Canadian Journal of Fisheries and Aquatic Sciences

O_LIAssessing the degree to which at-risk species are regulated by density dependent versus density independent factors is often complicated by incomplete or biased information. If not addressed in an appropriate manner, errors in the data can affect estimates of population demographics, which may obfuscate the anticipated response of the population to a specific action.\nC_LIO_LIWe developed a Bayesian integrated population model that accounts explicitly for interannual variability in the number of reproducing adults and their age structure, harvest, and environmental conditions. We apply the model to 41 years of data for a population of threatened steelhead trout Oncorhynchus mykiss using freshwater flows, ocean indices, and releases of hatchery-born conspecifics as covariates.\nC_LIO_LIWe found compelling evidence that the population is under strong density dependence, despite being well below its historical population size. In the freshwater portion of the lifecycle, we found a negative relationship between productivity (offspring per parent) and peak winter flows, and a positive relationship with summer flows. We also found a negative relationship between productivity and releases of hatchery conspecifics. In the marine portion of the lifecycle, we found a positive correlation between productivity and the North Pacific Gyre Oscillation. Furthermore, harvest rates on wild fish have been sufficiently low to ensure very little risk of overfishing.\nC_LIO_LISynthesis and applications. The evidence for density dependent population regulation, combined with the substantial loss of juvenile rearing habitat in this river basin, suggests that habitat restoration could benefit this population of at-risk steelhead. Our results also imply that hatchery programs for steelhead need to be considered carefully with respect to habitat availability and recovery goals for wild steelhead. If releases of hatchery steelhead have indeed limited the production potential of wild steelhead, there are likely significant tradeoffs between providing harvest opportunities via hatchery steelhead production, and achieving wild steelhead recovery goals.\nC_LI

Management of data-limited populations is a key challenge to the sustainability of fisheries around the world. For example, sockeye salmon (Oncorhynchus nerka) spawn and rear in many remote coastal watersheds of British Columbia (BC), Canada, making population assessment a challenge. Estimating conservation and management targets for these populations is particularly relevant given their importance to First Nations and commercial fisheries. Most sockeye salmon have obligate lake-rearing as juveniles, and total abundance is typically limited by production in rearing lakes. Although methods have been developed to estimate population capacity based on nursery lake photosynthetic rate (PR) and lake area or volume, they have not yet been widely incorporated into stock-recruit analyses. We tested the value of combining lake-based capacity estimates with traditional stock-recruit based approaches to assess population status using a hierarchical-Bayesian stock-recruit model for 70 populations across coastal BC. This analysis revealed regional variation in sockeye population productivity (Ricker ), with coastal stocks exhibiting lower mean productivity than those in interior watersheds. Using moderately-informative PR estimates of capacity as priors reduced model uncertainty, with a more than five-fold reduction in credible interval width for estimates of conservation benchmarks (e.g. SMAX - spawner abundance at carrying capacity). We estimated that almost half of these remote sockeye stocks are below one commonly applied conservation benchmarks (SMSY), despite substantial reductions in fishing pressure in recent decades. Thus, habitat-based capacity estimates can dramatically reduce scientific uncertainty in model estimates of management targets that underpin sustainable sockeye fisheries. More generally, our analysis reveals opportunities to integrate spatial analyses of habitat characteristics with population models to inform conservation and management of exploited species where population data are limited.

Accurate estimation of post-release survival is fundamental to fisheries stock assessment and effective management. Conventional tag-return studies and acoustic telemetry are commonly used to estimate this probability, yet each approach has limitations when applied independently. Using gag (Mycteroperca microlepis) as a case study, we integrated data from a large-scale conventional tagging program and an acoustic telemetry experiment within a discrete-time statistical modeling framework that links relative recapture risk with telemetry-derived fate. This approach enabled estimation of post-release survival across a broad gradient of capture depths representative of recreational fishing conditions. Estimated survival was high in shallow waters ({approx}97%) but declined with increasing capture depth, consistent with depth-related barotrauma. Applying model predictions to depth distributions from the recreational fishery yielded annual and monthly post-release survival probabilities. Annual estimates were consistent with values assumed in recent stock assessments, while monthly values highlighted seasonal patterns potentially relevant for management. This integrated framework advances post-release survival estimation by combining the extensive sample sizes and environmental coverage characteristic of conventional tagging data with the direct fate observations provided by acoustic telemetry, and offers a transferable approach for other highly targeted fisheries.

A key challenge in ecosystem-based fisheries management is sustainably harvesting co-occurring species and populations that differ in their vulnerability to fishing. This challenge is exemplified in western Alaska Chinook salmon, where recent population declines have led to closures of in-river subsistence fisheries, but identifying the cause of these declines is limited by an inability to identify the river of origin for marine-caught fish in offshore fisheries that target more abundant species and populations. This problem is particularly acute for estimating the impacts of bycatch on individual salmon populations which have demographic independence but no genetic differentiation from which stock assignments can be made. Here we use machine learning approaches to assess the efficacy of using the microchemical history preserved in fish otoliths to assign individuals to their river of origin in western Alaska. We tested the classification ability of three machine learning algorithms (Random Forest, K-Nearest Neighbors, and Support Vector Machines) combined with two time series smoothing techniques (Moving Average and Generalized Additive Models) to classify Chinook salmon to their river of origin using otolith time series data. Model accuracy ranged from 71.9% to 92.5%, with optimal performance achieved by Random Forest applied to GAM-smoothed data. Watershed-specific performance ranged from 86.8% to 93.7%, with most misclassifications occurring between spatially proximate Kuskokwim and Nushagak rivers. Raw predicted probabilities from classification algorithms were calibrated to reflect true class probabilities, enabling the incorporation of model results into decision analyses with explicit consideration of misclassification risk tolerance. The success of these models offers immediate utility for estimating marine mortality impacts across the regions three major river systems as well as an opportunity to understand commercial fisheries impacts on individual populations at substantially finer spatial scales than had been previously possible.

Bycatch impacts on non-target species present significant management problems in diverse fisheries throughout the world. Despite successful efforts to minimize bycatch in US West Coast Pacific Hake fisheries, these impacts remain a concern, particularly for sensitive populations of Chinook Salmon. NOAA Fisheries needed predictive models to estimate proportions of Chinook Salmon Evolutionarily Significant Units (ESUs) expected in bycatch. We used genetic mixture analysis to estimate ESU proportions from at-sea bycatch between 2008 and 2015. Using latitude as a predictor and applying jackknife cross validation, we found Dirichlet regression more accurately estimated abundant ESUs, whereas multinomial logistic regression performed better with rare ESUs. This targeted, ESU-specific approach showed the spatial distribution of sensitive stocks in bycatch and supported NOAAs obligations to forecast impacts on listed ESUs. The overarching goal of this continuing work is to maximize sustainable harvest while protecting threatened and endangered Chinook Salmon ESUs.

Restoration of salmon populations in the upper Lewis River Basin depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (Project) operated by PacifiCorp and Cowlitz PUD (Utilities), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Coho salmon (Oncorhynchus kisutch) population upstream of the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult Coho salmon at Merwin Dam, the lower most dam within the Project, and transporting them by truck to spawn above Swift Dam, the upper most dam within the Project; and (2) the collection of out-migrating juvenile Coho salmon at the downstream collection facility at Swift Dam for transport and release below the Project. The reintroduction program began once the downstream collection facility at Swift Dam was commissioned in late-2012 with the first year of transport data being collected in 2013. Over the past decade, the Utilities have been collecting data on juvenile outmigrants and adult fish returns at the dams. The need to construct a life cycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (>15) of data collection are needed to adequately measure the life cycle production of coho salmon. Use of past data to construct models could help inform future data collection and provide a framework that can be updated annually to measure trap and haul program performance within a life cycle context (Note: Data are not currently available from PacifiCorp. Contact organization Chris Karchesky for further information). Because Coho salmon can live as long as five years, estimating demographic parameters for Coho salmon populations over their life cycle requires at least 10 or more years of data collection. Over the past decade, PacifiCorp has been collecting data on fish collection efficiency and the numbers of adult and juvenile salmon transported around the Lewis River dams, providing sufficient data to formulate a life cycle model that can guide future data collection efforts and provide preliminary information to resource managers The goal of the statistical life cycle model was to estimate annual production and survival during two critical life-stage transitions (1) the freshwater production from escapement of adults released upstream of Swift Dam, and the collection of downstream migrating juveniles at the passage facility at Swift Dam, and (2) the smolt-to-adult survival from the time of collection at Swift Dam to their return as adults. We used the Beverton-Holt stock-recruitment model to estimate juvenile production from the number of spawners. This approach allowed us to test for density dependence at current spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. Productivity was then expressed as a function of the number of juveniles collected and transported downstream of the Project. Because juvenile Fish Collection Efficiency (FCE) directly affects the number of juveniles that survive to continue downstream migration, FCE is a primary determinant of fish production. Consequently, the modeling framework is well suited to evaluate the performance of trap and haul programs within a life cycle context. The objectives of this study were to: (1) gather and collate available data on adult and juvenile Coho salmon at Merwin and Swift dams, (2) quantify adult escapement, juvenile abundance, and the age at outmigration and adult return, (3) describe, formulate, and fit the integrated population model (IPM) to the data, and (4) summarize our findings, identify data gaps, and identify potential opportunities for future studies that could provide information used to improve model estimation and inference. Our key findings were: (1) over and above the number of spawning females, FCE was the primary factor affecting productivity of Coho salmon above Swift Dam, (2) smolt-to-adult return (SAR) rates were relatively high considering that harvest was included in the estimate, averaging about 4.5% and ranging as high as 12.9%, and (3) juvenile capacity upriver of Swift Dam was difficult to estimate due to the limited range in spawning females over the time series of data, suggesting the model may be improved by collecting data at higher spawner abundances. In addition, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE = 1, was 64 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river versus the ocean, the model estimates should help inform fishery managers about the overall role that fish collection at Swift Dam plays in the recovery and sustainability of Lewis River Coho salmon. By providing the model with (1) more years of data, (2) higher numbers of spawning females, and (3) data on age at juvenile migration in relation to age at adult return greater certainty in the estimates of capacity and SAR can be attained. Ultimately, information provided by the model can assist in the evaluation and continued improvement of the current trap and haul program to support anadromous fishes in the Lewis River Basin. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/651546v1_ufig1.gif" ALT="Figure 1"> View larger version (106K): org.highwire.dtl.DTLVardef@1fb0bf1org.highwire.dtl.DTLVardef@cd0576org.highwire.dtl.DTLVardef@21aa4aorg.highwire.dtl.DTLVardef@330024_HPS_FORMAT_FIGEXP M_FIG C_FIG Cover. Looking upstream on the Lewis River at Merwin Dam, Washington, August, 2024. Photograph by John Plumb, U.S. Geological Survey. Conversion Factors O_TBL View this table: org.highwire.dtl.DTLVardef@4e45d8org.highwire.dtl.DTLVardef@cb7879org.highwire.dtl.DTLVardef@528ad0org.highwire.dtl.DTLVardef@1176401org.highwire.dtl.DTLVardef@a6bed6_HPS_FORMAT_FIGEXP M_TBL C_TBL

Environmental and biological processes acting on fish larvae can drive fishery cohort strength, but predictive ability oftentimes falls short, and larval abundance is generally considered more useful as a proxy for spawning biomass. Under a changing ocean, studies that relate environmental covariates, larval abundance, and fishery recruitment are worthy of continued research, especially in data-limited contexts. We focus on a popular, recreational-only, multispecies saltwater bass fishery (genus Paralabrax) whose population status and recovery potential are uncertain. We used 54 years of ichthyoplankton data (1963-2016) and a species distribution model to 1) deconstruct species-specific standardized indices of larval abundance, 2) test these indices as indicators of adult stock status or predictors of future fishery recruitment, and 3) evaluate spatiotemporal trends in their population dynamics relative to environmental variables. Contrary to expectation, species-specific larval abundance predicted future catch, with recent elevated larval abundance suggesting imminent fishery recovery. Additionally, we identified strong relationships with environmental variables, thereby providing additional tools for predicting fishery recruitment and anticipating population change. Our findings paint a path forward for improving estimates of current and future fishery status under changing natural and anthropogenic influences and the incorporation of ecosystem considerations into fishery management.

The U.S. Fish and Wildlife Service monitors species-specific waterfowl (ducks, seaducks, geese, and brant) harvest through two hunter surveys, one that estimates the total harvest for each waterfowl group, and a second that estimates the species composition of each waterfowl group. Point estimates for species-specific harvest can be computed by multiplying the estimated total harvest by the estimated proportion of the total harvest of each species. However, to date, no uncertainty estimates have been available. Here, we combine these two data sources to provide species-specific harvest estimates at the state and flyway level while characterizing the uncertainty via Bayesian estimation. We take a similar approach to Smith et al. (2022), providing both estimates that treat yearly data as independent and estimates that share information across years via a random walk process. We then discuss the advantages and disadvantages of each approach.

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.

The hockey-stick (HS) stock recruitment relationship (SRR) has been widely used as an empirical alternative to conventional SRRs such as the Beverton-Holt (BH) and Ricker (RI) models. However, the management performance and risks associated with estimating maximum-sustainable-yield (MSY) reference points (RPs) based on HS remain insufficiently understood. This study first defines deterministic and stochastic MSY RPs under the HS model and provides an overview of their properties. We then conduct simulation experiments to investigate the bias and management consequences that arise when MSY RPs are estimated from the HS model (HS-derived MSY RPs) rather than from the true SRR (e.g., BH) across a range of biological and stochastic parameters, with particular focus on scenarios with insufficient data contrast. Our results show that HS-derived MSY RPs tend to exhibit higher bias but lower variance than MSY RPs derived from the true SRR. Management strategy evaluation simulations further reveal that management procedures combining HS-derived MSY RPs with adaptive model learning and some precautionary measures gradually reduce this bias and achieve average spawning biomass and yield that are comparable to those obtained under management based on the true BH SRR. We also show that the management effectiveness of the precautionary measures depends on life-history traits and recruitment variability. These findings indicate that although HS-derived MSY RPs may be biased and require cautious use, combining them with appropriate precautionary measures allows management to remain robust while limiting variability and yield losses. This broadens the range of management options that are available for supporting sustainable fisheries management.

An organisms body condition describes its mass given its length and is often positively associated with fitness. The condition of Atlantic cod (Gadus morhua) in the Baltic Sea has declined dramatically since the early 1990s, possibly due to increased competition, food limitation, and hypoxia. However, the effect of biotic and abiotic variables on body condition have not been evaluated at local scales, which is important given spatial heterogeneity. We evaluate changes in distribution, experienced environmental conditions, and individual-level condition of cod in relation to covariates at different spatial scales using geostatistical models with spatial and spatiotemporal random effects. Oxygen, sprat biomass, and temperature were positively related to condition, and depth negatively associated, but the effect sizes of these variables were small--spatial and spatiotemporal latent variables explained almost five times more variation than fixed effects. We also show that accounting for the heterogenous distribution of cod leads to both lover levels and steeper trends over time in experienced oxygen compared to those in the environment. Understanding the drivers of spatiotemporal variation in body condition is critical for predicting responses to environmental change and to effective fishery management; yet low explanatory power of covariates on individual condition constitutes a major challenge.

Aggregation-based fisheries are notorious for booms and busts driven by aggregation discovery and subsequent fishing-induced collapse. However, environment-driven sporadic recruitment in some since-protected populations has delayed recovery, suggesting recruitment-limitation may be a key driver of their population dynamics and fishery recovery potential. To glean insight into this dynamic, we focused on an overexploited temperate aggregate spawner (Barred Sand Bass; Paralabrax nebulifer) and leveraged a long-term mark-recapture data set spanning different oceanographic and harvest histories in a custom Bayesian capture-mark-reencounter modeling framework. We coupled this demographic analysis with long-term trends in sea surface temperature, harvest, adult and juvenile densities, and historical accounts in the literature. Our results point to a history of multidecadal windows of fishing opportunity and fishing-induced collapse that were largely driven by sporadic, warm water recruitment events, which may be externally sourced. Nevertheless, we found that environment-driven sporadic recruitment was not a factor impeding recovery following the last collapse, as recruitment remained elevated due to novel, anomalously warm conditions. Despite signs of incipient population recovery, spawning aggregations remain absent, indicating other potential factors (e.g., continued fishing during spawning season, residual Allee effects) have delayed fishery recovery to date. Aggregate spawner populations that are dependent on sporadic recruitment, especially those at their geographic margins, are thus highly susceptible to sudden and potentially extended periods of collapse, making them ill-suited to high CPUE fishing that occurs on spawning grounds. If the goal is to balance the protection of spawning aggregations with long-term fishery sustainability, then limiting aggregation-based fishing during spawning season may be the best insurance policy against collapse and recovery failure.

Catch inequality--the disproportionate distribution of catch across anglers-- is a fundamental but overlooked driver of recreational fisheries dynamics. Here, we use 11 years (2012-2022) of compulsory angler report cards to characterize long-term catch dynamics in the specialized recreational steelhead (Oncorhynchus mykiss) fishery in California, U.S.A. Spatialized catch data reveal the fishery is principally supported by wild fish, despite evidence of widespread hatchery straying. California steelhead appear to represent the most catch-unequal recreational fishery studied yet, exhibiting a statewide Gini coefficient of 0.81. Across basins, inequality varies substantially but remains relatively stable over time and flow conditions; high inequality is primarily driven by significant proportions of zero-catch anglers. We find the relationship between sample size and inequality measures is especially influential in fisheries data. Hence, we develop a three-prong approach for identifying minimal sample sizes required for robust Gini estimation. Across basins and years, an average minimum of 77 report cards were required for the present fishery. Collectively, these findings demonstrate the necessity of considering catch inequality in fisheries management, particularly when utilizing angler data. Graphical AbstractN.a.

Understanding variation in age at maturity is important for endangered species recovery because older, larger adults contribute disproportionately to the next generation. Conditions in early life stages may have underappreciated impacts on age at maturity. Our study objective was to associate adult age of individually tagged wild, spring/summer Chinook Salmon (Oncorhynchus tshawytscha) outmigrating from the Snake River (Idaho and Washington, USA) in 1998-2020 with covariates measured during juvenile and subadult stages. We used a hierarchical Bayesian ordinal probit regression model to estimate statistical effects of juvenile body length, seasonal migration timing or river temperature, transported or in-river hydrosystem passage, river flow, and a large-scale ocean index. Results indicated notable carryover effects consistent with underlying biological mechanisms related to growth and development, in which shorter juvenile length and later seasonal migration timing were associated with older adults. These biological and behavioural factors were more important than riverine or marine environmental conditions examined. Our study suggests that managers and decision makers should consider carryover effects from the juvenile life stage on age structure in conjunction with survival.

Red Knots (Calidris canutus rufa) rely on Atlantic horseshoe crab (Limulus polyphemus) eggs in the Delaware Bay to refuel during northward migration. Intensive harvest of horseshoe crabs in the 1990s contributed to declines in Red Knot numbers. In 2013, the Atlantic States Marine Fisheries Commission adopted an Adaptive Resource Management (ARM) framework to balance sustainable horseshoe crab harvest with ecosystem integrity and Red Knot recovery, requiring annual stopover population estimates. We estimated the 2025 passage population of Red Knots at Delaware Bay using a Bayesian analysis of a Jolly-Seber mark-resight model which accounts for population turnover and imperfect detection. We also evaluated change in migration timing between 2011 and 2025 with model-derived estimates of arrival at the Delaware Bay each year. The 2025 passage population was 54,043 individuals (95% credible interval: 47,926-61,928), an increase of approximately 17% over 2024 and only the second year since 2011 to exceed 50,000 individuals. Despite the increase, overlapping credible intervals across years indicate a stable stopover population. Migration timing has remained consistent, with 50% of the population typically arriving by 18 May and no evidence of advancement since 2011. These findings provide meaningful input for the ARM framework, supporting sustainable harvest of horseshoe crabs while maintaining adequate foraging opportunities for Red Knots and other shorebirds. Parts of the Introduction, Methods, and Appendices were originally published in Lyons (2024) and are summarized herein.

Estuaries across the globe have been subject to extensive abiotic and biotic changes and are often monitored to track trends in species abundance. The San Francisco Estuary is a novel ecosystem that has been deeply altered by anthropogenic factors, resulting in fish declines over the past 100 years. To track these species declines, a patchwork of monitoring programs has operated regular fish surveys dating back to the late 1950s. While most of these surveys are designed to track population-scale changes in fish abundance, they are methodologically distinct, with different target species, varying spatial coverage and sample frequency, and differing gear types. To remediate for individual survey limitations, we modeled pelagic fish distributions with integrated data from many sampling programs. We fit binomial generalized linear mixed models with spatial and spatiotemporal random effects to map annual trends in the distribution of detection probabilities of striped bass, Delta smelt, longfin smelt, threadfin shad, and American shad for the years 1980 to 2017. Detection probabilities decreased dramatically for these fishes in the Central and South Delta, especially after the year 2000. In contrast, Suisun Marsh, one of the largest tidal marshes on the west coast of the United States, acted as a refuge habitat with reduced levels of decline or even increased detection probabilities for some species. Our modeling approach demonstrates the power of utilizing disparate datasets to identify regional trends in the distribution of estuarine fishes.

Despite increasing calls for sustainability and ecosystem objectives to manage fishing gear interactions with bottom habitats there are few quantitative approaches for assessing risks from bottom contact fishing. Risk assessments for bottom longline fisheries are particularly challenging due to a lack of information for estimating bottom contact areas from longline gear. In this paper, we demonstrate how data sensors and video cameras deployed on fishing gear can be used to quantify the bottom contact area for longline trap and hook fishing gear from the British Columbia Sablefish fishery. Our bottom contact estimates indicate that Sablefish fishing risks to bottom habitat are low in the majority of fishing areas, since 91.8% of the area fished is expected to have had zero bottom contact over the last 17 years. For the other 8.2% of Sablefish fishing areas that experience some contact from fishing gear, the majority are only contacted once. This indicates that most habitats contacted by Sablefish gear can be expected to have a minimum of 17 years to recover between subsequent bottom contact events. We demonstrate an approach for estimating fisheries bottom contact that can be widely implemented across longline fisheries. Our findings address key data gaps in bottom impacts research for longline gear fisheries, allowing fishing risks to be quantified over fine spatial scales. Such quantitative approaches for habitat risk assessment can provide essential information for management decisions aimed at determining acceptable trade-offs between habitat preservation and fishery benefits.

The recovery of marine mammals from historical over-exploitation in the 1970s represents one of the largest changes in trophic structure in the northeast Pacific Ocean over the last century, for which the impacts on key forage species such as Pacific Herring (Clupea pallasii) are poorly understood. This has prompted hypotheses that increasing marine mammal populations are the primary cause for productivity declines for some fish stocks and their lack of recovery to historical abundance levels. In this study, we evaluate such a hypothesis for Pacific Herring by quantifying historical predation rates by key predators including cetaceans (Pacific Humpbacks, Grey Whales), pinnipeds (Stellar Sea Lions, Harbour Seals), and piscivorous fish (Pacific Hake). Predation mortality is quantified via a novel approach that integrates a single-species catch-at-age model with estimates of predator consumption derived from bioenergetic models. We found that predator consumption, largely driven by Humpback Whales, explained increasing Pacific Herring natural mortality rates in recent years and could be used to forecast future mortality. Incorporating higher future natural mortality rates produced higher estimates of current stock status (1.09-1.2B0) based on lower estimates of equilibrium unfished biomass (17.5-20.3 kt). Conversely, models that assumed mortality was more like the historical average had lower stock status (0.63B0) and higher estimates of unfished biomass (32.4 kt). We demonstrate a practical approach for ecosystem modelling that can be used to develop operating model scenarios for management strategy evaluation, improving scientific defensibility by removing an element of analyst choice for future mortality scenarios. We discuss how simpler modifications to single-species model assumptions can be more pragmatic for providing fisheries management advice, while more complex multi-species or ecosystem models might provide more nuanced insights for exploring research questions related to multi-species ecosystems and fisheries interactions.

We investigate environmental drivers of pre-season abundance of US West Coast legal-sized male Dungeness crab (Cancer magister), with the goal of developing an environmental index that can be used to forecast crab abundance in advance of the fishery. A conceptual life history approach is used to generate life-stage-specific and spatio-temporally-specific mechanistic hypotheses regarding oceanographic variables that influence survival at each life stage. Linear models are fit using the logarithms of pre-season abundance estimates of the coastal population of legal-sized male Dungeness crab as the dependent variable and environmental drivers from outputs developed using a regional oceanographic model for the California Current System as the independent environmental variables. Using different model selection methods, we show that the so-called best models differ substantially among model selection approaches, illustrating the need to carefully choose performance metrics for model selection. Since our goal was to forecast crab abundance, we selected the best model using a cross-validation metric that accounts for the time-series nature of the data. The resulting best models suggest that the mechanisms that drive preseason abundance differ among regions widely recognized for spatially and seasonally varying dominant physical processes. We found that the processes determining pre-season abundance of legal-sized male Dungeness crab could be identified with sufficient precision to enable a predictive skill, suggesting that the predictions may be useful for management purposes. Moreover, we found that transport (within and between regions), as well as temperature were likely drivers of pre-season abundance, highlighting that future studies should focus on multiple processes.

Every year, 100 hectares of saltmarsh in the United Kingdom are lost due to sea level rise. The remaining areas are threatened by land conversion, agricultural activities, and climate change. There are important economic consequences to saltmarsh loss, as saltmarsh provides valuable ecosystem services including flood protection, carbon sequestration, and nursery habitat for commercially fished species. Quantifying the economic value of these ecosystem services can help target policies for saltmarsh restoration, or managed realignment, of new saltmarsh areas. In this study, we quantify the economic value of saltmarsh as a habitat for commercially fished species by developing a residency index. The residency index weights the relative importance of saltmarsh along a species lifecycle by explicitly incorporating the target species life histories and the estimated proportion of time it spends in saltmarsh at juvenile and adult life stages. Using this index, we estimate the value of saltmarsh to UK commercial fisheries landings. We find that UK saltmarsh contributes annually between 16.7% and 18.2% of total UK commercial landings for European seabass (Dicentrarchus labrax), European plaice (Pleuronectes platessa), and Common sole (Solea solea). Our findings highlight the importance of saltmarsh protection and restoration. Furthermore, our approach provides a general framework that integrates population ecology methods and economic analyses to assess the value of saltmarsh and other coastal habitats for fisheries worldwide.