A cookbook for using model diagnostics in integrated stock assessments

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Marine Fisheries Stock Assessment Improvement Plan: report of the National Marine Fisheries Service National Task Force for Improving Fish Stock Assessments

This report argues for greatly increased resources in terms of data collection facilities and staff to collect, process, and analyze the data, and to communicate the results, in order for NMFS to fulfill its mandate to conserve and manage marine resources. In fact, the authors of this report had great difficulty defining the "ideal" situation to which fisheries stock assessments and management should aspire. One of the primary objectives of fisheries management is to develop sustainable harvest policies that minimize the risks of overfishing both target species and associated species. This can be achieved in a wide spectrum of ways, ranging between the following two extremes. The first is to implement only simple management measures with correspondingly simple assessment demands, which will usually mean setting fishing mortality targets at relatively low levels in order to reduce the risk of unknowingly overfishing or driving ecosystems towards undesirable system states. The second is to expand existing data collection and analysis programs to provide an adequate knowledge base that can support higher fishing mortality targets while still ensuring low risk to target and associated species and ecosystems. However, defining "adequate" is difficult, especially when scientists have not even identified all marine species, and information on catches, abundances, and life histories of many target species, and most associated species, is sparse. Increasing calls from the public, stakeholders, and the scientific community to implement ecosystem-based stock assessment and management make it even more difficult to define "adequate," especially when "ecosystem-based management" is itself not well-defined. In attempting to describe the data collection and assessment needs for the latter, the authors took a pragmatic approach, rather than trying to estimate the resources required to develop a knowledge base about the fine-scale detailed distributions, abundances, and associations of all marine species. Thus, the specified resource requirements will not meet the expectations of some stakeholders. In addition, the Stock Assessment Improvement Plan is designed to be complementary to other related plans, and therefore does not duplicate the resource requirements detailed in those plans, except as otherwise noted

A spatially explicit individual-based model to support management of commercial and recreational fisheries for European sea bass Dicentrarchus labrax

The European sea bass (Dicentrarchus labrax) is a slow growing and late maturing high value fish that is exploited by both commercial and recreational fisheries. In recent years, scientific assessments have shown a rapid decline in spawning stock biomass around the UK attributed to poor recruitment (driven by environmental factors) and high fishing mortality. This resulted in significant reductions in the harvest of sea bass following technical measures implemented by the European Commission to conserve stocks. Individual-based models (IBMs) are simulations of individual ‘agents’ of organisms that interact with each other and their environment locally and have been shown to be effective management tools in many systems. Here, an IBM that simulates the population dynamics and spatial distribution of sea bass was developed to assess how technical management measures applied to subsets of the population impact the overall stock. Conventional stock assessment techniques were used to model the processes affecting population dynamics, while the spatial distribution was simulated using a combination of temperature preferences and information from tagging studies. The IBM was parameterised using existing knowledge from the literature and can mimic key assessment outputs used to inform management and advice on fishing opportunities. Utility of the IBM is demonstrated by simulating the population consequences of several key management scenarios based on those implemented by the European Commission, including short-term bans on pelagic trawling in spawning areas, commercial and recreational catch limits and increasing the minimum conservation reference size. The IBM has potential to complement the annual stock assessment in managing European sea bass because it models individual movement, environmental drivers and emergent spatial distribution, thereby providing enhanced predictions of management strategy outcomes that could inform spatial advice on fishing opportunities and policy

Comparing the performance of three data weighting methods when allowing for time-varying selectivity

How to properly weight composition data is an important ongoing research topic for fisheries stock assessments, and multiple methods for weighting composition data have been developed. Although several studies indicated that properly accounting for time-varying selectivity can reduce estimation biases in population biomass and management-related quantities, no study to date has compared the performance of widely used data-weighting methods when allowing for time-varying selectivity. Here, we conducted four simulation experiments on this topic, aiming to provide guidance on weighting age-composition data given time-varying selectivity. The first simulation experiment showed that over-weighting should be avoided in general and even when estimating time-varying selectivity. The second simulation experiment compared three data-weighting methods (McAllister–Ianelli, Francis, and Dirichlet-multinomial), within which the Dirichlet-multinomial method outperformed the other two methods when selectivity is time-varying. The third and fourth simulation experiments further showed that given time-varying selectivity, the Dirichlet-multinomial method still performed well when age-composition data were over-dispersed and when the level of selectivity variation needed to be simultaneously estimated. Our simulation results support using the Dirichlet-multinomial method when estimating time-varying fishery selectivity. Also, the simulations suggest that improving stock assessments by accounting for time-varying selectivity requires simultaneously addressing data weighting and time-varying selectivity.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Effects of California El Niño 1982-1984 on the northern anchovy

El Niño caused physical and biological changes in the northern anchovy habitat off southern California. Anomalous sea surface temperatures, surface currents, mixed layer depths, and plankton biomass levels began to appear in late 1982 and persisted into 1984. Growth of juvenile and adult anchovy slowed during El Niño, probably due to reduced availability of zooplankton prey. A decrease in size-at-age in early 1983, with a recovery in late 1984, can be explained by movements of the stock and the latitudinal cline in size-at-age. Spawning range expanded in 1983 due to shifts in sea surface temperature boundaries. Early larval mortality was unusually high in the yolk-sac stage. Fecundity per unit spawning biomass was low in 1983, due primarily to a high proportion of first-year spawners. Size-at-age was very low by spring 1984, but specific fecundity was surprisingly high. Although El Niño had a variety of significant effects on the northern anchovy, the stock seems to have recovered in 1985

National Oceanic and Atmospheric Administration Report 119

The following document is a report taken during a three-day workshop to estimate natural mortality for use in stock assessment applications. The workshop covered biological aspects of mortality, methods for estimation of mortality, and best practices for use of mortality in assessment models. This document presents the findings during this workshop

A new semi-parametric method for autocorrelated age- and time-varying selectivity in age-structured assessment models

Selectivity is a key parameter in stock assessments that describes how fisheries interact with different ages and sizes of fish. Here, we introduce a new semi-parametric selectivity method, which we implement and test in Stock Synthesis. This selectivity method includes a parametric component and an autocorrelated non-parametric component, consisting of deviations from the parametric component. We explore the new selectivity method using two simulation experiments, which show that the two autocorrelation parameters for selectivity deviations of data-rich fisheries are estimable using either mixed-effect or simpler sample-based algorithms. When selectivity deviations of a data-rich fishery are highly autocorrelated, using the new method to estimate the two autocorrelation parameters leads to more precise estimations of spawning biomass and fully-selected fishing mortality. However, this new method fails to improve model performance in low data-quality cases where measurement error in the data overwhelms the pattern caused by the autocorrelated process. Finally, we use a case study involving North Sea herring to show that our new method substantially reduces autocorrelations in the Pearson residuals in fit to age-composition data.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Evaluating Rebuilding Revision Rules for Assessing Progress Towards Rebuilding of OverFished West Coast groundfish

Eight west coast groundfish stocks have been declared overfished and rebuilding plans have been implemented to restore them to levels that can support productive, sustainable fisheries. These stocks are: bocaccio (Sebastes paucispinis), cowcod (S. levis), canary rockfish (S. pinniger)