”

Section: Discussionmentioning

confidence: 99%

Misspecification in stock assessments: Common uncertainties and asymmetric risks

2019

View full text Add to dashboard Cite

Common uncertainties in stock assessment relate to parameters or assumptions that strongly determine both the estimates of quantities of management interest (e.g. stock depletion) and related reference points (e.g. biomass at maximum sustainable yield). The risks associated with these uncertainties are often presented to managers in the form of decision tables. However, a formal evaluation of the risks from misspecifying an assessment model over time‐horizons spanning multiple assessment cycles requires closed‐loop simulation. There were two aims of this study: (a) develop an approach to identify and evaluate asymmetries in risk to yields and spawning biomass due to biases in key parameters and data sources in a stock assessment model, (b) quantify the relative importance of correctly specifying the various assessment attributes. A computationally efficient stock reduction analysis was evaluated using closed‐loop simulation to identify risks associated with a stock assessment with persistent positive and negative biases in the key parameters and inaccurate assumptions regarding data sources. Six types of assessment misspecification were examined, namely the assumed natural mortality rate, the assumed recruitment compensation ratio, the assumed age of maturity, a hyper‐stable or hyper‐deplete index of abundance, over‐ or under‐reporting of historical catch, and misspecification of the assumed shape of the selectivity curve. This study reveals large asymmetries in risk associated with common uncertainties in stock assessment processes. We highlight the value of reproducible and computationally efficient stock assessment models that can be investigated by closed‐loop simulation before being used for fisheries management.

show abstract

Evaluation of the prediction skill of stock assessment using hindcasting

Cited by 23 publications

References 43 publications

Operating model design in tuna Regional Fishery Management Organizations: Current practice, issues and implications

Operating model design in tuna Regional Fishery Management Organizations: Current practice, issues and implications

Assessing the Exploitation Strategies of the Shrimp Fishery in the Gulf of California

Misspecification in stock assessments: Common uncertainties and asymmetric risks

Contact Info

Product

Resources

About