Fisheries Management Advice Research Articles

Bycatch estimation of Rajiformes in multispecies and multigear fisheries

To assess the exploitation status of marine resources and to formulate scientific advice for fisheries management, reliable fishery data are required. When dealing with data-poor stocks, like skates and rays (Rajiformes) caught by multispecies and multigear fisheries in Portugal, strategies need to be defined to surpass data limitations, like species misidentification and the lack of fishing gear information in landings data. This paper presents a stepwise statistical procedure, involving factor analysis for mixed data and flexible discriminant analysis, to estimate the total number of trips and the correspondent total landed weight by species. Interviews and self-sampling that took place under a pilot study (2011 – 2013) focused on skate and ray fisheries showed that collaborative research is a low cost and valuable tool to improve our knowledge on fisheries and their catches and may contribute to increase the accuracy. Given the persistence of species misidentification errors in the official statistics, the procedure here presented is currently used to report the Portuguese annual estimates of species-specific landed weight. This procedure may be considered to be applied to data deficient fishery bycatch resources for which dedicated sampling programs are not priority.

Adapting to climate‐driven distribution shifts using model‐based indices and age composition from multiple surveys in the walleye pollock (Gadus chalcogrammus) stock assessment

AbstractThe northern Bering Sea is transitioning from an Arctic to subarctic fish community as climate warms. Scientists and managers aim to understand how these changing conditions are influencing fish biomass and spatial distribution in this region, as both are used to inform stock assessments and fisheries management advice. Here, we use a spatio‐temporal model for walleye pollock (Gadus chalcogrammus) to provide two inputs to its stock assessment model: (a) an alternative model‐based biomass index and (b) alternative model‐based age compositions. Both inputs were derived from multiple fishery‐independent data that span different regions of space and time. We developed an assessment model that utilizes both the standard and model‐based inputs from multiple surveys despite inconsistencies in spatial and temporal coverage, and we found that using these data provide an improved spatial and temporal scope of total pollock biomass. Age composition information indicated that pollock density is increasing and moving farther north, particularly for older pollock. We found that including an index of cold pool extent could be used to extrapolate pollock densities in the northern Bering Sea in unsampled years. Stock assessment parameter estimates were similar for standard and model‐based input. This study demonstrates that spatio‐temporal model‐based estimates of a biomass index and age composition can facilitate rapid changes in stock assessment structure in response to climate‐driven shifts in spatial distribution. We conclude that assimilating data from regions neighboring standard survey areas, such as the Chukchi Sea and western Bering Sea, would improve understanding and management efforts as fish distributions change under a warming climate.

Abundance and spatial distribution of brown crab (Cancer pagurus) from fishery-independent dredge and trawl surveys in the North Sea

Abstract Brown crab (Cancer pagurus) is a widely distributed crustacean that occurs around the British coastline supporting important commercial fisheries. The habitat preferences of brown crab around Scotland are poorly documented and for the purposes of stock assessment, the species is considered data-poor. Based on an analysis of dredge and trawl surveys taking place in the North Sea (2008–2018), we describe the spatial distribution of brown crab and for the first time, develop abundance and recruitment indices for the species. We make use of geostatistical methods and apply generalized additive models to model catch rates in relation to a number of explanatory variables (depth, distance to the coast, sediment type and year). The dredge and trawl abundance indices were correlated showing a similar trend of increasing catch rates in the early years of the time series up to 2016 and a subsequent reduction. The recruitment index showed a gradual increase in captured juvenile crabs up to 2014 followed by a steep decrease with 2018 being the lowest value estimated. The derivation of robust indicators of stock abundance will contribute to the stock assessment of this species and enable the provision of improved fisheries management advice for brown crab around Scotland.

Estimating the biomass of a mixed species complex using hydroacoustics and catch data from the Bay of Fundy and Scotian Shelf summer ecosystem survey

An acoustic-based index of biomass was developed due to concerns that the existing bottom-trawl index for western component pollock (Pollachius virens) was inaccurate and imprecise. Acoustic data were recorded during annual summer ecosystem surveys. Pollock and other common groundfish could not be readily identified from echo-traces within echograms. Survey catch data were analyzed concurrently with acoustic data to estimate biomass from echo-integrals contributed by the six most commonly caught fish species: pollock, Atlantic cod (Gadus morhua), haddock (Melanogrammus aeglefinus), redfish (Sebastes fasciatus), Atlantic herring (Clupea harengus), and spiny dogfish (Squalus acanthias). A cluster analyses that used a Bayesian conditional probability classified homogeneous regions based on species composition. Species composition, nautical area scatter coefficient, and backscattering cross-section of fishes for regions were used to calculate the biomass of fishes. Acoustic indices were considered as appropriate as bottom-trawl indices for fisheries management advice because the bias and variance were similar between the indices when analyzed using repeated K-fold cross-validation.

Checking the pulse of the major commercial fisheries of lake Victoria Kenya, for sustainable management

AbstractThe present study demonstrates the declining state of the major commercial fisheries of Lake Victoria, Kenya, a situation threatening sustainability of the lake's fishery. Data in the present study were derived from resource monitoring programmes that included hydro‐acoustics (2009–2018), trawl net fishing (2011–2018), frame surveys (2000–2016) and catch assessment surveys (2000–2015). The activities provided information on fish stocks and supported advice for fisheries management. The average fish stock densities for Tanzania, Uganda and Kenya of 8.92, 8.25 and 8.19 t/km2, respectively, were relatively similar. Diplomatic and sustainable efforts for harmony in fish harvesting among the fishers of the riparian countries are encouraged given the interdependence of the lake. The Kenyan and River Kagera regions had a higher proportion (≈ 4% each) of big‐sized Nile perch (≥50 cm total length) in 2018, signifying the critical breeding areas for Nile perch. To sustain the fishery, there is need to enforce a 36%–44% effort reduction for all the major fisheries, and enforcement of gear limits to avoid harvesting of immature fish and destruction of the lake ecosystem.

Comparing spatial distribution modelling of fisheries data with single-area or spatially-explicit integrated population models, a case study of toothfish in the Ross Sea region

Most models used for assessing the status of fish stocks and providing quantitative advice for fisheries management are not spatially explicit despite the well-known spatial heterogeneity of fish populations. Statistical spatial distribution modelling, which can derive spatially-resolved biomass from catch rates, is a method increasingly used to infer trends in population biomass, particularly where integrated population models are not available. Although the spatial distribution modelling tool VAST was developed to analyze survey data, such methods have also been used with fisheries-dependent catch and effort data, particularly when survey data are not available. We developed a statistical spatial distribution model for Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea region of the Southern Ocean using the VAST (Vector Autoregressive Spatio-Temporal model) approach. We based the VAST model on catch-rate (catch per unit effort) data from the long-line fishery and compared the biomass time series obtained to that of existing single-area and spatially-explicit integrated population models which have also been developed for this population. The time series obtained from the statistical spatial distribution modelling approach was highly variable between years, inconsistent with constraints imposed on population dynamics by biological parameters, and substantially different from biomass trends obtained from the integrated models. Although it has been used successfully in other analyses, in this instance, the spatial distribution modelling could not overcome fine-scale spatial and vessel-based variability in fishery catch rates to estimate the underlying abundance of toothfish at the scale of the Ross Sea region measurable with the more-informed integrated models.

Time-variant productivity in biomass dynamic models on seasonal and long-term scales

Abstract The productivity of fish populations varies naturally over time, dependent on integrated effects of abundance, ecological factors, and environmental conditions. These changes can be expressed as gradual or abrupt shifts in productivity as well as fluctuations on any time scale from seasonal oscillations to long-term changes. This study considers three extensions to biomass dynamic models that accommodate time-variant productivity in fish populations. Simulation results reveal that neglecting seasonal changes in productivity can bias derived stock sustainability reference levels and, thus, fisheries management advice. Results highlight the importance of biannual biomass indices and their timing relative to the peaks of the seasonal processes (i.e. recruitment, growth, mortality) for the estimation of seasonally time-variant productivity. The application to real-world data of the eastern Baltic cod (Gadus morhua) stock shows that the model is able to disentangle differences in seasonal fishing mortality as well as seasonal and long-term changes in productivity. The combined model with long-term and seasonally varying productivity performs significantly better than models that neglect time-variant productivity. The model extensions proposed here allow to account for time-variant productivity of fish populations leading to increased reliability of derived reference levels.

Lessons learned from data-limited evaluations of data-rich reef fish species in the Gulf of Mexico: implications for providing fisheries management advice for data-poor stocks

Specifying annual catch limits for artisanal fisheries, low economic value stocks, or bycatch species is problematic due to data limitations. Many empirical management procedures (MPs) have been developed that provide catch advice based on achieving a stable catch or a historical target (i.e., instead of maximum sustainable yield). However, a thorough comparison of derived yield streams between empirical MPs and stock assessment models has not been explored. We first evaluate trade-offs in conservation and yield metrics for data-limited approaches through management strategy evaluation (MSE) of seven data-rich reef fish species in the Gulf of Mexico. We then apply data-limited approaches for each species and compare how catch advice differs from current age-based assessment models. MSEs identified empirical MPs (e.g., using relative abundance) as a compromise between data requirements and the ability to consistently achieve management objectives (e.g., prevent overfishing). Catch advice differed greatly among data-limited approaches and current assessments, likely due to data inputs and assumptions. Adaptive MPs become clearly viable options that can achieve management objectives while incorporating auxiliary data beyond catch-only approaches.

Overcoming challenges of harvest quota allocation in spatially structured populations

Ignoring spatial population structure in the development of fisheries management advice can affect population resilience and yield. However, the resources required to develop spatial stock assessment models that match the spatial scale of management are often unavailable. As a result, quota recommendations from spatially aggregated assessment models are commonly divided among management areas based on empirical methods. We developed a spatially explicit simulation model to 1) explore how variation in population structure influences the spatial distribution of harvest that produces maximum system yield, and 2) contrast the performance of empirical quota allocation methods in approximating ideal spatial harvest strategies. Spatial scenarios that included post-recruitment movement resulted in a broader range of spatial management options (e.g., setting regional total allowable catch) that achieved near maximum system yield compared to scenarios without movement. Stochastic projections showed that using the proportion of total survey biomass in each management area to spatially allocate quota performed best for maximizing system yield when the true spatial structure was unknown, considerably outperforming equal allocation and allocation based on a recruitment index. However, with all methods, area-specific harvest rates sometimes led to unintended depletion within management units. Improved data and understanding of spatial stock dynamics can reduce the need for ad hoc approaches for spatial harvest allocation, allow for a greater range of management options, and increase the efficacy of spatial management procedures.

Ecosystem-based reference points under varying plankton productivity states and fisheries management strategies

Abstract In the context of ecosystem-based fisheries management, which should consider changing and uncertain environmental conditions, the development of ecosystem-based biological reference points (EBRPs) to account for important multi-species (MS) interactions, fishery operations, and climate change, is of paramount importance for sustainable fisheries management. However, EBRPs under varying plankton productivity states and fisheries management strategies are seldom developed, and the ecosystem effects of these changes are still largely unknown. In this study, ecosystem-based FMSY (fishing mortality rate at MSY) values were estimated within an end-to-end ecosystem model (OSMOSE) for three focused fish species (Pacific Herring, Clupea pallasii; Pacific Cod, Gadus macrocephalus; Lingcod, Ophiodon elongatus) under three plankton productivity states of differing plankton biomass at high, current, and low levels. In addition, ecosystem effects were compared across different plankton productivity and fisheries management strategies with the latter consisting of two fishery scenarios (i.e. single-species-focused (SS) and MS-focused), various fishing mortality rates, and two harvest policies (with and without harvest control rules, HCRs). Main findings of this study include: (i) plankton productivity change affected the values of ecosystem-based FMSY, which increased as plankton productivity states changed from low to high plankton biomass; (ii) ecosystem-based FMSY for Pacific Herring and Pacific Cod stocks increased when fishery scenarios shifted from SS-focused to MS-focused; (iii) fisheries management incorporating HCR yielded more stable system catch and system biomass; and (iv) high plankton biomass combined with fisheries management using HCR could maintain stable ecosystem production and sustainable fisheries. Based on our findings, we highlight possible adaptive fisheries management strategies in the face of future climate and ocean changes. Overall, EBRPs complement SS stock assessments by incorporating key ecological processes and ecosystem properties, thus providing supporting evidence for better incorporation of ecosystem considerations into scientific advice for sustainable fisheries management.

Improving the interpretation of fishing effort and pressures in mixed fisheries using spatial overlap metrics

Managing mixed fisheries requires understanding fishers’ behaviour to allow predicting future fisheries distribution and impact on marine ecosystems. A new approach was developed to compare fine-scale fishing effort distribution of Eastern English Channel (EEC) bottom trawlers to the monthly and spatially resolved abundance distributions of commercial species. First, the added value of using species-specific spatial overlap metric to quantify effective fishing effort and improve the relationship between fishing effort and fishing mortality was assessed. Second, based on the Ideal Free Distribution (IFD) theory, the species-specific weights given by fishers to different species were estimated by maximizing the overlap between target species assemblage and effort distributions in October. At a seasonal scale, our results emphasized the importance of cuttlefish (Sepia officinalis) and red mullet (Mullus surmuletus) for the global distribution of EEC bottom trawlers. In October, cuttlefish and red mullet were clearly more determining fishers’ location choice than historically harvested species and also than the overall expected revenue. This is likely due to external constraints such as low cod (Gadus morhua) quota, causing IFD assumptions violated. This study evidenced the importance of getting good insights into spatiotemporal distributions of stocks and fleets to understand fishers’ behaviour and improve mixed fisheries management advice.

Model uncertainty and simulated multispecies fisheries management advice in the Baltic Sea.

Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. Thus, we suggest that disagreements among the ecosystem models will not impede their use for providing strategic advice on how to reach management objectives that go beyond the traditional maximum yield targets and for informing on the potential consequences of pursuing such objectives. This is especially true for scenarios aiming at exploiting forage fish sprat and herring, for which the agreement was the largest among our models. However, the quantitative response to altering fishing pressure differed among models. This was due to the diverse environmental covariates and the different number of trophic relationships and their functional forms considered in the models. This suggests that ecosystem models can be used to provide quantitative advice only after more targeted research is conducted to gain a deeper understanding into the relationship between trophic links and fish population dynamics in the Baltic Sea.

Response of Scotian Shelf silver hake (Merluccius bilinearis) to environmental variability

AbstractCommercially‐exploited fish populations are not only shaped by fishing pressure, but also by the dynamics of their environment. By quantifying the influence of environmental variability, fisheries management advice can be improved and uncertainties reduced. To this end, we developed statistical models of the response of Scotian Shelf silver hake stock metrics to variability in zooplankton community composition and phenology over the past 18 years and in the physical environment since 1985. Dominant modes of variability in these pelagic habitat indicators were characterized using principal component analysis, and the relationships of silver hake condition, abundance, and recruitment to pelagic habitat variability were assessed using generalized additive models. Condition was largely modulated by the onset and duration of the spring bloom, which controls food availability. In contrast, adult abundance was governed by composition of the zooplankton community and bottom‐water temperature, which dictates the distribution of silver hake. Finally, recruitment was affected by both thermal conditions and food availability. Our results presented here form the basis for qualitative assessment of ecosystem attributes and the influence on silver hake stock productivity.

Working Towards a Framework for Stock Evaluations in Data‐Limited Fisheries

AbstractData‐limited approaches to managing fisheries are widespread in regions where insufficient data prevent traditional stock assessments from determining stock status with sufficient certainty to be useful for management. Where severe data limitations persist, a catch‐only approach is commonly employed, such as in the U.S. Caribbean region. This approach, however, has not received the level of scrutiny required to determine the potential long‐term risks (e.g., probability of overfishing) to fish stocks. In this study, we present a framework for comparison and implementation of data‐limited methods, including the static Status Quo approach, which uses average catch landings. Candidate species for stock evaluation were identified through a data triage and included Yellowtail Snapper Ocyurus chrysurus (Puerto Rico), Queen Triggerfish Balistes vetula (St. Thomas and St. John), and Stoplight Parrotfish Sparisoma viride (St. Croix). Feasible data‐limited methods, based on data availability and quality, included empirical indicator approaches using relative abundance (i.e., catch per unit effort) or mean length. Results from the management strategy evaluation support the use of adaptive data‐limited methods, which incorporate feedback in contrast to the static Status Quo approach. The proposed framework can help guide the development of catch advice for dynamic fisheries management in data‐limited regions.

Unravelling the scientific potential of high resolution fishery data

Fisheries science and fisheries management advice rely on both scientific and commercial data to estimate the distribution and abundance of marine species. These two data types differ, with scientific data having a broader geographical coverage but less intensity and time coverage compared to commercial data. Here we present a new type of commercial data with high resolution and coverage. To our knowledge, the dataset presented in this study has never been used for scientific purposes. While commercial datasets usually include the total weight by species on per haul basis, the new data also include the commercial size class for the species landed, recorded directly on a haul-by-haul basis. Thus, this dataset has the potential to provide knowledge on landed fish with as high spatio-temporal resolution as when coupling logbooks and sales slips but with the addition of detailed knowledge on the size distribution. Such information may otherwise be obtained through on-board observer programmes but unlike the observers’ data, the dataset presented here is routinely collected on most of the trips of the vessels involved, which means that the coverage of the data for the individual vessel is larger than observers’ data. Furthermore, the risk of changes in fishing behaviour due to the presence of an observer on-board is avoided. This paper describes the coverage and completeness of the dataset, and explores the reliability of the data available. We conclude that the main limitation is the small number of fishing vessels covered by the program, but that the data from those vessels are accurate, detailed, and relatively reliable.

Understanding biology to improve advice for fisheries management

Understanding biology to improve advice for fisheries management

Landscape effects on demersal fish revealed by field observations and predictive seabed modelling.

Nature conservation and fisheries management often focus on particular seabed features that are considered vulnerable or important to commercial species. As a result, individual seabed types are protected in isolation, without any understanding of what effect the mixture of seabed types within the landscape has on ecosystem functions. Here we undertook predictive seabed modelling within a coastal marine protected area using observations from underwater stereo-video camera deployments and environmental information (depth, wave fetch, maximum tidal speeds, distance from coast and underlying geology). The effect of the predicted substratum type, extent and heterogeneity or the diversity of substrata, within a radius of 1500 m around each camera deployment of juvenile gadoid relative abundance was analysed. The predicted substratum model performed well with wave fetch and depth being the most influential predictor variables. Gadus morhua (Atlantic cod) were associated with relatively more rugose substrata (Algal-gravel-pebble and seagrass) and heterogeneous landscapes, than Melanogrammus aeglefinus (haddock) or Merlangius merlangus (whiting) (sand and mud). An increase in M. merlangus relative abundance was observed with increasing substratum extent. These results reveal that landscape effects should be considered when protecting the seabed for fish and not just individual seabed types. The landscape approach used in this study therefore has important implications for marine protected area, fisheries management and monitoring advice concerning demersal fish populations.

On the importance of clarity in scientific advice for fisheries management

Fisheries management is a difficult process that requires policymakers and scientists to work in concert with one another to set quotas or other management actions that conserve fisheries resources for long-term use. Policymakers take such actions based on advice from their scientists, who serve as independent knowledge providers. There are many examples, however, of policymakers allowing short-term financial or political objectives to drive their decision making rather than strictly adhering to the advice of their scientists. Throughout the histories of the International Commission for Conservation of Atlantic Tunas and the Western and Central Pacific Fisheries Commission, policymakers have followed the advice of their scientists only 39% and 17% of the time, respectively. There are also a number of cases where a lack of clarity in the scientific advice leads to undesirable management actions, either a result of simple misinterpretation by policymakers or imprecision in the advice allowing for a range of actions not intended by the scientists. To improve the likelihood that managers and scientists interpret language in the same way, it is important that scientists provide advice that is explicit and precise and clearly states the appropriate management measures to be applied. Here, a set of guidelines that may help scientists to achieve the necessary clarity is presented. Following these steps would allow scientists to clearly describe stock assessment results and other complex scientific processes and provide their expert advice in a manner that is most useful for policymakers but without sacrificing their reputation of independent knowledge provision.

Space oddity: The mission for spatial integration

Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability and, ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.

From single species surveys towards monitoring of the Barents Sea ecosystem

The Barents Sea, a large, high-latitude shelf sea, has been monitored and investigated for more than a century. More than 1800 occasional expeditions have been organized both by Norway and Russia, and since the1960s the collaboration between the Institute of Marine Research (IMR, Bergen) and the Knipovich Polar Research Institute of Marine Fisheries and Oceanography (PINRO, Murmansk) has been strengthened by developing and carrying out joint surveys. Monitoring changes in the Barents Sea fish stocks and collecting information needed for stock assessments and advice for fisheries management were the driving forces behind the increased effort spent on marine research. This triggered the development of sampling and observation methodology, the design of scientific research vessels for using various equipment and gear, and the development of new technologies for processing several types of samples. Increased data collection generated a need for the development of complex database systems and software that, could analyze larger data sets. Joint large-scale monitoring over the last 50years, together with joint management of living marine resources during the last 20years, resulted in high stock biomasses of commercially important fish stocks and thus the successful development of fisheries in the Barents Sea. Here, we describe the development of Barents Sea monitoring from single species (or fishery) surveys that were focused on target species/groups to integrated ecosystem surveys that aim to describe the status and main changes in the Barents Sea ecosystem.