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603 results for “fisheries”
Fig. 2 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 2: Flowchart of steps and methods followed (AHP: Analytic Hierarchy Process, FM: Fuzzy Membership).
Fig. 7 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 7: Spatial representation of the Fishing pressure index from the small scale coastal fishery (FPc).
Fig. 2 in Vulnerability of elasmobranchs caught as bycatch in the grouper longline fishery in the Gulf of Gabès, Tunisia Abstract
Fig. 2: Productivity, susceptibility and vulnerability scores of elasmobranch species caught by the grouper demersal longline fishery in the Gulf of Gabès. Numbers correspond to elasmobranch species as listed in Table 4. The colors represent the relative vulnerability: the green areas being the lowest, the yellow ones being the moderate and the red areas being the highest.
Fig. 1 in Vulnerability of elasmobranchs caught as bycatch in the grouper longline fishery in the Gulf of Gabès, Tunisia Abstract
Fig. 1: Map showing the location of the grouper demersal longline sets surveyed during 2016 () and 2017 () in the Gulf of Gabès.
Fig. 15 in Seasonal dynamics of small-scale fisheries in the Adriatic Sea
Fig. 15: Size-frequency distributions of trammel net landings. TL = total length; CL = carapace length; ML = mantle length. Vertical lines: minimum landing size.
Fig. 7 in Seasonal dynamics of small-scale fisheries in the Adriatic Sea
Fig. 7: Composition of traps landings. ITA_17_A = Italy GSA17 traps for S. officinalis; ITA_17_B = Italy GSA17 traps for T. mutabilis; SLOV = Slovenia; CRO = Croatia.
Fig. 6 in Seasonal dynamics of small-scale fisheries in the Adriatic Sea
Fig. 6: Composition of trammel net landings. CRO_rocky = Croatia rocky bottoms; CRO_soft = Croatia soft bottoms; ITA_18 = Italy GSA18; MONT = Montenegro; SLOV = Slovenia.
Fig. 5 in Seasonal dynamics of small-scale fisheries in the Adriatic Sea
Fig. 5: Composition of gillnet landings. CROA = Croatia; ITA_17 = Italy GSA17; ITA_18 = Italy GSA18; MONT = Montenegro; SLOV = Slovenia.
Fig 6 in Evaluating the sustainability of fishery resources and fishing gears: Case study of Ngoyè and Elabè, Kribi, South Cameroon
Fig 6: Size structure of the three most fish species caught by bottom-set gillnet: a) Pseudotolithus typus; b) Pseudotolithus senegalensis; c) Cynoglossus sp.
Fig 5 in Evaluating the sustainability of fishery resources and fishing gears: Case study of Ngoyè and Elabè, Kribi, South Cameroon
Fig 5: Size structure of the three most fish species caught by beach seine: a) Ilisha Africana; b) Pseudotolithus senegalensis; c) Pseudotolithus typus
Mediterranean risk assessment data based on the concurrency between climate change, fisheries, stocks, and biodiversity
<p>Data associated to the paper "Detecting Ecosystem Risk Hotspots: A Mediterranean Case Study" by G. Coro, L. Pavirani, A. Ellenbroek.</p>
Figure 4 in Ecological and economic impacts of exotic fish species on fisheries in the Pearl River basin
Figure 4. Multipanel display of the pairwise relationships between the biomass percentages of different species in catches, with bivariate scatter plots in the lower panels, histograms on the diagonal and Pearson's r correlations in the upper panels (statistical significance: P <0.001 ***, P <0.01 **, P <0.05 *).
Figure 3 in Ecological and economic impacts of exotic fish species on fisheries in the Pearl River basin
Figure 3. Correlation analysis between the CPUE, number of economic exotic species, biomass percentage of exotic species and environmental variables.
Figure 2 in Ecological and economic impacts of exotic fish species on fisheries in the Pearl River basin
Figure 2. Biomass percentages (mean ± SE) of exotic and native species at different sites (A) and in different months (B).
Fig. 6 in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 6. Sábalo fishery status according to spawning potential ratio (SPR) and fishing mortality (F) variability across time. TRP: Target reference point; LRP: Limit reference point. PS76: Puerto Sánchez 1976; PS02: Puerto Sánchez 2002; V89: Victoria 1989; V94: Victoria 94; V05: Victoria 2005; H05: Helvecia 2005.
Fig. 5. a in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 5. a) Analysis of yield per recruitment for different size at first capture. b)Spawning potential ratio (SPR) over time based on the estimated exploitation rate (μ) and the capture length. PS76: Puerto Sánchez 1976; PS02: Puerto Sánchez 2002; V89: Victoria 1989; V94: Victoria 94; V05: Victoria 2005; H05: Helvecia 2005.
Fig. 4 in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 4. Variation in the mean length (wide bars), the maximum length (thin bars), and the mesh size (points) between 1976 and 2005.
Fig. 2 in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 2. Capture records of sábalo in the Paraná basin. The data taken from 1920 to 1988 were compiled by the National Agency of Freshwater Fisheries. The data from 1994 to 2009 correspond to the exportation records of the Sanitary National Service (SENASA). No data from 1988 to 1993 were available.
Fig. 1 in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 1. Study area and the location of the main landing sites of the sábalo fisheries in the lower Paraná basin.
Fig. 3. a in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 3. a) Variation of average flow from 1920 to 2009. b) Variation in the channel-connectivity index (CCI) from 1920 to 2009, expressed as a percent of the time that the water level surpasses the bankfull level (3 m). c) Variation of the floodplain connectivity index (FCI) from 1920 to 2009, expressed as the percentage of the time that the water level surpassed a height of 4.3 m flooding the alluvial valley. Vertical grey lines indicate different hydrological periods considered in this study.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.