Time filter

Source Type

Minte-Vera C.V.,Inter American Tropical Tuna Commission | Maunder M.N.,Center for the Advancement of Population Assessment Methodology | Casselman J.M.,Queens University | Campana S.E.,University of Iceland
Fisheries Research | Year: 2015

As the commonly-used von Bertalanffy growth function (VB) does not explicitly incorporate changes in growth due to allocation of energy to reproduction, a more flexible function could be used when attempting to model juvenile and adult growth simultaneously. Here we review biphasic growth models, with emphasis on those that explicitly incorporate the cost of reproduction, and propose two new models: the von Bertalanffy logistic-L∞ (VB log-L∞) and the Cost of Reproduction (CoR) models. We fitted the models to eight data sets from males and females of four unfished or lightly-fished Arctic lake trout (Salvelinus namaycush) populations, and compared their fits to those of the commonly-used growth functions. In all cases, a biphasic growth model fitted the data better than simpler models such as the VB and the Richards models. Of the biphasic models, those that explicitly represent the reproductive process fitted the data best, particularly the Quince-Boukal model with the allometric exponent on the growth rate-weight relationship β =0.8. The proposed models and the Quince-Boukal model provide a smooth transition between juvenile and adult growth by incorporating a logistic function with parameters dependent on the proportion of mature fish (or probability of being mature) at age. In addition to fitting growth models to the size-at-age data, we also attempted an integrated estimation for the three models that predict the age at maturity (the models are simultaneously fit to two data components, size at age and maturity at age.) The integrated estimation was the best compromise between modeling the two biological processes (growth and reproduction), but the separated estimation provided similar results in most cases, and may be easier to implement. We believe that taking the cost of reproduction into consideration is central for growth curves used in stock assessment models, as changes in growth trajectories may impact the perception of stock status. Future research should focus on the sensitivity of management advice to these growth curves for commercially-important fish stocks. For data-poor stocks, the models based on first principles, such as the Quince-Boukal model, can be used to produce management advice based on life history invariants, taking into account information on metabolic rates that can be obtained from other studies. © 2015. Source

Hurtado-Ferro F.,University of Washington | Szuwalski C.S.,University of Washington | Szuwalski C.S.,University of California at Santa Barbara | Valero J.L.,Center for the Advancement of Population Assessment Methodology | And 11 more authors.
ICES Journal of Marine Science | Year: 2014

Retrospective patterns are systematic changes in estimates of population size, or other assessment model-derived quantities, that occur as additional years of data are added to, or removed from, a stock assessment. These patterns are an insidious problem, and can lead to severe errors when providing management advice. Here, we use a simulation framework to show that temporal changes in selectivity, natural mortality, and growth can induce retrospective patterns in integrated, age-structured models. We explore the potential effects on retrospective patterns of catch history patterns, as well as model misspecification due to not accounting for time-varying biological parameters and selectivity. We show that non-zero values for Mohn's ρ (a common measure for retrospective patterns) can be generated even where there is no model misspecification, but the magnitude of Mohn's ρ tends to be lower when the model is not misspecified. The magnitude and sign of Mohn's ρ differed among life histories, with different life histories reacting differently from each type of temporal change. The value of Mohn's ρ is not related to either the sign or magnitude of bias in the estimate of terminal year biomass. We propose a rule of thumb for values of Mohn's ρ which can be used to determine whether a stock assessment shows a retrospective pattern. © 2014 © International Council for the Exploration of the Sea 2014. All rights reserved. Source

Ono K.,University of Washington | Licandeo R.,University of British Columbia | Muradian M.L.,University of Washington | Cunningham C.J.,University of Washington | And 13 more authors.
ICES Journal of Marine Science | Year: 2014

Management of marine resources depends on the assessment of stock status in relation to established reference points. However, many factors contribute to uncertainty in stock assessment outcomes, including data type and availability, life history, and exploitation history. A simulation-estimation framework was used to examine the level of bias and accuracy in assessment model estimates related to the quality and quantity of length and age composition data across three life-history types (cod-, flatfish-, and sardine-like species) and three fishing scenarios. All models were implemented in Stock Synthesis, a statistical age-structured stock assessment framework. In general, the value of age composition data in informing estimates of virgin recruitment (R0), relative spawning-stock biomass (SSB100/SSB0), and terminal year fishing mortality rate (F100), decreased as the coefficient of variation of the relationship between length and age became greater. For this reason, length data were more informative than age data for the cod and sardine life histories in this study, whereas both sources of information were important for the flatfish life history. Historical composition data were more important for short-lived, fast-growing species such as sardine. Infrequent survey sampling covering a longer period was more informative than frequent surveys covering a shorter period. © 2014 © International Council for the Exploration of the Sea 2014. All rights reserved. Source

Wang S.-P.,National Taiwan Ocean University | Maunder M.N.,Inter American Tropical Tuna Commission | Maunder M.N.,Center for the Advancement of Population Assessment Methodology | Nishida T.,Japan National Research Institute of Fisheries And Environment of Inland Sea | Chen Y.-R.,National Taiwan Ocean University
Fisheries Research | Year: 2015

Results from stock assessment modelling are often highly sensitive to model assumptions. It is therefore important that models are correctly specified and sensitivity analyses are conducted to evaluate the impact of model uncertainty. Model misspecification, changes in parameters over time, and data weighting are common issues that arise when developing stock assessment models. We conducted a stock assessment for swordfish Xiphias gladius in the Indian Ocean, using an integrated age-structured model, and evaluated estimates of management quantities under alternative assumptions about (1) changes in catchability for CPUE-based indices of abundance, (2) changes in gear selectivity, (3) weighting of abundance indices, and (4) the impact of sex-specific growth. The results indicated that assuming time-blocks for both catchability and selectivity may be appropriate to reflect the changes in fishing operations of Japanese and Taiwanese longline fleets. This assumption also provided better model performance and more optimistic assessment results because it implied that the decline in indices of abundance resulted from changes in catchability rather than depletion of biomass. Inappropriate choices for selectivity curves can deleteriously affect model performance, and attempting to account for model misspecification through downweighting of data may not be appropriate. Care must be taken when modelling changes in selectivity because selectivity can be distorted to accommodate changes in catchability. More generally, substantial changes in catchability (e.g., due to changes in targeting) may not be fully addressed in CPUE standardization and may require modelling changes over time in catchability within the stock assessment model. Finally, we found that misspecification of growth is at least as influential, if not more so, than misspecification of catchability and selectivity, or data weighting. © 2014 Elsevier B.V. Source

Johnson K.F.,University of Washington | Monnahan C.C.,University of Washington | McGilliard C.R.,National Oceanic and Atmospheric Administration | McGilliard C.R.,University of Washington | And 13 more authors.
ICES Journal of Marine Science | Year: 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. © 2014 © International Council for the Exploration of the Sea 2014. All rights reserved. Source

Discover hidden collaborations