Estimating natural mortality within a fisheries stock assessment model: An evaluation using simulation analysis based on twelve stock assessments

2011 ◽  
Vol 109 (1) ◽  
pp. 89-94 ◽  
Author(s):  
Hui-Hua Lee ◽  
Mark N. Maunder ◽  
Kevin R. Piner ◽  
Richard D. Methot
Keyword(s):  
Simulation Analysis ◽  
Stock Assessment ◽  
Assessment Model ◽  
Natural Mortality ◽  
Stock Assessments

scholarly journals A method for calculating a meta-analytical prior for the natural mortality rate using multiple life history correlates

2014 ◽  
Vol 72 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Owen S. Hamel
Keyword(s):  
Life History ◽  
Mortality Rate ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Assessment Model ◽  
Natural Mortality ◽  
Uncertainty Interval ◽  
Free Data ◽  
Stock Assessments ◽  
Measure Of Uncertainty

Abstract The natural mortality rate M is an important parameter for understanding population dynamics, and is extraordinarily difficult to estimate for many fish species. The uncertainty associated with M translates into increased uncertainty in fishery stock assessments. Estimation of M within a stock assessment model is complicated by its confounding with other life history and fishery parameters which are also uncertain, some of which are typically estimated within the model. Ageing error and variation in growth, which may not be fully modelled, can also affect estimation of M, as can various assumptions, including the form of the stock–recruitment function (e.g. Beverton–Holt, Ricker) and the level of compensation (or steepness), which may be fixed (or limited by a prior) in the model. To avoid these difficulties, stock assessors often assume point estimates for M derived from meta-analytical relationships between M and more easily measured life history characteristics, such as growth rate or longevity. However, these relationships depend on estimates of M for a great number of species, and those estimates are also subject to errors and biases (as are, to a lesser extent, the other life history parameters). Therefore, at the very least, some measure of uncertainty in M should be calculated and used for evaluating uncertainty in stock assessments and management strategy evaluations. Given error-free data on M and the covariate(s) for a meta-analysis, prediction intervals would provide the appropriate measure of uncertainty in M. In contrast, if the relationship between the covariate(s) and M is exact and the only error is in the estimates of M used for the meta-analysis, confidence intervals would appropriate. Using multiple published meta-analyses of M’s relationship with various life history correlates, and beginning with the uncertainty interval calculations, I develop a method for creating combined priors for M for use in stock assessment.

Can data collected from marine protected areas improve estimates of life-history parameters?

2011 ◽  
Vol 68 (10) ◽  
pp. 1761-1777 ◽  
Author(s):  
Thomas M. Garrison ◽  
Owen S. Hamel ◽  
André E. Punt
Keyword(s):  
Life History ◽  
Protected Areas ◽  
Fisheries Management ◽  
Marine Protected Areas ◽  
Stock Assessment ◽  
Assessment Model ◽  
Natural Mortality ◽  
Stock Assessments ◽  
Fishery Data ◽  
Maturity Parameters

One of the argued research-related benefits of marine protected areas (MPAs) to fisheries management is that because there is no fishing inside of an MPA, it may be possible to precisely estimate the rate of natural mortality and better determine growth and maturity rates, parameters that are often prespecified in stock assessments. This study assesses the degree to which having an MPA increases the ability to estimate these parameters in a integrated stock assessment model, Stock Synthesis; how long it would take for these benefits to be reflected in improved estimates of management quantities; and the extent to which these improvements will be reduced or lost if there is movement of adults (i.e., spillover) from the MPA to the fished area. A two-area, age- and length-structured simulation model is used to examine these benefits on estimation performance for Stock Synthesis. Given the data and process assumptions explored here, the extent of improvement in estimation of growth and maturity parameters with data collected from MPAs is small, but estimation of natural mortality is substantially improved compared with directly estimating these parameters using fishery data. The extent of this improvement depends on the degree of spillover and the complexity of the assessment model.

A new way to visualize and report structural and data uncertainty in stock assessments

2020 ◽  
Vol 77 (8) ◽  
pp. 1275-1280
Author(s):  
Jason Cope ◽  
Vladlena Gertseva
Keyword(s):  
Sensitivity Analysis ◽  
Alternative Model ◽  
Reference Model ◽  
Stock Assessment ◽  
Assessment Model ◽  
Data Uncertainty ◽  
Model Comparisons ◽  
Modelling Framework ◽  
Stock Assessments ◽  
General Method

We present a visual and tabular representation of fisheries stock assessment model outputs to rapidly examine and effectively communicate sensitivity analysis results from numerous alternative model comparisons. This approach uses multiple output metrics to identify which alternative stock assessment model configurations relative to the reference model deserve further attention when quantifying intermodel uncertainty. An accompanying table of likelihood components, parameters, and model-derived quantities highlights where major changes exist compared with the reference model. The general method is applicable to any stock assessment and should aid in model behavior diagnosis and communicating uncertainty to managers. Specific examples and code are provided for the Stock Synthesis modelling framework.

scholarly journals SPAM (Sex-Structured Pandalus Assessment Model): a stock assessment model for Pandalus stocks

2012 ◽  
Vol 69 (4) ◽  
pp. 770-783 ◽  
Author(s):  
Hilaire Drouineau ◽  
Louise Savard ◽  
Mathieu Desgagnés ◽  
Daniel Duplisea
Keyword(s):  
Stock Assessment ◽  
Sex Change ◽  
Assessment Model ◽  
Natural Mortality ◽  
The Novel ◽  
Fishing Mortality ◽  
Novel Structure ◽  
Shrimp Fisheries ◽  
Analytical Tools ◽  
Mortality Estimates

Despite the economic importance of Pandalus shrimp fisheries, few analytical tools have been developed to assess their stocks, and traditional stock assessment models are not appropriate because of biological specificities of Pandalus species. In this context, we propose SPAM (Sex-Structured Pandalus Assessment Model), a model dedicated to protandric hermaphrodite pandalids stock assessment. Pandalids are difficult to assess because the cues affecting sex change, size at recruitment, and mortality variability are not well understood or characterized. The novel structure of the model makes it possible to adequately describe variability in natural mortality by stage and in time, as well as variability in size at sex change and recruitment. The model provides traditional stock assessment outputs, such as fishing mortality estimates and numbers of individuals, and provides in addition yearly natural mortality estimates. The model is applied to the exploited shrimp stock of Pandalus borealis in Sept-Îles (Québec, Canada) as an illustrative example of the utility of the approach.

scholarly journals Demonstration of a spatially explicit, tag-integrated stock assessment model with application to three interconnected stocks of yellowtail flounder off of New England

2014 ◽  
Vol 72 (1) ◽  
pp. 164-177 ◽  
Author(s):  
Daniel R. Goethel ◽  
Christopher M. Legault ◽  
Steven X. Cadrin
Keyword(s):  
New England ◽  
Integrated Assessment ◽  
Stock Assessment ◽  
Assessment Model ◽  
Spatially Explicit ◽  
Closed Population ◽  
Yellowtail Flounder ◽  
Limanda Ferruginea ◽  
Stock Assessments ◽  
Source Sink

Abstract Ignoring population structure and connectivity in stock assessment models can introduce bias into important management metrics. Tag-integrated assessment models can account for spatially explicit population dynamics by modelling multiple population components, each with unique demographics, and estimating movement among them. A tagging submodel is included to calculate predicted tag recaptures, and observed tagging data are incorporated in the objective function to inform estimates of movement and mortality. We describe the tag-integrated assessment framework and demonstrate its use through an application to three stocks of yellowtail flounder (Limanda ferruginea) off New England. Movement among the three yellowtail flounder stocks has been proposed as a potential source of uncertainty in the closed population assessments of each. A tagging study was conducted during 2003–2006 with over 45 000 tagged fish released in the region, and the tagging data were included in the tag-integrated model. Results indicated that movement among stocks was low, estimates of stock size and fishing mortality were similar to those from conventional stock assessments, and incorporating stock connectivity did not resolve residual patterns. Despite low movement estimates, new interpretations of regional stock dynamics may have important implications for regional fisheries management given the source-sink nature of movement estimates.

scholarly journals “The Elephant in the Room”: Exploring Natural Mortality Uncertainty in Statistical Catch at Age Models

2020 ◽  
Vol 7 ◽  
Author(s):  
Alessandro Mannini ◽  
Cecilia Pinto ◽  
Christoph Konrad ◽  
Paraskevas Vasilakopoulos ◽  
Henning Winker
Keyword(s):  
Stock Assessment ◽  
Assessment Process ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Food And Agriculture ◽  
Stock Assessments ◽  
The Mediterranean ◽  
The Impact

The natural mortality rate (M) of a fish stock is typically highly influential on the outcome of age-structured stock assessment models, but at the same time extremely difficult to estimate. In data-limited stock assessments, M usually relies on a range of empirically or theoretically derived M estimates, which can vary vastly. This article aims at evaluating the impact of this variability in M using seven Mediterranean stocks as case studies of statistical catch-at-age assessments for information-limited fisheries. The two main bodies carrying out stock assessments in the Mediterranean and Black Seas are European Union’s Scientific Technical Economic Committee for Fisheries (STECF) and Food and Agriculture Organization’s General Fisheries Commission for the Mediterranean (GFCM). Current advice in terms of fishing mortality levels is based on a single “best” M assumption which is agreed by stock assessment expert working groups, but uncertainty about M is not taken into consideration. Our results demonstrate that not accounting for the uncertainty surrounding M during the assessment process can lead to strong underestimation or overestimation of fishing mortality, potentially biasing the management process. We recommend carrying out relevant sensitivity analyses to improve stock assessment and fisheries management in data-limited areas such as the Mediterranean basin.

A framework to incorporate environmental effects into stock assessments informed by fishery-independent surveys: a case study with American lobster (Homarus americanus)

2020 ◽  
Vol 77 (10) ◽  
pp. 1700-1710
Author(s):  
Cameron T. Hodgdon ◽  
Kisei R. Tanaka ◽  
Jocelyn Runnebaum ◽  
Jie Cao ◽  
Yong Chen
Keyword(s):  
Environmental Variability ◽  
Stock Assessment ◽  
Homarus Americanus ◽  
Assessment Model ◽  
American Lobster ◽  
Multiple Model ◽  
Environmental Covariates ◽  
Model Based ◽  
Stock Assessments ◽  
Abundance Indices

Stock assessments for a majority of the world’s fisheries often do not explicitly consider the effects of environmental conditions on target species, which can raise model uncertainty and potentially reduce forecasting quality. Model-based abundance indices were developed using a delta generalized linear mixed model that incorporates environmental variability for use in stock assessment to understand how the incorporation of environmental variability impacts our understanding of population dynamics. For this study, multiple model-based abundance indices were developed to test the incorporation of environmental covariates in a length-structured assessment of the American lobster (Homarus americanus) stock in the Gulf of Maine – Georges Bank on the possible improvement of stock assessment quality. Comparisons reveal that modelled indices with environmental covariates appear to be more precise than traditional indices, but model performance metrics and hindcasted fishery statuses revealed that these improvements to indices may not necessarily mean an improved assessment. Model-based abundance indices are not intrinsically better than design-based indices and should be tested for each species individually.

scholarly journals A state-space stock assessment model for northern cod, including under-reported catches and variable natural mortality rates

2016 ◽  
Vol 73 (2) ◽  
pp. 296-308 ◽  
Author(s):  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Gadus Morhua ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Assessment Model ◽  
Data Sources ◽  
Natural Mortality ◽  
Similar Data ◽  
Subjective Data ◽  
Northern Cod

A state-space assessment model for the northern cod (Gadus morhua) stock off southern Labrador and eastern Newfoundland is developed here. The model utilizes information from offshore trawl surveys, inshore acoustic surveys, fishery catch age compositions, partial fishery landings, and tagging. This is done using an approach that avoids the use of subjective data-weighting. Estimates of fishing mortality rates (F) are usually conditional on assumptions about natural mortality rates (M) in stock assessment models. However, by integrating much of the information on northern cod, it is possible to estimate F and M separately. It is also possible to estimate a change in the offshore survey catchability by including inshore acoustic biomass estimates. The proposed model also accounts for biased total catch statistics, which is a common problem in stock assessments. The main goal of the model is to provide realistic projections of the impacts of various levels of future fishery catches on the recovery of this stock. The projections incorporate uncertainty about M and catch. This is vital information for successful future fisheries. The model has been developed for the specific data sources available for northern cod, but it could be adapted to other stocks with similar data sources.

A Bayesian hierarchical formulation of the De Lury stock assessment model for abundance estimation of Falkland Islands' squid (Loligo gahi)

2004 ◽  
Vol 61 (6) ◽  
pp. 1048-1059 ◽  
Author(s):  
Murdoch K McAllister ◽  
Simeon L Hill ◽  
David J Agnew ◽  
Geoffrey P Kirkwood ◽  
John R Beddington
Keyword(s):  
Sampling Error ◽  
Stock Assessment ◽  
Assessment Model ◽  
Abundance Estimation ◽  
Falkland Islands ◽  
Parameter Estimates ◽  
Bayesian Hierarchical ◽  
Stock Assessments ◽  
Catch Rates ◽  
Using Data

In stock assessments of short-lived species, De Lury depletion models are commonly applied in which commercial catches and changing catch rates are used to estimate resource abundance. These methods are applied within fishing seasons to decide when to close the fishery and can be reliable if the data show a distinct decline in response to the catch removals. However, this is not always the case, particularly when sampling error variation masks trends in abundance. This paper presents a Bayesian hierarchical formulation of the De Lury model in which data from previous years are combined hierarchically in the same stock assessment model to improve parameter estimation for future stock assessments. The improved precision in parameter estimates is demonstrated using data for the Falkland Islands' Loligo gahi squid fishery.

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