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4 results for “fishing activity hotspots”
HIdden fishing activity hotspots in the Adriatic Sea in 2019
<p>The animated image shows the unreported fishing activity hotspots in the Adriatic in 2019. The datasets report the fishing activity ban areas in the Adriatic over the months and the reported, unreported, total, unreported/total fishing hour distributions across the months estimated by our workflow for vessel data processing (Coro et al., 2023).</p>
Hidden and total fishing activity hotspots in the Mediterranean Sea between 2017 and 2022 estimated from AIS data
<p>Hidden and total fishing activity hotspots in the Mediterranean Sea between 2017 and 2022 estimated from AIS data</p>
Fishing activity hotspots in the Mediterranean and Atlantic Seas at 0.5°
<p>Statistically significant hotspots of fishing activities in the Mediterranean and Atlanti Seas were identified by the application of the Getis-Ord Gi statistic (Getis and Ord 2010) though the statistical software R using the globalG.test function (spdep package). The function computes a global test for spatial autocorrelation using a Monte Carlo simulation approach. It tests the null hypothesis of no autocorrelation against the alternative hypothesis of positive spatial autocorrelation. Then the local spatial autocorrelation was tested calculating the Gi statistic, using the local_g_perm function (dfdep package), which indicates the strength of the clustering.</p> <p>Categorization of hotspots was performed, according to the Gi value and the p-value of a folded permutation test obtained for each grid cell, as follows:</p> <ul> <li>Gi>0 and p_value <=0.01 as Very hot</li> <li>Gi>0 and p_value <=0.05 as Hot</li> <li>Gi>0 and p_value <=0.1 as Somewhat hot</li> <li>Gi<0 and p_value <=0.1 as Somewhat cold</li> <li>Gi<0 and p_value <=0.05 as Cold</li> <li>Gi<0 and p_value <=0.01 à Very cold</li> </ul> <p>Grid cells with a p-value > 0.1 were categorized as Insignificant.</p> <p>The analyses were performed on cumulative fishing activity data at 0.5° resolution of seven different gears separately for the two macroareas.</p> <p>The dataset presented includes for each area maps of each gear hotspot and spatial layers of the gears hotspots (.shp; .csv)</p>
Fishing activity hotspots in case study areas of the Mediterranean, Black and Atlantic Seas at 0.1°
<p>Statistically significant hotspots of fishing activities in specific case study areas (Adriatic Sea, Aegean Sea, Balearic Sea, Baltic Sea, Bay of Biscay, Black Sea, Levantine Sea and North Sea) were identified by the application of the Getis-Ord Gi statistic (Getis and Ord 2010) though the statistical software R using the globalG.test function (spdep package). The function computes a global test for spatial autocorrelation using a Monte Carlo simulation approach. It tests the null hypothesis of no autocorrelation against the alternative hypothesis of positive spatial autocorrelation. Then the local spatial autocorrelation was tested calculating the Gi statistic, using the local_g_perm function (dfdep package), which indicates the strength of the clustering.</p> <p>Categorization of hotspots was performed, according to the Gi value and the p-value of a folded permutation test obtained for each grid cell, as follows:</p> <ul> <li>Gi>0 and p_value <=0.01 as Very hot</li> <li>Gi>0 and p_value <=0.05 as Hot</li> <li>Gi>0 and p_value <=0.1 as Somewhat hot</li> <li>Gi<0 and p_value <=0.1 as Somewhat cold</li> <li>Gi<0 and p_value <=0.05 as Cold</li> <li>Gi<0 and p_value <=0.01 à Very cold</li> </ul> <p>Grid cells with a p-value > 0.1 were categorized as Insignificant.</p> <p>The analyses were performed on cumulative fishing activity data at 0.1° resolution of nine different gears separately for the eight case study areas.</p> <p>Trawling hotspot cells categorized as “Very hot” (highly pressured) and “Hot” and “Somewhat hot” (medium pressured) were intersected with repositories of stocks and species-observation data (Coro et al., 2023) in order to retrieve information of species potentially caught by those fishing activities.</p> <p>The dataset presented includes for each case study area tables of species potentially caught within the trawling hotspots, maps of each gear hotspot, spatial layers of the gears hotspots (.shp; .csv)</p>
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