Ecosystem-based Fisheries Management Research Articles

The Environmental Niche of the Light Purse Seine Fleet in the Northwest Pacific Ocean Based on Automatic Identification System Data

Ecosystem-based fisheries management requires high-precision fisheries information to provide relevant data for natural resource management, assessment, and marine spatial planning. This study utilizes Automatic Identification System (AIS) data from light purse seine vessels from the Chinese mainland that were collected from May to November between 2020 and 2022, along with the corresponding environmental data. By applying boosted regression trees (BRTs) and generalized additive models (GAMs), this study establishes nonlinear relationships between fishing intensity and predictor variables and explores the ecological and environmental drivers behind the spatial distribution of light purse seine vessels from the Chinese mainland in the Northwest Pacific. This research identifies the key influencing factors and reveals significant seasonal preferences for different marine environments in various months, with chlorophyll-a being the primary influencing factor. The predicted fishing effort closely resembles observed data, providing valuable information to support fisheries resource management and planning.

An explicit solution to harvesting behaviors in a predator–prey system

AbstractThis paper derives closed‐form solutions for a strategic, simultaneous harvesting in a predator–prey system. Using a parametric constraint, it establishes the existence and uniqueness of a linear feedback‐Nash equilibrium involving two specialized fleets and allows for continuous time results for a class of payoffs that have constant elasticity of the marginal utility. These results contribute to the scarce literature on analytically tractable predator–prey models with endogenous harvesting. A discussion based on industry size effects is provided to highlight the role played by biological versus strategic interactions in the multispecies context.Recommendations for Resource Managers This model presents a thorough examination of the economic inefficiencies inherent in the exploitation dynamics of two interdependent species, elucidating the complex interplay between ecological interactions and economic outcomes. The size of the fishing industries constitutes a significant variable that must be integrated into the formulation of pertinent policy recommendations. This constitutes an advancement towards a more time‐consistent approach to Ecosystem‐Based Fishery Management (EBFM).

Seasonal Distribution of Key Small-Sized Fish in the South Inshore of Zhejiang, China

Small-sized fish are a vital food source for large predatory commercial fish and play a key role in marine food webs, bridging lower and higher trophic levels. They are indispensable in maintaining the energy flow and material cycling within aquatic ecosystems. This study utilized bottom-trawl survey data from 2017 to 2020 along the south inshore of Zhejiang, China, complemented by concurrent environmental data, to examine the influence of environmental factors on the resource density and seasonal distribution patterns of four dominant small-sized fish species. The research findings indicated that SSH (sea surface height) and Chl (chlorophyll-a concentration) emerged as the key environmental factors influencing resource densities, with all four species exhibiting similar preferences toward these variables. However, significant disparities were observed in their preferences for SST (sea surface temperature), SSS (sea surface salinity), and DO (dissolved oxygen). The various species’ resource density and distribution patterns underwent significant seasonal variations. Additionally, the seasons and regions with the highest resource densities consistently aligned, occurring predominantly in autumn within the northern waters of the study area. This research further elucidated the environmental predilections and seasonal spatial distribution traits of small-sized fish in the south inshore of Zhejiang, an important feeding ground for economic fish species in the East China Sea. This provides scientific backing for forecasting alterations in coastal fishery resources under environmental and climate change scenarios and supports ecosystem-based fisheries management strategies.

Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends

In the context of ecosystem-based fisheries management (EBFM), multi-species models offer a potential alternative to traditional single-species models for managing key species, particularly in mixed-fishery settings. These models account for interactions between different species, providing a more holistic approach to fisheries compared to traditional single-species management. There is currently no comprehensive list or recent analysis of the diverse methods used to account for species interactions in fisheries worldwide. We conducted a systematic review to objectively present the current multi-species models used in fisheries. The systematic search identified 86 multi-species models, which were then evaluated to assess their similarities. Employing a clustering analysis, three distinct groups were identified: extensions of single-species/dynamic multi-species models, aggregated ecosystem models, and end-to-end/coupled and hybrid models. The first group was among the most diverse, owing to their ability to integrate biological components, while maintaining an intermediate level of complexity. The second group, primarily defined by the EwE method, features an aggregated biomass pool structure incorporating biological components and environmental effects. The third cluster featured the most complex models, which included a comprehensive representation of size and age structure, the ability to incorporate biological components and environmental effects, as well as spatial representation. The application of these methods is primarily concentrated on small pelagic and demersal species from North America and Europe. This analysis provides a comprehensive guide for stakeholders on the development and use of multi-species models, considering data constraints and regional contexts.

A roadmap for generating annual bycatch estimates from sparse at-sea observer data

Abstract To support ecosystem-based fisheries management, monitoring data from at-sea observer (ASO) programs should be leveraged to understand the impact of fisheries on discarded species (bycatch). Available techniques to estimate fishery-scale quantities from observations range from simple mean estimators to more complex spatiotemporal models, each making assumptions with differing degrees of support. However, the resulting implementation and analytical trade-offs are rarely discussed when applying these techniques in practice. Using blue shark (Prionace glauca) bycatch in the Canadian pelagic longline fishery as a case study, we evaluated the performance of seven contrasting approaches to estimating total annual discard amounts and assessed their trade-offs in application. Results demonstrated that simple approaches such as mean estimator and nearest neighbors are feasible to implement and can be as efficient for prediction as complex models such as random forest and mixed-effects models. The traditionally used catch-ratio estimator consistently underperformed among all tested models, likely due to misspecified correlative relationships between target and bycatch species. Overall, efforts in model-based approaches were rewarded with very small gains in predictive ability, suggesting that such models relying on environmental, biological, spatial, and/or temporal patterns to improve prediction of bycatch may lack sufficient foundation in data-limited contexts.

Environmental drivers affecting the status of top commercial fish stocks in the Baltic Sea: review

IntroductionLike in many parts of the world, the Baltic Sea experiences a multitude of processes and stressors that influence fish stock dynamics. This paper compartmentalizes 250 publications that examine the cumulative effects and trade-offs of some of the most significant environmental drivers (temperature change, hypoxia, nutrient enrichment, acidification, low salinity, and food-web dynamics) on the ecology of top commercial fish species in the Baltic Sea (cod, sprat, whiting, herring, flounder, and plaice).MethodsA systematic review method was applied to ensure rigorous coverage of existing literature and to provide a comprehensive synthesis of the current knowledge on the subject.ResultsThe results illustrate the extent of scientific research applicable to commercial fisheries knowledge in the Baltic Sea and identify which pressures have the greatest negative impacts on which stocks. Additionally, the findings demonstrate how well top commercial fish species have adapted to the changing environmental conditions of the Baltic Sea. In doing so, the review illustrates the upcoming challenges and underscores which stocks are likely to dominate in the future and which will face difficulties.DiscussionBy considering ecosystem-based fisheries management, this paper emphasizes the need to account for complex ecosystem interactions beyond single-stock monitoring. With increased natural hazards, top commercial fish species have reacted differently, depending on the region and their adaptive capabilities. In most cases, Clupeidae species have adapted the best to their new surroundings, Pleuronectidae resilience is varied, while Gadidae species are finding the Baltic Sea increasingly challenging.

Leveraging ecological indicators to improve short term forecasts of fish recruitment

AbstractForecasting the recruitment of fish populations with skill has been a challenge in fisheries for over a century. Previous large‐scale meta‐analyses have suggested linkages between environmental or ecosystem drivers and recruitment; however, applying this information in a management setting remains underutilized. Here, we use a well‐studied database of groundfish assessments from the West Coast of the USA to ask whether environmental variables or ecosystem indicators derived from long‐term monitoring datasets offer an improvement in our ability to skilfully forecast fish recruitment. A secondary question is which types of modelling approaches (ranging from linear models to non‐parametric methods) yield the best forecast skill. Third, we examine whether simultaneous forecasting of multiple species offers an advantage over generating species‐specific forecasts. We find that for approximately one third of the 29 assessed stocks, ecosystem indicators from juvenile surveys yields the highest out of sample predictive skill compared to other covariates (including environmental variables from Regional Ocean Modeling System output) or null models. Across modelling approaches, our results suggest that simpler linear modelling approaches do as well or better than more complicated approaches (reducing out of sample Root Mean Square Error by ~40% compared to null models), and that there appears to be little benefit to performing multispecies forecasts instead of single‐species forecasts. Our results provide a general framework for generating recruitment forecasts in other species and ecosystems, as well as a benchmark for future analyses to evaluate skill. The most promising applications are likely for species that are short lived, have relatively high recruitment variability, and moderate amounts of age or length data. Forecasts using our approach may be useful in identifying covariates or mechanisms to include in operational assessments but also provide qualitative advice to managers implementing ecosystem based fisheries management.

Using joint species distribution modelling to predict distributions of seafloor taxa and identify vulnerable marine ecosystems in New Zealand waters

Effective ecosystem-based management of bottom-contacting fisheries requires understanding of how disturbances from fishing affect seafloor fauna over a wide range of spatial and temporal scales. Spatial predictions of abundance for 67 taxa were developed, using an extensive dataset of faunal abundances collected using a towed camera system and spatially explicit predictor variables including bottom-trawl fishing effort, using a Joint Species Distribution Model (JSDM). The model fit metrics varied by taxon: the mean tenfold cross-validated AUC score was 0.70 ± 0.1 (standard deviation) for presence–absence and an R2 of 0.11 ± 0.1 (standard deviation) for abundance models. Spatial predictions of probability of occurrence and abundance (individuals per km2) varied by taxon, but there were key areas of overlap, with highest predicted taxon richness in areas of the continental shelf break and slope. The resulting joint predictions represent significant advances on previous predictions because they are of abundance, allow the exploration of co-occurrence patterns and provide credible estimates of taxon richness (including for rare species that are often not included in more commonly used single-species distribution modelling). Habitat-forming taxa considered to be Vulnerable Marine Ecosystem (VME) indicators (those taxa that are physically or functionally fragile to anthropogenic impacts) were identified in the dataset. Spatial estimates of likely VME distribution (as well as associated estimates of uncertainty) were predicted for the study area. Identifying areas most likely to represent a VME (rather than simply VME indicator taxa) provides much needed quantitative estimates of vulnerable habitats, and facilitates an evidence-based approach to managing potential impacts of bottom-trawling.

Assessing impacts of bycatch policies and fishers' heterogeneous information on food webs and fishery sustainability.

Ecosystem-based fisheries management (EBFM) has emerged as a promising framework for understanding and managing the long-term interactions between fisheries and the larger marine ecosystems in which they are nested. However, successful implementation of EBFM has been elusive because we still lack a comprehensive understanding of the network of interacting species in marine ecosystems (the food web) and the dynamic relationship between the food web and the humans who harvest those ecosystems. Here, we advance such understanding by developing a network framework that integrates the complexity of food webs with the economic dynamics of different management policies. Specifically, we generate hundreds of different food web models with 20-30 species, each harvested by five different fishers extracting the biomass of a target and a bycatch species, subject to two different management scenarios and exhibiting different information in terms of avoiding bycatch when harvesting the target species. We assess the different ecological and economic consequences of these policy alternatives as species extinctions and profit from sustaining the fishery. We present the results of different policies relative to a benchmark open access scenario where there are no management policies in place. The framework of our network model would allow policymakers to evaluate different management approaches without compromising on the ecological complexities of a fishery.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Quantifying stability and resilience of eco-social keystone species complexes for coastal marine ecosystems of the Caribbean Sea and eastern Pacific: applications in conservation and monitoring programmes.

The local stability and resilience of 13 eco-social keystone species complexes (eco-social KSCs)-considered as conservation and monitoring units-were quantified in coastal marine ecosystems located in the Caribbean and eastern Pacific. Based on Routh-Hurwitz's criterion and Levins' criteria, the eco-social KSCs corresponding to Islas Marietas National Park (Mexico) emerged as the most locally stable and resilient ecosystem. To the contrary, the eco-social KSCs determined for Guala Guala Bay (Chile) and Xcalak Reef National Park (Caribbean) were the least stable and resilient, respectively. In terms of sensitivity, the eco-social KSCs corresponding to El Cobre Bay (Chile) presented the greatest number of sensitive components. The ecological section of the KSCs is formed by a tri-trophic network, dominating self-negative feedbacks. In the case of the socio-economic section, the fisher could exhibit the three types of self-feedbacks, and instead, the demand should be controlled. The identification of eco-social KSCs and the quantification of their stabilities and resiliences allow us to approach ecosystem-based fisheries management under a climate change context. Therefore, we suggest assessing and monitoring the persistence of the eco-social KSCs herein analysed over time, as a way to conserve the fundamental network structure of these ecosystems intervened by fishing.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Croakers in three coastal areas of Lagos state, Nigeria: Sustainability levels and stakeholders’ perceptions on the use of ecosystem-based fisheries management

Croakers are an economically important fish species in Nigeria. Croakers are harvested by artisanal and industrial fisheries, providing a significant source of income and livelihood for coastal communities. Yet, human activities pose a significant threat to the survival of croakers in Nigeria. This study aims to evaluate the sustainability of croakers in the coastal waters of Lagos, Nigeria. The study also examines stakeholders' perceptions of Ecosystem-Based Fisheries Management (EBFM) as a tool for sustainable fisheries management in Nigeria. Questionnaires are used to collect data, and the Multidimensional Scaling Tool “Rapfish” is used to assess the sustainability level of croakers in three study areas. The results indicate that stakeholders have a positive attitude toward implementing EBFM. The sustainability analysis indicates degrees of sustainability of croakers at the boundary of being “less sustainable”. Specifically, the sustainability scores along the five dimensions analyzed are Ecological sustainability (55.69 %), economic (56.35 %), ethical (54.02 %), social (42.31 %), and technological sustainability (57.51 %). Based on these findings, the study derives several policy recommendations to improve the sustainability of croakers in Nigeria.

Trophic effects of jellyfish blooms on fish populations in ecosystems of the coastal waters of China

Jellyfish play an important role in the material cycling and energy flow of food webs, and massive aggregations may have deleterious consequences for local fisheries; yet a theoretical framework of the trophic effects of jellyfish blooms on coastal fisheries is unclear. To address this knowledge gap, we assessed the trophic interactions between cooccurring bloom jellyfish and dominant fish groups (omnivorous fish and piscivorous fish) in the coastal waters of China (CWC) via stable isotope analysis; we subsequently discussed how jellyfish blooms may affect energy flow through coastal ecosystems. Our results indicate a considerable degree of trophic overlap (mean ratio > 65 %) between jellyfish and small omnivorous fish (< 10 cm), highlighting a similarity in feeding habits, while the overlap ratio decreased to <55 % of the large omnivorous fish group (> 10 cm). Relatively higher trophic levels and smaller overlaps of large omnivorous fish were found in the ecosystem with high jellyfish biomass, which suggested that they may reinforce the ontogenetic trophic shift pattern to alleviate the potential for resource competition with jellyfish under conditions of jellyfish explosion. The smallest trophic overlap (< 20 %) highlighted the strong trophic differentiation between jellyfish and piscivorous fish. Additionally, our study suggested that a massive aggregation of jellyfish can negatively influence zooplankton but may not transfer energy further up efficiently, implying a weak trophic coupling between jellyfish and upper-trophic levels in CWC ecosystems. Thus, we speculate that jellyfish play an important role in shaping pathways involved in the energy transfer of food webs and that large blooms may negatively affect fisheries through bottom-up control affecting prey availability. In general, these results hold strong potential to further improve the understanding of the trophic interactions between jellyfish and fish populations. Furthermore, this study provides valuable data for predicting the consequences of jellyfish blooms on ecosystems, and is crucial for ecosystem-based management of coastal fisheries.

Fish biodiversity status and threats of Chinadi Beel in Bangladesh

This study examined the fish fauna of Chinadi Beel in Bangladesh in terms of diversity, quantity, and state of conservation. A pre-tested questionnaire and a direct catch evaluation survey were employed to conduct the study in the beel. In the examined beel, a comprehensive count of 3,360 fish specimens, encompassing 52 distinct fish species from 8 orders and 19 families, was documented. Cypriniformes was identified as the dominating order among the 8 orders examined, accounting for 51.49% of the total. Out of 52 fish species about 31 least concern (59.61%), 8 endangered (15.38%), 6 vulnerable (11.54%), 6 near threatened (11.54%) and 1 critically endangered (1.92%) species were observed according to the International Union for Conservation of Nature. The study utilized population diversity indices, specifically the Shannon-Weiner diversity index (H'), Margalef species richness (d), Pielou's evenness index (J'), and Simpson dominance index (c), to assess the species diversity, richness, and evenness of fish which value were found to be 2.50, 4.30, 0.90, and 0.30, respectively. Chinadi Beel has the capacity to function as a significant reservoir of fishing resources and a repository of genetic information for many fish species. However, the present study emphasized several anthropogenic and environmental issues, such as unregulated fishing, agricultural pollutants, illegal or harmful fishing, the construction of infrastructure for development, and climate change. Hence, it is highly recommended to implement ecosystem-based fisheries management that actively involves the local population in order to guarantee the long-term preservation of these water bodies.

Development and analyses of stakeholder driven conceptual models to support the implementation of ecosystem-based fisheries management in the U.S. Caribbean.

Fisheries management agencies in the U.S. Caribbean are currently taking steps into transitioning from a single species approach to one that includes Ecosystem Based Fisheries Management (EBFM) considerations. In this study, we developed and analyzed stakeholder-driven conceptual models with seven different stakeholder groups in Puerto Rico and the US Virgin Islands to assess and compare their perceptions of the fishery ecosystem. Conceptual models were developed for each stakeholder group during 29 separate workshops involving a total of 236 participants representing Commercial Fishers, Managers, Academics, Local Businesses, Environmental NGOs, and the Caribbean Fishery Management Council (CFMC) District Advisory Panels (DAPs) and Scientific and Statistical Committee (SSC). Non-Metric Multidimensional Scaling (nMDS) and two-mode social network analysis were used to investigate differences and similarities between stakeholder groups as well as to identify priority ecosystem elements and threats. Results show important variations between stakeholders and islands in terms of their perceived importance of ecosystem components and relationships, which supports the need for collaborative approaches and co-production of knowledge in the United States (U.S.) Caribbean region. Despite this variation, important areas of common concern among stakeholders were identified such as: habitat integrity (e.g., coral reefs), water quality, and influence of recreational fisheries and tourism on marine ecosystems. Findings of this study support the use of stakeholder-driven conceptual models as effective tools to guide decision-making, aid prioritization of data collection, and increase collaboration and cooperation among stakeholders in the context of fisheries management.

Feeding strategies of the ocean white fish (Caulolatilus princeps) and white spotted sand bass (Paralabrax albomaculatus) inside the Galapagos Marine Reserve

Understanding the diet of two demersal species, the ocean white fish (Caulolatilus princeps) and white spotted sand bass (Paralabrax albomaculatus) provides insights into the trophic strategies they have evolved to co-exist in rocky reefs and soft bottom habitats in the Galapagos Marine Reserve (GMR). We applied two complementary techniques (stomach content and stable isotopes analysis) to determine the trophic habits between species, and categories (sex, life stages and seasons). Sampling was carried out in several sites of fishing importance within the GMR between 2017 and 2018, obtaining 254 stomachs and 58 muscle samples for C. princeps, and 14 stomachs and 34 muscle samples for P. albomaculatus. Trophic spectrum (diet composition), of both predators contained pelagic and benthic prey. The slender anchovy (Anchoa ischana) was the most important prey for C. princeps with no significant differences in the diet between sex, life stages or seasons (p > 0.05); while the most important prey for P. albomaculatus was the threadfin bass (Pronotogrammus multifasciatus). The δ13C and δ15N signatures were significantly different among species (tvalue = 11.81, p < 0.05 and tvalue = 4.67, p <0.05, respectively) suggesting differences in the carbon source (i.e., feeding areas) as well as the preference for different trophic levels (i.e., different prey). Intraspecific analysis in C. princeps showed no differences within sex, life stage and seasons (p > 0.05). Feeding strategies were similar for both predators, with a reduced trophic niche and high variability between preys consumed. This work provides baseline information on two species of ecological and commercial importance within the GMR and highlights the value of trophic studies to generate useful information for an ecosystem-based fisheries management.

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.

Decadal changes in biomass and distribution of key fisheries species on Newfoundland's Grand Banks.

Canadian fisheries management has embraced the precautionary approach and the incorporation of ecosystem information into decision-making processes. Accurate estimation of fish stock biomass is crucial for ensuring sustainable exploitation of marine resources. Spatio-temporal models can provide improved indices of biomass as they capture spatial and temporal correlations in data and can account for environmental factors influencing biomass distributions. In this study, we developed a spatio-temporal generalized additive model (st-GAM) to investigate the relationships between bottom temperature, depth, and the biomass of three key fished species on The Grand Banks: snow crab (Chionoecetes opilio), yellowtail flounder (Limanda ferruginea), and Atlantic cod (Gadus morhua). Our findings revealed changes in the centre of gravity of Atlantic cod that could be related to a northern shift of the species within the Grand Banks or to a faster recovery of the 2J3KL stock. Atlantic cod also displayed hyperaggregation behaviour with the species showing a continuous distribution over the Grand Banks when biomass is high. These findings suggest a joint stock assessment between the 2J3KL and 3NO stocks would be advisable. However, barriers may need to be addressed to achieve collaboration between the two distinct regulatory bodies (i.e., DFO and NAFO) in charge of managing the stocks. Snow crab and yellowtail flounder centres of gravity have remained relatively constant over time. We also estimated novel indices of biomass, informed by environmental factors. Our study represents a step towards ecosystem-based fisheries management for the highly dynamic Grand Banks.

Fluctuations in abundance of the striped venus clam Chamelea gallina in the southern Adriatic Sea (Central Mediterranean Sea): knowledge, gaps and insights for ecosystem-based fishery management

An assessment on the fluctuations in abundance of the striped venus clam (Chamelea gallina) in the southern Adriatic Sea (Central Mediterranean Sea), and the northern Gargano area, has been conducted through both historical information and recent data from monitoring surveys during the period 1997–2019. Production trends, conditions of the commercial stock biomass, and depth distribution pattern of juveniles and commercial sizes were analysed testing temporal differences. Moreover, the exploitation of the clam beds and recruitment events were investigated in 2018–2019. Changes in abundance were analysed using non-parametric tests for both juvenile (length class, LC < 22 mm) and commercial (LC ≥ 22 mm) fractions. Hydrodynamic changes, temperature and salinity variations were explored using a 3D hydrodynamic numerical model (MIKE 3 FM-HD) and statistical analysis, as well as changes in benthic assemblages impacted by hydraulic dredges were investigated through PERMANOVA and other multivariate analysis.The results showed a temporal decline of production and biomass of C. gallina during the 1997–2019 period, and a regression of the depth limit in the clams’ distribution towards shallower waters. A significant reduction in juveniles was observed during 2018–2019 with a very limited recruitment. The fishing exploitation showed high impacts on the commercial stock and benthic assemblages in the summer of 2018. Overall, water currents were predominantly directed offshore in 2018, during the C. gallina spawning period. This could affect the larval dispersal and settlement on unsuitable bottoms. Anomalies in temperature (high peaks in August 2018, > 28 °C) and salinity (low values in spring 2018, < 37 PSU) could have induced stress and mortality events on the entire clam bed in the study area. This first study highlights the need to integrate environmental information in the assessment of commercial stocks of clams in the Adriatic Sea, to better understand climate change effects on the fluctuations and to support effective ecosystem-based fishery management.

Linking climate stressors to ecological processes in ecosystem models, with a case study from the Gulf of Alaska

Abstract As climate stressors are impacting marine ecosystems and fisheries across the world, ecosystem models that incorporate environmental variables are increasingly used to inform ecosystem-based fisheries management. The assumptions around the mechanistic links between climate stressors and the biological processes in these models are important, but the implications for model outcomes of which stressors are captured and how they affect modeled biological processes are seldom explored. Using a whole-ecosystem model (Atlantis) for the Gulf of Alaska, we explore the effects of capturing physical (increased temperature) and biogeochemical (decreased low trophic level productivity) climate stressors, and disentangle the effects of each stressor on the productivity of forage fish, groundfish, and fish-eating seabirds. We then test the effects of alternative model specifications of temperature-driven habitat determination and bioenergetics. Increased temperature resulted in increased weight-at-age and higher natural mortality, while decreased productivity resulted in decreased weight-at-age and higher natural mortality. Model specification of temperature dependence of movement and spawning influenced model outcomes, and decoupling these processes from temperature led to overly optimistic biomass predictions. As the use of ecosystem models to inform fisheries management becomes more operational, we illustrate that the assumptions around the links between climate stressors and ecological processes influence model outcomes.

An updated end-to-end ecosystem model of the Northern California Current reflecting ecosystem changes due to recent marine heatwaves.

The Northern California Current is a highly productive marine upwelling ecosystem that is economically and ecologically important. It is home to both commercially harvested species and those that are federally listed under the U.S. Endangered Species Act. Recently, there has been a global shift from single-species fisheries management to ecosystem-based fisheries management, which acknowledges that more complex dynamics can reverberate through a food web. Here, we have integrated new research into an end-to-end ecosystem model (i.e., physics to fisheries) using data from long-term ocean surveys, phytoplankton satellite imagery paired with a vertically generalized production model, a recently assembled diet database, fishery catch information, species distribution models, and existing literature. This spatially-explicit model includes 90 living and detrital functional groups ranging from phytoplankton, krill, and forage fish to salmon, seabirds, and marine mammals, and nine fisheries that occur off the coast of Washington, Oregon, and Northern California. This model was updated from previous regional models to account for more recent changes in the Northern California Current (e.g., increases in market squid and some gelatinous zooplankton such as pyrosomes and salps), to expand the previous domain to increase the spatial resolution, to include data from previously unincorporated surveys, and to add improved characterization of endangered species, such as Chinook salmon (Oncorhynchus tshawytscha) and southern resident killer whales (Orcinus orca). Our model is mass-balanced, ecologically plausible, without extinctions, and stable over 150-year simulations. Ammonium and nitrate availability, total primary production rates, and model-derived phytoplankton time series are within realistic ranges. As we move towards holistic ecosystem-based fisheries management, we must continue to openly and collaboratively integrate our disparate datasets and collective knowledge to solve the intricate problems we face. As a tool for future research, we provide the data and code to use our ecosystem model.