Kelli F. Johnson

The environment is a dominant driver of fish recruitment, but ecological and statistical challenges have prevented widespread adoption of environmental recruitment indices in stock assessments. We conducted a simulation study to better understand the behavior of environmental recruitment indices in stock assessment models and provide advice for what benefits they might provide and how to specify them. We simulated recruitment indices of different lengths and different correlations to true recruitment (“precision”) across four different operating models encompassing different life histories, data collection, and fishing histories. We found that recruitment indices generally led to more precise estimates of recruitment near the end of the estimation period, though this improved precision was sometimes also more biased. The improvement in terminal recruitment generally propagated into improvements in the population forecast, particularly for the operating model with fewer observations of young fish in other data sources. However, for estimation models with more precise and longer indices, estimates associated with overall population productivity were biased. To ensure recruitment indices are improving forecasts but not biasing other key parameters, we recommend fitting models with and without recruitment indices. While estimates of annual recruitment should differ between models, quantities like reference points should not. Truncating recruitment indices to more recent years can reduce bias when reference point estimates differ. Additional considerations should be based on retrospective forecast skill, not on fits to modeled data. When used with care, recruitment indices in stock assessments can be a valuable tool to promote ecosystem-based fishery management.

Objective: Variability in somatic growth of marine fish can affect their reproductive potential and survival and, therefore, the productivity of a population. Understanding how growth might vary among species can improve predictions of population status and responses to environmental change. Our objective was to characterize the variability in growth and body condition of groundfish species along the U.S. West Coast to support their monitoring and assessment. Methods: We used geostatistical models to estimate growth rate and body condition, two interrelated traits associated with somatic growth, across space and time for nine commercially important U.S. West Coast groundfish species. We fit generalized linear mixed models with Gaussian Markov random fields to biological data collected from annual bottom trawl surveys to estimate variability at a 4- × 4-km spatial resolution. Results: Our models uncover spatiotemporal variability in growth rate and body condition in all nine groundfish species with limited trends shared among species with similar traits, suggesting a greater influence from niche partitioning acting on local scales. Such interspecific differences in growth rate and body condition also occurred at regional scales, with some species exhibiting positive responses while others declined. Conclusions: These findings reveal the dynamic nature of somatic growth among groundfish species and provide insight into potential mechanisms of its variability that could be considered within climate-enhanced assessments of population status for marine fish.

Fisheries management faces challenges due to political, spatial, and ecological complexities, which are further exacerbated by variation or shifts in species distributions. Effective management depends on the ability to integrate fisheries data across political and geographic boundaries. However, such efforts may be hindered by inconsistent data formats, limited data sharing, methodological differences in sampling, and regional governance differences. To address these issues, we introduce the surveyjoin R package, which combines and provides public access to bottom trawl survey data collected in the Northeast Pacific Ocean by NOAA Fisheries and Fisheries and Oceans Canada. This initial database integrates over 3.3 million observations from 14 bottom trawl surveys spanning Alaska, British Columbia, Washington, Oregon, and California from the 1980s to present. This database standardizes variables such as catch-per-unit-effort (CPUE), haul data, and in-situ measurements of bottom temperature. We demonstrate the utility of this database through three case studies. Our first case study develops a coastwide biomass index for Pacific hake (Merluccius productus) using geostatistical index standardization, comparing results to independent acoustic survey estimates. The second case study examines spatial patterns in groundfish community structure, highlighting breakpoints between assemblages in their mixture of life histories and trophic compositions. Our third example applies spatially varying coefficient models to assess sablefish (Anoplopoma fimbria) biomass trends, identifying regional variability in increases in occurrence and biomass. Together, these case studies demonstrate how the surveyjoin R package and database may improve species and ecosystem assessments by providing insights into population trends across geopolitical boundaries. This database and package represent an important step toward offering a scalable framework that can be extended to include additional data types, surveys, and species. By fostering collaboration, transparency, and data-driven decision making, surveyjoin supports international efforts to sustainably manage shared marine resources under dynamic environmental conditions.

Variability in somatic growth of marine fish affects their reproductive potential and survival, and therefore, the productivity of a population. Understanding how growth might vary among species with similar traits can improve predictions of population status and responses to environmental change. We used geostatistical models to characterize spatiotemporal variability in growth rate and body condition, two interrelated traits associated with somatic growth, of nine commercially important U.S. West Coast groundfish species with a range of life-history traits and depth distributions. Our models uncover spatiotemporal variability in growth rate and body condition in all nine groundfish species with limited trends shared among species with similar traits, suggesting a greater influence from niche partitioning acting on local scales. Such interspecific differences in growth rate and body condition responses also occurred at regional scales, with some species exhibiting positive responses while others declined. These findings reveal the dynamic nature of somatic growth among groundfish species and provide insight into potential mechanisms of its variability that could be considered within climate-enhanced assessments of population status for marine fish.

Fisheries management faces challenges due to political, spatial, and ecological complexities, which are further exacerbated by variation or shifts in species distributions. Effective management depends on the ability to integrate fisheries data across political and geographic boundaries. However, such efforts may be hindered by inconsistent data formats, limited data sharing, methodological differences in sampling, and regional governance differences. To address these issues, we introduce the surveyjoin R package, which combines and provides public access to bottom trawl survey data collected by NOAA Fisheries and Fisheries and Oceans Canada in the Northeast Pacific Ocean. This initial database integrates over 3.3 million observations from 14 bottom trawl surveys spanning Alaska, British Columbia, Washington, Oregon, and California from the 1980s to present. This effort standardizes variables such as catch-per-unit-effort (CPUE), haul data, and in-situ measurements of bottom temperature. We demonstrate the utility of this database through three case studies. Our first case study develops a coastwide biomass index for Pacific hake ( Merluccius productus ) using geostatistical index standardization, comparing results to independent acoustic survey estimates. The second case study examines changes in the spatial distribution of groundfish species across marine heatwave and non-heatwave years, highlighting species-specific and community-level responses to warming events. Our third example applies spatially varying coefficient models to assess sablefish ( Anoplopoma fimbria ) biomass trends, identifying regional variability in increases in occurrence and biomass. Together, these case studies demonstrate how the surveyjoin R package and database may improve species and ecosystem assessments by providing insights into population trends across geopolitical boundaries. This database and package represent an important step toward offering a scalable framework that can be extended to include additional data types, surveys, and species. By fostering collaboration, transparency, and data-driven decision-making, surveyjoin supports international efforts to sustainably manage shared marine resources under dynamic environmental conditions.

Understanding the dynamic relationship between marine species and their changing environments is critical for ecosystem based management, particularly as coastal ecosystems experience rapid change (e.g., general warming, marine heat waves). In this paper, we present a novel statistical approach to robustly estimate and track the thermal niches of 30 marine fishes along the west coast of North America. Leveraging three long-term fisheries-independent datasets, we use spatiotemporal modeling tools to capture spatiotemporal variation in species densities. Estimates from our models are then used to generate species-specific estimates of thermal niches through time at several scales: coastwide and for each of the three regions. By synthesizing data across regions and time scales, our modeling approach provides insights into how these marine species may be tracking or responding to changes in temperature. While we did not find evidence of consistent temperature-density relationships among regions, we are able to contrast differences across species: Dover sole and shortspine thornyhead have relatively broad thermal niche estimates that are static over time, whereas several semi-pelagic species (e.g., Pacific hake, walleye pollock) have niches that are both becoming warmer over time and simultaneously narrowing. This illustrates how several economically and ecologically valuable species are facing contrasting fates in a changing environment, with potential consequences for fisheries and ecosystems. Our modeling approach is flexible and can be easily extended to other species or ecosystems, as well as other environmental variables. Results from these models may be broadly useful to scientists, managers, and stakeholders—monitoring trends in the direction and variability of thermal niches may be useful in identifying species that are more susceptible to environmental change, and results of this work can form quantitative metrics that may be included in climate vulnerability assessments, estimation of dynamic essential fish habitat, and assessments of climate risk posed to fishing communities.

Forecasting 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.

Understanding the dynamic relationship between marine species and their changing environments is critical for ecosystem based management, particularly as coastal ecosystems experience rapid change (e.g., general warming, marine heat waves). In this paper, we present a novel statistical approach to robustly estimate and track the thermal niches of 30 marine fishes along the west coast of North America. Leveraging three long-term fisheries-independent datasets, we use spatiotemporal modeling tools to capture spatiotemporal variation in species densities. Estimates from our models are then used to generate species-specific estimates of thermal niches through time at several scales: coastwide and for each of the three regions. By synthesizing data across regions and time scales, our modeling approach provides insights into how these marine species may be tracking or responding to changes in temperature. While we did not find evidence of consistent temperature-density relationships among regions, we are able to contrast differences across species: Dover sole and shortspine thornyhead have relatively broad thermal niche estimates that are static over time, whereas several semi-pelagic species (e.g., Pacific hake, walleye pollock) have niches that are both becoming warmer over time and simultaneously narrowing. This illustrates how several economically and ecologically valuable species are facing contrasting fates in a changing environment, with potential consequences for fisheries and ecosystems. Our modeling approach is flexible and can be easily extended to other species or ecosystems, as well as other environmental variables. Results from these models may be broadly useful to scientists, managers, and stakeholders — monitoring trends in the direction and variability of thermal niches may be useful in identifying species that are more susceptible to environmental change, and results of this work can form quantitative metrics that may be included in climate vulnerability assessments, estimation of dynamic essential fish habitat, and assessments of climate risk posed to fishing communities.