Shore-based observers are increasingly being used in place of at-sea observers to monitor and sample commercial fisheries catch. However, few evaluations assess whether these programs meet their stated goals or how to optimize them, and industry data are rarely tested for accuracy despite serving as the foundation for catch accounting. Using a high-volume trawl fishery as a case study, we evaluated observer performance, assessed the accuracy of industry data, and present a transferrable framework for evaluating observer performance and optimizing sampling. Observers performed well under expanded duties, meeting high-priority objectives, nearly meeting secondary goals, and detected species at low catch fractions (similar to 0.7%). Comparisons with industry data revealed under-reporting or aggregation for some managed species, underscoring the need for independent verification. Results highlight that shore-based observers can fulfill expanded duties, maintain core functions, and provide critical checks on industry-reported data. The framework employed here is applicable to other programs seeking to evaluate and optimize shore-based monitoring programs.

While there have been recent improvements in reducing bycatch in many fisheries, bycatch remains a threat for numerous species around the globe. Static spatial and temporal closures are used in many places as a tool to reduce bycatch. However, their effectiveness in achieving this goal is uncertain, particularly for highly mobile species. We evaluated evidence for the effects of temporal, static, and dynamic area closures on the bycatch and target catch of 15 fisheries around the world. Assuming perfect knowledge of where the catch and bycatch occurs and a closure of 30% of the fishing area, we found that dynamic area closures could reduce bycatch by an average of 57% without sacrificing catch of target species, compared to 16% reductions in bycatch achievable by static closures. The degree of bycatch reduction achievable for a certain quantity of target catch was related to the correlation in space and time between target and bycatch species. If the correlation was high, it was harder to find an area to reduce bycatch without sacrificing catch of target species. If the goal of spatial closures is to reduce bycatch, our results suggest that dynamic management provides substantially better outcomes than classic static marine area closures. The use of dynamic ocean management might be difficult to implement and enforce in many regions. Nevertheless, dynamic approaches will be increasingly valuable as climate change drives species and fisheries into new habitats or extended ranges, altering species -fishery interactions and underscoring the need for more responsive and flexible regulatory mechanisms.

Developing unbiased estimates of incidental bycatch poses a challenge for species where fishing-induced mortality is a rare occurrence. Expanding rare mortality events using ratio estimators or bycatch of proxy species can result in highly variable estimates based on untested and often untestable assumptions. We estimated short-tailed albatross bycatch in a U.S. West Coast groundfish fishery using Bayesian time series modeling. The best model used a constant bycatch rate and inferred annual expected bycatch and variability using a Poisson distribution, given specified levels of observed effort. Fleet-wide bycatch estimates varied annually and peaked at 1.35 birds in 2011 (the year of the only observed mortality). The probability of exceeding the limit of five estimated takes in a 2-year period was very low throughout the time series, and estimated takes in the unobserved portion of the fleet are more likely with lower observer coverage and higher fishing effort. The Bayesian model-based approach avoids assumptions inherent in ratio estimators and proxy methods; it incorporates uncertainty, reduces volatility, and enables comparisons of bycatch estimates to management thresholds. This analytical approach offers natural resource managers a framework for estimating bycatch in data-limited contexts, which can result in better guidance for management actions and mitigation strategies.

Protected species bycatch can be rare, making it difficult for fishery managers to develop unbiased estimates of fishing-induced mortality. To address this problem, we use Bayesian time-series models to estimate the bycatch of humpback whales ( Megaptera novaeangliae ), which have been documented only twice since 2002 by fishery observers in the United States West Coast sablefish pot fishery, once in 2014 and once in 2016. This model-based approach minimizes under- and over-estimation associated with using ratio estimators based only on intra-annual data. Other opportunistic observations of humpback whale entanglements have been reported in United States waters, but, because of spatio-temporal biases in these observations, they cannot be directly incorporated into the models. Notably, the Bayesian framework generates posterior predictive distributions for unobserved entanglements in addition to estimates and associated uncertainty for observed entanglements. The United States National Marine Fisheries Service began using Bayesian time-series to estimate humpback whale bycatch in the United States West Coast sablefish pot fishery in 2019. That analysis resulted in estimates of humpback whale bycatch in the fishery that exceeded the previously anticipated bycatch limits. Those results, in part, contributed to a review of humpback whale entanglements in this fishery under the United States Endangered Species Act. Building on the humpback whale example, we illustrate how the Bayesian framework allows for a wide range of commonly used distributions for generalized linear models, making it applicable to a variety of data and problems. We present sensitivity analyses to test model assumptions, and we report on covariate approaches that could be used when sample sizes are larger. Fishery managers anywhere can use these models to analyze potential outcomes for management actions, develop bycatch estimates in data-limited contexts, and guide mitigation strategies.

Effective management of multispecies fisheries in large marine ecosystems is challenging. To deal with these challenges, fisheries managers are moving toward ecosystem-based fishery management (EBFM). Despite this shift, many species remain outside protective legislation or fishery management plans. How do species that fall outside of formal management structures respond to changes in fisheries management strategies? In 2011, the US West Coast Groundfish Fishery (WCGF) shifted management to an Individual Fishing Quota (IFQ) program. We used data collected by fisheries observers to examine the impact of this shift on elasmobranch catch (sharks, skates, rays). Historically, not all elasmobranchs were included in the WCGF Management Plan, making them vulnerable to fishing mortality. We grouped elasmobranchs into 8 groups based on 14 ecomorphotypes to examine relative catch within groundfish fishing sectors during the period 2002-2014. Of the 22 sharks and 18 skates and rays that these fisheries capture, 9 are listed as Near Threatened or greater on the IUCN Red List and 10 species are listed as Data Deficient by IUCN. The bycatch of 4 non-managed elasmobranch species was reduced under the IFQ program; IFQ management had no significant impact on the remaining 27 species caught by the IFQ fleet. Overall, catch of non-managed elasmobranchs was relatively low. We show that groups of ecomorphotypes co-occur within fisheries, suggesting natural management units for use in EBFM. This work helps identify gaps in monitoring and assessing the impact of management and policy on elasmobranch populations.

The Northwest Fisheries Science Center (NWFSC) West Coast Groundfish Observer Program (WCGOP) will brief the Council on the status of Pacific halibut bycatch estimates for the 2012 groundfish trawl and fixed gear fisheries (Agenda Item D.1.b, WCGOP Report). Additionally, WCGOP provided further analysis in response to a 2012 request by the Council’s Scientific and Statistical Committee (SSC) (Agenda Item D.1.b, WCGOP Response to SSC). The SSC is expected to review and provide comments on the reports. Council action under this agenda item is to review and provide guidance on the Pacific halibut bycatch estimates which will be submitted by the National Marine Fisheries Service (NMFS) to the International Pacific Halibut Commission Area (IPHC) for use in establishing the 2014 Pacific halibut total allowable catch.

This report presents observed and estimated bycatch of green sturgeon ( Acipenser medirostris ) in fishery sectors observed by the West Coast Groundfish Observer Program (WCGOP) and the At-Sea Hake Observer Program (A-SHOP) from 2002-2019. Three federal groundfish fisheries observed by the WCGOP and A-SHOP encountered green sturgeon over this time period, though none of these observations occurred during the most recent two years (2018 and 2019). These fisheries with observed green sturgeon bycatch include the limited entry (LE) bottom trawl fishery (active 2002-2010), the individual fishing quota (IFQ) bottom trawl fishery (active 2011-present), and the at-sea hake fishery (active 2002-present). observe distinct sectors of the groundfish fishery. The WCGOP observes the following groundfish sectors: IFQ (formerly LE) shore-based delivery of trawl-allocated groundfish and Pacific hake, LE and OA non-nearshore fixed gear; and state-permitted nearshore fixed gear sectors. The WCGOP also observes several state-managed fisheries that incidentally catch groundfish, including the California halibut trawl and ocean shrimp trawl fisheries, and the directed Pacific halibut fishery, which is permitted by the International Pacific Halibut Commission. The A-SHOP observes the IFQ fishery that processes Pacific hake at sea including catcher-processor, mothership, and tribal vessels. Details on how fishery observers operate in both the IFQ and non-IFQ sectors can be found online at the Fisheries Observation Program website.

Spatiotemporal predictions of bycatch (i.e., catch of nontargeted species) have shown promise as dynamic ocean management tools for reducing bycatch. However, which spatiotemporal model framework to use for generating these predictions is unclear. We evaluated a relatively new method, Gaussian Markov random fields (GMRFs), with two other frameworks, generalized additive models (GAMs) and random forests. We fit geostatistical delta-models to fisheries observer bycatch data for six species with a broad range of movement patterns (e.g., highly migratory sea turtles versus sedentary rockfish) and bycatch rates (percentage of observations with nonzero catch, 0.3%–96.2%). Random forests had better interpolation performance than the GMRF and GAM models for all six species, but random forests performance was more sensitive when predicting data at the edge of the fishery (i.e., spatial extrapolation). Using random forests to identify and remove the 5% highest bycatch risk fishing events reduced the bycatch-to-target species catch ratio by 34% on average. All models considerably reduced the bycatch-to-target ratio, demonstrating the clear potential of species distribution models to support spatial fishery management.

The spatial structure and dynamics of populations, their environment, interacting species, and anthropogenic stressors influences community stability and ecological resilience. Despite the importance of spatial processes in ecological outcomes and increasing desire to implement ecosystem-based management, fine-scale spatial dynamics have been rarely incorporated in marine fisheries management. However, advances in population modeling and data availability provide the necessary ingredients to address this disconnect between the fields of ecology and fisheries. We used random forests and spatial indices to quantify spatial heterogeneity and dynamics of US west coast demersal marine faunal density (biomass of a community or assemblage per unit area) and the total removals (catches plus discards) from the system by the groundfish bottom trawl fishery from 2002 to 2017. We expected spatial heterogeneity of removals and density to increase following implementation of depth and habitat closures - due to proximally increasing density gradients and fishing-the-line - and following catch shares because of fleet consolidation and behavioral consequences of eliminating the race to fish. However, we found mixed responses, where at the broadest community levels spatial variation in removals and density declined with habitat closures, while spatial autocorrelation of removals increased with habitat closures and declined with catch shares. Our results reveal a complex interdependence between spatial distributions of faunal density and fishery removals that has been absent in previous studies focusing on catch only, and shows how these patterns are shaped by marine policy. Values of spatial variation of density and removals were positively correlated within year (i.e., each responded with the same sign and timescale), while there was also evidence that interannual changes in the spatial variation of removals among years led those of density by one year (i.e., increases in patchiness of removals were followed by increased patchiness of density). These results hint at the presence of a stronger than expected top-down effect of fishing, given that this system is considered to be dominated by strong bottom-up effects of environmental variation on primary and secondary productivity.