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3 results for “mixed fisheries”

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zenodo44/100

Data from: Identifying priority areas for spatial management of mixed fisheries using ensemble of multi-species distribution models. Panzeri D. et al., 2023, Fish and Fisheries

<p>Panzeri D.<sup>1</sup>, Russo T., Arneri E., Carlucci R., Cossarini G., Isajlović I., Krstulović &Scaron;ifner S., Manfredi C., Masnadi F., Reale M., Scarcella G., Solidoro C., Spedicato M.T., Vrgoč N., W. Zupa, Libralato S<sup>2</sup>.</p> <p><sup>1&nbsp;</sup>dpanzeri@ogs.it<br> <sup>2&nbsp;</sup>slibralato@ogs.it</p> <p>Spatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the&nbsp;effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e-SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient-boosting machine methods in a training and testing protocol. The e-SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three-dimensional physical-biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e-SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e-SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.</p> <p>Data (csv)&nbsp;for Panzeri et al. 2023</p> <p>1.&nbsp;<a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Ensemble_density_F&amp;F_D.Panzeri_et_al_2023.csv: CSV file with density values&nbsp; (column pred) in terms of number of individuals (log N/km2) for each species (column sp) and life stage (column age) for each grid cell (X = longitude and Y = latitude).</a>&nbsp;</p> <p>2.&nbsp;<a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Getis_hotspot_F&amp;F_D.Panzeri_et_al_2023.csv: CSV file with Getis ord Gi* values (column Gi) derived from the previous file 1, developed for each species and life stage for each grid cell (X = longitude and Y = latitude).</a></p> <p>3.&nbsp;<a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Multispecies_HotSpot_F&amp;F_D.Panzeri_et_al_2023.csv: Frequency map expressed as the number of species for each grid cell (column freq) that has the hotspot (previous file 2) above the third quartile.</a></p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2023View details →
dryad36/100

Origins of green turtle fishery bycatch in the Central Pacific revealed by mixed genetic markers

<p>Longline fishing vessels, such as those that target tuna or billfish, also unintentionally catch endangered marine turtle species on the high seas. The stock composition of this bycatch is often unknown but potentially complex, with individuals coming from many possible origins on an ocean-basin scale. To better understand the stock composition of green turtle (<em>Chelonia</em> <em>mydas</em>) bycatch, we obtained 46 turtles, 27–78 cm in curved carapace length, caught by Hawaii- and American Samoa-based pelagic longline fishing vessels across large areas of the North- and South-central Pacific. We genotyped these at nine microsatellite loci and one mitochondrial DNA marker and used a baseline of 1,043 nesting female green turtles from beaches across the Pacific for population assignment and mixed-stock analysis. By analyzing both marker types jointly we were able to increase power and genetically resolve ten baseline stocks of nesting females with mean self-assignment and simulated accuracies of 75–97%. Above the Equator, green turtle bycatch was composed mostly of individuals from Hawaiian and Eastern Pacific stocks, with a small number from the Western Pacific. Below the Equator, the most common stocks in the bycatch were from Australia and the Coral Sea, American Samoa and French Polynesia, and the Galápagos Islands. Overall, turtles originating from East, West, and Central Pacific breeding populations were major components of the bycatch, suggesting that the geographic ranges of these populations overlap across large tracts of ocean during the pelagic life history stages.</p>

opencc-zeroFeb 2023View details →
dryad36/100

Origins of green turtle fishery bycatch in the Central Pacific revealed by mixed genetic markers

Open the record for dataset details and reuse information.

publicFeb 2023View details →

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