Fisheries Research最新文献

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.

The mahseer populations in various regions of India are undergoing rapid declines due to factors such as unregulated fishing of juveniles and brood stock, severe degradation of aquatic ecosystems, and the construction of barrages, dams, and weirs as part of river valley projects. Given the significance of this species, it is crucial to assign high conservation value to mahseers in India. To safeguard this important resources, efficient conservation and propagation strategies must be planned and implemented throughout the country. Conserving mahseer fishery resources demands integrated efforts, culture fisheries, blending capture, and environmental programs, with strict enforcement of environmental laws. Taxonomic clarity within the Tor and Neolissochilus genus is crucial for effective conservation planning, given the endangered status of all mahseer species. Conservation efforts should be embedded in new hydel projects, utilizing artificial breeding and pond culture, while adaptive fishing regulations are needed to protect vulnerable spawning populations. However, comprehensive knowledge of the genetic deviation and population structure of wild endangered mahseer populations is currently lacking. This paper aims to review the evolutionary history, present status, and the importance of conservation for mahseers, while emphasizing the function of biological conservation and genetics in preserving their germplasm, promoting sustainable utilization, and enhancing their populations. Additionally, we propose new ideas and suggestions that can contribute to the conservation efforts aimed at protecting these magnificent mighty mahseers across the country.

Management decisions for the eastern oyster (Crassostrea virginica) fishery in Maryland are made at a finer spatial scale than the spatial data resolution of the current stock assessment. This mismatch creates concerns that the consequences of management actions and fishing activities are not being adequately represented when assessing fishery status. To produce a model that could support a participatory modeling process intended to differentiate results of fine-scale management actions we developed a method for conditioning a down-scaled oyster stock assessment model to produce a spatially-explicit operating model at the scale of individual oyster bars for eastern oysters in Chesapeake Bay, Maryland. To ensure that parameter values of the operating model were consistent with data at multiple scales we fitted the model to bar-specific harvest data during 2004–2020 and regional abundance estimates from the current Maryland Oyster Stock Assessment during 1999–2020. The operating model can then predict effects of different management actions, such as planting hatchery-reared oysters, addition of substrate, or modifying fishing regulations, at a bar-specific scale and compare outcomes among different scenarios. Model outputs included a suite of management performance metrics, including but not limited to oyster abundance and fishery harvest, that were important to stakeholders. These bar-specific scenarios would not have been possible using an operating model with the same spatial resolution as the current Maryland Oyster Stock Assessment. Accounting for fine scale spatial processes can be important to engaging participants and our model provides an expedient option to develop an operating model that downscales stock assessment models.

Fish parasites are widely used as biological indicators of stocks and populations of their hosts. In this work we examine the stability of the stock structure of Argentine anchovy, Engraulis anchoita, after a period of three decades using parasite tags. A total of 295 anchovies were examined for parasites. Two samples were collected at Northern stock (Necochea and El Rincón), two from the Southern stock (Rawson and San Jorge Gulf), and two from the intermediate zone between Northern and Southern stocks (San Matías Gulf and boundary between Northern and Southern stock). The structure and composition of both parasite infracommunities and component communities were analysed by uni and multivariate statistics. Our results showed certain compositional homogeneity after three decades as well as the presence of three groupings, with those from San Matias Gulf being part of a “central” stock or population distributed also outside the gulf on the continental shelf. This newly identified stock was probably overlooked in the previous study since all parasites were considered in the multivariate comparisons, whereas the present data were restricted to long-lived, and therefore more suitable biological tags, parasitic species. Further studies based on other kinds of evidence and carried out at broader temporal and spatial scales are necessary to corroborate the occurrence of a population in San Matías Gulf. In such a case, considering the ecosystem relevance of E. anchoita, the establishment of its temporal dynamics will be a first step for the conservation and safeguarding of the entire marine ecosystem at a regional scale.

Handling of crustaceans can result in injuries such as limb damage, reducing post-release survival and subsequent growth. Quantifying the impact of handling damage can provide insight into the effects of increased handling, which can occur when undersized animals are released by fishers or during translocations of animals between areas. We investigated the impact of handling on the Southern Rock Lobster (Jasus edwardsii) using three decades of scientific tag-recapture data from a no-fishing reserve. We used a Bayesian modeling approach with a modified Von Bertalanffy growth model which is robust to measurement error and Cormack-Jolly-Seber capture-recapture model to estimate growth and survival probability parameters. We found that even low levels of damage (1–4 appendages) can decrease growth by ∼ 10 % in the subsequent moult. Male lobsters suffered greater effects of handling-induced damage than did females, potentially due to the additional energy reserves available to brooding females.

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.

Climate change is expected to influence aquatic habitats and associated fish populations, yet we know little about the impact on recreational anglers. Our goal was to explore whether interannual fluctuations in waterbody surface area and other explanatory variables could be used as indicators of changes in angler fishing effort. Our approach leveraged a combination of remotely sensed waterbody surface area, environmental and fish population data, and onsite angler survey monitoring data for Devils Lake, North Dakota, USA during the open-water fishing period (May 1st to August 31st) for 9 years (1992–2021). The information was used to develop a dynamic waterbody size-angler effort model. Changes in waterbody surface area reliably predicted changes in angler effort (r² = 0.60). Increases in waterbody surface area led to increases in angler effort, and decreases in waterbody surface area led to decreases in angler effort. Our findings show promise that remotely sensed fluctuations in waterbody surface area could be used as an indicator of interannual angler effort dynamics. Dynamic waterbody size-angler effort models could provide managers the ability to predict changes in angler effort via climate-related hydrological cycles that affect the size and distribution of waterbodies on the landscape.

Evaluating drivers and the predictability of catch is valuable for the management of mixed fisheries. Drivers can represent or help to identify levers for management and predictable catch compositions are a key component of simulation tools and dynamic management strategies. But modelling mixed fisheries can be challenging due to the large number of taxa, and analysis typically focuses on a few key species or highly aggregated taxa.

Here we employ seven types of stacked and joint species distribution models to explore the drivers and predictability of trawl-level catches in an ocean prawn trawl fishery, in New South Wales, Australia. Catch data was sourced from an observer program, with 130 taxa able to be modelled. The main drivers of catch composition were latitude, depth, and seasonality represented here by water temperature. Water column mixing, lunar illumination, and fishing effort were also important for some taxa. Up to 60–80 taxa were predicted with good predictive skill (AUC>0.8, >35 % decline in mean absolute error relative to an intercept-only model), and an additional 40–60 taxa were predicted with lower but still useful predictive skill (AUC>0.7, 25–35 % decline in error). However, the level of predictive skill varied considerably among model type.

The best framework for prediction was stacked random forests using a hurdle modelling approach, followed by a spatial joint species distribution model. Our results show that predictive models at a fine spatial-temporal and taxonomic resolutions can be a viable information tool for highly mixed fisheries, but these tools ultimately need to be tested against specific management objectives and performance metrics, such as spatial closures and bycatch:target catch ratios.

Identification of genetic population structures in classical marine species—species with large population sizes, wide range distributions, and high dispersal potential—can be a challenging task because of expectedly weak genetic signals of population structure. The Japanese jack mackerel, Trachurus japonicus, is a classical marine species and one of the most important fishery resources in the East Asian seas. In this study, we tested the hypothesis of genetic panmixia in the Japanese jack mackerel using genome-wide SNP analyses coupled with geographic and reproductive phenology information. We generated a highly contiguous genome assembly and performed Genotyping by Random Amplicon Sequencing-Direct (GRAS-Di) to produce at least 19,904 SNPs that were genotyped in 614 samples from seas around the Japanese archipelago. Genetic population structure analyses did not reveal any evidence of genetic differentiation. Neither geographical barriers in the Japanese archipelago nor phenological differences in reproductive timing affected the genetic population structure. Overall, these findings were consistent with the interpretation of genetic panmixia, providing evidence for high genetic connectivity across the population’s distribution. Considering the current knowledge about the distribution and life history of T. japonicus, we suggest that the panmictic status may reflect a metapopulation structure with source-sink dynamics and/or extensive gene flow across the distribution range.

We conducted a Productivity Susceptibility Analysis (PSA) to empirically assess the vulnerability risk of marine ornamental reef fish in Sri Lanka for exploitation. We considered distribution, accessibility, ecological niche, and market price as susceptibility attributes, while fecundity, larval development, maximum length, and longevity were productivity attributes. The vulnerability score, demand, and market price were used to assess species prioritization, and then compositions of the prioritized species were computed. The veracity of primary and secondary data collected on susceptibility and productivity attributes was confirmed by interviewing traditional fishers in situ. The IUCN and present PSA classifications for the medium susceptibility risk species were comparatively assessed. Four species out of 17 medium susceptibility risk species were encountered as the medium vulnerability risk species for exploitation. The Pacific cleaner shrimp (Lysmata amboinensis) emerged as the highest prioritized species. In addition, we observed significant differences in the species’ status assessed through the PSA approach compared to the IUCN status. The study affirms that demand and market prices substantially influence the exploitation vulnerability of species, and the PSA offers a promising multidisciplinary approach to evaluating intrinsic and extrinsic factors in conservation ecology compared to widely used IUCN status for assessing extinction risk. Furthermore, the present findings have practical implications, as they warrant essential policy changes for conserving the prioritized species and the medium vulnerability risk species encountered in the present research to extinction risk.