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603 results for “fisheries”
FIGURE 59 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 59. Salmo tigridis, from top: holotype, FFR 1250, 220 mm SL; paratype, FFR 1253, 201 mm SL.
FIGURE 57 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 57. Salmo opimus, from top: holotype, FFR 3047, 171 mm SL; paratype, FFR 3048, 165 mm SL.
FIGURE 54 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 54. Salmo labecula, from top: holotype, FFR 3056, 208 mm SL; paratype, FFR 3058, 197 mm SL.
FIGURE 53 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 53. Salmo kottelati, from top: holotype, FFR 3180, 205 mm SL; paratype, FFR 3182, 172 mm SL.
FIGURE 17 in Notes on shark and ray types at the South China Sea Fisheries Research Institute (SCSFRI) in Guangzhou, China
FIGURE 17. Dorsal view of the holotype of Springeria stenosoma SCSFRI O 0065 (female 520 mm TL).
FIGURE 2 in Notes on shark and ray types at the South China Sea Fisheries Research Institute (SCSFRI) in Guangzhou, China
FIGURE 2. Lateral view of Squalus mitsukurii (CSIRO H 7403–02, female 632 mm TL) from Taiwan.
Figure 2 from: Carvalho-Batista A, Negri M, Pileggi LG, Castilho AL, Costa RC, Mantelatto FL (2014) Inferring population connectivity across the range of distribution of the stiletto shrimp Artemesia longinaris Spence Bate, 1888 (Decapoda, Penaeidae) from DNA barcoding: implications for fishery management. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 271-288. https://doi.org/10.3897/zookeys.457.6569
Figure 2 - Dendrogram based on Neighbor-Joining distance method of COI gene sequences of individuals of Artemesia longinaris. Localities represent the analyzed specimens. Numbers are bootstrap support values (1000 replicates); values below 50% are not shown.
Figure 4 from: Carvalho-Batista A, Negri M, Pileggi LG, Castilho AL, Costa RC, Mantelatto FL (2014) Inferring population connectivity across the range of distribution of the stiletto shrimp Artemesia longinaris Spence Bate, 1888 (Decapoda, Penaeidae) from DNA barcoding: implications for fishery management. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 271-288. https://doi.org/10.3897/zookeys.457.6569
Figure 4 - Haplotype network of Artemesia longinarisaccording to Median-Joining analysis. Each circle represent one haplotype found in the localities (53 haplotypes in 60 specimens). The size of the circle of each haplotype is proportional to its frequency in the sample. Each small dash represents a mutational step.
Figure 1 from: Carvalho-Batista A, Negri M, Pileggi LG, Castilho AL, Costa RC, Mantelatto FL (2014) Inferring population connectivity across the range of distribution of the stiletto shrimp Artemesia longinaris Spence Bate, 1888 (Decapoda, Penaeidae) from DNA barcoding: implications for fishery management. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 271-288. https://doi.org/10.3897/zookeys.457.6569
Figure 1 - Southwest Atlantic collection sites. Map showing the localities of the specimens of Artemesia longinaris analyzed: 1 Macaé, Brazil 2 Ubatuba, Brazil 3 Santos, Brazil 4 Cananéia, Brazil 5 São Francisco do Sul, Brazil 6 Rio Grande, Brazil 7 Mar del Plata, Argentina. The gray band indicates the complete geographical distribution of Artemesia longinaris.
Figure 3 from: Carvalho-Batista A, Negri M, Pileggi LG, Castilho AL, Costa RC, Mantelatto FL (2014) Inferring population connectivity across the range of distribution of the stiletto shrimp Artemesia longinaris Spence Bate, 1888 (Decapoda, Penaeidae) from DNA barcoding: implications for fishery management. In: Wehrtmann IS, Bauer RT (Eds) Proceedings of the Summer Meeting of the Crustacean Society and the Latin American Association of Carcinology, Costa Rica, July 2013. ZooKeys 457: 271-288. https://doi.org/10.3897/zookeys.457.6569
Figure 3 - Phylogram for individuals of Artemesia longinaris inferred from Maximum Likelihood analysis of COI gene sequences. Localities represent analyzed specimens. Numbers are bootstrap support values (1000 replicates); values below 50% are not shown.
Seasonal ocean forecasts to improve predictions of Dungeness crab catch rates, co-developed with state and tribal fishery managers
<p>Historical (hindcast) and September initialized forecast fields from the J-SCOPE system (more information here: https://www.nanoos.org/products/j-scope/). The historical fields are annual averages while the forecasts are averaged monthly. The fields here were used to generate the CPUE models described in Norton et al. (2023). </p> <p>Abstract from the paper: The commercial Dungeness crab (Metacarcinus magister) fishery in Oregon and Washington (USA) is one of the most valuable fisheries in the region, but it experiences high interannual variability. These fluctuations have been attributed to environmental drivers on seasonal and annual timescales. In this study, researchers and state and tribal fisheries managers develop a statistical model for Dungeness crab catch per unit effort (CPUE) to help inform dynamic management decisions in Oregon and Washington. Fishing observations were matched to seasonally forecast and lagged ocean conditions from J-SCOPE, a regional forecast system (http://www.nanoos.org/products/j-scope/). Inclusion of dynamic and lagged ocean conditions improved model skill compared to simpler models, and the best model captured intraseasonal trends and interannual variability in catch rates, and spatial catch patterns. We also found that model skill relied on fishing behaviour, which varies interannually, highlighting the need for advanced fishing behaviour modelling to reduce uncertainty. The relationships between catch rates and ocean conditions may help elucidate environmental influences of catch variability. Forecast products were co-designed with managers to meet their needs for key decision points. Our results illustrate a seasonal forecasting approach for management of other highly productive, but also dynamic, invertebrates that increasingly contribute to global fisheries yield.</p>
Identification and characterization of Western Province reef fisheries; Developing management and conservation protocols using traditional ecological knowledge, underwater monitoring and catch assessments
<p>Solomon Islands has highly biodiverse coral reef ecosystems critically important to cultural identity and socio-economic security. Because Solomon Islanders maintain among the highest global fish consumption rates largely from inshore fisheries valued at USD$65 million yr<sup>-1</sup>, maintaining these resources is critical to livelihoods and health. Among these resources are coral reef fish that form (fish) spawning aggregations (FSA). For these species, FSAs are the primary means of population replenishment and form the basis of a trophic web ranging from detritivores to marine megafauna. FSAs are highly vulnerable to overfishing and in Solomon Islands have experienced increasing fishing pressure from a changing economy and a domestic export fishery. Recent estimates show Western Province exporting at least 6 mt mo<sup>-1</sup> to Honiara markets, with an unknown but substantial quantity of this supply derived from FSAs. In Solomon Islands, marine tenure remains a core element of coral reef management, but its effectiveness relies on community awareness and participation in monitoring. The project seeks to improve site-based and national scale enabling conditions for FSA management through: (1) evaluating FSA sites known to be experiencing fishing; (2) providing awareness presentations to traditional reef owners; (3) training local communities and dive operator staff in developing appropriate monitoring protocols; (3) implementing these protocols at known FSA sites; (4) co-developing EAFM plans with traditional reef owners and dive operators; (5) providing information sharing from successful regional LMMAs; (6) working to improve enforcement of existing FSA regulations and local and provincial scales; and (7) building consensus to adapt existing regulations to improve management effectiveness.</p>
UTILIZATION OF CHLORELLA VULGARIS IN FISH FEEDING IN FISHERY INDUSTRY
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Figure 4 in A review of amphidromous freshwater fishes of the Chocó biogeographical region (Colombia and Ecuador): diversity, ecology, fisheries and conservation
Figure 4. – Some amphidromous species from the rivers of the Chocó Biogeographic Region. A: Eleotris picta; B: Gobiomorus maculatus; C: Awaous transandeanus; D: Hemieleotris latifasciata; E: Sicydium hildebrandi.
Supporting fisheries management with genomic tools: a case study of kingklip (Genypterus capensis) off southern Africa
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Data from: The response of correlated traits following cessation of fishery-induced selection
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Data from: Temporal genetic stability and high effective population size despite fisheries-induced life-history trait evolution in the North Sea sole.
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Data from: Functional genetic diversity in an exploited marine species and its relevance to fisheries management
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Identification and characterization of Western Province reef fisheries; Developing management and conservation protocols using traditional ecological knowledge, underwater monitoring and catch assessments
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Data from: Demonstrating multiple benefits from periodically harvested fisheries closures
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International Brain Laboratory public data
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