scholarly journals Evaluating the role of data quality when sharing information in hierarchical multistock assessment models, with an application to Dover sole

2019 ◽  
Vol 76 (10) ◽  
pp. 1819-1835
Author(s):  
Samuel D.N. Johnson ◽  
Sean P. Cox
Keyword(s):  
Statistical Power ◽  
Fishery Management ◽  
Stock Assessment ◽  
Simulated Data ◽  
Assessment Model ◽  
Production Model ◽  
Estimation Errors ◽  
Lower Estimation ◽  
Relative Errors ◽  
Dover Sole

An emerging approach to data-limited fisheries stock assessment uses hierarchical multistock assessment models to group stocks together, sharing information from data-rich to data-poor stocks. In this paper, we simulate data-rich and data-poor fishery and survey data scenarios for a complex of Dover sole (Microstomus pacificus) stocks. Simulated data for individual stocks were used to compare estimation performance for single-stock and hierarchical multistock versions of a Schaefer production model. The single-stock and best-performing multistock models were then used in stock assessments for the real Dover sole data. Multistock models often had lower estimation errors than single-stock models when assessment data had low statistical power. Relative errors for productivity and relative biomass parameters were lower for multistock assessment model configurations. In addition, multistock models that estimated hierarchical priors for survey catchability performed the best under data-poor scenarios. We conclude that hierarchical multistock assessment models are useful for data-limited stocks and could provide a more flexible alternative to data pooling and catch-only methods; however, these models are subject to nonlinear side effects of parameter shrinkage. Therefore, we recommend testing hierarchical multistock models in closed-loop simulations before application to real fishery management systems.

scholarly journals Ecological Reference Points for Atlantic Menhaden Established Using an Ecosystem Model of Intermediate Complexity

2020 ◽  
Vol 7 ◽  
Author(s):  
David Chagaris ◽  
Katie Drew ◽  
Amy Schueller ◽  
Matt Cieri ◽  
Joana Brito ◽  
...  
Keyword(s):  
Striped Bass ◽  
Fishery Management ◽  
Stock Assessment ◽  
Reference Points ◽  
Atlantic Menhaden ◽  
Assessment Model ◽  
Total Allowable Catch ◽  
Important Species ◽  
Ecosystem Impacts ◽  
Intermediate Complexity

Atlantic menhaden (Brevoortia tyrannus) are an important forage fish for many predators, and they also support the largest commercial fishery by weight on the U.S. East Coast. Menhaden management has been working toward ecological reference points (ERPs) that account for menhaden’s role in the ecosystem. The goal of this work was to develop menhaden ERPs using ecosystem models. An existing Ecopath with Ecosim model of the Northwest Atlantic Continental Shelf (NWACS) was reduced in complexity from 61 to 17 species/functional groups. The new NWACS model of intermediate complexity for ecosystems (NWACS-MICE) serves to link the dynamics of menhaden with key managed predators. Striped bass (Morone saxatilis) were determined to be most sensitive to menhaden harvest and therefore served as an indicator of ecosystem impacts. ERPs were based on the tradeoff relationship between the equilibrium biomass of striped bass and menhaden fishing mortality (F). The ERPs were defined as the menhaden F rates that maintain striped bass at their biomass target and threshold when striped bass are fished at their Ftarget, and all other modeled species were fished at status quo levels. These correspond to an ERP Ftarget of 0.19 and an ERP Fthreshold of 0.57, which are lower than the single species reference points by 30–40%, but higher than current (2017) menhaden F. The ERPs were then fed back into the age-structured stock assessment model projections to provide information on total allowable catch. The ERPs developed in this study were adopted by the Atlantic menhaden Management Board, marking a shift toward ecosystem-based fishery management for this economically and ecologically important species.

scholarly journals Environmental influences on commercial oceanic ommastrephid squids: a stock assessment perspective

2017 ◽  
Vol 81 (1) ◽  
pp. 37 ◽  
Author(s):  
Jintao Wang ◽  
Xinjun Chen ◽  
Kisei Tanaka ◽  
Jie Cao ◽  
Yong Chen
Keyword(s):  
Environmental Variability ◽  
Mean Squared Error ◽  
Stock Assessment ◽  
Reference Points ◽  
Assessment Model ◽  
Production Model ◽  
Northwest Pacific ◽  
Dosidicus Gigas ◽  
Southwest Atlantic ◽  
Data Assessment

Ommastrephid squids are short-lived ecological opportunists and their recruitment is largely driven by the surrounding environment. While recent studies suggest that recruitment variability in several squid species can be partially explained by environmental variability derived from synoptic oceanographic data, assessment of ommastrephid stocks using environmental variability is rare. In thisstudy, we modified asurplus production model to incorporate environmental variability into the assessment of threeommastrephid squids (Ommastrephes bartramii in the northwest Pacific, Illex argentinus in the southwest Atlantic and Dosidicus gigas in the southwest Pacific). We assumed that the key environmental variables—suitable sea surface temperature on spawning grounds during the spawning seasons and feeding grounds during the feeding seasons—have effects on the carrying capacity and the instantaneous population growth rate, respectively, in the surplus production model. For each squid stock, the assessment model with environmental variability had the highest fitting accuracy and the lowest mean squared error and coefficient of variation, and the management reference points based on the optimal model were more precautionary. This study advances our understanding of the interactions between the environment and ommastrephid squid population dynamics and can therefore improve the management of these commercially valuable stocks with a short life cycle.

scholarly journals Failure to eliminate overfishing and attain optimum yield in the New England groundfish fishery

2013 ◽  
Vol 71 (2) ◽  
pp. 226-233 ◽  
Author(s):  
Brian J. Rothschild ◽  
Emily F. Keiley ◽  
Yue Jiao
Keyword(s):  
New England ◽  
Management System ◽  
Fishery Management ◽  
Stock Assessment ◽  
Single Species ◽  
Recent Change ◽  
Production Model ◽  
Optimum Yield ◽  
Management Regime ◽  
Groundfish Fishery

Abstract Rothschild, B. J., Keiley, E. F., and Jiao, Y. 2014. Failure to eliminate overfishing and attain optimum yield in the New England groundfish fishery. – ICES Journal of Marine Science, 71: 226–233. Under US law, fishery management is required to eliminate overfishing and attain optimum yield (OY). In New England, many groundfish stocks continue to be overfished, and the fishery continues to harvest less than OY. The reasons for the shortfalls are rooted in the socio-economic structure of the management regime, and technical and scientific issues that constrain the management system. The most recent change in the management regime (days-at-sea to catch shares) and performance relative to OY and the prevention of overfishing are analyzed along with metrics used to gauge performance. The commonly used age-based production model gives a problematic perception of stock abundance. Structural issues that seem to impair achieving OY are the adherence to the single-species interpretation of multiple-species yield and the use of the Fx% proxy. Simpler approaches to stock assessment are discussed. A management system that creates feasible goals and uses improved and simpler metrics to measure performance is needed to facilitate attainment of management goals.

Statistical Power of Trends in Fish Abundance

1987 ◽  
Vol 44 (11) ◽  
pp. 1879-1889 ◽  
Author(s):  
Randall M. Peterman ◽  
Michael J. Bradford
Keyword(s):  
Time Trends ◽  
Statistical Power ◽  
Stock Assessment ◽  
Cohort Analysis ◽  
Assessment Methods ◽  
Trawl Survey ◽  
Estimation Errors ◽  
Management Objectives ◽  
Fish Abundances ◽  
Parophrys Vetulus

Estimation errors inherent in stock assessment methods may make it difficult to estimate time trends in fish abundances correctly. Our objective was to quantify the probability that trends in abundance of recruits will be successfully identified. For this analysis, we used an empirically based simulation model of English sole (Parophrys vetulus) off the west coast of North America. The unique wealth of data and past analyses of this population permitted us to include deterministic and stochastic components of growth, mortality, and reproduction in a realistic manner. Errors were also included in two simulated stock assessment methods: a trawl survey and cohort analysis. Under various conditions, we calculated the probability (analogous to statistical power) that these methods will meet three management objectives concerning time trends in recruitment. Monte Carlo simulations showed that although power depends on the objective, under most realistic conditions the probability of correctly detecting recruitment time trends may be unacceptably low. These results suggest new management guidelines for fisheries.

Separating recruitment and mortality time lags for a delay-difference production model

2015 ◽  
Vol 72 (2) ◽  
pp. 161-165 ◽  
Author(s):  
Emilius A. Aalto ◽  
E.J. Dick ◽  
Alec D. MacCall
Keyword(s):  
Stock Assessment ◽  
Recovery Period ◽  
Time Lag ◽  
Simulated Data ◽  
Assessment Method ◽  
Production Model ◽  
Time Lags ◽  
Age At Maturity ◽  
Production Models ◽  
Pacific Rockfish

Many fishery production models implicitly incorporate a single time lag for both recruitment and mortality despite the fact that in populations of breeding adults, deaths occur yearly while the entry of new adults comes from juveniles born potentially many years prior to adulthood. Models that do not account for this difference in timing will overestimate abundance for a decreasing stock and underestimate increases during a recovery period. We investigated the effect of incorporating unequal recruitment and mortality time lags into depletion-based stock reduction analysis (DB-SRA), a stock assessment method for data-poor species. Using both simulated data and catch series of Pacific rockfish (Sebastes spp.), we found that for declining stocks with no mortality delay and a recruitment time lag equal to age-at-maturity, estimated overfishing limits were up to 40% lower than those from the model with both time lags equal to age-at-maturity. Deviation between the two models’ predictions increases with age-at-maturity and natural mortality rate, suggesting that time lag separation is most important for long-lived species. We propose a correction factor for net production models that eliminates stock overestimation due to implicitly equal time lags.

Evaluating a seasonal, sex-specific size-structured stock assessment model for the American lobster, Homarus americanus

2008 ◽  
Vol 59 (1) ◽  
pp. 41 ◽  
Author(s):  
Minoru Kanaiwa ◽  
Yong Chen ◽  
Carl Wilson
Keyword(s):  
Growth Parameters ◽  
Stock Assessment ◽  
Temporal Trends ◽  
Simulated Data ◽  
Homarus Americanus ◽  
Assessment Model ◽  
American Lobster ◽  
Fisheries Resources ◽  
Data Process ◽  
Wide Range

Many models of different complexities are developed for fisheries stock assessment, and yet few have been rigorously evaluated for their performance in capturing fisheries population dynamics. This causes confusion about when a model should be used or not in assessing fisheries resources. This is especially true for models with complex structures. The present study evaluated the performance of a seasonal, sex-specific and size-structured stock assessment model with respect to the temporal pattern of recruitment, observation errors associated with input data, process errors and violation of model assumptions for the American lobster Homarus americanus. Using an individual-based lobster simulator, a series of lobster fisheries with different characteristics were simulated and the model was applied to the simulated data to estimate key fisheries parameters. Estimated values were then compared with the true values in the simulated fisheries to evaluate the model’s ability to capture the temporal trend in stock abundance, biomass and recruitment, and to identify factors that might result in model failure. Results show that this newly developed lobster stock assessment model performs well in capturing the dynamics of the lobster population under a wide range of conditions. Temporal trends in natural mortality and biased estimates of growth parameters posed the most serious problems. The present study shows the importance of model evaluation.

scholarly journals Incorporating Stakeholder Knowledge Into a Complex Stock Assessment Model, the Case of Eel Recruitment

2021 ◽  
Author(s):  
Hilaire Drouineau ◽  
Vanacker Marie ◽  
Estibaliz Diaz ◽  
Mateo Santos Maria ◽  
Korta Maria ◽  
...  
Keyword(s):  
Western Europe ◽  
Fishery Management ◽  
Stock Assessment ◽  
Assessment Model ◽  
The Other ◽  
Complex Life Cycle ◽  
European Eel ◽  
Complex Models ◽  
Prior Construction ◽  
Multiple Actors

Mistrust between scientists and non-scientist stakeholders is a key challenge in fishery management. This problem is exacerbated with the use of complex models to support management: these models suffer from difficulties in communicating their results and a lack of confidence from end users. The European eel is an illustrative example; its complex life cycle raises problems of coordination and discussion among the multiple actors involved in the management of the species. The GEREM model has been proposed as a tool for estimating recruitment, but its complexity, which is essential for addressing the characteristics of the species, makes it difficult to understand and accept by all stakeholders. In the context of the SUDOANG project, we proposed a co-parametrization of this assessment model to tackle this mistrust. Through the use of various questionnaires and appropriate statistical analyses, stakeholders were involved in two important choices for the model (zone definition and prior construction). Regular workshops and presentations were organised to explain the model rationales and to gather feedback and expectations. The results show that stakeholders have very similar perceptions of the potential definitions of sub-areas of recruitment in south-western Europe, and these perceptions are consistent with the underlying environmental conditions. On the other hand, the stakeholders have contrasting opinions about the exploitation rates of fisheries in different river basins, and the use of their knowledge currently has little effect on GEREM estimates. More importantly, the overall approach of this study is thought to have reconstructed the trust and confidence among participants.

scholarly journals Simulation testing methods for estimating misreported catch in a state-space stock assessment model

2020 ◽  
Vol 77 (3) ◽  
pp. 911-920 ◽  
Author(s):  
Charles T Perretti ◽  
Jonathan J Deroba ◽  
Christopher M Legault
Keyword(s):  
Random Walk ◽  
State Space ◽  
Stock Assessment ◽  
Assessment Model ◽  
Testing Methods ◽  
Multiple Sources ◽  
Estimation Model ◽  
Estimation Errors ◽  
Simulation Testing ◽  
Over Time

Abstract State-space stock assessment models have become increasingly common in recent years due to their ability to estimate unobserved variables and explicitly model multiple sources of random error. Therefore, they may be able to better estimate unobserved processes such as misreported fishery catch. We examined whether a state-space assessment model was able to estimate misreported catch in a simulated fishery. We tested three formulations of the estimation model, which exhibit increasing complexity: (i) assuming no misreporting, (ii) assuming misreporting is constant over time, and (iii) assuming misreporting follows a random walk. We tested these three estimation models against simulations using each of the three assumptions and an additional fourth assumption of uniform random misreporting over time. Overall, the worst estimation errors occurred when misreporting was ignored while it was in fact occurring, while there was a relatively small cost for estimating misreporting when it was not occurring. Estimates of population scale and fishing mortality rate were particularly sensitive to misreporting assumptions. Furthermore, in the uniform random scenario, the relatively simple model that assumed misreporting was fixed across ages and time was more accurate than the more complicated random walk model, despite the increased flexibility of the latter.

Evaluation of alternative modelling approaches to account for spatial effects due to age-based movement

2017 ◽  
Vol 74 (11) ◽  
pp. 1832-1844 ◽  
Author(s):  
Hui-Hua Lee ◽  
Kevin R. Piner ◽  
Mark N. Maunder ◽  
Ian G. Taylor ◽  
Richard D. Methot
Keyword(s):  
Population Dynamics ◽  
Stock Assessment ◽  
Simulated Data ◽  
Assessment Method ◽  
Error Modeling ◽  
Assessment Model ◽  
Future Research ◽  
Observation Error ◽  
Time Varying ◽  
Spatial Effects

Spatial patterns due to age-specific movement have been a source of unmodelled process error. Modeling movement in spatially explicit stock assessments is feasible, but hampered by a paucity of data from appropriate tagging studies. This study uses simulation analyses to evaluate alternative model structures that either explicitly or implicitly account for the process of time-varying age-based movement in a population dynamics model. We simulated synthetic populations using a two-area stochastic population dynamics operating model. Simulated data were fit in seven different estimation models. Only the model that includes the correct spatial dynamic results in unbiased and precise estimates of derived and management quantities. In a single-area assessment model, using the fleets-as-area (FAA) approach may be the second best option to estimate both length-based and time-varying age-based selectivity to implicitly account for the contact selectivity and annual availability. An FAA approach adds additional observation error performed nearly as well. Future research could evaluate which stock assessment method is robust to uncertainty in movement and is more appropriate for achieving intended management objectives.

scholarly journals Can spawning origin information of catch or a recruitment penalty improve assessment and fishery management performance for a spatially structured stock assessment model?

2018 ◽  
Vol 75 (12) ◽  
pp. 2136-2148 ◽  
Author(s):  
Yang Li ◽  
James R. Bence ◽  
Travis O. Brenden
Keyword(s):  
Fishery Management ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Assessment Model ◽  
Biomass Estimation ◽  
Management Performance ◽  
Population Mixing ◽  
Standard Assessment ◽  
Stock Biomass ◽  
Spawning Stock

We used simulations based on lake whitefish (Coregonus clupeaformis) populations to explore the benefits of using spawning origin information for parsing catch to spawning populations in stock assessments for intermixed fisheries exhibiting an overlapping movement strategy. We compared this origin-informed assessment model with a standard assessment model that did not parse catch. We additionally evaluated the influence of including annual recruitment penalties. For standard assessment models, spawning stock biomass estimates could be unstable and biased (sometimes by more than 50%), depending upon population mixing and productivity, and in some cases estimated near average zero recruitment in the terminal year. Incorporating information on population-specific harvest age composition improved spawning stock biomass estimation (e.g., by sometimes essentially removing 50% biases and improving accuracy). Assessments with recruitment penalties produced less biased terminal recruitment estimates (sometimes a 100% bias was removed). Under status quo target mortality rates, improvements in assessments did not necessarily translate to improved fishery management performance (e.g., avoiding depletion of spawning biomass), but such improvements, and overall better performance, were seen at lower target mortality rates.

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