Why natural mortality is estimable, in theory if not in practice, in a data-rich stock assessment

2022 ◽  
Vol 248 ◽  
pp. 106203
Author(s):  
William G. Clark
Keyword(s):  
Stock Assessment ◽  
Natural Mortality

Natural mortality diagnostics for state-space stock assessment models

2021 ◽  
Vol 243 ◽  
pp. 106062
Author(s):  
Andrea M.J. Perreault ◽  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Natural Mortality

Understanding historical summer flounder (Paralichthys dentatus) abundance patterns through the incorporation of oceanography-dependent vital rates in Bayesian hierarchical models

2019 ◽  
Vol 76 (8) ◽  
pp. 1275-1294 ◽  
Author(s):  
Cecilia A. O’Leary ◽  
Timothy J. Miller ◽  
James T. Thorson ◽  
Janet A. Nye
Keyword(s):  
Population Dynamics ◽  
Gulf Stream ◽  
Stock Assessment ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Natural Mortality ◽  
Vital Rates ◽  
Summer Flounder ◽  
Paralichthys Dentatus ◽  
Abundance Patterns

Climate can impact fish population dynamics through changes in productivity and shifts in distribution, and both responses have been observed for many fish species. However, few studies have incorporated climate into population dynamics or stock assessment models. This study aimed to uncover how past variations in population vital rates and fishing pressure account for observed abundance variation in summer flounder (Paralichthys dentatus). The influences of the Gulf Stream Index, an index of climate variability in the Northwest Atlantic, on abundance were explored through natural mortality and stock–recruitment relationships in age-structured hierarchical Bayesian models. Posterior predictive loss and deviance information criterion indicated that out of tested models, the best estimates of summer flounder abundances resulted from the climate-dependent natural mortality model that included log-quadratic responses to the Gulf Stream Index. This climate-linked population model demonstrates the role of climate responses in observed abundance patterns and emphasizes the complexities of environmental effects on populations beyond simple correlations. This approach highlights the importance of modeling the combined effect of fishing and climate simultaneously to understand population dynamics.

scholarly journals An integrated tagging model to estimate mortality rates of Albemarle Sound – Roanoke River striped bass

2017 ◽  
Vol 74 (7) ◽  
pp. 1061-1076 ◽  
Author(s):  
Julianne E. Harris ◽  
Joseph E. Hightower
Keyword(s):  
Striped Bass ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Albemarle Sound ◽  
High Reward ◽  
Accuracy And Precision ◽  
Summer Mortality ◽  
Roanoke River

We developed an integrated tagging model to estimate mortality rates and run sizes of Albemarle Sound – Roanoke River striped bass (Morone saxatilis), including (i) a multistate component for telemetered fish with a high reward external tag; (ii) tag return components for fish with a low reward external or PIT tag; and (iii) catch-at-age data. Total annual instantaneous mortality was 1.08 for resident (458–899 mm total length, TL) and 0.45 for anadromous (≥900 mm TL) individuals. Annual instantaneous natural mortality was higher for resident (0.70) than for anadromous (0.21) fish due to high summer mortality in Albemarle Sound. Natural mortality for residents was substantially higher than currently assumed for stock assessment. Monthly fishing mortality from multiple sectors (including catch-and-release) corresponded to seasonal periods of legal harvest. Run size estimates were 499 000–715 000. Results and simulation suggest increasing sample size for the multistate component increases accuracy and precision of annual estimates and low reward tags are valuable for estimating monthly fishing mortality rates among sectors. Our results suggest that integrated tagging models can produce seasonal and annual mortality estimates needed for stock assessment and management.

Estimating multifleet catchability coefficients and natural mortality from fishery catch and effort data: comparison of Bayesian state–space and observation error models

2011 ◽  
Vol 68 (7) ◽  
pp. 1171-1181 ◽  
Author(s):  
Shijie Zhou ◽  
André E. Punt ◽  
Roy Deng ◽  
Janet Bishop
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Observation Error ◽  
Natural Mortality ◽  
Posterior Median ◽  
Median Estimate ◽  
Penaeus Semisulcatus ◽  
Process Error ◽  
Two Parameters ◽  
Delay Difference

Catchability and natural mortality are key quantities in fisheries stock assessment. However, it is difficult to estimate these two parameters simultaneously using only fishery catch and effort data. A Bayesian state–space modified delay–difference model is outlined that can estimate time series of catchability by fleet as well as natural mortality. This model, and three variants thereof, is fitted to data for grooved tiger prawns ( Penaeus semisulcatus ) in Australia’s Northern Prawn Fishery during the period of the year when there is little recruitment. A model that allows for both observation and process error and estimates natural mortality is best, in terms of model selection criteria as well as fit diagnostics. The posterior median estimate for catchability for the primary target fleet ranges from 6.15 × 10−4 to 1.09 × 10−4 during 1980–2007, while the posterior median estimate for catchability for a fleet with P. semisulcatus as its byproduct is about 20% of that for the primary fleet. Fishing efficiency increased at approximately 2% annually during 1980–2007, while the weekly natural mortality is estimated to be 0.053 week–1.

Detecting mortality variation to enhance forage fish population assessments

2018 ◽  
Vol 76 (1) ◽  
pp. 124-135 ◽  
Author(s):  
Nis S Jacobsen ◽  
James T Thorson ◽  
Timothy E Essington
Keyword(s):  
Test Performance ◽  
Size Structure ◽  
Stock Assessment ◽  
Reference Points ◽  
Forage Fish ◽  
Natural Mortality ◽  
Time Varying ◽  
Fishing Mortality ◽  
Catch Data ◽  
Over Time

Abstract Contemporary stock assessment models used by fisheries management often assume that natural mortality rates are constant over time for exploited fish stocks. This assumption results in biased estimates of fishing mortality and reference points when mortality changes over time. However, it is difficult to distinguish changes in natural mortality from changes in fishing mortality, selectivity, and recruitment. Because changes in size structure can be indicate changes in mortality, one potential solution is to use population size-structure and fisheries catch data to simultaneously estimate time-varying natural and fishing mortality. Here we test that hypothesis, using a simulation experiment to test performance for four alternative estimation models that estimate natural and fishing mortality from size structure and catch data. We show that it is possible to estimate time-varying natural mortality in a size-based model, even when fishing mortality, recruitment, and selectivity are changing over time. Finally, we apply the model to North Sea sprat, and show that estimates of recruitment and natural mortality are similar to estimates from an alternative multispecies population model fitted to additional data sources. We recommend exploring potential trends in natural mortality in forage fish assessments using tools such as the one presented here.

scholarly journals Time-varying natural mortality in fisheries stock assessment models: identifying a default approach

2014 ◽  
Vol 72 (1) ◽  
pp. 137-150 ◽  
Author(s):  
Kelli F. Johnson ◽  
Cole C. Monnahan ◽  
Carey R. McGilliard ◽  
Katyana A. Vert-pre ◽  
Sean C. Anderson ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Assessment Method ◽  
Reference Points ◽  
Natural Mortality ◽  
Time Varying ◽  
Fishing Mortality ◽  
Total Allowable Catch ◽  
Robust Approach ◽  
Structured Population Models ◽  
Trade Offs

Abstract A typical assumption used in most fishery stock assessments is that natural mortality (M) is constant across time and age. However, M is rarely constant in reality as a result of the combined impacts of exploitation history, predation, environmental factors, and physiological trade-offs. Misspecification or poor estimation of M can lead to bias in quantities estimated using stock assessment methods, potentially resulting in biased estimates of fishery reference points and catch limits, with the magnitude of bias being influenced by life history and trends in fishing mortality. Monte Carlo simulations were used to evaluate the ability of statistical age-structured population models to estimate spawning-stock biomass, fishing mortality, and total allowable catch when the true M was age-invariant, but time-varying. Configurations of the stock assessment method, implemented in Stock Synthesis, included a single age- and time-invariant M parameter, specified at one of the three levels (high, medium, and low) or an estimated M. The min–max (i.e. most robust) approach to specifying M when it is thought to vary across time was to estimate M. The least robust approach for most scenarios examined was to fix M at a high value, suggesting that the consequences of misspecifying M are asymmetric.

Integrating catch-at-age and multiyear tagging data: a combined Brownie and Petersen estimation approach in a fishery context

2006 ◽  
Vol 63 (3) ◽  
pp. 534-548 ◽  
Author(s):  
Tom Polacheck ◽  
J Paige Eveson ◽  
Geoff M Laslett ◽  
Kenneth H Pollock ◽  
William S Hearn
Keyword(s):  
Mortality Rate ◽  
Population Size ◽  
Stock Assessment ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Catch Data ◽  
Coefficients Of Variation ◽  
Southern Bluefin Tuna ◽  
Catch Rates ◽  
Comprehensive Framework

A comprehensive framework for modelling data from multiyear tagging experiments in a fishery context is presented that incorporates catch data into the traditional Brownie tag–recapture model. Incorporation of catch data not only allows for improved estimation of natural and fishing mortality rates, but also for direct estimation of population size at the time of tagging. These are the primary quantities required to be estimated in stock assessments — having an approach for directly estimating them that does not require catch rates provides a potentially powerful alternative for augmenting traditional stock assessment methods. Simulations are used to demonstrate the value of directly incorporating catch data in the model. Results from the range of scenarios considered suggest that in addition to providing a precise estimate of population size (coefficients of variation ranging from ~15% to 30%), including catch data can decrease biases in the mortality rate estimates (natural mortality especially) and improve precision of fishing mortality rate estimates (by as much as 60% at age 1). The model is applied to southern bluefin tuna (Thunnus maccoyii) tag–recapture and catch data collected in the 1990s to provide estimates of natural mortality, fishing mortality, and abundance for five cohorts of fish.

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.

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