Fisheries Research最新文献

The northern rockfish (Sebastes polyspinis) is an economically valuable, long-lived species distributed over the continental shelf of the North Pacific Ocean. Ages for this species which can be in excess of 80 years comprise an essential component of models for assessing population status and are crucial for fisheries management. Traditional microscope-based methods of estimating age using otoliths can be time-intensive and prone to reader variability. We explored the application of Fourier transform near infrared (FT-NIR) spectroscopy coupled with multimodal convolutional neural networks (MMCNN) for age prediction. Our study included 2613 FT-NIR scans and associated ages of northern rockfish otoliths from years 2013–2019, with ages ranging from 3 to 66 years. The optimal MMCNN model demonstrated strong performance, yielding an R² of 0.92 and an RMSE of 3.38 for the training set and an R² of 0.89 and an RMSE of 3.74 for the test set. Spectral information in the 11,500 to 4000 cm⁻¹ wavenumber range, otolith weight, and other biological/geospatial data contributed to age predictions that were comparable to traditional age estimates. Despite challenges, FT-NIR spectroscopy coupled with MMCNN emerged as a promising alternative for age estimation in long-lived species. This approach, while demonstrating effectiveness for northern rockfish, could be a valuable tool for diverse fish species, supporting sustainable fisheries practices and population monitoring.

The catches of the Spanish purse seine fleet targeting tropical tunas in the Indian Ocean have been systematically sampled in port and at sea by scientific research centres since the fleet began to operate in the 1980s. During these samplings, some silky shark (Carcharhinus falciformis) specimens were found in the wells of these vessels which had not previously been recorded by at-sea scientific observers. To quantify the occurrence of these undetected incidental catches of silky sharks, this study compared two sets of data: on-board data collected by scientific observers and port sampling data. The European Union's long-term data collection program (PNDB), coordinated by the Spanish Fisheries Secretariat, provides on-board data collected by scientific observers as well as port sampling data which is collected while a vessel arrives to the port to begin unloading. The sampling focused on target species up until January 2021, when sampling started including non-target species as well. The datasets examined in this study are from January 2021 to December 2022. The results show significant differences between silky shark sizes observed on-board and those measured in port. A logistic model indicates a significant probability of observing silky sharks in wells, with a strong goodness of fit and high discrimination capacity as a function of the total catch of the fishing operation. Further analysis reveals differences in average sizes and weights of silky sharks caught in free-schools compared with those caught with tuna schools aggregated beneath Fish Aggregating Devices or FADs. The presence of unnoticed silky sharks suggests unreported captures, indicating that rates of mortality of the species are underestimated. In conclusion, the research emphasizes the need to address undetected silky shark bycatch in the purse seine fishery in the Indian Ocean. Obtaining accurate data and understanding the magnitude of this bycatch are crucial for developing management strategies that mitigate the impact and promote the sustainability of silky shark populations in the region.

Spiny lobster (Panulirus argus) fishers in Florida garner the highest price for lobsters that are sold to the live export market. Lobsters are “graded” using a visual qualitative assessment before export to remove any lobsters unlikely to survive shipping. The current qualitative grading process, while effective in reducing mortality, is conservative and results in a significant number of healthy lobsters being sold at lower prices for the frozen market. This study sought to develop lobster grading methods that more accurately predict lobster mortality to increase the proportion of lobsters suitable for the high-value live export market; thus, we compared two alternative grading/mortality predictor methods to the current exporter grading method. For this, we examined nine candidate lobster reflexes (i.e., appendix turgor and movement in response to a probe) and eight other lobster physiologic and morphometric parameters (i.e., number of injuries, molt stage, nutritional condition via blood serum protein, presence of shell disease, presence of tail fan necrosis, sex, and size) to develop two reflex action mortality predictors. The first mortality predictor was developed using reflex impairment alone, and the second mortality predictor was a quantitative mortality model developed with as many parameters as necessary to increase the model’s performance in predicting mortality. The classification accuracy of these mortality assessments (reflex impairment and quantitative mortality model) was then compared with the current qualitative grading process that occurs prior to shipping. The current grading process was a moderate predictor of mortality (area under the receiver operating characteristic curve, AUC 0.807), which correctly predicted the outcome (survival or mortality) 74.5 % of the time. Both mortality models performed better than the current grading process. A logistic regression indicated reflex impairment alone was a significant predictor of mortality (AUC 0.897), which was able to correctly predict mortality 88 % of the time. The quantitative mortality model included three predictors – blood serum protein, reflex impairment, and collection month – and was also a significant predictor of mortality (AUC 0.938) and had the highest accuracy (90 %) of the three assessments we examined. Results from this study show that mortality assessments using reflex impairment and health indicators can successfully predict mortality in P. argus. These mortality assessments could be applied at fish houses to increase the value of the fishery (3–9 %, $1.71 million USD/season) by increasing the number of lobsters sold for live export.

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.

Indices of relative abundance directly inform how population abundance changes over time, providing one of the most important pieces of information for a stock assessment. Ideally, indices of abundance should be calculated based on fishery-independent survey data. Survey data are characterized by a spatially random or fixed sampling design, and consistent employment of the same fishing gear and fishing operation across time. However, the unavailability of survey data for most tuna species means that the derivation of abundance indices for these species comes solely from fishery-dependent catch-per-unit-effort (CPUE). We conduct two simulation experiments, based on real fishery-dependent longline data, to quantitatively evaluate the impacts of reduced fishing effort on the standardized longline CPUE for bigeye tuna in the eastern Pacific Ocean. The key findings of the two simulation experiments are 1) a reduced spatial coverage of CPUE data leads to increased bias in the abundance index; 2) the index bias has a minor long-term trend if the reduced spatial coverage of CPUE data is not caused by local depletion; and 3) that bias has a positive long-term trend (i.e., hyper-stable abundance index) if the reduced spatial coverage of CPUE data co-occurs with a local depletion in the abandoned area. This bias, however, can be significantly reduced if the CPUE standardization model includes a temporal correlation structure in spatiotemporal random fields. In addition, the CPUE standardization model provides more realistic estimates of the coefficient of variation of fish abundance when its spatiotemporal random fields are assumed to be correlated in time. This study underscores the necessity of accounting for the temporal correlation structure in spatiotemporal random fields in cases where local depletion and depletion-driven fishery contraction co-occur.

We fit a biphasic Lester Model to back-calculated size-at-age data for Atlantic bluefin tuna (Thunnus thynnus) captured in the western Atlantic management area that had been genetically assigned to either the western (Gulf of Mexico) or eastern (Mediterranean) spawning stocks. We tested the hypothesis that spawning-stock variation exists in age-at-maturity for this species using a Bayesian approach to incorporate and compare the support for different growth models and maturity scenarios considered for the western spawning stock. The biphasic Lester Model out-performed the uniphasic von Bertalanffy model and showed good fits for describing individual growth variability in Atlantic bluefin tuna. The Lester Model provided estimates of individual age-at-maturity and spawning, from which spawning ogives were generated and compared to two reproductive scenarios currently considered for the western spawning stock; either an early (age at 50 % maturity at 4 years) or late maturity scenario (age at 50 % maturity at 10). The results derived from the Lester Model demonstrate a lack of stock-specific variation in reproductive dynamics for Atlantic bluefin tuna, and provide support for an early maturity scenario for the western spawning stock.

Capelin (Mallotus villosus) populations on the Newfoundland shelf collapsed in the early 1990s, coinciding with a regime shift and greatly reduced capelin and groundfish biomasses which both persist to this day. The biphasic nature of this stock’s history suggest it may experience nonlinear dynamics, which are difficult to predict using linear models. This study explores the application of Empirical Dynamic Modelling (EDM) nonlinear, nonparametric time series forecasting tools to capelin biomass data, seeking to detect nonlinear dynamics, compare performance of linear and nonlinear multivariate predictive models, identify drivers of capelin biomass using convergent cross-mapping, and measure the sign and strength of capelin species interactions. We found capelin dynamics were nonlinear, and multivariate EDM predictive models returned equal or improved model diagnostics to linear models in most situations. We identified long-term climate dynamics and timing of sea ice retreat as the primary drivers of capelin dynamics, but some indications of potential top-down effects from Greenland halibut were also detected. Atlantic cod biomass, and capelin catch were investigated as potential drivers of capelin dynamics, but both were found more likely to be driven by capelin dynamics. Overall, our results support the idea that capelin dynamics are mostly bottom-up driven, and that capelin itself is a driver of its predators, suggesting that the overall ecosystem may be largely bottom-up driven. This study also clearly identifies the utilities of EDM as a complementary tool for stock assessments by detecting and forecasting nonlinear stock dynamics, and identifying and characterizing relationships between stock biomass and the factors which drive it.

Individual and environmental factors may influence gamete characteristics and contributions to recruitment in fishes. We tested for the influence of maternal, abiotic, and biotic factors on egg diameter and quality (i.e., oil droplet diameter) for walleye Sander vitreus in Escanaba Lake, Wisconsin, during 2018–2023 (omitting 2020). Analyses were conducted on fish captured once and for the same individuals captured multiple times during our study period. In the single-capture analysis, increasing maternal length was weakly related to larger egg diameter and oil droplet size. Increased yellow perch abundance was somewhat related to increased intra-clutch variation, whereas a later ice-off date was related to reduced intra-clutch variation. Fish that spawned later had more variable egg and oil droplet diameters. Among fish that were sampled over multiple years, individual identity was a strong predictor of egg and oil diameter. Our results suggest that regulations that preserve among individual variation in egg traits could increase the chances that environmental conditions will be favorable for spawning and recruitment for at least some fish.

The potential fish provisioning services of the Ria Formosa lagoon (Portugal) were calculated for single cohorts of 7 commercially fished species, based on densities of juveniles sampled with beach seines on a monthly basis over a 17-month period at 41 locations. The potential maximum yield per recruit (F_0.1 criteria) was calculated for vegetated (V) and unvegetated (UV) habitat for low and high natural mortality values. Vegetated habitat enhanced yield (g m⁻²) of 5 of the 7 species, with the greatest enhancement for the herbivore Sarpa salpa (137 and 150 fold for low and high M). At F_0.1, the calculated total potential yield of the 7 cohorts was 463 tons (low M) and 333 tons (high M), worth EUR 5,649,084 and 3,651,881, respectively. Mean annual landings of the 7 species from 1997 to 2017 ranged from 407 to 577 tons, with a mean of 495 tons (s.e. = 11.1), highlighting the importance of the lagoon nursery as a major source of recruits for local small-scale coastal fisheries. The methodology used here is the first to calculate the potential maximum yield and the corresponding fishing mortality (F_0.1) for single cohorts and for different habitats within an important fish nursery. It provides more realistic values of potential fish provisioning services and economic contribution to local fisheries than studies that do not consider fishing mortality.