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40 results for “fishing activities”
Fishing activities and trajectories for 2 fishing vessels
<p>This data set provides the pseudo-positions in space and time of two fishing vessels and the associated activities (fishing, cruising, stopped, recorded by an on board observer). It supports the analyses provided in a paper published in Methods in Ecology and Evolution and the methods of the R package m2b (https://cran.r-project.org/package=m2b). For privacy concerns, original latitude, longitude, time and vessels id were modified. Spatial data were scaled and centred to a fictional position (R'lyeh position, Lovecraft 1928) keeping the relative geometry unchanged (acceleration, time between two positions....). Time and vessel id were modified in the same manner, keeping the relative properties of the tracks unchanged (time succession, different vessel id...). Vessel id and time are purely fictional and follow the historical context proposed by Lovecraft (1928) in the R'lyeh surroundings. Again, if the absolute spatial and temporal description of the fishing track were changed, their relative mathematical properties are conserved and can support behaviour detection based on relative movement analysis.</p> <p> </p> <p>For the data_vessel.csv file (csv file with header), the variables are</p> <p>x : pseudo longitude</p> <p>y : pseudo latitude</p> <p>t : pseudo time in year-month-day hour:minutes:second format</p> <p>b: fishing activity, namely "fishing", "cruising", "stopped"</p> <p>id: unique id by vessels (fictional names).</p> <p><br> Reference</p> <p>H. P. Lovecraft, "The Call of Cthulhu" (1928)</p> <p> </p>
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>
Fig. 1 in Antioxidant activity of bee products added to water in tebuconazole-exposed fish
Fig. 1. Levels of TBARS (nmol MDA mg-1 protein) and GSH (µmol GSH g-1 of wet tissue) in Rhamdia quelen after exposure to 16.6% of LC 50 of tebuconazole, to bee product, and to tebuconazole + bee product for 96 h. Different small letters indicates statistical differences between the means (ANOVA followed by Tukey´s multiple range test). Mean ± SEM; n = 10. * P <0.05.
FIGURE 3 in Daily rhythm of locomotor and reproductive activity in the annual fish Garcialebias reicherti (Cyprinodontiformes: Rivulidae)
FIGURE 3 | Contextual modulation of locomotor activity of Garcialebias reicherti. Total daily locomotor activity for isolated (n = 10) and paired fish (n = 10). Each dot represents the mean number of events for each fish. *shows statistical significance (see p value in the main text). Box height from upper to lower quartile, whiskers represent standard deviation, median shown by horizontal line.
FIGURE 2 in Daily rhythm of locomotor and reproductive activity in the annual fish Garcialebias reicherti (Cyprinodontiformes: Rivulidae)
FIGURE 2 | Daily rhythm of locomotor activity in paired fish of Garcialebias reicherti recorded during four days in LD. A. Representative time series (actograms) and cosinor fit diagrams for two female (orange) and a male (green) dyads. Amount of locomotor activity (number of events) is normalized for visualization purposes. Gray areas in the actogram represent the dark phase of each 24 h period. The cosinor representation for each individual of the dyad is shown next to the actogram. Black outlines represent the duration of the night. The internal circumference depicts the p = 0.05 confidence limit. Radial lines show the extreme values of the acrophases calculated for each of six days. B. Rayleigh test for all paired individuals (5 males and 5 females) analyzed collectively. Triangles signal individual male acrophases, diamonds signal individual female acrophases. Members of each dyad are presented in the same color. The internal circumference depicts the p = 0.05 confidence limit and length of the black radial line marks the p value (external circumference is p = 0, see main text for p value). The black outline represents the duration of the night.
FIGURE 4 in Daily rhythm of locomotor and reproductive activity in the annual fish Garcialebias reicherti (Cyprinodontiformes: Rivulidae)
FIGURE 4 | Number and allocation of reproductive events at different hours in Garcialebias reicherti. Bars show the occurrence of events at different timepoints for each dyad (see references). Concentric circumferences show the number of events at that hour throughout the 4-day period. Black outline signals the duration of the night.
FIGURE 1 in Daily rhythm of locomotor and reproductive activity in the annual fish Garcialebias reicherti (Cyprinodontiformes: Rivulidae)
FIGURE 1 | Daily rhythm of locomotor activity in isolated fish of Garcialebias reicherti recorded during eight days in LD. A. Representative actograms and cosinor fit diagrams for a female (orange) and a male (green) fish. Amount of locomotor activity (number of events) is normalized for visualization purposes. Gray areas in the actogram represent the dark phase of each 24 h period. The cosinor representation for each individual is shown below the actogram. Black outlines represent the duration of the night. The internal circumference depicts the p = 0.05 confidence limit. Radial lines show the extreme values of the acrophases calculated for each of six days. B. Rayleigh test for all isolated individuals (5 males and 5 females) analyzed collectively. Triangles signal individual acrophases. The internal circumference depicts the p = 0.05 confidence limit and length of the black radial line marks the p value (external circumference is p = 0, see main text for p value). The black outline represents the duration of the night.
Fig. 1 in Fallen leaves on the water-bed: diurnal camouflage of three night active fish species in an Amazonian streamlet
Fig. 1. Habitat and aspect of three root-tangle and leaf-litter inhabiting fish species photographed underwater in an Amazonian streamlet: Tetranematichthys quadrifilis (77.7 mm SL, INPA 25107, top right), Steatogenys duidae (129.2 2 mm TL, INPA 25018, bottom left), and Helogenes marmoratus (59.8 mm SL, INPA 25111, bottom right).
Fig. 2 in Fallen leaves on the water-bed: diurnal camouflage of three night active fish species in an Amazonian streamlet
Fig. 2. Three leaf-shaped and cryptically colored fish species photographed underwater lying on their sides, and one escape response out of the root-tangle: Steatogenys duidae (top left), Helogenes marmoratus (top and bottom right), and Tetranematichthys quadrifilis (bottom left). Note body shape and color resemblance to dead leaves in the three species, as well as the fore body of H. marmoratus above the water surface in the bottom right picture (mauve asterisk).
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>
"The sound comes from a meadow in the Sierra Nevada Mountains in California. The meadow is at an elevation of 2400 meters near a mountain named Olancha Peak, which is 3700 meters in altitude. Ihave a group of friends with which Ibackpack (trek) into the mountains. Our goal was to spend some time in the mountains and hike to the top of Olancha Peak (…) By the time we reached the meadow, we were in a forest and there was still snow on the ground in some places. We took the trip in June of 2006. The Sierra Nevada Mountains are a large mountain range. Much of the range is protected by national parks or preserved areas we call 'wilderness areas' (…) Ihave been backpacking for nearly 40 years and Iwill hopefully continue with this challenging activity for 40 years more! Many of my friends are much younger than Iam and it gives me much satisfaction to be able to have as much or more stamina for this activity than they have! When we are on these trips, we hike up peaks, catch fish, drink some whiskey around campfires and enjoy our time in the beautiful solitude. My memories of this trip were of the steep, hot hike from the desert to the cool meadow; the overall beauty of the nature, the absolute solitude of our campsite near the meadow; the strenuous hike to the top of Olancha Peak; the camaraderie of my friends; and, of course the sound of the frogs in the meadow. The frog sounds were astounding to me and Iwould listen in awe of the creature's instinctual desire to reproduce and continue the existence of their kind. Surely there were different species in the meadow for some of the frog sounds were different than others. The sounds only occurred after the Sun went down for the evening. Istood next to the creek in the meadow and recorded the sounds using my digital camera." [Peter/plentz1960]16 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice
"The sound comes from a meadow in the Sierra Nevada Mountains in California. The meadow is at an elevation of 2400 meters near a mountain named Olancha Peak, which is 3700 meters in altitude. Ihave a group of friends with which Ibackpack (trek) into the mountains. Our goal was to spend some time in the mountains and hike to the top of Olancha Peak (…) By the time we reached the meadow, we were in a forest and there was still snow on the ground in some places. We took the trip in June of 2006. The Sierra Nevada Mountains are a large mountain range. Much of the range is protected by national parks or preserved areas we call 'wilderness areas' (…) Ihave been backpacking for nearly 40 years and Iwill hopefully continue with this challenging activity for 40 years more! Many of my friends are much younger than Iam and it gives me much satisfaction to be able to have as much or more stamina for this activity than they have! When we are on these trips, we hike up peaks, catch fish, drink some whiskey around campfires and enjoy our time in the beautiful solitude. My memories of this trip were of the steep, hot hike from the desert to the cool meadow; the overall beauty of the nature, the absolute solitude of our campsite near the meadow; the strenuous hike to the top of Olancha Peak; the camaraderie of my friends; and, of course the sound of the frogs in the meadow. The frog sounds were astounding to me and Iwould listen in awe of the creature's instinctual desire to reproduce and continue the existence of their kind. Surely there were different species in the meadow for some of the frog sounds were different than others. The sounds only occurred after the Sun went down for the evening. Istood next to the creek in the meadow and recorded the sounds using my digital camera." [Peter/plentz1960]16
Data from: Freshwater fish functional diversity shows diverse responses to human activities, but consistently declines in the tropics
Open the record for dataset details and reuse information.
eDNA metabarcoding in lakes to quantify influences of landscape features and human activity on aquatic invasive species prevalence and fish community diversity
<p>Aim: Our goal was to use eDNA metabarcoding to characterize fish community diversity, detect aquatic invasive species (AIS), and assess how measures of community (or AIS) diversity are influenced by lake physical and environmental covariates, measures of hydrological connectivity, and human accessibility.<br> Location: Michigan, USA.<br> Methods: eDNA samples collected from 22 lakes were sequenced using two mitochondrial gene regions (12S and 16S rRNA). Metabarcoding data were compared to traditional fisheries survey data for a subset of lakes, and data from all 22 lakes were combined with environmental information to identify significant associations with community diversity and AIS relative abundance.<br> Results: Occupancy modeling indicated that detection probabilities were generally higher with eDNA than traditional fisheries gear. Measures of connectivity with upstream aquatic habitats were positively associated with both AIS relative abundance and fish species diversity. We also demonstrate the use of spatial interpolation methods to map distributions of species diversity and AIS relative abundance within lakes.<br> Conclusions: eDNA metabarcoding methods provided information on the composition and diversity of fish assemblages and the presence of AIS in freshwater lakes that varied greatly in drainage connectivity and anthropogenic development. Our case study identified associations between environmental covariates and fish diversity or AIS relative abundance across lakes. This information is of particular importance given increasing anthropogenic disturbance, invasive species spread, and associated declines in aquatic biodiversity. Incorporating eDNA metabarcoding as a supplement to traditional fisheries surveys will permit managers to identify greater numbers of taxa, including early detection of AIS, with less field effort and fish mortality. Further, eDNA methods may more accurately identify physical and biological features that correlate with diversity and abundance, and allow agencies to more effectively direct AIS management activities. </p>
Fish eDNA detections in ports mirror fishing fleet activities and highlight the spread of non-indigenous species in the Mediterranean Sea. Environmental DNA Metabarcoding DATASET
<p>Environmental DNA metabarcoding data set. Environmental samples were collected in 2018 (one sample replicate of 2L surface water) and 2019 (four replicates of 1 L surface water) from several Mediterranean ports and data were generated using 12S rRNA and mitochondrial COI. For each sampling campaign (2018 and 2019) and marker two sheets are presented (with the same numeration): the first one represents all the ASV/MOTUs after the bioinformatics pipelines; the second one shows the curated assignment. The last two sheets are the OTU tables (presence-absence).</p>
Low-Fat Diet and Fish Oil in Men on Active Surveillance for Prostate Cancer
ClinicalTrials.gov study NCT02176902. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effect of Fish Oil Plus Fenofibrate on Triglyceride Levels in People Taking Highly Active Antiretroviral Therapy (HAART)
ClinicalTrials.gov study NCT00076518. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Efficacy of Seluang Fish Oil (Rasbora Argyrotaenia) and Synbiotics Supplementation on CD4+CD25+ Foxp3+ T-regulator Cells, IL17/IL-10 Ratio, and Disease Activity in Systemic Lupus Erythematosus Patient
ClinicalTrials.gov study NCT06659068. IPD Sharing: Not stated. Countries: 1. Publications: 2.
eDNA metabarcoding in lakes to quantify influences of landscape features and human activity on aquatic invasive species prevalence and fish community diversity
Open the record for dataset details and reuse information.
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