Climate change is proving to be a driving factor reshaping the distribution and altering the movement of marine species, dynamics of which are crucial for sustainable development and marine resources management. However, how Pacific Ocean squids – boasting the salient biological features of a one-year life span and strong adaptive abilities, and which support more than 25% of global squid catches – respond to climate change is overlooked. We address this knowledge gap by constructing spatio-temporal generalized additive mixed models based on hundreds of thousands of digitized Chinese squid-jigging logbooks covering three Pacific stocks of two squid species (Ommastrephes bartramii and Dosidicus gigas) spanning 2005 – 2018. Here we show the relationships between environmental variables and local abundance of squids (reflected by response curves) track changes in climate; the squid biomass peaks and troughs coinciding with La Niña and El Niño events, respectively are moderate in contrast to the effects of directional climate change. We find substantial poleward shifts by squids inhabiting low latitude and middle latitudes. These findings have broad implications both for food security and open ocean ecosystem dynamics.
Abstract With consideration of sophisticated modern commercial fisheries, the commonly used metric catch per unit effort (CPUE) may not be a reasonable proxy for generating abundance indices (AIs) for all species. Presumably, spatiotemporal scale is a critical factor that affects the accuracy of local/aggregated AIs derived from spatial modelling approaches, thus it is necessary to evaluate how scale affects scientific estimates of abundance. We explored three commonly utilized AI proxies, including aggregated catch (CatchAI), aggregated effort (EffortAI), and CPUEAI from the perspective of accuracy and spatial representational ability using a neural network (NN) model at different spatiotemporal scales. As a case example, we grouped the Chinese fleet's Northwest Pacific neon flying squid (Ommastrephes bartramii) fishery dataset (2009–2018) at four spatial scales (0.25° × 0.25°, 0.5° × 0.5°, 1° × 1°, 2° × 2°) to construct monthly and annual resolution models. The results showed that for both simulated and real datasets, AIs based on catch data had better accuracy, consistency, and spatial representational ability compared to CPUE and effort-dependent AI models at all spatial scales. Relative to the finest spatial scale, only results from the model with 0.5° × 0.5° resolution preserved enough distributional detail to reflect the known migration route for O. bartramii. Model results exhibited large variation dependent on spatial scale, particularly amongst CPUEAI scenarios. We suggest that scale comparisons among potential proxies should be conducted prior to AIs being used for applications such as population trends in stock assessment.
Abstract Despite their growing socio‐economic importance globally, relatively little is understood about how crustacean stocks are assessed, which has potential to compromise fishery sustainability, especially under heavy exploitation and environmental changes. To inform stock assessment model application for emergent fisheries, we evaluated model use for crustacean stocks available in the RAM Legacy Database (RAMLDB) and the evolution of model use for four case‐study fisheries, emphasizing the relationship between data availability and model complexity. Differences in model use between FAO fishing regions and crustacean species sub‐groups were identified. Only 60.9% of crustacean stocks in the RAMLDB identified the model used for assessment. For the remaining stocks, we collected ancillary data to fill the information gaps, amounting to 92.5% of crustacean stocks in RAMLDB. Of these, model complexity varied from count‐based to environmentally explicit statistical catch‐at‐length methods, but tended to be data intensive, likely due to biases towards regions with more developed fishery management programmes. Furthermore, regional comparisons indicated that crustaceans are only well‐assessed in a few geographical hotspots. The progression of model use over time was inconsistent between case‐study fisheries, being driven by myriad factors including data availability, confidence in biological processes and ecological considerations. Our findings can be used as a resource to help inform model choice for fisheries management. Towards the goal of seeking global best practices for crustacean stock assessments, future work should address knowledge gaps in regional stock assessment model use and conduct comparative studies to evaluate stock‐specific costs and benefits relating to model complexity.
Single-species fisheries management (SSFM) is applied to many fisheries ecosystems around the world. The associated ecological impacts are usually not well understood due to the lack of considering trophic interactions among species in the ecosystem. This impedes the implementation of SSFM in an ecosystem context and reduces our ability to understand the possible ecological impacts of fishing activities. This study focuses on two economically important species in the Jiaozhou Bay, China: the short-lived, fast-growing, and relatively abundant Japanese mantis shrimp ( Oratosquilla oratoria ) and the long-lived, slow-growing, and less abundant Korean rockfish ( Sebastes schlegelii ). We evaluated how varying trophic interactions influenced O. oratoria and S. schlegelii (i.e., target-species) who were managed under constant fishing pressure. The increase of fishing pressure to other species (i.e., non-target species) was beneficial to O. oratoria and S. schlegelii . O. oratoria was more sensitive to the decrease of fishing pressure to other species. The predation mortality of age-0 O. oratoria increased with the increased fishing pressure to other species. The predation mortality of age-1 O. oratoria and age-0 S. schlegelii had negative relationships with the fishing pressure to other species. Age-1 S. schlegelii seemed not to be sensitive to the changes in trophic interactions. The predation mortality of O. oratoria and S. schlegelii had bigger changes than the starvation mortality after fishing changed. It suggested the prey-predator relationship had a bigger impact than the food competition. The increase of high-trophic-level fish Johnius belangerii fishery positively impacted O. oratoria , but negatively impacted S. schlegelii . S. schlegelii was more sensitive to the changes of the low-trophic-level fish Pholis fangi fishery. Given the complex dynamics of ecosystems, this study highlights the importance of species-specific responses of fishes to shifting trophic interactions in fisheries management.
Climate change influences marine environmental conditions and is projected to increase future environmental variability. In the North Atlantic, such changes will affect the behavior and spatiotemporal distributions of large pelagic fish species (i.e., tunas, billfishes, and sharks). Generally, studies on these species have focused on specific climate-induced changes in abiotic factors separately (e.g., water temperature) and on the projection of shifts in species abundance and distribution based on these changes. In this review, we consider the latest research on spatiotemporal effects of climate-induced environmental changes to HMS’ life history, ecology, physiology, distribution, and habitat selection, and describe how the complex interplay between climate-induced changes in biotic and abiotic factors, including fishing, drives changes in species productivity and distribution in the Northwest Atlantic. This information is used to provide a baseline for investigating implications for management of pelagic longline fisheries and to identify knowledge gaps in this region. Warmer, less oxygenated waters may result in higher post-release mortality in bycatch species. Changes in climate variability will likely continue to alter the dynamics of oceanographic processes regulating species behavior and distribution, as well as fishery dynamics, creating challenges for fishery management. Stock assessments need to account for climate-induced changes in species abundance through the integration of species-specific responses to climate variability. Climate-induced changes will likely result in misalignment between current spatial and temporal management measures and the spatiotemporal distribution of these species. Finally, changes in species interactions with fisheries will require focused research to develop best practices for adaptive fisheries management and species recovery.
Fisheries monitoring in the United States exists in many forms and serves many functions due to geographically varying objectives, practices, technology, institutional structures, and funding. In the U.S and abroad, diverse catch methods commonly exist for the same stock, thus monitoring and reporting strategies need to be tailored to unique operational needs. Common management challenges include funding limitation, survey design, coverage, and implementation. We describe three innovative examples of fisheries monitoring in the United States. These stories of success and failure can inform the design and implementation of new monitoring pilots and aid crafting both regional and national policies. We explore the innovative vessel monitoring and electronic logbook practices across multiple sectors for Gulf of Mexico red snapper (Lutjanus campechanus). Then, we examine a unique monitoring program that produces critical, near real-time genetic and population surveys for sockeye salmon (Oncorhynchus nerka) in Bristol Bay, Alaska. Our final case study describes the many fishery-dependent and -independent data streams for American lobster (Homarus americanus) in New England. Across all monitoring cases exists an explicit focus on the most critical aspects of organism life history. We find strong cross-institutional working relationships and adept agency coordination are imperatives in instances of stocks occupying multiple state or federal boundaries. Our results suggest the most effective approaches address the unique data needs of a fishery, and for this, thorough understanding of both biological and socioeconomic aspects of the fishery is a prerequisite. Ultimately, the monitoring program should jointly incentivize compliance while promoting continued and evolving interaction between resources users, scientists, and management.
Abstract Climate-induced environmental variability is proving to be a driving factor reshaping the distribution and altering the movement of marine species. However, how Pacific Ocean squids, with their 1-year life span and adaptive abilities, and which support >25% of global squid fisheries, respond to environmental variability is poorly understood. We address this knowledge gap by constructing spatio–temporal models for two squid species in three fishing grounds (Ommastrephes bartramii in the northwest Pacific Ocean and Dosidicus gigas in the eastern Pacific Ocean) using generalized additive mixed models based on data from digitized Chinese squid-jigging logbooks for 2005–2017. The relationships between environmental variables and local abundance of squids reflected by environmental and traditional spatial response curves track changes in climate. The peaks and troughs in squid biomass coincide with La Niña and El Niño events, but are moderate in contrast to the effects of directional climate-induced environmental variability. We find substantial poleward shifts by squids inhabiting low and middle latitudes. These findings have broad implications for food security and open ocean ecosystem dynamics.
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