Stock Assessment Results Research Articles

Using the best of two worlds: A bio‐economic stock assessment (BESA) method using catch and price data

AbstractReliable stock assessments are essential for successful and sustainable fisheries management. Advanced stock assessment methods are expensive, as they require age‐ or length‐structured catch and detailed fishery‐independent data, which prevents their widespread use, especially in developing regions. Furthermore, modern fisheries management increasingly includes socio‐economic considerations. Integrated ecological‐economic advice can be provided by bio‐economic models, but this requires the estimation of economic parameters. To improve accuracy of data‐limited stock assessment while jointly estimating biological and economic parameters, we propose to use price data, in addition to catches, in a new bio‐economic stock assessment (‘BESA’) approach for de‐facto open access stocks. Price data are widely available, also in the Global South. BESA is based on a state‐space approach and uncovers biomass dynamics by use of the extended Kalman filter in combination with Bayesian estimation. We show that estimates for biological and economic parameters can be obtained jointly, with reliability gains for the stock assessment from the additional information inherent in price data, compared to alternative assessment methods for data‐poor stocks. In a real‐world application to Barents Sea shrimp (Pandalus borealis, Pandalidae), we show that BESA benchmarks well also against advanced stock assessment results. BESA can thus be both a stand‐alone approach for currently unassessed stocks as well as a complement to other available methods by providing bio‐economic information for advanced fisheries management.

Lost in translation: understanding divergent perspectives on a depleted fish stock

Fishers commonly disagree with stock assessment results, particularly when a stock declines and strict harvest controls become necessary. Such regulations alter fisher perceptions of stock dynamics, contributing to a divergence in perspectives. Some assessments have inconsistent terminal year values (retrospective patterns) which fuel distrust in scientific advice. When assessment and fishery perspectives disagree, independent surveys can help identify biases and interpret discrepancies. We examine fishery trends and assessment results for Atlantic cod in the Gulf of Maine, a stock which has declined for decades. Trends were compared to a scientific industry cooperative trawl survey and a telephone survey of fisher perceptions. Trawl survey results generally corroborate the assessment perspective on population scale and decline, yet suggest a different view of the age structure. Fisher perceptions were at odds with the assessment and trawl survey and likely resulted from regulations that altered fisher behavior, causing catch rates to increase while the stock declined. Divergent perspectives may be an unavoidable consequence of fishery management, yet acknowledging the underlying mechanisms might help avoid future conflict.

Fishery and biology of cutlass fishes from Indian seas with special reference to the largehead hairtail Trichiurus lepturus Linnaeus, 1758 - A review

Cutlass fishes of the family Trichiuridae form an important group in the commercial fishery in India, contributing >7% to the pelagic marine fish landings of the country during 2018-19. The largehead hairtail Trichiurus lepturus Linnaeus, 1758 forms a significant component of marine fish landings in India and several studies have reported its length-weight relationship, growth patterns, sex ratio, population parameters and stock status. Age and growth of T. lepturus were reported by the authors mostly using inverse interpolation of von Bertalanffy growth equation and ageing using hard parts is desirable to validate these observations. The present review highlights the importance of applying uniform methodologies for creating fisheries biology databases and timely publication of stock assessment results. Focussed utilisation of fisheries biology databases of commercially important fishery resources, including cutlass fishes using meta-analyses to validate and base fisheries management decisions should be considered. Keywords: Age and growth, Condition factor, Length-weight relationship, Population parameters, Ribbonfishes, Stock assessment, Trichiuridae

Estimation of Postrelease Longline Mortality in Pacific Halibut Using Acceleration‐Logging Tags

AbstractPacific HalibutHippoglossus stenolepiscaptured in directed commercial longline fisheries in Canada and the USA that are below the legal minimum size for retention must be returned to the sea without incurring additional injury. Estimates of mortality caused by discarding sublegal‐sized fish are included in annual estimates of total mortality from all sources and affect the results of stock assessment and the yield available to fisheries. Currently, an average discard mortality rate (DMR) of 16% is applied to all sublegal‐sized longline discards. These discards consist of fish that suffer injuries ranging from minor to severe. The 16% DMR that is currently applied was derived by averaging injury‐specific DMRs that in turn assume 3.5% mortality of Pacific Halibut that are released to the sea with only minor injuries. The latter has been derived experimentally but only in captivity. Here, we used acceleration‐logging pop‐up archival transmitting tags to infer individual survival outcomes for Pacific Halibut that were released in situ following capture on longline gear. Postrelease behavioral data were evaluated for 75 fish that were at liberty for 2–96 d. Three fish were confidently inferred to have died after periods at liberty of 41–80 d, and another three fish may have died 96 d after release, resulting in minimum and maximum estimated 96‐d postrelease DMRs of 4.2% (range = 0.0–8.7%) and 8.4% (range = 1.7–14.6%), respectively. These ranges are consistent with the currently applied value of 3.5%. However, the observation that no mortalities occurred until after 40 d postrelease departs from the findings of captive studies, in which the majority of capture‐induced mortality occurred within 20 d of release.

A Bayesian state-space production model for Korean chub mackerel (Scomber japonicus) stock

The main purpose of this study is to fit catch-per-unit-effort (CPUE) data about Korea chub mackerel (Scomber japonicus) stock with a state-space production (SSP) model, and to provide stock assessment results. We chose a surplus production model for the chub mackerel data, namely annual yield and CPUE. Then we employed a state-space layer for a production model to consider two sources of variability arising from unmodelled factors (process error) and noise in the data (observation error). We implemented the model via script software ADMB-RE because it reduces the computational cost of high-dimensional integration and provides Markov Chain Monte Carlo sampling, which is required for Bayesian approaches. To stabilize the numerical optimization, we considered prior distributions for model parameters. Applying the SSP model to data collected from commercial fisheries from 1999 to 2017, we estimated model parameters and management references, as well as uncertainties for the estimates. We also applied various production models and showed parameter estimates and goodness of fit statistics to compare the model performance. This study presents two significant findings. First, we concluded that the stock has been overexploited in terms of harvest rate from 1999 to 2017. Second, we suggest a SSP model for the smallest goodness of fit statistics among several production models, especially for fitting CPUE data with fluctuations.

The influence of metrics for spawning output on stock assessment results and evaluation of reference points: An illustration with yellowfin tuna in the eastern Pacific Ocean

Reference points are used to determine whether overfishing is occurring, a stock is overfished, or the abundance of the stock is approaching an undesirable level. Reference points are often classified as limit reference points, which indicate an undesirable state, or target reference points, which specify a desirable one. Limit reference points frequently indicate a state for which the reproductive potential of the stock is impacted, and are thus based on spawning output. Spawning output is also used in the stock-recruitment curve, which is a key component of stock-assessment models. We investigated the effect on stock assessment results of metrics of spawning output that are used either in the stock-recruitment relationship or to evaluate reference points. We use yellowfin tuna (Thunnus albacares) in the eastern Pacific Ocean as an example. The metrics biomass of mature females and fecundity attribute higher reproductive potential to the older ages, while numbers of mature females and summary biomass attribute more to the younger ages. Both the stock assessment results and the evaluation of reference points are sensitive to the metric used. The most optimistic perceptions of stock status are obtained when using numbers of mature females, female summary biomass or summary biomass to evaluate the reference points. The choice of metric may be as important as the uncertainty about steepness of the stock-recruitment curve. Given the difficulty in determining the appropriate measure of spawning output and the fact that populations fluctuate naturally, it is recommended that fishing mortality-based reference points are given more consideration for management advice aiming to maintain stocks at desirable states (target reference points) and that harvest control rules based on both types of reference points be compared for their relative effectiveness in avoiding recruitment overfishing and achieving other fisheries objectives using Management Strategy Evaluation.

Long-term fishing impact on the Senegalese coastal demersal resources: diagnosing from stock assessment models

For the first time in Senegal, assessments based on both stochastic and deterministic production models were used to draw a global diagnosis of the fishing impact on coastal demersal stocks. Based one national fisheries databases and scientific trawl surveys data: (i) trends in landings since 1971 were examined, (ii) abundance indices of 10 stocks were estimated using linear models fitted to surveys data and commercial catch per unit efforts, and (iii) stock assessments were carried out using pseudo-equilibrium Fox and Pella-Tomlinson models and a Biomass dynamic production model fitted in a Bayesian framework to abundance indices. Most stocks have seen their abundance sharply declining over time. All stocks combined, results of stock assessments suggest a 63% reduction compared to virgin state. Three fifth of demersal stocks are overexploited and excess in fishing effort was estimated until 75% for the worst case. We conclude by suggesting that the fishing of such species must be regulated and an ecosystem approach to fisheries management should be implemented in order to monitor the whole ecosystem.

Get the biology right, or use size-composition data at your own risk

Weighting of size-composition data (length or weight composition of the catches) can have a large influence on the results of contemporary integrated stock assessment models in the presence of model misspecification. Model misspecification leads to conflicting information among data sets, and the choice of data weighting will determine the results. Information content on absolute abundance and abundance trends contained in size-composition data is particularly susceptible to misspecification of the biological processes. Biological processes are often misspecified in assessment models for exploited fish stocks due to lack of information. The misspecification can be in a functional form (e.g., the growth curve) or in the values assumed for pre-specified parameters. Our application to bigeye tuna in the eastern Pacific Ocean shows how one needs to “get the biology right”, i.e. minimize model misspecification, to reduce the dependency of stock assessment results on the weighting of the various data components. The stock assessment results are sensitive to the conversion from processed weight to total weight, a common, but often overlooked, component of model specification, and to the asymptotic length of the growth curve. The results are also sensitive to the weighting of the composition data. Application of the Age-Structured Production Model diagnostic shows that recruitment variation must be taken into account to interpret the absolute abundance and trend information contained in a CPUE-based index of relative abundance. Unfortunately, recruitment cannot typically be estimated from the relative index of abundance alone, so composition data are needed. The abundance estimates from an age-structured production model with estimated recruitment deviates are too uncertain (i.e., have wide confidence intervals) to be of use for management advice. Therefore, there is a trade-off between using composition data to estimate recruitment and its influence on estimates of absolute abundance through a catch-curve type process. We conclude that (i) integrated analysis, the current approach for assessing fish stocks, is supported by our results; (ii) composition data are needed to estimate recruitment; and (iii) addressing key model misspecifications should be a major component of integrated analysis.

Using pop-up satellite archival tags to inform selectivity in fisheries stock assessment models: a case study for the blue shark in the South Atlantic Ocean

Abstract Selectivity has traditionally been well estimated internally in stock assessment models when length or age composition data are available. However, in stock assessment, temporal or spatial variation in fishery or stock structure can lead to misspecification of the selectivity pattern, which can contribute substantially to the uncertainty in stock assessment results. Consequently, generating auxiliary information to help stock assessment scientists avoid unrealistic specifications of selectivity patterns should be encouraged. Here, we combine data from pop-up satellite archival tags (PSATs) deployed on blue sharks in the South Atlantic Ocean, and information on maximum pelagic longline fishing depths, to introduce an alternative approach for estimating selectivity of fishing gear. Further, we present how this externally estimated tag-based selectivity can be used to inform the most appropriate form of selectivity curves (e.g. asymptotic or dome-shaped) in a spatially structured stock assessment model for the South Atlantic blue shark population. The estimated tag-based selectivity showed substantially different selectivity patterns within the area of the assessed stock, in one area the depth range of the longline gear is inhabited mostly by adults, which is consistent with an asymptotic selectivity. In another area, the overlap shifts to younger ages, with older sharks located in deeper waters, consequently the expected selectivity is more dome-shaped. To account for this variability in the stock assessment model, we assigned fishing fleets with different selectivity patterns. The form of the selectivity curve assigned for each fleet was based on the tag-based selectivity estimates for the area of where that fleet operates. The assessment model demonstrated relatively good fit to the data and that the estimated management quantities were robust. This study provides additional evidence that externally derived estimates of selectivity using PSATs data can assist implementing stock assessments that capture some of the spatial variability of pelagic fish species.

Fishery selection and its relevance to stock assessment and fishery management

Fishery selection (selectivity for short) is the term often used to describe the phenomenon whereby a fish stock experiences mortality due to fishing that is age- or size-specific. Selectivity operates both at a local scale, as in the direct interactions of individual fish with the fishing gear (contact selection), and at a stock-wide scale (population selection), as evidenced by the differential rates of fishing mortality-at-age that are generally observed in stock assessment results. All age-structured stock assessment models have some form of fishery selection to modulate the impact of fishing mortality on differing age-classes, but selection coefficients, from a stock assessment viewpoint, generally are nuisance parameters rather than a focus of attention. This paper provides an overview of the three main processes that contribute to and influence population selection: (1) physical sorting by the fishing gear or differential behavioral responses of the fish to the gear produce the phenomenon of contact selection; (2) differing selection properties of different types of fishing gear (e.g., trawl versus longline) in turn generate a composite selection curve that is a weighted average of the different kinds of contact selection; and (3) when the fish are not well mixed spatially, then the spatial distribution of fishing relative to the spatial distribution of the fish also affects population selectivity. Fishing mortality-at-age estimates derived from a published Virtual Population Analysis of Scotian Shelf haddock are used to illustrate the diversity of shapes that can be seen in population selection curves and their considerable temporal variability. A spatial model for fishery age-selectivity is then used to demonstrate that the maximum relative yield harvested from a stock can be a function of both contact selection and the spatial distribution of fishing.

Towards the implementation of an integrated ecosystem fleet-based management of European fisheries

Using the Celtic Sea and the North Sea as case studies, the fleet-based approach is shown to be the pathway to implement an effective ecosystem approach to fisheries management (EAFM) in European seas. First, a diagnostic on the health of each ecosystem is proposed based on the reconstruction of long time-series of catch, the analysis of mean indicators or stocks trajectories derived from ICES stock assessment results, and the analysis of ecosystem indicators. Then, a fleet-based synthesis is presented using indicators of both the ecological impact and the economic performances of the major fleets operating within each ecosystem. In particular, assessment diagrams show whether each fleet segment, on average, sustainably exploits the stocks. Although results are preliminary due to the poor quality of available data, the analysis shows that simple indicators can be estimated and clearly highlight contrasts between fleet segments. Such an approach contributes to the evolution from a stock-based to a fleet-based management, which reflects the ecological, economical and social pillars of the sustainable development of fisheries.

Population Dynamics and Stock Assessment of Blue Swimming Crab (Portunus pelagicus Linnaeus, 1758) in the Coastal Area of Trang Province, Thailand

The population dynamics and stock assessment of blue swimming crab ( Portunus pelagicus Linnaeus, 1758) in the coastal area of Trang province, Southern Thailand was done through stratified sampling of 7,499 crabs that were caught by crab gill nets and crab traps. The sampling was done from September 2006 to August 2007. The carapace width and weight relationship was measured, including parameters such as asymptotic outer carapace width (OCW a ), curvature (K), asymptotic inner carapace width (ICW a ), total mortality coefficient (Z), natural mortality coefficient (M), fishing mortality coefficient (F), exploitation rate (E), and total stock at first catch (L c ). The maximum sustainable yield (MSY), maximum economic yield (MEY) and total biomass (B) were estimated. Results showed that the asymptotic outer carapace width was 17.30. The asymptotic inner carapace width was 16.70 cm and its curvature was 1.5 per year. The total mortality coefficient was 8.96 per year, natural mortality coefficient was 1.61 per year and fishing mortality coefficient was 7.35 per year. The exploitation rate was 0.82. The total stock of blue swimming crab at first catch at 2.5 - 3.0 cm was 7,895,170 individuals. Results of stock assessment also showed that the maximum sustainable yield was 364.33 tons, maximum economic yield was 25.29 million Baht (1 Baht = US$ 33) and total biomass was 139.83 MT. A 40 % decrease in the level of fishing effort is recommended to ensure sustainability of the blue swimming crab stock.

Stock Assessment of Scalloped Hammerheads in the Western North Atlantic Ocean and Gulf of Mexico

AbstractThe status of the western North Atlantic Ocean population of scalloped hammerheads Sphyrna lewini (Sphyrnidae [hammerhead sharks]) was assessed from 1981 through 2005 by using Schaefer (logistic) and Fox surplus‐production models. The population declined rapidly before 1996 but began rebuilding in the late 1990s as fishing pressure decreased. The Akaike information criterion for small sample sizes—a test of goodness of fit for statistical models—indicated that the Fox model provided a slightly better fit to the data. Bootstrapped parameter values showed that in 2005 the probability of the scalloped hammerhead's being overfished was greater than 95% (the population was estimated to be 45% of that which would produce the maximum sustainable yield [MSY]) and a 73% probability that overfishing was occurring (fishing mortality was approximately 129% of that associated with the MSY). The size of this population was estimated to be 17% of what it had been in 1981, that is, it has been depleted by about 83% from the virgin stock size. Monte Carlo simulation predicted that the population had a 58% probability of rebuilding in 10 years if the 2005 catch level (4,135 individuals) were maintained and an 85% probability of rebuilding if the 2005 total catch were halved. Sensitivity analyses showed that the stock assessment results were most sensitive to removing the University of North Carolina longline survey index of relative abundance, the method of weighting indices, and excluding fishery‐dependent indices of relative abundance.

Analytical reference points for age-structured models: application to data-poor fisheries

AbstractBrooks, E. N., Powers, J. E., and Cortés, E. 2010. Analytical reference points for age-structured models: application to data-poor fisheries. – ICES Journal of Marine Science, 67: 165–175. Analytical solutions for biological reference points are derived in terms of maximum lifetime reproductive rate. This rate can be calculated directly from biological parameters of maturity, fecundity, and natural mortality or a distribution for this rate can be derived from appropriate metadata. Minimal data needs and assumptions for determining stock status are discussed. The derivations lead to a re-parameterization of the common stock–recruit relationships, Beverton–Holt and Ricker, in terms of spawning potential ratio. Often, parameters in stock–recruit relationships are restricted by tight prior distributions or are fixed based on a hypothesized level of stock resilience. Fixing those parameters is equivalent to specifying the biological reference points. An ability to directly calculate reference points from biological data, or a meta-analysis, without need of a full assessment model or fisheries data, makes the method an attractive option for data-poor fisheries. The derivations reveal an explicit link between the biological characteristics of a species and appropriate management. Predicted stock status for a suite of shark species was compared with recent stock assessment results, and the method successfully identified whether each stock was overfished.

Development and evaluation of catch per unit effort indices for southern blue whiting (Micromesistius australis) on the Campbell Island Rise, New Zealand

Abstract This paper develops standardized commercial cpue indices for a highly aggregated spawning fishery in New Zealand waters, and verifies the indices using fishery-independent data. Indices were calculated for all vessels using three different measures of effort, and for vessel subsets based on processing type (surimi and dressed), and relative experience in the fishery. Trends in cpue were consistent with trends in fishery-independent acoustic surveys, age composition of the commercial catch, and recent stock assessment results. In particular, the cpue indices tracked the more than fourfold increase in abundance from 1993 to 1996 associated with the recruitment of the strong 1991 year class, and the decline in relative abundance as this year class was fished down. Despite this being a highly aggregated spawning fishery, there was little evidence for hyperstability. There were also significant differences in fishing strategies of the fleets between periods of high and low fish abundance.

Modelling the learning behaviour of fishers: learning more from their successes than from their failures

Learning occurs in all stages of a fishery, in the entire fishing career of a fisher, and even within a single fishing trip. It is an important aspect of fleet dynamics; failure to take it into proper account biases results of population dynamics studies and results of stock assessments. In this paper, I introduce and slightly generalise three learning models and derive a new one. I use them to analyse data on the short-term learning behaviour of all fishers as a group in the fishery of the western king prawn Penaeus latisulcatus in the Gulf St Vincent, Australia, to demonstrate their utilities. The damped periodic change inferred in fishing efficiency of all fishers as a group with time (shot number) over a fishing day in the P. latisulcatus fishery had a period of 9.44±1.06 shots and could have resulted from periodic ‘forgetting’ and forcing by good catch rates. The new learning model was used to test the hypothesis that fishers in the P. latisulcatus fishery learn more from their failures in catch rate than from their successes, or more from their successes than from their failures, or as much from their successes as from their failures. Although very limited, the data suggest that fishers as a group learn 69.03±311.52% more from their successes in good catch rates than from their failures.

Historical perspective of global billfish stock assessment

In spite of the substantial increase in information on billfish over the last decade, especially in the landing and catch per unit effort data, statistics for some of the commercial and recreational fisheries, basic biological information on billfish such as on growth, maturation, catch at age, and sex ratio by size, is still insufficient for the application of more data-demanding models. A family of production models is still the major tool for the stock assessment of billfish. Although there are significant increases in information on catch per unit effort, it is still hard to obtain solutions from these models in many cases without putting subjective constrains on the model parameters. In addition to the uncertainty in catch information, major uncertainty in the results of stock assessments comes from the difficulties in the realistic estimation of effective fishing effort for each fishery harvesting billfish. Those difficulties arise mainly from operational changes in the fishing and partial coverage of geographical distribution of billfish by the fisheries. It is very hard to overcome these problems only by improvement of the fishery-dependent statistics. Additional information on habitat preferences of billfish and the vertical distribution of longline gears, facilitated by the newly developed equipment such as pop-up archival tags and small time-depth recorders, is very useful to evaluate gear efficiency and stock availability to fishing gear. The assessment of billfish will be improved by the habitat-based standardization models utilizing these additional data..

A meta-assessment for elasmobranchs based on dietary data and Bayesian networks

We developed a new approach, meta-assessment, as a tool for identifying declining (and potentially threatened) fish stocks in situations where a lack of data precludes traditional stock assessments. Meta-assessments are models enhanced by the incorporation of other stock assessment results. We used this idea to estimate historic biomass trends for demersal elasmobranchs of the Irish Sea. Bayesian networks, constructed from published dietary data and resembling food webs, allowed us to incorporate into our estimates the results from virtual population analysis (VPA) for Irish Sea cod, sole, plaice and whiting. To assess accuracy, we used cross-validation, estimating historic biomass trends in each individual VPA species from trends in the other three plus trends in fishing effort. We compared predicted annual trends to those derived from VPA and found 66% accuracy. We also compared biomass trends estimated from annual trawl surveys to corresponding network predictions, recovering survey trends correctly 61% of the time for elasmobranchs, 78% of the time for gurnards (Triglidae) and 89% for bib and pout (Trisopterus spp.). Results suggest that of the 11 elasmobranchs examined, the angel shark (Squatina squatina) increased in biomass least frequently from 1987 to 1997, a view consistent with survey results. Our approach also suggested a marked decline in common skate (Dipturus batis) over the period 1965–1978, during which time the skate was extirpated from the Irish Sea. We conclude that meta-assessment can serve as an exploratory method for identifying potentially threatened stocks, where even landings data are unavailable.

Improving the Precision of Abundance Estimates of Eastern Scotian Shelf Atlantic Cod from Bottom Trawl Surveys

Abstract Abundance estimates from bottom trawl surveys are important elements in the evaluation of stock status. The reliability of stock assessment results are greatly influenced by the precision of the survey abundance estimates. In this study, a new stratified random design, based upon historical spatial distribution, for estimating the abundance of ages 5–12 Atlantic cod Gadus morhua on the eastern Scotian Shelf off Nova Scotia was evaluated. Gains in precision from the new design, relative to simple random sampling, were mainly due to the improved allocation of trawl sets to strata, whereas the gains solely due to the new stratification scheme were minimal. We conclude that any reasonable stratification scheme that is flexible enough to allow for the optimization of the allocation of sets to strata should perform well. In our study, the allocation scheme was based upon the historical spatial distribution of abundances. Although annual changes in spatial distribution would require revision of the allo...

Assessment and Management of the Georges Bank Cod Fishery: An Historical Review and Evaluation

Assessment and Management of the Georges Bank Cod Fishery: An Historical Review and Evaluation