Fishery-dependent Data Research Articles

Mapping essential juvenile habitats of exploited marine fish: Complementary insights from a scientific survey-based model, fishers’ knowledge and fisheries-dependent data

In the Bay of Biscay (BoB, Northeast Atlantic), a preexisting habitat suitability model (HSM) fitted on ecological scientific trawl survey data with restricted partial coverage revealed the concentration of Young of the Year (YoY) common sole (Solea solea) on restricted coastal and estuarine nurseries. To extend the nursery map of sole in the BoB to zones where survey data are lacking and fit with the sole population and stock management extent, we crossed HSM, fishers’ ecological knowledge (FEK) and fisheries-based (FB) data. FB and FEK data also complemented knowledge on juvenile sole habitat and seasonal migration. Thirteen fishers with potential knowledge about the YoY sole distribution were directly interviewed. Direct interviews included both information about the location of juveniles and YoY distribution mapping. With good consensus among fishers, FEK allowed the identification of four new areas hosting essential juvenile habitat for the common sole, revealed the accuracy of the HSM model outside the spatial coverage of the ecological survey, and provided spatial refinement. The FB observation data confirmed the locations of the essential juvenile habitats given by FEK and the spatial distributions of YoY densities predicted from the scientific data. In addition, FB confirmed the seasonal migration of YoY sole, which was preliminarily hypothesized from a local and short-term survey-based study. Our results emphasized the local accuracy of FEK. These findings also underlined the interest in combining several sources of data and methods to map essential fish habitats outside areas well covered by ecological scientific surveys, on order to inform future spatial management measures.

Predicting the distribution of red king crab bycatch in Bering Sea flatfish trawl fisheries

Declining Bristol Bay red king crab (BBRKC) abundance has triggered recent closures of this iconic Bering Sea fishery and raised interest in bycatch in non-directed fisheries as a possible conservation concern. One particular concern is the effectiveness of static closed areas for bycatch fisheries in an era of climate warming and widespread distribution shifts. However, spatial data for supporting management decisions concerning bycatch is lacking, as fisheries-independent data are collected only in the summer, and the relationship to BBRKC distribution in the fall/winter/spring, when most bycatch occurs, is unknown. We filled this information gap by using fishery-dependent data to build predictive models of BBRKC bycatch distribution in non-pelagic trawl groundfish fisheries in the data-poor seasons. We trained Boosted Regression Tree models for bycatch occurrence and abundance of four BBRKC sex-size/maturity categories, and evaluation metrics indicated good to excellent predictive ability across all models. We found that flatfish directed-fishery CPUE, summer survey CPUE for BBRKC and flatfish, and depth were important predictors for bycatch occurrence and abundance. Physical variables (ice cover and temperature) were generally less important. We also found strong correlations between the mean latitude of observed bycatch and the summer survey for BBRKC, highlighting the ability of summer survey data to predict non-summer bycatch distributions. BBRKC bycatch prediction is a tractable problem, and our results are the first step towards operating models that may be used to evaluate proposed management actions. We also conclude that northward shifts in fishery-independent and -dependent data suggest the possible value of reassessing decades-old static closure areas for managing BBRKC bycatch.

Effects of sampling effort and data sources on precision of common carp and bigmouth buffalo population estimates

Biologists often manage abundant invasive Common Carp (Cyprinus carpio) populations for suppression below population density or biomass thresholds via commercial harvest that also removes large numbers of native Bigmouth Buffalo (Ictiobus cyprinellus). Thus, biologists need population estimates to monitor abundance but often avoid them due to the time and effort required to produce population estimates and pervading estimate imprecision. While population abundance of these fishes can be challenging to estimate, commercial fishers harvest large numbers of fish that could improve population estimates with less effort from biologists. Yet, how population estimates from fishery-dependent and fishery-independent data sources compare is unknown. We compared the precision of Schnabel fishery-independent (electrofishing) and Lincoln-Petersen fishery-dependent (commercial harvest) population estimates for Common Carp and Bigmouth Buffalo in seven northwest Iowa lakes. We then assessed how sampling effort and environmental factors affected the number of fish recaptured by electrofishing and how the number of fish marked and recaptured affected estimate variability. Lincoln-Petersen estimates were more precise and provided similar abundance estimates compared with Schnabel estimates for Bigmouth Buffalo, while both models provided comparable population estimates and precision for Common Carp. Common Carp electrofishing recaptures were positively related to electrofishing effort, number of fish tagged, lake size, and water temperature. Bigmouth Buffalo recaptures were positively related to number of fish tagged and negatively related to lake area and water temperature. Coefficient of variation for fishery-dependent estimates declined with number of fish tagged and recaptured; 750 Common Carp and 150 Bigmouth Buffalo needed to be marked at large to obtain precision of CV ≤ 0.25. Our results suggest Lincoln-Petersen estimates with fishery-dependent data represent an improvement over fishery-independent estimates for Bigmouth Buffalo while both techniques provided comparable estimates for Common Carp. Incorporating harvest data into population estimates can reduce sampling effort while improving or maintaining precision.

Let’s measure it: An approach of high-resolution estimates of bottom fixed net fishing effort at national level

Fisheries are one of the most important food sources for human consumption whilst being amongst the most impacting and extractive activities happening within the marine environment, which makes it imperative to properly manage this activity. To improve fisheries management, the precise quantification of fishing effort is of the outmost importance. Yet, present methods for effort estimation, especially at broad scales, are hampered by difficulties in data access and usually rely on coarse effort metrics or on costly data collection for quantifying fishing effort with higher resolution. In the present work, we propose an approach of high-resolution fishing effort estimates of net fishing, as length of nets operated by a given fleet, at the national level. It relies on sampling of effort, derived from classified and easy to access vessel tracking data – AIS, and fishery dependent data – logbook and landings data. The proposed methodology combines trip-based effort estimates, derived from AIS data, as a foundation to extrapolate the total fishing effort, through the number of fishing trips linked to official landings and logbook data. It is estimated that in the years from 2014 to 2020 an average of 180 200 km of static nets (gillnets and trammel nets), which corresponds to approximately 4.5 and 210 times the lengths of the equator and the Portuguese Atlantic coastline respectively, are used in Portuguese mainland waters each year, by a fleet of slightly more than 100 vessels. The presented methodology allows to quantify and study the variation of the nominal fishing effort, at country level, with a higher resolution than what is usually used and at very low cost. We argue that such methodologies need to be developed and explored in order to have better and more comprehensive estimates of fishing effort which will contribute and improve the sustainable management of fisheries and the marine environment.

Fishery-dependent data revealing the spatio-temporal dynamics of under-monitored fisheries

Given that most of the world's fisheries are not properly monitored due to survey programs with limited spatio-temporal coverage, fishery-dependent data provide an opportunity to understand under-monitored species. However, due to the typically poor quality of fishery-dependent data resulting from spatially unbalanced sampling by fishermen, spatio-temporal interactions should be considered during modeling. In this study, we use fishery-dependent catch and effort data collected from fishing log of commercial vessels from 2012 to 2021 to fit a vector autoregressive spatio-temporal (VAST) model to analyze population dynamics of largehead hairtail (Trichiurus lepturus) in the Yellow and Bohai Seas. We considered both fixed and random factors including temporal variations, spatio-temporal interactions, vessel-level variations, and gear types. Our results suggested that the abundance index fluctuated inter-annually and showed a remarkable recovery trend since the large-scale summer moratorium extension in China seas in 2017. Population distributions also showed substantial shifts, with an eastward range expansion especially in the Yellow Sea after 2017. Our study highlights the opportunity of adopting fishery-dependent data to inform the spatial and temporal dynamics of under-monitored fishery species through a proper modeling framework, which may provide a basis for scientific management of data-limited fisheries.

Non-native fish species in the North Aegean Sea: a review of their distributions integrating unpublished fisheries data

Fisheries-dependent data and information gathered through fisheries-related scientific surveys can significantly contribute to research on the patterns and processes underlying marine biological invasions and their interactions with fisheries. This study presents an overview of the presence of non-native fish species in the North Aegean Sea, offering insights into their distributions and impact on fisheries. The findings are based on a comprehensive compilation of commercial fisheries-dependent and scientific survey data collected in Greece from 2016 to 2023, along with a systematic review of the international scientific literature. The study resulted in the documentation of the presence of 37 non-native fish species, including several recorded for the first time in the area. The results suggest that non-native fish species invasions in the North Aegean Sea are dynamic. Although most species were classified as casual, and the frequencies of occurrence as well as the quantities in commercial fisheries catches of established species are smaller than in the South Aegean Sea, species introductions and the extent of occurrence and area of occupancy of several species have been increasing since the 2000s. The significance of non-native fish species is becoming increasingly relevant to commercial fisheries in the study area. This is particularly evident in the Northeastern Aegean Sea, where catches of non-native species are on the rise, and new species with potential commercial value have emerged in recent years.

Accounting for spatio-temporal and sampling dependence in survey and CPUE biomass indices: simulation and Bayesian modeling framework

Abstract Estimating changes in the biomass of a fish stock is crucial for successful management. However, fishery assessment may be affected by the quality of the inputs used in stock assessment models. Survey biomass indices derived from fishery-independent and catch per unit effort (CPUE) biomass indices derived from fishery-dependent data are key inputs for model calibration. These indices have biases that could compromise the accuracy of the stock assessment models results. Therefore, there are plenty proposed methods to standardize survey or CPUE biomass data. From simpler models like generalized linear models (GLMs) to more complex models that take into account spatio-temporal correlation, like geostatistical models, and sampling dependence, like marked point processes. But many of them do not consider the underlying spatio-temporal or sampling dependence of these data. Hence, the goal of the study is to present a spatio-temporal simulation and Bayesian modeling framework to assess the impact of applying models that do not consider spatio-temporal and sampling dependence. Results indicate that geostatistical models and marked point processes achieve the lowest measures of error. Hence, to capture the underlying spatio-temporal process of the survey and CPUE biomass indices and data sampling preferentiality, it is essential to apply models that consider the spatio-temporal and sampling dependence.

Lessons from long-term monitoring of tropical rock lobsters to support fisheries management

Fishery-independent scientific surveys are highly valuable for monitoring lobsters and other fisheries. Yet, there are relatively few long-term monitoring surveys to support the provision of management advice. A number of challenges can prevent the continuity of long-term monitoring series. This paper uses the 35-year continuous annual dive surveys for Australia’s Torres Strait tropical rock lobster (TRL) to overview strengths and limitations of a long-term scientific survey, as well as lessons learnt from having overcome a range of challenges. Fishery-independent surveys are more reliable than fishery-dependent data and are more robust to external shocks such as market drivers and fuel prices. The primary purpose of the surveys is to provide a reliable index of stock abundance together with data to inform on size and age structure, plus model parameters and reference points. Here, we also highlight additional survey benefits including: yielding positive gains relative to cost, facilitating an adaptive management approach that serves as an early warning system, reducing and resolving inter-sector conflicts, reduced frequency of stock assessments, providing data from associated habitat monitoring, improved stakeholder buy-in, utility for development of Operating Models for Management Strategy Evaluation, contribution to achieving certification, contributing to biodiversity agreements and consistent cross-jurisdictional monitoring. We analyse lessons learnt from challenges such as changes in resource management, budget cuts, increased health and safety requirements, maintenance of capability and staff capacity, stakeholder buy-in, need to validate survey results, a pandemic and changing climate. Our experiences highlight why long-term scientific surveys are considered the gold standard for fisheries monitoring and we provide insights for building and maintaining key marine monitoring series.

Estimate of Growth Parameters of Penaeus kerathurus (Forskäl, 1775) (Crustacea, Penaeidae) in the Northern Adriatic Sea.

Crustacean fisheries are gaining prominence globally amid a decline in finfish stocks. Some decapod crustacean species have experienced increased landings in response to shifting market demands and environmental dynamics. Notably, the caramote prawn (Penaeus kerathurus-Forskål, 1775) in the northern Adriatic Sea, Geographical Sub Area (GSA) 17, has risen in both landings and economic importance in recent years. However, despite its significance, comprehensive information on fishery-dependent data, age, and growth in this region remains lacking. To address this gap, this study employs modal progression analysis and the ELEFAN approach, utilizing the "TropFishR" R package and newly developed functions, including bootstrapping procedures. These advancements aim to overcome issues identified in previous versions and enhance the accuracy and reliability of age and growth estimations. The study leverages one year of monthly length-frequency distributions (LFDs) collected from commercial bottom trawls in the northern Adriatic Sea. The results of the analysis confirm the presence of sexual dimorphism in the caramote prawn species, with females exhibiting faster growth rates compared to males. Additionally, the growth performance index supports this observation, further underscoring the importance of accounting for sexual dimorphism in growth modeling and fisheries management strategies. By contributing to a growing body of knowledge on the growth dynamics of the caramote prawn, this study provides valuable insights for sustainable fisheries management in the northern Adriatic Sea. Understanding the age and growth patterns of key crustacean species is essential for developing effective conservation measures and ensuring the long-term health and productivity of marine ecosystems. The findings of this study serve as a foundation for informed decision-making and proactive management practices aimed at preserving the ecological integrity and economic viability of crustacean fisheries in the region.

Using fisheries-dependent data to investigate landings of European lobster (Homarus gammarus) within an offshore wind farm

Abstract The need for alternative strategies to assist in the monitoring and sustainable management of fisheries’ resources is becoming increasingly important. In recent years, greater utilization of fishers’ knowledge has been advocated as a potentially valuable source of data that could be applied to fisheries management issues. In the current study, we addressed this by investigating the landing per unit effort (LPUE) of European lobster (Homarus gammarus) from within an offshore wind farm using a fisheries-dependent commercial fishing logbook. The logbook was provided by a single fisherman who targeted lobsters within the wind farm between 2015 and 2022 using single pots deployed in association with individual wind turbines. Generalized linear mixed modeling was used to investigate changes in LPUE over temporal scales and as the result of the presence of scour protection at turbine locations. LPUE was found to be significantly higher at turbine locations where scour protection was present compared to those turbines where it was not. Predictions from modeling suggested LPUE was nearly 1.5× greater at turbines where scour protection was present. Significant differences in mean monthly and yearly LPUE were detected with this variation likely to reflect seasonal changes in lobster activity and the effect of introducing fishing into a previously unfished area. This work highlights the potential for fishing logbooks to be applied in fisheries management. Our results also demonstrate potential fishing opportunities arising from the development of offshore wind farms and the potential for these opportunities to be enhanced.

Colonization, diversity, and seasonality of fishes at pelagic fish aggregating devices.

The pelagic zone of the ocean can be a challenging environment in which to conduct research and as a result we lack the robust baseline abundance and diversity data, compared to what is available in more accessible coastal habitats, to be able to track changes or stressors to the biota in this environment. Many large-scale fisheries target pelagic fish, and much of the information available on these species is based on fisheries-dependent data that may be biased towards hotspots and commercially valuable fishes. Here, a long-term video and visual fish survey was conducted on two subsurface moored fish aggregating devices (FADs) in the pelagic waters of the central Bahamas to determine the feasibility of using moored pelagic FADs as tools for collecting fish abundance and diversity data. A wide range of species was documented, including large migratory fish that are the focus of commercial and recreational fisheries, and smaller often overlooked species on which little abundance or seasonality information exists. We found that FADs colonize quickly and reach a peak stable (albeit seasonally cyclical) abundance and diversity within the first several months after deployment. Species richness was higher in video surveys, but abundance was higher in visual surveys, except for sharks. Our results highlight the need to tailor survey methods to fit the context and study objective, and provide further evidence for the importance of fisheries-independent data in monitoring pelagic species.

Human dimensions of angler nonresponse in California’s recreational steelhead fishing report card program

Angler demographics and behaviors have a significant impact on recreational fishery-dependent data, and recently, human dimensions have become more widely recognized as an important part of fisheries management. California’s steelhead (Oncorhynchus mykiss) report card program has served to track recreational fishing effort and catch each calendar year for management purposes through angler self-reporting. However, angler report card return rates are consistently low, and there has been no recent effort to investigate angler attributes that may be contributing to nonresponse. This study evaluated trends in angler demographics as they relate to annual steelhead report card return rates as well as online reporting rates across the 2012–2019 study period. The study also assessed whether specific demographic or behavioral characteristics may affect the likelihood of anglers returning their report cards. Older, more avid anglers were found to have a greater likelihood of reporting in general. Motivations or deterrents for response vs. nonresponse could not be identified due to data limitations and should be the subject of future research.

Estimation of returning Atlantic salmon stock from rod exploitation rate for principal salmon rivers in England & Wales

Abstract For effective fishery management, estimated stock sizes, along with their uncertainties, should be accurate, precise, and unbiased. Atlantic salmon Salmo salar stock assessment in England and Wales (and elsewhere across the Atlantic) estimate returning salmon stocks by applying a measure of rod exploitation rate (RER), derived from less abundant fishery-independent stock estimates, to abundant fishery-dependent data. Currently, RER estimates are generated for individual principal salmon rivers based on available local data and assumptions. We propose a single, consistent, transparent, and statistically robust method to estimate salmon stocks that transfers strength of information from “data-rich” rivers, i.e. those with fisheries-independent data, to “data-poor” rivers without such data. We proposed, fitted, simplified, and then validated a Beta–Binomial model of RER, including covariates representing angler and fish behaviours, river flow, and random effects to control for nuisance effects. Our “best” model revealed covariate effects in line with our hypotheses and generalized to data not used to train it. We used this model to extrapolate stock estimates from 12 data-rich to 52 data-poor rivers, together with their uncertainties. The resulting river-specific salmon stock estimates were judged to be useful and can be used as key inputs to river-specific, national, and international salmon stock assessments.

Beyond discards: cascading socio-economic and environmental effects of a commercial aggregate landings program in Rhode Island

Flexible approaches to commercial fisheries harvest have been designed to meet management objectives. Rights-based management tools have been problematic for fishing businesses in certain scenarios, whereas aggregate landings approaches may offer similar flexibility while avoiding pitfalls like industry consolidation. This study evaluates a Rhode Island pilot aggregate landings program for summer flounder (Paralichthys dentatus) and black sea bass (Centropristis striata) from the perspective of the pilot program participants. Semi-structured interviews were conducted with participating commercial harvesters. Fishery-dependent data were also analyzed to supplement harvesters’ responses. Interview respondents overwhelmingly supported the aggregate landings approach and described benefits directly from the program, including cost savings, reduced discards, and improved safety. The program also led to increased average weekly harvest of both species and a slight increase in the price of catch for black sea bass for program participants. The aggregate landings approach encouraged fishers to take on less risk through added flexibility in when they chose to fish, while still maximizing their utility. Although the original goals of the program were to reduce regulatory discards and make businesses more efficient, it also resulted in improvements to fishers’ well-being, suggesting that aggregate landings approaches should be considered for other fisheries.

Catches, bycatches and stock indicators of fisheries targeting cyprinids along the Swedish Baltic Sea coast

Decreasing abundance of many traditionally exploited fish stocks in the Baltic Sea force small-scale fisheries to find new ways to make a living. In line with Swedish national strategies on food supply there is an interest to develop commercial cyprinid fisheries. In the Bothnian Bay in the northern part of the Baltic Sea, annual catches have increased from zero-catches 2018–30 tonnes 2021. To aid a sustainable development of these cyprinid fisheries that target mainly bream (Abramis brama) and ide (Leuciscus idus), we study catch efficiency of target species and bycatch in different gears and seasons using logbook data from the Bothnian Bay. Using cameras, we also assessed bycatch rates. To assist the sustainability of the fishery we develop potential stock indicators. Our results suggests that larger gear (pound-nets) are more effective in catching bream, and that the proportion of bycatch decreased with gear size, being < 10% in the largest gear, which is similar or lower than many other Baltic Sea fisheries. By-catches of salmon is of concern in the Bothnian Bay, but the camera study indicates that salmon bycatches are sporadic. Catch per unit effort (CPUE) of bream was highest in spring and fall, and we conclude that site specific median CPUE is the most suitable stock abundance indicator. The size indicator L90, the 90th percentile of the length distribution, was similar among areas and we propose it as a suitable indicator of the demographic structure of the targeted bream stocks. Our results provide reference points for relatively unfished conditions, but as the study was based on mainly fishery dependent data, it is important to also include fishery independent data to assess ecosystem effects of a future and intensified cyprinid fishery.

Modelling drivers of trawl fisheries discards using Bayesian spatio-temporal models

Effective spatial fisheries management requires a proper understanding of the spatial distribution of both target species and discards. Also, spatial modelling of fishery-dependent data is an effective tool to capture uncertainties in data-limited situations. This study analyses the drivers behind discarding by comparing the standardising properties of three different components: Total Discards, Discards Per Unit of Effort and Total Discard Ratio. These metrics were analysed by means of Bayesian hierarchical spatio-temporal Gamma regression models to correctly to identify areas with high discards values that are characterized as discards hotspots. Our results showed that Total Discards is the component which better quantified the aggregated ecological impact of discarding practices, whereas Total Discard Ratio and Discards Per Unit of Effort identify complementary issues of benefits versus loss of biomass. Spatial maps obtained by combining these three approaches are a powerful tool for the spatial management of discards.

Preferential aggregation areas of Seriola dumerili: Estimation of environmental influences and insights towards sustainable exploitation

A key aspect of the sustainable management of commercially important coastal pelagic fish stocks is the identification of the spatio-temporal dynamics of aggregation behaviour. An exemplary case species is the greater amberjack, Seriola dumerili. This top-predator is an important commercial resource exploited by recreational and commercial fisheries worldwide. Greater amberjack is known to form aggregations during important stages of its life-history, making it highly vulnerable to overfishing with potential consequences to its conservation. To improve the limited knowledge on the spatio-temporal aggregation areas of this important resource, this study combined fishing fleet dynamics (Vessel Monitoring System records), environmental and landing data into a species distribution model to predict such vulnerable events in space and time around the Balearic Islands. Our results indicated that S. dumerili aggregations were generally encountered in coastal areas at shallow depths (<100 m), low salinities, low chlorophyll concentrations, and weak meridional and zonal current velocities around the Balearic Islands. The preference for these environmental variables and processes is probably related to searching for an optimal scenario that maximises the success of larval development and survival of its offspring. Moreover, the distribution model suggested the possibility of a longer spawning period than previously predicted. This research demonstrates the use of a perceptive statistical tool that efficiently combines fisheries-dependent data and environmental data to highlight essential factors that influence the aggregation behaviour of S. dumerili and thus provides essential information for the conservation and sustainable exploitation not only of the greater amberjack, but also for other gregarious species highly-vulnerable to fishing by their aggregation behaviour.

Bycatch information complements the understanding of spatial distribution for commercially-important fish species

The distribution of most commercially-important marine species was estimated with target catch data, while bycatch information has often been neglected. In this study, we aim to investigate the effect of including bycatch data on species distribution modeling (SDM) and to determine if the improvement was because of sampling-related data characteristics or other gear-specific effects. We used logbook data from stick-held dip net and pole-and-line fisheries, which were collected in the East China Sea from September to November, 2009–2019. The stick-held dip net caught hairtail (Trichiurus spp.) as bycatch, while the pole-and-line fishery targeted hairtail. We conducted presence-only SDM using maximum entropy approach based on the bycatch, target, and integrated data, then compared the predictability among models. We found that models with integrated data had the best predictability for species distribution. However, in certain months, the bycatch or target models performed as well as the integrated models. The better performance of bycatch models may be because of the larger sample size, wider sampling range, and lower sampling bias; however, after ruling out these effects, the target model had a better distribution predictability, indicating other factors related to fishing method may influence model performance as well. Our finding supports the need to incorporate bycatch information for SDM when species spatial information is only recorded in fishery-dependent data. Data availabilityData will be shared on request to the corresponding author.

Supporting a stock assessment with spatio-temporal models fitted to fisheries-dependent data

Supporting a stock assessment with spatio-temporal models fitted to fisheries-dependent data

Bringing in the experts: application of industry knowledge to advance catch rate standardization for northern shortfin squid (Illex illecebrosus)

Sources of fisheries information outside of fishery-independent surveys (e.g. fishery-dependent data) are especially valuable for species that support productive fisheries and lack reliable biological information, such as the northern shortfin squid (Illex illecebrosus). Fishery-dependent data streams are available for most species, however collaboration with industry members is critical to ensure that these fishery-dependent data are collected, applied, and interpreted correctly. Despite the need for collaboration and the frequency that fishery data are used in scientific research, there is limited literature on the structure of interactions and knowledge sharing that inform the analysis and application of fishery data. Between 2019 and 2022, a group of researchers collaborated with members of the northern shortfin squid fishing industry to bring together research data sets and knowledge from harvesters and processors to better describe the fishery dynamics, distribution, life history, and oceanographic drivers of the species. The collaboration focused on developing custom standardized fishery catch per unit effort (CPUE) indices to provide indicators of population trends that accounted for the impacts of technical and economic aspects of harvesting, processing and marketing on fishing effort, selectivity and landings of northern shortfin squid. We describe the methods used to inform and interpret the CPUE analyses, focusing on novel structure of interactions we had with industry members, and suggest best practices for integrating industry knowledge into CPUE standardization. The information shared and research products produced through this science-industry research collaboration advanced understanding of northern shortfin squid population and fishery dynamics, and contributed directly to the 2022 stock assessment and management process. Given the complex and stochastic nature of the northern shortfin squid population and fishery, we found it critical to maintain open communication and trust with processors and harvesters, who have unique insight into the factors that may be driving changes in catch, landings, and productivity of the valuable resource species.