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.

scholarly journals A modelling approach to evaluate the impact of fish spatial behavioural types on fisheries stock assessment

2018 ◽  
Vol 76 (2) ◽  
pp. 489-500 ◽  
Author(s):  
Josep Alós ◽  
Andrea Campos-Candela ◽  
Robert Arlinghaus
Keyword(s):  
Stock Assessment ◽  
Fishing Effort ◽  
Fish Stock ◽  
Catch Per Unit Effort ◽  
Wide Range ◽  
Stock Assessments ◽  
Theoretical Predictions ◽  
Behavioural Types ◽  
Catch Rates ◽  
The Impact

Abstract Spatial behavioural types (SBTs) arise from between-individual differences in behavioural traits that foster spatial behavioural patterns that are consistent over time and ecological contexts. Fish stocks are regularly assessed using catch per unit effort (CPUE) as input data that may non-linearly co-vary with the underlying abundance (N) of the exploited stock when SBT affect catchability. We hypothesized that SBT promote characteristic changes in catchability within harvesting seasons that affect catch rates and in turn catch-based fish stock assessments. To test this hypothesis, we developed a spatially explicit agent-based simulation where we measured encounters between fish and fishers and estimated the shape of the CPUE–N relationship. We ran the simulation in a prototypical fish–fisher encounter-leads-to-catch-type fishery and systematically studied outcomes in the presence or absence of SBTs. It was revealed that the existence of SBTs leads to CPUE inevitably declining faster than N (a process known as hyperdepletion) when compared with a simulation lacking SBTs. This finding was consistent in a wide range of fishing effort scenarios. The emergent hyperdepletion of catch rates was caused by fast and behavioural-selective exploitation of vulnerable SBT that encompassed the mobile component of the fish stock. The theoretical predictions received support from field data from a coastal recreational fishery. Our work suggests that the consideration of SBT when interpreting trends in CPUE data may notably improve stock assessments by providing a more reliable CPUE–N relationship.

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.

scholarly journals Estimation of the parameters of fish stock dynamics from catch-at-age data and indices of abundance: can natural and fishing mortality be separated?

2007 ◽  
Vol 64 (8) ◽  
pp. 1130-1142 ◽  
Author(s):  
Sondre Aanes ◽  
Steinar Engen ◽  
Bernt-Erik Sæther ◽  
Ronny Aanes
Keyword(s):  
Gadus Morhua ◽  
State Space Model ◽  
Population Projections ◽  
Quality Data ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Absolute Size ◽  
Data Set ◽  
Long Time

Models for fluctuations in size of fish stocks must include parameters that describe expected dynamics, as well as stochastic influences. In addition, reliable population projections also require assessments about the uncertainties in estimates of vital parameters. Here we develop an age-structured model of population dynamics based on catch-at-age data and indices of abundance in which the natural and fishing mortality are separated in a Bayesian state–space model. Markov chain Monte Carlo methods are used to fit the model to the data. The model is fitted to a data set of 19 years for Northeast Arctic cod (Gadus morhua). By simulations of the fitted model we show that the model captures the dynamical pattern of natural mortality adequately, whereas the absolute size of natural mortality is difficult to estimate. Access to long time series of high-quality data are necessary for obtaining precise estimates of all the parameters in the model, but some parameters cannot be estimated without including some prior information. Nevertheless, our model demonstrates that temporal variability in natural mortality strongly affects perceived variability in stock sizes. Thus, using estimation procedures that neglect temporal fluctuations in natural mortality may therefore give biased estimates of fluctuations in fish stock sizes.

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 Spatiotemporal analysis of compositional data: increased precision and improved workflow using model-based inputs to stock assessment

2019 ◽  
Vol 76 (3) ◽  
pp. 401-414 ◽  
Author(s):  
James T. Thorson ◽  
Melissa A. Haltuch
Keyword(s):  
Sample Size ◽  
Compositional Data ◽  
Stock Assessment ◽  
Future Research ◽  
Sex Composition ◽  
Abundance Index ◽  
Composition Data ◽  
Model Based ◽  
Stock Assessments ◽  
The Impact

Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composition data that are estimated from survey and fishery records. Research has developed spatiotemporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age–length–sex composition data. We demonstrate a spatiotemporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatiotemporal and design-based methods demonstrates a 32% increase in input sample size for the spatiotemporal estimator. A Stock Synthesis assessment used to manage lingcod (Ophiodon elongatus) in the California Current also shows a 17% increase in sample size and better model fit using the spatiotemporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatiotemporal approaches are feasible for estimating both abundance-index and compositional data, thereby providing a unified approach for generating inputs for stock assessments. We hypothesize that spatiotemporal methods will improve statistical efficiency for composition data in many stock assessments and recommend that future research explore the impact of including additional habitat or sampling covariates.

Comparison of multiple approaches to calculate time-varying biological reference points in climate-linked population-dynamics models

2019 ◽  
Vol 77 (3) ◽  
pp. 930-941 ◽  
Author(s):  
Cecilia A O’Leary ◽  
James T Thorson ◽  
Timothy J Miller ◽  
Janet A Nye
Keyword(s):  
Climate Model ◽  
Careful Consideration ◽  
Reference Points ◽  
Fish Stock ◽  
Natural Mortality ◽  
Time Varying ◽  
Summer Flounder ◽  
Stock Status ◽  
Management Procedures ◽  
The Impact

Abstract Fisheries managers use biological reference points (BRPs) as targets or limits on fishing and biomass to maintain productive levels of fish stock biomass. There are multiple ways to calculate BRPs when biological parameters are time varying. Using summer flounder (Paralichthys dentatus) as a case study, we investigated time-varying approaches in concert with climate-linked population models to understand the impact of environmentally driven variability in natural mortality, recruitment, and size-at-age on two commonly used BRPs [B0(t) and F35%(t)]. We used the following two approaches to calculate time-varying BRPs: dynamic-BRP and moving-average-BRP. We quantified the variability and uncertainty of different climate dependencies and estimation approaches, attributed BRP variation to variation in life-history processes, and evaluated how using different approaches impacts estimates of stock status. Results indicate that the dynamic-BRP approach using the climate-linked natural mortality model produced the least variable reference points compared to others calculated. Summer flounder stock status depended on the estimation approach and climate model used. These results emphasize that understanding climate dependencies is important for summer flounder reference points and perhaps other species, and careful consideration is warranted when considering what time-varying approach to use, ideally based upon simulation studies within a proposed set of management procedures.

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 Estimating the mortality caused by great cormorant predation on fish stocks: pikeperch in the Archipelago Sea, northern Baltic Sea, as an example

2016 ◽  
Vol 73 (1) ◽  
pp. 84-93 ◽  
Author(s):  
Outi Heikinheimo ◽  
Pekka Rusanen ◽  
Katja Korhonen
Keyword(s):  
Age Groups ◽  
Total Mortality ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Great Cormorant ◽  
Phalacrocorax Carbo ◽  
Fish Stocks ◽  
Archipelago Sea ◽  
Phalacrocorax Carbo Sinensis ◽  
The Impact

Estimates of the mortality rates caused by cormorants are needed to assess the impact on fish stock dynamics and fisheries. In this study, we calculated the annual instantaneous mortality caused by great cormorants (Phalacrocorax carbo sinensis) on young pikeperch (Sander lucioperca), using data from Archipelago Sea, southwestern coast of Finland. The pikeperch are vulnerable to cormorant predation mainly at the ages 2–4. The annual instantaneous mortality caused by cormorants was between 0.04 and 0.13, and the estimated effect on the pikeperch stock size at recruitment to the fishery ranged from 4% to 23%, respectively. The average annual cormorant-induced mortality accounted for 5%–34% of the total mortality in these age groups. The sensitivity analyses proved that the rates of mortality from other sources largely affect the estimated mortality from cormorant predation. In cases with strong fluctuations in the abundance of the prey fish stocks, ignoring the size and density dependence of the natural mortality may lead to overestimation of the importance of cormorants as competitors of fisheries.

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