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52 results for “fish products”
Barley as a production platform for oral vaccines in sustainable fish aquaculture
<p>Experimental data for the study "Barley as a production platform for oral vaccines in sustainable fish aquaculture"</p>
Dataset - Drying out fish ponds, for an entire growth season, as an agroecological practice: maintaining primary producers for fish production and biodiversity conservation
<p>This dataset is based on samples taken from fish ponds in the Dombes region between 2007 and 2014. It includes sediment and water physio-chemistry data, as well as primary producer diversity, benthic invertebrate density and fish yield for 85 different ponds. All these data are linked to the distance to the last dry-out, a major practice in extensive fish farming in this region.</p> <p>There are two .tab and .csv files:<br> One containing the dataset<br> One containing the description of the different variables (Metadata)</p>
UCSB SONGS Mitigation Monitoring: Reef Performance Standard – Fish Production
These data describe annual estimates of the somatic and gonadal tissue production in five species of reef fishes at an artificial reef (Wheeler North Reef in Orange County, CA) and two natural reference reefs (San Mateo Kelp in Orange County, CA and Barn Kelp in San Diego County, CA). Data were collected from 2009 – 2023 as part of a comprehensive mitigation program aimed at evaluating the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of the San Onofre Nuclear Generating Station (SONGS).
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.
Data for: D3.6 - Assessment of organoleptic and nutritional quality of fish products from the demonstration tests
<p>Data for: D3.6 - Assessment of organoleptic and nutritional quality of fish products from the demonstration tests </p> <p>https://ifishienci.eu/wp-content/uploads/2024/01/iFishIENCi_D3.6.pdf</p> <p>Corresponding Author</p> <p>Name: Anneli Rost<br>ttz Bremerhaven, Germany<br>Address: Knurrhahnstraß 22-24 /Packhalle X 27572 Bremerhaven<br>Email: arost@ttz-bremerhaven.de</p>
FIGURE 7 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 7 | The first two axes from the distance-based redundancy analysis (dbRDA) that correlate the structure of the shallow water fish assemblage and predictors (in bold; from the fitted model) sampled from May 2000 to April 2001 in the north-south axis of the Paranaguá Bay Estuarine Complex (southern Brazilian coast). ED = early dry season (April–June), LD = Late dry season (July–September), EW = early rainy season (October–December) and LW = late rainy season (January–March). Achirus lineatus = Ac.li; Bathygobius soporator = Ba.so; Chaetodipterus faber = Ch.fa; Eucinostomus argenteus = Eu.ar; Menticirrhus americanus = Me.am; M. littoralis = Me.li; Sphoeroides greeleyi = Sp.gr; S. testudineus = Sp.te; Trachinotus carolinus = Tr.ca; T. falcatus = Tr.fa; T. goodei = Tr.go; T. marginatus = Tr.ma. Only species with Pearson correlation coefficient |r| ≥ 0.3 with the axes are shown. Percentage explained by the axis (fitted) and total variation explained by the model are provided on the axes.
FIGURE 4 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 4 | Cumulative species curve calculated with fish samples sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. In gray, the modeled curve based on the Coleman Estimator (Coleman et al., 1982). Boxplots were generated from mean. Crosses represent outliers.
FIGURE 2 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 2 | Salintity, tranparency (Transp) and dissolved oxygen (DO) along the estuarine gradient of shallow areas of the north-south axis of the PEC from monthly sampling of May 2000 to April 2001. For a better visualisation, the values were averaged by seasons and the error bars were omitted. ED = early dry season (April–June), LD = Late Dry season (July– September), EW = early rainy season (October–December) and LW = late rainy season (January– March).
FIGURE 1 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 1 | Maps of study area, their location in the coast of Paraná (Southestern Brazil) and, in detail, the sampling points (1–8) along the north-south axis of the Paranaguá Bay Estuarine Complex. The geographical limits of the Guaraqueçaba Area of Enviromental Protection (in Portuguese acronimous – APA) and Superagui National Park are also shown. To compute the values of distance from the mouth of the estuary and the sampling point (see methods), we used the ocean-turned face of the Island Mel as the reference of the mouth of the estuary. Distance from the estuarine mouth: Site 1 = 33.97 km, Site 2 = 34.41, Site 3 = 26.27 km, Site 4 = 29.2 km, Site 5 = 24.85 km, Site 6 = 19.30 km, Site 7 = 7.5 km, Site 8 = 5.18 km.
FIGURE 6 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 6 | Abundance (n) relationship with the environmental variables that formed the most parsimonious linear model. Line represents the modeled values, and a gray area corresponds to the standard deviation. l.n = number of individuals in logscale. Temp = temperature; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys; D = distance from the mouth of the estuary (see Material and Methods section for details).
FIGURE 3 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 3 | Monthly variation in the mean historical rainfall data (monthly average between 1975 and 2015) and mean water temperature sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. For temperature, the values were averaged by month and bars represent standard deviation. Months were ordered according to the sequence of the sampling surveys.
FIGURE 5 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 5 | Richness (S) relationship with the environmental variables that formed the most parsimonious GLM. Line represents the modeled values, and a gray area corresponds to the standard deviation. Temp = temperature; Transp = transparency; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys (see Material and Methods section for details).
Multi-decadal stability of fish productivity despite increasing coral reef degradation
<p>1. Under current trajectories, it is unlikely that the coral reefs of the future will resemble those of the past. As multiple stressors, such as climate change and coastal development, continue to impact coral reefs, understanding the changes in ecosystem functioning is imperative to protect key ecosystem services.</p> <p>2. We used a 26-year dataset of benthic reef fishes (including cryptobenthic fishes) to identify multi-decadal trends in fish biomass production on a degraded coral reef. We converted fish abundances into estimates of community productivity to track the long-term trend of fish biomass production through time.</p> <p>3. Following the first mass coral bleaching event in 1998, the abundance, standing biomass, and productivity of fish communities remained remarkably constant through time, despite the occurrence of multiple stressors, including extreme sedimentation, cyclones, and mass coral bleaching events. Species richness declined following the 1998 bleaching event, but rebounded to pre-bleaching levels and also remained relatively stable.</p> <p>4. Although the species composition of the communities changed over time, these new community configurations still maintain a steady level of fish biomass production. While these highly dynamic and increasingly degraded systems can still provide some critical ecosystem functions, it is unclear whether these patterns will remain stable over future decades.</p>
Data for: Mediterranean Sea heatwaves jeopardize greater amberjack's (Seriola dumerili) aquaculture productivity through impacts on the fish microbiota.
<p>The data in this repository with the DOI 10.5281/zenodo.8414745 is licensed under a Creative Commons Attribution 4.0 International License.<br> For more information, see https://creativecommons.org/licenses/by/4.0.</p> <p>Physicochemical, microbiome and growth data for:</p> <p>Paper title: Mediterranean Sea heatwaves jeopardize greater amberjack’s (Seriola dumerili) aquaculture productivity through impacts on the fish microbiota<br> Paper DOI: 10.3389/fmars.2023.1168953 </p> <p>Code repository DOI for reproducing the Figures: https://doi.org/10.1038/s43705-023-00243-7</p> <p>Corresponding Author</p> <p>Name: Pablo Sanchez<br> LEITAT Technological Center, 08225, Terrassa, Spain<br> Address: Carrer Innovació, 2, 08225 Terrassa, Barcelona, Spain<br> Email: psanchez@leitat.org<br> </p> <p> </p>
Multi-decadal stability of fish productivity despite increasing coral reef degradation
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Prevalence of Listeria monocytogenes and other Listeria species in fish, fish products and fish processing environment: A systematic review and meta-analysis
<p>Dane wykorzytsane w publikajci "Prevalence of <em>Listeria monocytogenes</em> and other <em>Listeria</em> species in fish, fish products and fish processing environment: A systematic review and meta-analysis" . Dane obejmują wyniki surowe z baz artykułów, dane wykorzystane do wykonania metaanalizy oraz wyniki surowe uzyskane po przeprowadzaniu metaanalizy</p>
Productivity-Susceptibility Analysis for Top 250 Marine Aquarium Fish Supplemental Information
<p>Data storage for supplemental information, containting the full dataset, a summarized dataset, and comparing vulnerability scores between FishBase and our Productivity-Susceptibility Analysis. </p>
Data on the occurrence on anisakids and other parasites in fishery products from wild and farmed fish in all countries (Jan 2010 – Sept 2023)
<p><span>This file contains data on anisakids and other parasites in fishery products from wild and farmed fish in all countries, covering studies published between January 2010 and September 2023. The systematic review protocol used to identify and extract the information is available at <a href="https://zenodo.org/records/10270810"> https://zenodo.org/records/10270810</a>. For data on anisakids for the period 2010-2020, this file is complementary to the zenodo file https://zenodo.org/records/14047972, and includes publications that were not selected in published meta-analyses. </span></p>
Linking variation in planktonic primary production to coral reef fish growth and condition
<p class="MsoNormal"><span>Within low nutrient tropical oceans, islands and atolls with higher primary production support higher reef fish biomass and reef organism abundance. External energy subsidies can be delivered onto reefs via a range of physical mechanisms. However, the influence of spatial variation in primary production on reef fish growth and condition is largely unknown. It is not yet clear how variability in food delivery onto a reef interacts with reef depth and slope, and affects reef fish productivity. </span><span>Here we test the hypothesis that with increased proximity to deep-water oceanic allochthonous nutrient sources, or at sites where transportation of these water bodies onto reefs is facilitated by shallower reef slopes, parameters of fish growth and condition will be higher, and this pattern will be further emphasised in areas naturally higher in primary production. Contrary to expectations, we found no association between fish growth rate and sites with higher mean chlorophyll values. There were no differences in </span><span>δ</span><sup><span>15</span></sup><span>N or</span><span> δ</span><sup><span>13</span></sup><span>C values in fish collected at greater depths across reefs, suggesting a homogeneous primary production resource. However, the relationship between fish condition and primary production was influenced by depth of collection, driven by higher fish condition at shallow depths within a study site which is a 'hotspot' of primary production. Carbon </span><span>δ</span><sup><span>13</span></sup><span>C values were depleted at sites with increasing primary production, and this trend was reversed by an interactive effect with shallower reef slopes. </span><span>Our results indicate that deep-water ocean nutrient influences did not </span><span>translate into observable increases in overall population growth in </span><span>planktivorous </span><em><span>Chromis fieldi </span></em><span>with</span><span>in the </span><span>10–17.5 m</span><span> </span><span>depth range, but show the importance of site specific variation in hydrodynamics and reef physical characteristics influencing fish carbon isotopic composition and condition. </span></p>
Fig 2 in Opportunities and its challenges in fish production: The case of Lake Koka, East Showa Zone, Oromia National Regional State, Ethiopia
Fig 2: Expansion of water hyacinth in Lume district at Koka Lake, February, 2020
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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