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21 results for “bottom trawling”
Field and Model Data for Bottom Trawling Impacts in the North Sea
<p>This dataset includes both field measurement and modeled results of bottom trawling in the North Sea for the period of 1950-2020.</p>
Annual bottom trawling hours and hotspots in the Mediterranean for 2019
<p>An enhanced version of the R4AIS workflow (Galdelli et al., 2021) was used to process T-AIS data, with a poll frequency of 5 min, of fishing vessels operating in the Mediterranean Sea in 2019. Data of vessels categorized as bottom trawlers were aggregated to obtain yearly fishing hours at 0.1° and 0.5° resolution. Besides information of the number of vessels involved in the fishing activity and their nationality were retrived.</p> <p>Besides, statistically significant trawling hotspots of fishing activities in the Mediterranean 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> </p> <p>The present dataset includes layers of the annual bottom trawling activity and their hotspot in the Mediterranean (.shp; .csv) at both resolutions (0.1°; 0.5°)</p>
Figure 2 in Potential impacts of bottom trawling on species of skates (Rajiformes: Rajidae): the case of the Gulf of Cádiz and the Western Mediterranean
Figure 2. – Landings (kg) of Raja spp., Raja asterias, R. clavata and R. undulata from the Gulf of Cádiz (1985-2018).
Figure 1 in Potential impacts of bottom trawling on species of skates (Rajiformes: Rajidae): the case of the Gulf of Cádiz and the Western Mediterranean
Figure 1. – Marine areas included in the study: the Gulf of Cádiz and the Western Mediterranean Sea (Alboran Sea).
Cumulative and average bottom trawling fishing hours in the Mediterranean Sea for the period 2015-2022
<p>An enhanced version of the R4AIS workflow (Galdelli et al., 2021) was used to process T-AIS data, with a poll frequency of 5 min, of fishing vessels operating in the Mediterranean Sea during 8 years (2015-2022). Data of vessels categorized as bottom trawlers were aggregated to obtain cumulative (fahs) and average (mfahs) fishing hours by fishing category at 0.1° and 0.5° resolution.</p> <p>Maps of bottom trawling fishing activity were created for four main areas at 0.1° (Adriatic Sea, Aegean Sea, Balearic Sea and Levantine Sea) and at 0.5° for the Mediterranean basin.</p> <p> </p>
Dataset for "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data"
<p>Bathymetric point cloud data and ship log data used for the article "Quantifying the physical impact of bottom trawling based on high-resolution bathymetric data" by Mischa Schönke, David Clemens and Peter Feldens (<a href="https://doi.org/10.3390/rs14122782">https://doi.org/10.3390/rs14122782</a>)</p>
Data and Code for Analysis of Bottom Trawling Impact on Sedimentary Organic Carbon in the North Sea
<p>Data and Code for Analysis of Bottom Trawling Impact on Sedimentary Organic Carbon in the North Sea</p>
Data from: Bottom trawling affects fish condition through changes in the ratio of prey availability to density of competitors
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Selection of indicators for assessing and managing the impacts of bottom trawling on seabed habitats
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Data from: Bottom trawling and multi-marker eDNA metabarcoding surveys reveal highly diverse vertebrate and crustacean communities: A case study in an urbanized subtropical estuary
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Data from: Estimating sensitivity of seabed habitats to disturbance by bottom trawling based on the longevity of benthic fauna
Bottom fishing such as trawling and dredging may pose serious risks to the seabed and benthic habitats, calling for a quantitative assessment method to evaluate the impact and guide management to develop mitigation measures. We provide a method to estimate the sensitivity of benthic habitats based on the longevity composition of the invertebrate community. We hypothesize that long-lived species are more sensitive to trawling mortality due to their lower pace of life (i.e. slower growth, late maturation). We analyse data from box-core and grab samples taken from 401 stations in the English Channel and southern North Sea to estimate the habitat-specific longevity composition of the benthic invertebrate community and of specific functional groups (i.e. suspension feeders and bioturbators), and examine how bottom trawling affects the longevity biomass composition. The longevity biomass composition differed between habitats governed by differences in sediment composition (gravel and mud content) and tidal bed-shear stress. The biomass proportion of long-lived species increased with gravel content and decreased with mud content and shear stress. Bioturbators had a higher median longevity than suspension feeders. Trawling, in particular by gears that penetrate the seabed >2cm, shifted the community towards shorter-lived species. Changes from bottom trawling were highest in habitats with many long-lived species (hence increasing with gravel content, decreasing with mud content). Benthic communities in high shear stress habitats were less affected by bottom trawling. Using these relationships, we predicted the sensitivity of the benthic community from bottom trawling impact at large spatial scale (the North Sea). We derived different benthic sensitivity metrics that provide a basis to estimate indicators of trawling impact on a continuous scale for the total community and specific functional groups. In combination with high resolution data of trawling pressure, our approach can be used to monitor and assess trawling impact and seabed status at the scale of the region or broadscale habitat and to compare the environmental impact of bottom-contacting fishing gears across fisheries.
Data from: Estimating sensitivity of seabed habitats to disturbance by bottom trawling based on the longevity of benthic fauna
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Figure 5 in Potential impacts of bottom trawling on species of skates (Rajiformes: Rajidae): the case of the Gulf of Cádiz and the Western Mediterranean
Figure 5. – Catch Per Unit Effort (CPUE, kg/boat) for different species of skate in the Gulf of Cádiz (2015-2018) and in the Aboran Sea (2012-2018).
Figure 4 in Potential impacts of bottom trawling on species of skates (Rajiformes: Rajidae): the case of the Gulf of Cádiz and the Western Mediterranean
Figure 4. – Landings (kg) by month of Raja asterias, R. clavata and R. undulata in the Gulf of Cádiz (on average, between 2016-2018) and R. asterias in the Alboran Sea (on average, between 2012-2018, by the Andalusian fleet).
Figure 3 in Potential impacts of bottom trawling on species of skates (Rajiformes: Rajidae): the case of the Gulf of Cádiz and the Western Mediterranean
Figure 3. – Landings (kg) of Raja spp. and Raja asterias in the south-western Mediterranean, from the Alboran Sea (1985-2018).
Data from: Assessing bottom-trawling impacts based on the longevity of benthic invertebrates
1. Bottom trawling is the most widespread human activity directly affecting seabed habitats. Assessment and effective management of the effects of bottom trawling at the scale of fisheries requires an understanding of differences in sensitivity of biota to trawling. Responses to disturbance are expected to depend on the intrinsic rate of increase of populations (r), which is expected to be linearly related to the reciprocal of longevity. 2. We examine the relationship between the longevity of benthic invertebrates and their response to bottom trawling; both in terms of the immediate mortality following a trawl pass and their subsequent rates of recovery. We collate all available data from experimental and comparative trawling studies, and test how longevity influences these aspects of sensitivity. 3. The shortest-lived organisms (<1yr) increased in abundance shortly after experimental trawling, but showed no response to trawling in longer-term comparative studies. Conversely, the abundance of biota with a life-span >1yr decreased by ~9% immediately following a trawl pass. The effect of bottom trawling in comparative studies increased with longevity, with a 2-3× larger effect on biota living >10yr than on biota living 1-3yr. We attribute this difference to the slower recovery rates of the longer-lived biota. 4. The observed relationship between the intrinsic rate of population increase (r, our metric of recovery rate) and the reciprocal of longevity matches theoretical expectation and predicts that the sensitivity of habitats to bottom trawling is higher in habitats with higher proportions of long-lived organisms. 5. Synthesis and Applications. Where the longevity of a species or the longevity distribution of a community is known or can be inferred, our estimates of depletion and intrinsic rate of increase can be combined with high-resolution maps of trawling intensity to assess trawling impacts at the scale of the fishery or other defined unit of assessment. Our estimates of r may also be used to estimate recovery times following other forms of seabed disturbance.06-Sep-2018
Data from: Assessing bottom-trawling impacts based on the longevity of benthic invertebrates
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Figure 2a from: Shao K, Lin J, Wu C, Yeh H, Cheng T (2012) A dataset from bottom trawl survey around Taiwan. ZooKeys 198: 103-109. https://doi.org/10.3897/zookeys.198.3032
Figure 2a - Spatial coverage(fishing harbors of four regions)
Figure 1 from: Shao K, Lin J, Wu C, Yeh H, Cheng T (2012) A dataset from bottom trawl survey around Taiwan. ZooKeys 198: 103-109. https://doi.org/10.3897/zookeys.198.3032
Figure 1 - Taxonomic coverage. A Class B Order C Family.
Figure 2b from: Shao K, Lin J, Wu C, Yeh H, Cheng T (2012) A dataset from bottom trawl survey around Taiwan. ZooKeys 198: 103-109. https://doi.org/10.3897/zookeys.198.3032
Figure 2b - Spatial coverage (trawling routes)
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