Single-species Stock Assessments Research Articles

Integrating the US Caribbean Reef Fish Visual Census into fishery stock assessments

The United States Caribbean Reef Fish Visual Census (RVC) is a fishery-independent survey of the coral reef fish community, comprised of hundreds of species, designed to provide quantitative information for data-poor fisheries to support regional stock assessments. The Caribbean RVC, implemented in 2014 as part of the National Coral Reef Monitoring Program (NCRMP), uses a probabilistic stratified random sampling design capitalizing on the strong mean-variance relationship of population abundance dependent on hardbottom habitats and depths. Here we highlight RVC data for queen triggerfish in Puerto Rico, where survey precision improved from CVs of 20.6% in 2014 to 12.6% in 2021, which produced accurate and cost-effective estimates of key assessment metrics like size- structured relative population abundance and biomass. We estimated a relatively stable exploited-phase average population abundance for 2014–2021 at 2.3 million queen triggerfish with a biomass of 1246 metric tons. To support stock assessments using "statistical catch at age" models, we generated a 2001–2021 time series of several population metrics by a statistical conversion of spatially-restricted, pre- NCRMP data to the RVC frame. To cross-check assessment modeling, we combined 2014–2021 RVC results with life history demographics in an alternative length-based risk analysis (LBRA) model to evaluate stock sustainability consequences using two lifetime growth scenarios. LBRA models indicated low overfishing risks. We concluded that only a few quality fishery-independent surveys are needed to obtain understanding of stock sustainability status, and that RVC not only provides reliable data for single-species stock assessments, but also for design evaluation of marine protected areas and ecosystem-based fishery management.

Correlations in recruitment patterns of Atlantic reef fishes off the southeastern United States based on multi-decadal estimates from stock assessments

Atlantic reef fishes off the southeastern United States support a multispecies fishery important to both commercial and recreational fleets. Productivity of this reef-fish complex is driven to a large degree by recruitment of new individuals into their respective populations. In this study, we analyzed patterns in time series of annual recruitment of ten Atlantic reef-fish species, primarily snappers and groupers, that have been the subject of separate single-species stock assessments. Our focus was on identifying patterns in autocorrelation of recruitment within species and on uncovering patterns in correlation across species. We found that autocorrelation of recruitment deviations was evident in the majority (9/10) of species with a dominant lag of one year. Pairwise correlations between species were both positive and negative. Principal component analysis revealed two general groups of species: those that exhibited lower-than-expected recruitment in recent years and those that did not exhibit such low recruitment (either near expected or higher-than-expected). These results point toward common drivers of recruitment (e.g., environmental, ecological, exploitation) in this complex of reef-associated fishes, and they are a critical first step for developing hypotheses of underlying mechanisms. Additionally, they have practical importance for stock assessments that forecast recruitment when forming fishery management advice.

Canada's forage fish: an important but poorly understood component of marine ecosystems

Forage fish form a critical trophic link in marine ecosystems, and yet, for many species, there is limited information available. As nations move from single species stock assessments to ecosystem approaches to fisheries management (EAFMs), more information on forage fish will be required. In this study, 50 years of scientific literature were systematically mapped for 11 forage fish species in Canada's Arctic, Atlantic, and Pacific oceans. The objectives were to identify (1) knowledge clusters and gaps and (2) the pressures studied in relation to forage fish outcomes. Of the 2897 articles mapped, the majority studied adults and the distribution, productivity, growth, and life history of commercially fished species. Knowledge gaps were identified for forage fish: (1) that were noncommercially exploited; (2) egg and larval life history stages of most species and juveniles of noncommercial species; (3) diets of most species; (4) migration and performance for all species and survival of noncommercial species; and (5) the effects of some pressures (e.g., large-scale climate pressures). Addressing these knowledge gaps would improve the application of EAFMs.

Time-varying predation as a modifier of constant natural mortality for Gulf of Alaska walleye pollock

Although highly variable in time and space, predation remains the greatest source of mortality for juvenile and lower trophic-level fishes. As such, predation can have substantial and long-term effects on the dynamics of these prey. Gulf of Alaska walleye pollock (Gadus chalcogrammus) has shown considerable variability in biomass over the past four decades. During this same time, the demersal fish community transitioned from being dominated by pollock to a system comprised primarily of upper trophic-level predators. We estimated time-varying predation mortality to better understand its effects on the population dynamics of pollock in this currently “top heavy” system. Our index of predation accounted for spatiotemporal variation in predator biomass, bioenergetics-based rations, and age-specific proportions of pollock consumed (1990–2019). To evaluate population-level impacts of predation, we included an index of removals as part of the stock assessment model. This formulation allowed for non-annual data inputs and included a proportionality constant with which to scale predation. Age-specific natural mortality was allowed to vary according to a penalized random walk. We found that natural mortality ranged from 37% higher to 17% lower than the long-term mean. Resulting estimates of total pollock biomass differed by as much as 37% relative to a model without time-varying natural mortality, though the maximum difference for exploitable biomass was only 14%. Using an empirically-derived predation index to modify constant natural mortality allows stock assessment scientists to evaluate impacts of time-varying predation on assessed species. This approach provides a relatively simple way of incorporating ecological information into single-species stock assessments and may reduce bias compared to conventional models that do not account for changes in predation mortality. Notably, including predation mortality in single-species assessments may help identify inconsistencies in biomass estimates that warrant further consideration.

Synthesizing integrated ecosystem research to create informed stock-specific indicators for next generation stock assessments

Over the past two decades, numerous ecosystem surveys and process studies have emerged to monitor and assess the large marine ecosystems of Alaska. Several regional collaborative integrated ecosystem research projects (IERPs) were conducted to gain understanding of fish population fluctuations in relation to the surrounding environment. The Gulf of Alaska (GOA) IERP is one example of such an effort. Products of this program include a suite of in situ observations from fully integrated ecosystem surveys, laboratory experiments of physical thresholds for fish condition, and high-resolution oceanographic, planktonic, and habitat distribution models. When coupled, the synthesis products of this program can be utilized to understand system connectivity and highlight the primary ecosystem drivers of the GOA. Much of this information was included in annual GOA ecosystem status reports through individual indicator contributions. However, assimilation of these data into single-species stock assessments has remained limited. We provide a clear and direct avenue for including the products of these IERPs through the new ecosystem and socioeconomic profile (ESP) framework that identifies mechanistic relationships and tests ecosystem linkages within the stock assessment process. We present a case study using a data synthesis of the five commercially and ecologically valuable focal species of the GOAIERP (sablefish, pollock, Pacific cod, arrowtooth flounder, and Pacific ocean perch). Information was organized along the categories of distribution, phenology, and condition by life history stage to develop life history narratives for each species. These narratives identified critical ecosystem processes that could impact survival of each species. We then used habitat distribution models, seasonal phenology, and energy allocation strategies to sequentially reduce two gridded temperature datasets to reflect the life experience of the stock. This method essentially aligns ecosystem information at a spatial and temporal scale relevant to a stock and creates informed indicators that could then be related to a stock assessment parameter of interest, such as recruitment. Informed temperature indicators differed in magnitude and variability when compared to non-informed indicators and demonstrating species and stage-specific thermal preferences. The difference between the informed indicators and the non-informed indicators can also highlight thresholds and trends in habitat preference that could be further investigated with targeted process studies or laboratory experiments. The coordinated nature of the IERP allowed for the creation of these informed indicators that would not be possible with the results of any one process study. Both the stock-specific narratives and the informed indicators can be included into the ESPs for further monitoring and development. This integration ensures that the identified ecosystem linkages are evaluated concurrently with the stock assessment and ultimately transferred to fishery managers in an efficient and effective format for informing management decisions.

Evaluating the risks of red tide mortality misspecification when modeling stock dynamics

Extensions of single-species stock assessments to include ecosystem considerations are one step towards achieving an ecosystem approach to fisheries management. While red tide mortality has been estimated within base assessment models for both gag grouper and red grouper in the Gulf of Mexico since the late 2000 s, considerable uncertainty remains regarding how best to incorporate this source of mortality in stock assessment and the potential risks of misspecifying its timing and its effect across age-classes. We conduct simulation testing of an approach to estimating red tide mortality, which treats red tide as a bycatch fleet where all encountered fish are discarded dead. Accounting for episodic natural mortality events by correctly specifying the years in which these events occurred was the most unbiased and precise approach for estimating population quantities, although the estimated red tide mortalities were highly variable in magnitude. While not estimating red tide mortality provided reasonably unbiased estimates of terminal biomass and fishing mortality rate, which are used to determine stock status, caution must be exercised when red tide events occur in the terminal year(s), as ignoring episodic mortality can lead to these events being misinterpreted in model fitting and inflating estimates of fishing mortality (and potentially overfishing status). Our simulations highlight the importance of continued data collection on how red tides affect marine resources, and continued community and stakeholder engagements to gain an understanding of the historical timing and impact of red tide events.

Distinguishing species-specific targeting practices within the main Hawaiian islands Deep 7 bottomfish fishery

The main Hawaiian islands Deep 7 bottomfish fishery is a multispecies fishery that uses hook-and-line gear to catch seven primary species and is currently managed and assessed as a single population. Management plans support, and recent assessment reviews recommend, assessing species on an individual basis. When fisheries catch multiple species, but information about abundance is desired for a single species, it is important to use data subsets that reliably inform abundance trends for that individual species. We use a previously unanalyzed dataset collected from a subset of Deep 7 bottomfish fishermen who reported targeting practices –including the species or group of species targeted, fishing practices, catches, and environmental variables– while fishing in the summer of 2016. Using three statistical classification methods, we show that targeting occurs, and is primarily for two groups: opakapaka (Pristipomoides filamentosus), and a combined group of ehu (Etelis carbunculus) and onaga (Etelis coruscans). Depth was a significant explanatory variable for targeting, statistically distinguishing shallower opakapaka targeting from deeper ehu/onaga targeting at 188 m. In the absence of information about depth, catch composition data can be used to distinguish between opakapaka and ehu/onaga groups nearly as well as when depth is included. Applying these methods to the full fisher reporting database revealed that an opakapaka group and an ehu/onaga group could be distinguished. Further information on targeting within the fisher reported data, or consistent information on depth if targeting preferences cannot be reported, would improve classification. Ultimately, any of the methods used herein can be applied to filter fishing events based on predicted targeting to produce more representative indices of abundance for use in single-species stock assessments.

It’s Not the Destination, It’s the Journey: Multispecies Model Ensembles for Ecosystem Approaches to Fisheries Management

As ecosystem-based fisheries management becomes more ingrained into the way fisheries agencies do business, a need for ecosystem and multispecies models arises. Yet ecosystems are complex, and model uncertainty can be large. Model ensembles have historically been used in other disciplines to address model uncertainty. To understand the benefits and limitations of multispecies model ensembles (MMEs), cases where they have been used in the United States to address fisheries management issues are reviewed. The cases include: (1) development of ecological reference points for Atlantic Menhaden, (2) the creation of time series to relate harmful algal blooms to grouper mortality in the Gulf of Mexico, and (3) fostering understanding of the role of forage fish in the California Current. Each case study briefly reviews the management issue, the models used and model synthesis approach taken, and the outcomes and lessons learned from the application of MMEs. Major conclusions drawn from these studies highlight how the act of developing an ensemble model suite can improve the credibility of multispecies models, how qualitative synthesis of projections can advance system understanding and build confidence in the absence of quantitative treatments, and how involving a diverse set of stakeholders early is useful for ensuring the utility of the models and ensemble. Procedures for review and uptake of information from single-species stock assessment models are well established, but the absence of well-defined procedures for MMEs in many fishery management decision-making bodies poses a major obstacle. The benefits and issues identified here should help accelerate the design, implementation, and utility of MMEs in applied fisheries contexts.

Morphometric relationships and non-parametric, length–frequency-based growth parameters and natural mortality for common marine forage fish in Florida waters (USA)

Life-history parameters are necessary in population and ecosystem analyses. But they are not always available, especially for species that, justifiably or not, are of low priority, such as the forage fish of Florida, USA. When these parameters are unavailable for analyses, they are often borrowed from species of other areas. To keep the borrowing of life-history parameters to a minimum for Florida forage fish, this study is devoted to developing the morphometric relationships, growth parameters, and natural mortality rates for forage fish species for which size data had been collected in inshore surveys that have been conducted during 1996–2017 by the Fishery Independent Monitoring program of the Florida Fish and Wildlife Conservation Commission’s Fish and Wildlife Research Institute. The parameters developed can be used in single-species stock assessments and in marine ecosystem modeling.

Characterizing marine ecosystems and fishery impacts using a comparative approach and regional food-web models

Conservation of marine ecosystems is important for the sustainable utilization of marine resources under environmental changes and anthropogenic impacts. In Japan, fishery management has been based on single-species stock assessments and little attempts have been made to assess and manage the impacts of multi-species multi-gear fisheries except for a few local case studies. In this study, we analyzed two local Ecopath food-web models constructed for Japanese waters (Northeastern Japan and Seto Inland Sea). We adopted a comparative approach to assess the ecosystem characteristics and fishery impacts through a comparison of these models with other published Ecopath models for various periods and regions of the world ocean. Among the metrics derived from Ecopath outputs, total biomass and total productivity represented the gross metabolic activities of the systems, and trophic level fractionation of biomass and catch reflected the trophic structure of the food webs and fishery removals. Loss of food for top predators, primary production required, and mean and variance of trophic level of catch were good indicators of the impacts and patterns of fishery removals. Our results illustrate the characteristics of food webs and fisheries in Japanese local ecosystems: The Northeastern Japan model showed the moderate productivity of the ecosystem, and fishery removals from lower and wider trophic levels. The Seto Inland Sea model indicated large impacts of fisheries on the low productivity neritic system. Such profiling of ecosystems and fisheries provides good overviews that will help initiate stakeholder discussion toward the set-up phase of ecosystem-based fishery management in Japan.

Future Ocean Observations to Connect Climate, Fisheries and Marine Ecosystems

Advances in ocean observing technologies and modeling provide the capacity to revolutionize the management of living marine resources. While traditional fisheries management approaches like single-species stock assessments are still common, a global effort is underway to adopt ecosystem-based fisheries management (EBFM) approaches. These consider changes in the physical environment and interactions between ecosystem elements, including human uses, holistically. For example, integrated ecosystem assessments aim to synthesize a suite of observations (physical, biological, socioeconomic) and modeling platforms (ocean circulation models, ecological models, short-term forecasts, management strategy evaluations) to assess the current status and recent and future trends of ecosystem components. This information provides guidance for better management strategies. A common thread in EBFM approaches is the need for high-quality observations of ocean conditions, at scales that resolve critical physical-biological processes and are timely for management needs. Here we explore options for a future observing system that meets the needs of EBFM by i) identifying observing needs for different user groups, ii) reviewing relevant datasets and existing technologies, iii) showcasing regional case studies, and iv) recommending observational approaches required to implement EBFM. We recommend linking ocean observing within the context of GOOS and other regional ocean observing efforts with fisheries observations, new forecasting methods, and capacity development, in a comprehensive ocean observing framework.

A model-based approach to incorporate environmental variability into assessment of a commercial fishery: a case study with the American lobster fishery in the Gulf of Maine and Georges Bank

AbstractChanges in bottom-up forcing are fundamental drivers of fish population dynamics. Recent literature has highlighted the need to incorporate the role of dynamic environmental conditions in stock assessments as a key step towards adaptive fishery management. Combining a bioclimate envelope model and a population dynamic model, we propose a model-based approach that can incorporate ecosystem products into single-species stock assessments. The framework was applied to a commercially important American lobster (Homarus americanus) stock in the Northwest Atlantic. The bioclimate envelope model was used to hindcast temporal variability in a lobster recruitment habitat suitability index (HSI) using bottom temperature and salinity. The climate-driven HSI was used to inform the lobster recruitment dynamics within the size-structured population dynamics model. The performance of the assessment model with an environment-explicit recruitment function is evaluated by comparing relevant assessment outputs such as recruitment, annual fishing mortality, and magnitude of retrospective biases. The environmentally-informed assessment model estimated (i) higher recruitment and lower fishing mortality and (ii) reduced retrospective patterns. This analysis indicates that climate-driven changes in lobster habitat suitability contributed to increased lobster recruitment and present potential improvement to population assessment. Our approach is extendable to other stocks that are impacted by similar environmental variability.

Inclusion of ecosystem information in US fish stock assessments suggests progress toward ecosystem-based fisheries management

Abstract The appetite for ecosystem-based fisheries management (EBFM) approaches has grown, but the perception persists that implementation is slow. Here, we synthesize progress toward implementing EBFM in the United States through one potential avenue: expanding fish stock assessments to include ecosystem considerations and interactions between species, fleets, and sectors. We reviewed over 200 stock assessments and assessed how the stock assessment reports included information about system influences on the assessed stock. Our goals were to quantify whether and how assessments incorporated broader system-level considerations, and to explore factors that might contribute to the use of system-level information. Interactions among fishing fleets (technical interactions) were more commonly included than biophysical interactions (species, habitat, climate). Interactions within the physical environment (habitat, climate) were included twice as often as interactions among species (predation). Many assessment reports included ecological interactions only as background or qualitative considerations, rather than incorporating them in the assessment model. Our analyses suggested that ecosystem characteristics are more likely to be included when the species was overfished (stock status), the assessment is conducted at a science centre with a longstanding stomach contents analysis program, and/or the species life history characteristics suggest it is likely to be influenced by the physical environment, habitat, or predation mortality (short-lived species, sessile benthic species, or low trophic-level species). Regional differences in stomach contents analysis programs may limit the inclusion of predation mortality in stock assessments, and more guidance is needed on best practices for the prioritization of when and how biophysical information should be considered. However, our results demonstrate that significant progress has been made to use best available science and data to expand single-species stock assessments, particularly when a broad definition of EBFM is applied.

Assessing the structure and functioning of the southern North Sea ecosystem with a food-web model

Single species stock assessment models are, and will remain, the workhorse of fisheries management. However, they are incapable of assessing the structure and functioning of the ecosystem the fisheries operate in. This study describes the trophic structure of the southern North Sea and the flows between the nodes of its food-web. It is based on the outputs of an Ecopath food-web model of the North Sea south of the Skagerrak (ICES area VIb and c), parametrized representing the year 1991. The study also compares the southern to a whole North Sea Ecopath model (whole ICES area IV) parametrized for the same year, 1991.The two dominant flows of biomass led from primary producers to detritus, and from there into benthos. The southern North Sea differed from the whole North Sea representation in its fish community composition, primarily attributable to the biogeography of the species. Flatfish were caught more and roundfish less in the south, even with a nominally identically gear, to wit, otter trawlers. The largely different fish and catch compositions call for a specific, local management of the shallow southern North Sea's fisheries, which is based on ecosystem boundaries, rather than politically defined areas.Beyond fished stocks, food-web network indicators suggest that both systems functioned similarly, if compared to a global set of Ecopath models. They also deem the 1991 North Sea and its southern sub-part a densely woven, mature and resilient food-web.

End-to-end model of Icelandic waters using the Atlantis framework: Exploring system dynamics and model reliability

Icelandic waters are very productive and the fisheries are economically important for the Icelandic nation. The importance of the fisheries has led to progressive fisheries management and extensive monitoring of the ecosystem. However, fisheries management is mainly built on single species stock assessment models, and multi-species or ecological models are essential for building capacity around ecosystem-based fisheries management. This paper describes the first end-to-end model for the Icelandic waters using the Atlantis modeling framework. The modeled area is 1,600,000 km2, and covers the area from Greenland through Icelandic waters to the Faroe Islands. The ocean area was divided into 51 spatial boxes, each with multiple vertical layers. There were 52 functional groups in the model: 20 fish groups (8 at a species level), 5 groups of mammals, 1 seabird group, 16 invertebrates, 5 primary producers, 2 bacteria and 3 detritus groups. The reliability of the model was evaluated using a skill assessment and a sensitivity analysis was conducted to understand the dynamics of the system. The sensitivity study revealed that saithe, redfish and tooth whales had the greatest effect on other groups in the system. The skill assessment showed that the model was able to replicate time-series of biomass and landings for the most important commercial groups and that modeling of the recruitment processes was important for some of the groups. This model now provides a solid basis for evaluating alternative ecosystem and fisheries management scenarios, and should produce reliable results for the most important commercial groups.

Comparing an ecosystem approach to single-species stock assessment: The case of Gazi Bay, Kenya

Abstract Gazi Bay located on the Kenyan South Coast is a semi-enclosed shallow tropical coastal ecosystem supporting an economically important multi-species and multi-gear artisanal fishery. In this study, we integrated the available scientific information of the system to develop a preliminary trophic mass-balance model to characterize the ecosystem structure and functioning, evaluate the ecological impacts of fishing on the ecosystem, and compare the results of the ecosystem assessment to those of previous single-species stock assessments. The model includes 23 functional groups aggregated into linear food chains, which resulted in nine discrete trophic levels sensu Lindeman (1942). Results from the mixed trophic impacts showed a bottom-up control in the system where herbivory dominated the energy flow to higher trophic levels but with a significant export of detritus out of the system. With a mean transfer efficiency of 12.6%, Finn cycling index 7.3%, path length 2.7, system omnivory index 0.19, and system ascendency and overhead 27 and 73%, respectively, it would appear that Gazi Bay is immature and perturbed likely due to fishery-induced exploitation. Overall, the fishery is operating at a level of primary consumers with a mean trophic level of the catch of 2.38. Fishing mortality is by far the leading cause of total mortality with the computed exploitation rates suggesting heavy exploitation of the key commercial species (F/Z > 0.5). A comparison of the results of the percentage of primary production required to sustain fisheries and the average trophic level of catch (%PPR–TLc) with those from similar tropical coastal systems shows that Gazi Bay is comparable to some of the most intensively exploited coastal ecosystems. This implies the impacts of the fishery are evident both at the species and ecosystem level, and there may be a need for precautionary measures for fisheries management.

Improving stock assessment and management advice for data-poor small-scale fisheries through participatory monitoring

Undetected but underlying biases in model parameterization strongly reduce the reliability and value of assessments of data-poor fisheries. We explore the effects of missing and misunderstood data on single-species stock assessments used to provide management advice. From 2006 to 2014, the Colombian government monitored landings of small-scale fisheries. During the same period, communities implemented a participatory monitoring program in the Central Guajira region. We found that the two data sources gave different results for the population status of the highest-valued fish, lane snapper (Lutjanus synagris), and the largest-landed species, white grunt (Haemulon plumierii). Recordings of landing points by the government monitoring program led to year-to-year underestimations and therefore misconceptions regarding population status and fishery trends. Overexploited and underexploited population statuses were seen to arise from the same fishing pressure as a result of the interplay between natural mortality and erroneous estimates of fishing mortality. The tested von Bertalanffy growth parameters affected the exploitation level, but not the population status, of the species. When data from the participatory monitoring program were incorporated, higher landings and a more severe overfishing trend emerged for both species. The management scenarios simulated using the best verified data available provided reasonable advice for recovering the lane snapper and white grunt populations. Furthermore, simulation of management measures sustained the employment and incomes of fishers. Our findings indicate that participatory monitoring should be incorporated into the assessment and management of data-poor resources.

The adaptation of acoustic data from commercial fishing vessels in resource assessment and ecosystem monitoring

The collection of scientific data from commercial fishing vessels will play an important role in the future assessment of fish stocks and ecosystem monitoring. Currently fishing vessel acoustic data collections range from fully structured random/systematic surveys to the ad hoc search patterns of pelagic vessels during standard fishing operations, and are used primarily in single species stock assessment. To effectively use these data a good understanding of the data collection methods, analytical procedures, and the limitations of the data is required. Consideration of the limitations and interpretation of the data are a major factor in evaluating the validity of the outputs, the uncertainties associated with the data and the acceptance of the results by the scientific community. In this paper we provide 3 case studies of how acoustic data from commercial fishing vessels are being used to provide information on fish resources and advice to management. We categorize a fishing trip into 3 phases: transiting, searching, and fishing, and we discuss the attributes and limitations of data collected during each phase. Examples of current fishing vessel data collections and their application in resource assessment and environmental monitoring are presented. In addition, we explore opportunities for acoustics to support broad-scale ecosystems monitoring, without interfering with the day-to-day operations of the vessels.

An Ecosystem Model of Intermediate Complexity to test management options for fisheries: A case study

Reduction of complexity and capacity to evaluate management strategies are important considerations when modelling complex ecosystems. Models of Intermediate Complexity for Ecosystem assessments (MICE) achieve this by representing interactions among a restricted number of crucial species in the ecosystem considered. MICE applications are question-driven, heavily dependent on available data for conditioning and aimed at addressing tactical issues. Here we present the development of a MICE for the central Adriatic Sea. This area is important ecologically and economically because it supports a commercial stock of Norway lobster (Nephrops norvegicus), and a nursery ground for European hake (Merluccius merluccius), as well as being subjected to high levels of fishing pressure. Here, Italian and Croatian bottom trawl fisheries mainly target Norway lobster while impacting juvenile hake. Single-species stock assessments for the target species indicate fluctuating trends between 2006 and 2013, as do the survey biomass trends of most of their prey, underlining the need for a multispecies management plan. The diet of the target species were examined and prey items partitioned into four groups. Consumption of prey groups by predators was modelled using a Holling Type II functional response. A modified biomass dynamic model was used to represent the prey dynamics, projecting them into the future for 10 years (2013–2022) and testing different management strategies, including a discard ban. The most effective management option was the protection of larger individuals, which led to a clear improvement in the stock abundance and spawning stock biomass of both hake and Norway lobster without significant adverse effects on their prey. The discard ban scenario appeared to have knock-on effects on both predators and some of their prey.

Multi-model inference for incorporating trophic and climate uncertainty into stock assessments

Ecosystem-based fisheries management (EBFM) approaches allow a broader and more extensive consideration of objectives than is typically possible with conventional single-species approaches. Ecosystem linkages may include trophic interactions and climate change effects on productivity for the relevant species within the system. Presently, models are evolving to include a comprehensive set of fishery and ecosystem information to address these broader management considerations. The increased scope of EBFM approaches is accompanied with a greater number of plausible models to describe the systems. This can lead to harvest recommendations and biological reference points that differ considerably among models. Model selection for projections (and specific catch recommendations) often occurs through a process that tends to adopt familiar, often simpler, models without considering those that incorporate more complex ecosystem information. Multi-model inference provides a framework that resolves this dilemma by providing a means of including information from alternative, often divergent models to inform biological reference points and possible catch consequences. We apply an example of this approach to data for three species of groundfish in the Bering Sea: walleye pollock, Pacific cod, and arrowtooth flounder using three models: 1) an age-structured “conventional” single-species model, 2) an age-structured single-species model with temperature-specific weight at age, and 3) a temperature-specific multi-species stock assessment model. The latter two approaches also include consideration of alternative future climate scenarios, adding another dimension to evaluate model projection uncertainty. We show how Bayesian model-averaging methods can be used to incorporate such trophic and climate information to broaden single-species stock assessments by using an EBFM approach that may better characterize uncertainty.