Fishery Assessment Models Research Articles

Balancing prey availability and predator consumption: a multispecies stock assessment for Lake Ontario

Trophic interactions are drivers of ecosystem change and stability, yet are often excluded from fishery assessment models, despite their potential capacity to improve estimates of species dynamics and future fishery sustainability. In Lake Ontario, recreational salmonine fisheries, including Chinook salmon ( Oncorhynchus tshawytscha) and lake trout ( Salvelinus namaycush), depend on a single prey species, alewife ( Alosa pseudoharengus). To accommodate strong trophic interactions among species, we developed a multispecies statistical catch-at-age assessment (MSCAA) model that links the dynamics of the salmonine fisheries and alewife via prey consumption and predator growth. We found that prey availability had declined since 2015 due to decreased alewife recruitment and increased Chinook salmon biomass, leading to higher alewife mortality rates and lower predator growth rates. Forward projections of predator–prey dynamics suggest that Chinook salmon stocking reductions may improve the probability for alewife population growth, but could be counteracted by increased natural Chinook salmon recruitment. Combined with predator- and prey-monitoring efforts, multispecies assessments show promise as models of intermediate complexity to support a transition to ecosystem-based approaches to fisheries management.

Eliminating implausible fisheries assessment models using fishers’ knowledge

Peer review of competing deepwater redfish (Sebastes mentella) assessment models revealed data inconsistencies where stock biomass decline shown by the survey in the 1990s was too rapid to be explained solely by reported catch. The models invoked different techniques to achieve fits, one by changing mortality at age and the other by survey weighting. The former fitted reported catch well, while the latter accepted a mismatch between reported and estimated catch. The assessments produced different estimates of historical stock size and future productivity. Interviews conducted with fishers of the stock suggested that catch was at least twice as high as the official record. In light of the fishers’ evidence, the model that invoked a large change in mortality with age to follow reported catch closely now appears less credible. This serves as a warning against introducing new biological mechanisms without credible justification. This is an example of how indicators derived from fisher’s knowledge, even if only from a small number of interviews, can be used to eliminate less plausible models.

Cost–Benefit Analysis of Alternative Techniques for Rehabilitating Abalone Reefs Depleted by Abalone Viral Ganglioneuritis

The relative cost–benefit of alternative methods for rehabilitating blacklip abalone (Haliotis rubra) reefs depleted by viral ganglioneuritis was evaluated using quantitative population and bio-economic modeling. Fishery assessment models were adapted to describe population dynamics and economics of reseeding, translocation, and natural rebuilding. Past and current literature on reseeding, translocation, and mortality rates informed a stakeholders’ workshop that agreed on the parameters for the analysis. Comparative economic performance was quantified as the impaired value of the individual transferable quota from the area until the stock recovered to the level of maximum sustainable yield, as it was prior to the abalone viral ganglioneuritis impact. When the cost of capital is considered, none of the intervention scenarios produced any cost–benefit above that estimated to accrue from an unfished natural recovery. The translocation of adults and reseeding of juveniles were found to be similarly effective largely due to the productivity of the assumed stock–recruitment relationship at low stock densities. Across the scenarios, translocation was estimated to always at least pay for direct costs but rarely covered capital costs while reseeding only covered direct costs if the price of abalone was >$25/kg and seed was <$0.50 per individual. When a depensatory form of stock–recruitment relationship, related to adult biomass, was assumed, translocation was estimated to be an order of magnitude more effective due to the time required to augment the breeding biomass with reseeded juveniles.

Using electronic tag data to improve mortality and movement estimates in a tag-based spatial fisheries assessment model

Despite increased deployment of archival tags on exploited fish species, analytical methods for including archival tag data in fishery assessment models are lacking. We present a method for integrating archival tag data into a spatial tag–recapture model for estimating natural mortality, fishing mortality, abundance, and movement. Archival tags provide important information on fish movement not available from conventional tags that facilitates separation of movement from mortality estimates. Using simulations, we evaluate the benefit of including archival tag data in the model using two model formulations: one with a general spatial structure and one with movement and fishery dynamics based on juvenile southern bluefin tuna (SBT; Thunnus maccoyii ). If fish are not tagged in all regions and time periods, then including archival tag data can substantially improve the precision of the fishing mortality and movement estimates. For example, with the general spatial structure and specific scenario presented, standard errors of the fishing mortality estimates decreased by an average of 34% (21%) when 25 archival tags were released in addition to 500 (2500) conventional tags in each region and period of tagging, respectively. Furthermore, with the SBT spatial structure, archival tag data were necessary for all parameters to be estimable.

Determining effective sample size in integrated age-structured assessment models

Abstract Hulson, P-J. F., Hanselman, D. H., and Quinn II, T. J. 2012. Determining effective sample size in integrated age-structured assessment models. – ICES Journal of Marine Science, 69:281–292. Effective sample size (ESS) is a quantity that allows for overdispersion of variance and is used commonly in integrated age-structured fishery assessment models to fit age-and-length-composition datasets. Owing to the sources of measurement, observation, process, and model-specification errors, the ESS is smaller than the actual sample size. In this study, methods to set a priori or to estimate the ESS when confronted with datasets that include these sources of error were investigated. In general, a number of methods previously proposed to incorporate the ESS resulted in accurate estimation of population quantities and parameters when different sources of error were included in the data on age and length compositions. Three objective methods to incorporate the ESS resulted in unbiased population quantities: (i) using sampling theory to derive the ESS from actual age and length compositions, (ii) iteratively estimating the ESS with the age-structured assessment model, and (iii) estimating the ESS as a parameter with the Dirichlet distribution.

Assessing Options for Using a Continuous Underway Fish Egg Sampler to Enhance Dedicated Daily Egg Production Studies Conducted from Small Research Vessels

This study was undertaken to identify options for using a Continuous Underway Fish Egg Sampler (CUFES) to enhance the application of the Daily Egg Production Method (DEPM) in situations where targeted surveys are conducted from small research vessels (e.g. <25m) and the time spent at each sampling site is short (e.g. <10 min). To do this, we conducted experiments to: 1) determine the reliability of information obtained from onboard examination of CUFES samples; 2) assess the sampling efficiency of CUFES while on-site and underway and 3) measure the effectiveness of underway CUFES samples in predicting the presence/absence of sardine eggs in the following CalVET net sample. We also compared the accuracy, precision and costs of estimates of total daily egg production obtained using data obtained from CalVET net samples taken at 1) predetermined sites (low and high sampling intensities) and 2) CUFES-determined sites. The accuracy of onboard estimates of egg abundance appeared to be affected by sea conditions. The efficiency of CUFES as an underway sampler was also lower when sea conditions were rough. Data from laboratory analyses of underway CUFES samples were a good predictor of egg abundance in the following CalVET net sample. Estimates of total egg production using CalVET samples from CUFES-determined sites based on laboratory analyses of CUFES samples differed by less than 10% from those obtained from pre-determined sites. However, estimates based on onboard analyses of CUFES samples differed from those obtained from pre-determined sites by up to 50%. When the time spent taking each CalVET sample is low (e.g. less than 10 minutes), using data from CUFES to reduce the number of samples taken using CalVET nets is not the optimal use of this technology. This is mainly because of difficulties associated with sorting plankton samples at sea, but also because in situations where the time spent at each site is short, the small decreases in field (cruise duration) and laboratory (sorting) costs do not outweigh the reductions in the reliability of estimates of egg production. However, CUFES data does appear to provide a potentially important source of information to increase the reliability of estimates of total daily egg production. Numerical techniques (e.g. analogous to integrated fishery assessment models) need to be developed to integrate data obtained from CUFES and CalVET nets to provide more accurate and precise estimates of total daily egg production for DEPM studies.

Adjusting for bias due to variability of estimated recruitments in fishery assessment models

Integrated analysis models provide a tool to estimate fish abundance, recruitment, and fishing mortality from a wide variety of data. The flexibility of integrated analysis models allows them to be applied over extended time periods spanning historical decades with little information from which to estimate the annual signal of recruitment variability to modern periods in which more information about recruitment variability exists. Across this range of data availability, the estimation process must assure that the estimated log-normally distributed recruitments are mean unbiased to assure mean unbiased biomass estimates. Here we show how the estimation method implemented in the integrated analysis model, Stock Synthesis, achieves this unbiased characteristic in a penalized likelihood approach that is comparable to the results from Markov chain Monte Carlo. The total variability in recruitment is decomposed into variability among annual recruitment estimates based on information in the data and a residual variability. Because data are never perfectly informative, we show that estimated recruitment variability will always be less than the true variability among recruitments and that the method implemented here can be used to iteratively estimate the true variability among recruitments.

FATORES QUE AFETAM A SAZONALIDADE DA CPUE NA PESCARIA BRASILEIRA DO BONITO LISTRADO (KATSUWONUS PELAMIS) E IMPLICAÇÕES PARA A AVALIAÇÃO DA PESCARIA

In the Brazilian skipjack tuna (Katswonus pelamis) pole and line fishery, large seasonal oscillations of catch per unit of effort (CPUE) has been observed. As an index, CPUE should reflect variation in the coefficient of catchability (q) as well as in the abundance of the exploited populations. In opposition to the interannual variations, seasonal variations in the population abundance are unimportant in the conceptual framework of most fishery assessment models. Therefore, a plausible simplification would be assume the analysis of factors affecting seasonal oscillations of CPUE as equivalent to the analysis of the seasonal oscillations of the coefficient of catchability. In the Brazilian skipjack tuna fishery, recruitment, migration, oceanographic circulation, sighting of schools, variation in the food availability and variations in the number and dimension of the schools have been identified as the main factors affecting seasonal oscillations in q. The study of these oscillations is important in order to identify and understand also the interannual oscillations in q which may prevent the use of CPUE data in the fishery assessment. Problems of interannual oscillations in q are generally related to the choice of the unit of effort. In the case of the skipjack tuna fishery, the estimation of an index reflecting the search effort (e. g. swept area), seems to be essential for the establishment of a more suitable unit of effort to be used in its stock assessment.

MYCOBACTERIOSIS‐ASSOCIATED MORTALITY IN WILD STRIPED BASS (MORONE SAXATILIS) FROM CHESAPEAKE BAY, USA

The striped bass (Morone saxatilis) is an economically and ecologically important finfish species along the Atlantic seaboard of the United States. Recent stock assessments in Chesapeake Bay (U.S.A.) indicate that non-fishing mortality in striped bass has increased since 1999, concomitant with very high (>50%) prevalence of visceral and dermal disease caused by Mycobacterium spp. Current fishery assessment models do not differentiate between disease and other components of non-fishing mortality (e.g., senescence, predation); therefore, disease impact on the striped bass population has not been established. Specific measurement of mortality associated with mycobacteriosis in wild striped bass is complicated because the disease is chronic and mortality is cryptic. Epidemiological models have been developed to estimate disease-associated mortality from cross-sectional prevalence data and have recently been generalized to represent disease processes more realistically. Here, we used this generalized approach to demonstrate disease-associated mortality in striped bass from Chesapeake Bay. To our knowledge this is the first demonstration of cryptic mortality associated with a chronic infectious disease in a wild finfish. This finding has direct implications for management and stock assessment of striped bass, as it demonstrates population-level negative impacts of a chronic disease. Additionally, this research provides a framework by which disease-associated mortality may be specifically addressed within fisheries models for resource management.

Decadal changes in the North Sea food web between 1981 and 1991 — implications for fish stock assessment

The North Sea ecosystem of the early 1980s differed substantially from that of the early 1990s. The current North Sea multispecies fisheries assessment models are parameterized by fish diet data sets that reflect both ecosystem states, as the stomachs were sampled in 1981 and 1991. In this study, multispecies virtual population analysis (MSVPA) was parameterized with either diet data set, leading to different model food webs, each representing the predator's diet selection behavior and spatiotemporal overlap with their prey in the two respective ecosystem states. The impact of these changes in predator preferences and spatiotemporal overlap on recruitment success and on stock developments could be demonstrated by using either stomach data set to estimate historic and future spawning stock biomass and recruitment trajectories. The observed changes in the food web mainly impacted the hindcasted recruitment trajectories, whereas spawning stock biomass estimates were quite robust. In the prediction runs, the differences in the survival rate of the recruits decided whether fish stocks of commercially important species (e.g., Gadus morhua, Merlangius merlangus) would recover or collapse in the near future.

Signature of an early genetic bottleneck in a population of Moroccan sardines ( Sardina pilchardus)

Fishery assessment models meant to determine sustainability of commercial marine fish failed to predict recent stock collapses due to overexploitation. One flaw of assessment models is that they strongly rely on catch and age-composition statistics, but largely ignore the genetic background of the studied populations. We examined population genetic structure of sardine ( Sardina pilchardus) in the centraleastern and northeastern Atlantic Ocean and Mediterranean Sea to aid fishery management of this heavily fished small pelagic species. We found that sardine has a striking mitochondrial control region, and sequenced a fragment of 387 bp of its 5′-end in 261 individuals collected off the coasts of Morocco (Dakhla, Tantan, Safi, Larache, and Nador), Portugal (Quarteira), Spain (Pasajes, Barcelona), and Greece (Kavala). High levels of haplotypic diversity rendered a rather unresolved NJ phylogeny. The recovered tree had no phylogeographic structuring except for the clustering of 13 individuals of Safi. In contrast, individuals grouped together according to the presence or absence of a 13-bp insertion in the sequence. ϕ ST pairwise comparisons and molecular variance analyses supported genetic differentiation between the population of Pasajes (Bay of Biscay), and those of the Mediterranean Sea and Moroccan coast, with a contact zone around the Strait of Gibraltar. This result confirms the existence of two subspecies, S. pilchardus pilchardus and S. pilchardus sardina that were previously identified based on meristics and morphometry. Mismatch distribution analysis showed that sardine populations are expanding since the Pleistocene. Surprisingly, the population of Safi showed strong and statistically significant levels of genetic differentiation that could be related with isolation and genetic drift. Comparative analysis of the Safi population versus the rest including mismatch distributions, and a Bayesian skyline plot suggest that the Safi population likely underwent an early genetic bottleneck. The genetic singularity of the Safi population could have been responsible for the historical collapse of this sardine stock in the 1970s.

A Bayesian Approach to Stock Assessment and Harvest Decisions Using the Sampling/Importance Resampling Algorithm

Scientific advice to fishery managers needs to be expressed in probabilistic terms to convey uncertainty about the consequences of alternative harvesting policies (policy performance indices). In most Bayesian approaches to such advice, relatively few of the model parameters used can be treated as uncertain, and deterministic assumptions about population dynamics are required; this can bias the degree of certainty and estimates of policy performance indices. We reformulate a Bayesian approach that uses the sampling/importance resampling algorithm to improve estimates of policy performance indices; it extends the number of parameters that can be treated as uncertain, does not require deterministic assumptions about population dynamics, and can use any of the types of fishery assessment models and data. Application of the approach to New Zealand's western stock of hoki (Macruronus novaezelandiae) shows that the use of Bayesian prior information for parameters such as the constant of proportionality for acoustic survey abundance indices can enhance management advice by reducing uncertainty in current stock size estimates; it also suggests that assuming historic recruitment is deterministic can create large negative biases (e.g., 26%) in estimates of biological and economic risks of alternative harvesting policies and that a stochastic recruitment assumption can be more appropriate.

Estimating the Intermolt Periods in Asynchronously Molting Crustacean Populations

SUMMARY In some crustacean populations, including many tropical lobsters and crabs, molting occurs asynchronously throughout the year. That is, at any time of year, the animals are uniformly distributed throughout the intermolt cycle. We present methods for finding maximum likelihood estimates of the size-specific intermolt period for this situation when mark-recapture data are available consisting of initial size, time at liberty, and whether the animal molted while at liberty. Alternatively, the intermolt period can be determined by the same estimation procedure when wild animals are brought into captivity and observations are made on which animals molt within some fixed time period or before a fixed date. The method is applied to data on spiny lobster (Panulirus argus) to estimate intermolt period as an exponential function of length. Crustacean growth is a discontinuous process that is often described in terms of two components: the change in size at molt and the duration of the intermolt period (Botsford, 1985). Information on these processes is used to construct a model of growth in size over time for use in fishery assessment models. Both growth components vary with the size of the animal. These can be studied by observing animals held in captivity though the results may not be representative of growth in wild populations. An alternative is to estimate the components of growth from mark-recapture data. In this paper, we focus on the problem of estimating the intermolt period under the assumption that the individuals in a population at any time are uniformly distributed throughout their intermolt period. We use the method of maximum likelihood to derive a procedure for estimating the intermolt periods of tropical and subtropical decapods from mark-recapture data when seasonal changes in growth are negligible. The procedures can also be used to analyze laboratory data on the proportion of animals molting when animals are held for periods of time sufficiently short to minimize the effects of captivity. In Section 2, we consider mark-recapture studies and develop the estimators for intermolt period as a function of body size and other covariates. The growth of spiny lobsters

Mixed-Species Yield-per-Recruitment Analyses Accounting for Technological Interactions

Multipecies fishery assessment models may be divided into two general categories: those involving analyses of the trophic interdependence of species (biological interactions) and those addressing the question of co-occurrence in fishing gear (technological interactions). Certainly, both categories of interactions may occur simultaneously. Nevertheless, the latter class of models is probably adequate if major species of interest exhibit a high degree of mutually exclusive food resource partitioning, and interspecific competition for food is low. In this study, multispecies analogs of the Thompson–Bell yield-per-recruit model are developed for alternative situations in which species groups (assemblages) are exploited solely by one fishery, and when several fisheries (defined by gear type, seasonal changes in species mix, etc), exploit the same species concurrently and/or sequentially. Species included in the analyses are assumed to have negligible trophic dependence. Equilibrium fishery yields (in aggregate and for individual species) are computed as functions of standardized effort levels and retention characteristics of gear (e.g. mesh size). The multiple fishery model allows for variable harvest strategies with respect to gear selectivity and effort levels among component fisheries. Simultation output includes total and individual equilibrium species yields, exploitation rates, and mean fish weights in the catch for all fisheries combined, and each separately. Applications of the models are illustrated for mixed-species otter trawl fisheries exploiting primarily Atlantic cod, Gadus morhua, haddock, Melanogrammus aeglefinus, yellowtail flounder, Limanda ferruginea, and winter flounder, Pseudopleuronectes americanus, in the Georges Bank region off the northeastern United States. Results emphasize the potential for growth underfishing or overfishing of individual species/stocks when total system yield is the optimization criterion.