Fisheries Reference Points Research Articles

Estimating fisheries reference points from catch and resilience

AbstractThis study presents a Monte Carlo method (CMSY) for estimating fisheries reference points from catch, resilience and qualitative stock status information on data‐limited stocks. It also presents a Bayesian state‐space implementation of the Schaefer production model (BSM), fitted to catch and biomass or catch‐per‐unit‐of‐effort (CPUE) data. Special emphasis was given to derive informative priors for productivity, unexploited stock size, catchability and biomass from population dynamics theory. Both models gave good predictions of the maximum intrinsic rate of population increase r, unexploited stock size k and maximum sustainable yield MSY when validated against simulated data with known parameter values. CMSY provided, in addition, reasonable predictions of relative biomass and exploitation rate. Both models were evaluated against 128 real stocks, where estimates of biomass were available from full stock assessments. BSM estimates of r, k and MSY were used as benchmarks for the respective CMSY estimates and were not significantly different in 76% of the stocks. A similar test against 28 data‐limited stocks, where CPUE instead of biomass was available, showed that BSM and CMSY estimates of r, k and MSY were not significantly different in 89% of the stocks. Both CMSY and BSM combine the production model with a simple stock–recruitment model, accounting for reduced recruitment at severely depleted stock sizes.

Revisiting safe biological limits in fisheries

AbstractThe appropriateness of three official fisheries management reference points used in the north‐east Atlantic was investigated: (i) the smallest stock size that is still within safe biological limits (SSBpa), (ii) the maximum sustainable rate of exploitation (Fmsy) and (iii) the age at first capture. As for (i), in 45% of the examined stocks, the official value for SSBpa was below the consensus estimates determined from three different methods. With respect to (ii), the official estimates of Fmsy exceeded natural mortality M in 76% of the stocks, although M is widely regarded as natural upper limit for Fmsy. And regarding (iii), the age at first capture was below the age at maturity in 74% of the stocks. No official estimates of the stock size (SSBmsy) that can produce the maximum sustainable yield (MSY) are available for the north‐east Atlantic. An analysis of stocks from other areas confirmed that twice SSBpa provides a reasonable preliminary estimate. Comparing stock sizes in 2013 against this proxy showed that 88% were below the level that can produce MSY. Also, 52% of the stocks were outside of safe biological limits, and 12% were severely depleted. Fishing mortality in 2013 exceeded natural mortality in 73% of the stocks, including those that were severely depleted. These results point to the urgent need to re‐assess fisheries reference points in the north‐east Atlantic and to implement the regulations of the new European Common Fisheries Policy regarding sustainable fishing pressure, healthy stock sizes and adult age/size at first capture.

A life-history evaluation of the impact of maternal effects on recruitment and fisheries reference points

Fishing causes dramatic changes in the age and size structure of fish stocks. In particular, the targeting of the largest and oldest individuals in a stock changes the age and size distribution of that stock. A large female produces a higher quantity of eggs than a young female because of its larger size, but recent laboratory evidence further indicates that large females also produce eggs of higher quality, a phenomenon known as maternal effects. However, most traditional management models assume that all female fish contribute equally per unit biomass to future recruitment. Here we investigate whether this assumption is valid by calculating the impact of maternal effects both before and after accounting for density-dependent effects. We find that the contribution of large individuals to reproduction is much more pronounced for unfished than for fished stocks. Fisheries reference points are largely unaffected by maternal effects. Our results indicate that the incorporation of maternal effects into impact assessments of fisheries is not expected to change advice substantially. Important exceptions are stocks whose demography is very vulnerable to fishing (and which therefore have low fishing reference points) for which maternal effects are relevant and necessary to consider.

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

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.

Beverton and Holt Reloaded – Incorporating Variable Growth into a Yield Per Recruit Model

Animals to be fattened must be fed with nearly the maximum feeding rate to achieve maximum yields – food supply and food consumption must coincide. This we know for centuries from agriculture. Yields decline immediately when the food supply is limited. Are there parallels between agriculture and fisheries? The only way to control the food consumption of fish stocks is by influencing the population size by fishing. In standard yield per recruit analyses fixed growth parameters are assumed. The effect of food supply on growth is not considered and thus, the implications of changes in growth for yield- and spawner-per-recruit curves due to variations in the availability of food are neglected. Under stock recovery density dependent changes in growth may severely bias biological reference points derived from such curves. Here, we present a revised Beverton and Holt yield per recruit model including a revised von Bertalanffy Growth model that is triggered by available food for assimilation and demonstrate the implications for fisheries reference points such as Fmax. The traditional Beverton and Holt yield-model should be replaced by our model; for overfished stocks it delivers identical output values but, if dietary deficiency is detected in overstocked populations then the results correspond to the measured response of the ecosystem.

Size structure, not metabolic scaling rules, determines fisheries reference points

AbstractImpact assessments of fishing on a stock require parameterization of vital rates: growth, mortality and recruitment. For ‘data‐poor’ stocks, vital rates may be estimated from empirical size‐based relationships or from life‐history invariants. However, a theoretical framework to synthesize these empirical relations is lacking. Here, we combine life‐history invariants, metabolic scaling and size‐spectrum theory to develop a general size‐ and trait‐based theory for demography and recruitment of exploited fish stocks. Important concepts are physiological or metabolic scaled mortalities and flux of individuals or their biomass to size. The theory is based on classic metabolic relations at the individual level and uses asymptotic size W∞ as a trait. The theory predicts fundamental similarities and differences between small and large species in vital rates and response to fishing. The central result is that larger species have a higher egg production per recruit than small species. This means that density dependence is stronger for large than for small species and has the consequence that fisheries reference points that incorporate recruitment do not obey metabolic scaling rules. This result implies that even though small species have a higher productivity than large species their resilience towards fishing is lower than expected from metabolic scaling rules. Further, we show that the fishing mortality leading to maximum yield per recruit is an ill‐suited reference point. The theory can be used to generalize the impact of fishing across species and for making demographic and evolutionary impact assessments of fishing, particularly in data‐poor situations.

Modelling the effects of density-dependent mortality in juvenile red snapper caught as bycatch in Gulf of Mexico shrimp fisheries: Implications for management

Density-dependent mortality of juvenile fishes is a key population regulation mechanism that is usually assumed to occur before fish recruit to fisheries. When density-dependent mortality occurs simultaneously with bycatch of juvenile fish but is not accounted for in stock assessments, estimates of population size and fishery reference points may be biased as a result. This paper develops an instantaneous, age-structured model accounting for simultaneous density-dependent mortality and bycatch in age-0 red snapper (Lutjanus campechanus), using equations derived from the Beverton–Holt stock-recruit function. Model equations are first presented and deterministic equilibrium properties of the model are explored. Two simplified Bayesian models (with and without post-recruitment density-dependent mortality) are then fitted to data from the 2009 Gulf of Mexico red snapper stock assessment to illustrate the effects of post-recruitment density-dependent mortality on estimates of stock size, stock status and recovery potential. Finally, the Bayesian models are re-run using simulated indices of abundance and age composition data to explore the estimability of model parameters under different amounts of process and observation error; and also to illustrate policy implications of model mis-specification in terms of timing of density-dependent processes. All analyses show that failure to account for post-recruitment density-dependent mortality in stock assessments can lead to overestimation of true abundance and recovery potential. Equilibrium analyses show that fishery reference points MSY and BMSY may be overestimated if true post-recruitment density-dependent mortality is not accounted for. These analyses also illustrate the problematic nature of defining and calculating reference points in the presence of numerous sources of mortality that affect different demographic components of the population. We note that when population dynamics were simulated without density-dependent age-0 mortality simultaneous with bycatch, estimates of stock size and productivity obtained from an assessment model that assumed density-dependent age-0 mortality had relatively little bias. This was because the density-dependence parameter was correctly estimated to be close to zero. This suggests that it may be advisable to use the density-dependence model if there is a possibility that post-recruitment density-dependent mortality is a factor governing population dynamics.

Quantifying the tradeoff between precaution and yield in fishery reference points

Abstract Hart, D. R. 2013. Quantifying the tradeoff between precaution and yield in fishery reference points. – ICES Journal of Marine Science, 70: 591–603. A method using Monte Carlo simulations for estimating fishery reference points that accounts for parameter uncertainty is presented. Uncertainties in the input parameters of yield-per-recruit and stock-recruit analyses are propagated to estimate uncertainty in reference points such as FMSY. These uncertainties are used to evaluate the tradeoffs between the risks of overfishing and stock collapse, and the cost of reduced expected yield due to setting fishing mortality below FMSY. At fishing mortalities near FMSY, reduction in fishing mortality substantially decreases the probability of overfishing and stock collapse in exchange for slightly reduced expected yield. At lower fishing mortality rates, the marginal benefit (in terms of lessened risk of overfishing and stock collapse) from further reductions in fishing mortality is less, and the cost in forgone yield is greater. Less resilient “low steepness” stocks require additional precaution due to the risk of complete population collapse. Marine protected areas can also reduce risks of collapse, but at a higher cost in terms of expected yield than effort reduction. Implementation uncertainty (i.e. uncertainty in achieving a fishing mortality target) increases the risk of overfishing as well the loss of yield due to precaution, except at fishing mortalities near or above FMSY.

Predicting species vulnerability with minimal data to support rapid risk assessment of fishing impacts on biodiversity

Summary1. Large‐bodied species are especially vulnerable to fishing in mixed fisheries. Their effective conservation requires predictions of sensitivity and exposure to fishing mortality, but such predictions are hard to make when the population dynamics of most of these species have not been described.2. We present a method for assessing sensitivity and conservation management reference points using widely available life‐history data. The method allows the sensitivity of all fish species in a community to be assessed in relation to conservation‐ and yield‐based fishery reference points.3. Knowledge of sensitivity is used to (i) rank species by sensitivity, (ii) conduct a risk assessment to identify species potentially vulnerable to current fishing pressure and (iii) examine potential trade‐offs between fishery catches and the conservation status of sensitive species.4. The method is applied to the Celtic Sea bottom‐dwelling fish community. For the species present, conservation threshold fishing mortalities ranged from 0·05 per year for the most sensitive large elasmobranchs to over 1 per year for small teleosts. The assessment predicts that current levels of fishing mortality may place all the elasmobranchs and over a quarter of the teleosts below conservation reference points.5. Depending on the relative mortality rates affecting commercially targeted species and species of conservation concern, up to 65% of the potential yield‐per‐recruit of commercially important species may have to be forgone to reduce fishing mortality below conservation limit reference points for the most sensitive species.6. Synthesis and applications.The method presented provides a clear objective procedure to construct ranked species sensitivity lists that can inform management, monitoring and research. The Celtic Sea case study demonstrated that limiting fishing pressure on key commercial stocks to meet fisheries production targets may be insufficient to guarantee the persistence of more sensitive species. Management actions that effectively decouple the mortality rates on commercial species and ‘conservation’ species are likely to be required to make progress in relation to conservation objectives. The method would support rapid assessment of sensitivity to fishing in many regions around the world as only taxonomic lists and estimates of body size are required.

Immediate maximum economic yield; a realistic fisheries economic reference point

Abstract Lleonart, J., and Merino, G. 2010. Immediate maximum economic yield; a realistic fisheries economic reference point. – ICES Journal of Marine Science, 67: 577–582. Unregulated or poorly managed fisheries tend towards overexploitation, but fisheries rent does not completely dissipate when immediate rent maximization is sought. The principle of immediate economic rent maximization is the basis of the derivation of a classic model and has led to the definition of a relationship in a catch-and-effort diagram termed the dynamic immediate maximum economic yield (DIMEY) curve. For any initial biomass, if the economic rent in the immediate fishing season is maximized, then the fishing effort and catch strategy that follows will be located on the DIMEY curve. The DIMEY curve is not only used for dynamic simulation but also used to identify a new reference point, the immediate maximum economic yield (IMEY), which is proposed as more realistic than the classic open-access solution for unregulated fisheries. IMEY is proposed as an asymptotic outcome for unregulated or poorly managed fisheries when short-term economic objectives drive fleet activities. IMEY properties are described and compared with traditional fisheries reference points in the yield-and-effort diagram. Theoretical conclusions are compared with empirical evidence provided by the red shrimp fishery off Blanes, Spain (NW Mediterranean). Observed catch-and-effort records are plotted and were positively correlated with the DIMEY curve and IMEY.

An age-structured model with leading management parameters, incorporating age-specific selectivity and maturity

Previous authors have shown analytically that the optimal equilibrium harvest rate (UMSY) for an iteroparous fish stock is a function of the slope of the stock-recruitment curve at low stock size (α) and that UMSY can therefore be considered a direct measure of stock productivity. As such, it can be used as a leading parameter in stock assessment models and directly estimated using Bayesian or similar techniques. Here we present an alternative method for deriving α from UMSY that incorporates age-specific selectivity and fecundity, avoiding assumptions of knife-edged recruitment and maturity. We present an age-structured model with two fisheries reference points (UMSY and maximum sustainable yield, MSY) as its leading parameters. We show equilibrium properties of the model, chiefly in terms of its ability to show relationships between life history traits, density dependence, and UMSY. We also demonstrate a simple Bayesian estimation routine to illustrate estimation of UMSY and MSY directly from data. We compare our results to those from a structurally identical model with leading biological parameters. Using models with leading management parameters can improve communicability of results to managers.

Bayesian nonparametric analysis of stock–recruitment relationships

The relationship between current abundance and future recruitment to the stock is fundamental to managing fish populations. However, many different recruitment models are plausible and the data are insufficient to distinguish among them. Although nonparametric methods may be used to circumvent this problem, these are devoid of biological underpinnings. Here, we present a Bayesian nonparametric approach that allows straightforward incorporation of prior biological information and use it to estimate several fishery reference points. We applied this method to artificial data sets generated from a variety of parametric models and compare the results with the fit of Ricker and Beverton–Holt models. We found that the Bayesian nonparametric method fit the data nearly as well as the true parametric model and always performed better than incorrect parametric alternatives. The estimated reference points agree closely with true values calculated for the underlying parametric model. Finally, we apply the method to empirical data for lingcod (Ophiodon elongatus) and several salmonids. Since this method is capable of reproducing the behavior of any of the parametric models and provides flexible, data-driven estimates of stock–recruitment relationships, it should be of great value in fisheries applications where the true functional relationship is always unknown.

Methods of assessing extinction risk in marine fishes

AbstractThe decline and disappearance of species from large parts of their former geographical range has become an important issue in fisheries ecology. There is a need to identify which species are at risk of extinction. The available approaches have been subject to considerable debate – particularly when applied to commercially exploited species. Here we have compiled methods that have been used or may be used for assessing threat status of marine organisms. We organize the methods according to the availability of data on the natural history, ecology and population biology of species. There are three general approaches to inferring or assessing extinction risk: (i) correlative approaches based on knowledge of life histories and ecology; (ii) time‐series approaches that examine changes in abundance; and (iii) demographic approaches based on age‐ or stage‐based schedules of vital rates and fisheries reference points. Many methods are well suited to species that are highly catchable and/or have relatively low productivity, but theory is less well developed for assessing extinction risk in species exhibiting narrow geographical distributions or ecological specialization. There is considerable variation in both definitions of extinction risk and the precision and defensibility of the available risk assessment methods, so we suggest a two‐tiered approach for defining and assessing extinction risk. First, simple methods requiring a few easily estimated parameters are used to triage or rapidly assess large numbers of populations and species to identify potentially vulnerable populations or species. Second, the populations and species identified as vulnerable by this process can then be subject to more detailed and rigorous population analysis explicitly considering sources of error and uncertainty.

Analytical models for fishery reference points

Fishery reference points are widely applied in formulating harvest management policies. We supply precise mathematical definitions for several reference points in common use. We then derive analytical expressions for these quantities from age-structured population models. In particular, we explain how the maximum sustainable harvest rate and catch (h*, C*), two quantities of management importance, can replace the classical recruitment parameters ( alpha , beta ) in the Beverton-Holt and Ricker recruitment curves. We also demonstrate dependencies of various reference points on subsets of model parameters. Although our analysis is restricted to special cases, our models still have general utility. For example, simple calculations from analytical formulas enable checks on the output from more complex models and guide the choice of reference points for fishery management.

Analytical models for fishery reference points

Analytical models for fishery reference points

Precision of exploitation-rate estimates in the Tasmanian rock-lobster fishery based on change-in-ratio techniques

Determination of exploitation rate is considered important for both stock assessment and establishment of fishery reference points. From 1992 to 1996, a project was undertaken to evaluate the change-in-ratio technique for estimating exploitation rates for male lobsters off southern Tasmania. Confidence limits of exploitation rate estimates were determined by bootstrap analysis. This showed wide confidence intervals around the estimates for the fishing years from 1992–93 to 1994–95. Bootstrap analysis was used to determine the appropriate sample size (number of pot-lifts) for improved precision in exploitation rate estimates for the 1995–96 fishing year. Results from field estimates confirm the expected decrease in confidence intervals. The level of exploitation had an inverse relationship to the precision of exploitation rate estimates. Relationships can be determined between the level of exploitation in the fishery and the degree of precision achievable for a set number of pot-lifts. Thus, sampling programmes can be designed to minimize cost and provide the degree of precision required for management strategies.