Assessing natural mortality of anchovy from surveys' population and biomass estimates (original) (raw)
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2008
The Spanish purse seine fishery targeting anchovy has suffered a strong decline throughout the second half of the past century. The relationship between fishing Capacity, Effort and fishing mortality is suspected to be weak for purse seines, given the catchability problems associated to these type of gears on small pelagic fisheries in other parts of the world. In this work we review this relationship for the Spanish purse seines operating on anchovy in the Bay of Biscay since 1987. This is made by revising the series of fishing vessels operating each year on anchovy, with their fishing characteristics defining their fishing capacity, and the actual fishing calendar defining the effort, taken into account the standarization performed by GLM in a former presentation. This series is coupled with a seasonal Integrated catch at age analysis applied to the different fleets in the Bay of Biscay, in order to fit the best catchability model to this purse seine fleet. The variability between...
Time-varying natural mortality in fisheries stock assessment models: identifying a default approach
ICES Journal of Marine Science, 2014
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.
ICES Journal of Marine Science, 2011
Ibaibarriaga, L., Fernández, C., and Uriarte, A. 2011. Gaining information from commercial catch for a Bayesian two-stage biomass dynamic model: application to Bay of Biscay anchovy. – ICES Journal of Marine Science, 68: 1435–1446. A two-stage biomass dynamic model for Bay of Biscay anchovy is presented. Compared with the model currently applied by ICES for the assessment of that stock, the new model separates the growth and natural mortality processes and allows them to differ by age class. Stochastic equations involving the observed weights by age class in surveys are incorporated to provide information on growth rates. The fishing process is modelled separating fishing mortality into year and age-class effects in each semester, and observation equations are introduced for total catch and catch proportion by age class (in biomass) by semester. The model is first tested on simulated data, then applied to real data for the years 1987–2008. Although the results are affected by survey...
Canadian Journal of Fisheries and Aquatic Sciences, 2007
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 catchat-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.
Canadian Journal of Fisheries and Aquatic Sciences, 2007
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 catchat-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.
Mediterranean Marine Science, 2014
Two different stock assessment models were applied to the North Aegean Sea anchovy stock (Eastern Mediterranean Sea): an Integrated Catch at age Analysis and a Bayesian two-stage biomass based model. Commercial catch data over the period 2000-2008 as well as acoustics and Daily Egg Production Method estimates over the period 2003-2008 were used. Both models results were consistent, indicating that anchovy stock is exploited sustainably in relation to an exploitation rate reference point. Further, the stock biomass appears stable or increasing. However, the limitations in age-composition data, potential problems related to misinterpretation of age readings along with the existence of missing values in the survey data seem to favour the two-stage biomass method, which is based on a simplified age structure.
Fisheries Research, 2022
Length-based methods have been widely applied to estimate biological parameters and understand the dynamics of marine resource populations within data-limited stocks. However, to date few studies have tested the sensitivity of parameters in length-based methods examining stocks with different traits and fishery contexts. In the Bay of Biscay and the Iberian Coast ecoregion, SE Europe (International Council for the Exploration of the Sea-ICES, Divisions 8 and 9a), many commercial resources are considered data-limited, and either little is known about their fisheries stock statuses or gaps remain in currently available assessments. Therefore, this study focuses on two of the most used length-based methods, which ICES considers to be the most appropriate to evaluate data-limited stocks, namely length-based indicators (LBI) and the length-based spawning potential ratio (LBSPR). Both methods have been applied to assess the stock statuses of various relevant species in the study area, such as: the small-spotted catshark (Scyliorhinus canicula), European anchovy (Engraulis encrasicolus), blackspot seabream (Pagellus bogaraveo), pouting (Trisopterus luscus), pollack (Pollachius pollachius), and Norway lobster (Nephrops norvegicus). For each stock, model results were compared with available knowledge on their current status. Furthermore, this paper discusses whether unexpected results are related to violations of the main model assumptions 2 (constant total mortality and recruitment, and logistic selectivity) or to a lack of representativeness of stock length composition. A sensitivity analysis was conducted on the two most important input parameters: L ∞ (von Bertalanffy asymptotic average maximum body size) and M/k (ratio of natural mortality to von Bertalanffy growth rate). This analysis concluded that the variation/misspecification of both parameters (M/k and L ∞) had a considerable impact on the results given by both methods, and that this effect is more significant in the case of the L ∞ parameter, thus highlighting the importance of its accuracy in a given assessment. Furthermore, the sensitivity analysis indicated that, among the LBI and LBSPR indicators, the least robust indicator was the LBI Pmega indicator. The remaining LBI method indicators can be considered more robust than the LBSPR indicators when there is uncertainty in the life history input parameters (M/k and L ∞). Among LBSPR indicators, SPR is more affected than F/M (relative fishing mortality) by the variation/misspecification of parameter L ∞ , whereas under the variation of M/k both indicators perform similarly. However, it is important to consider that LBI indicators are very rough measures of stock statuses, whereas LBSPR measures describe stock statuses more explicitly. Thus, both measures can be used together to obtain more precision in estimating stock status. Nevertheless, when critical parameters are uncertain (e.g., L ∞) and the results of both methods contradict one another, LBI method indicators, with the exception of Pmega, are more trustworthy than LBSPR indicators.
Anchovy (Engraulis encrasicolus, L.) is one of the most important commercial species of the northern and central Adriatic Sea, as well as one of the most productive fisheries in the whole Mediterranean. In the Adriatic Sea the stock of anchovy is shared between Italy, Croatia and Slovenia. A joint stock assessment was carried out using catch data from all the fleets for the time interval 1975-2009. Analyses were performed using estimates of natural mortality at age obtained by means of two different methods and two population dynamics methods based on the analysis of catch-at-age data: Laurec-Sheperd virtual population analysis (VPA) and integrated catch-at-age (ICA), both tuned to acoustic estimates of abundance. Gislason's estimates for natural mortality appeared to be more realistic and were thus preferred for short-lived species. The general trend of biomass and fishing mortality is similar for the two models, highlighting the major collapse of the stock in 1987. Nevertheless, ICA has enough flexibility to combine all the data available without adding too much complexity in comparison with a VPA approach and seems to perform better in terms of the spawning stock biomass/recruitment relationship and diagnostics (i.e. the retrospective pattern). For the stock status, the exploitation rate from ICA is higher than the suggested threshold of 0.4 proposed by Patterson for small pelagic species.