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2,595 results for “Fish species”
Fish and Amphibians species list of the Andrews Experimental Forest, 1987 to present
This is a compilation of fish species currently known to be present within the H.J. Andrews Experimental Forest. Species were extracted from several different aquatic vertebrate studies over time. Taxonomy is updated as needed.
RivFISH - An European database on fish species presence across river basins
<p>The RivFISH database aggregates the available data on freshwater-dependent fish presence in Europe, validated at the river basin level and considering taxonomical synonyms for species names, thus allowing for a maximization of data usage and robustness. This database also promotes interoperability with other datasets, including the IUCN Red List of Threatened Species, FishBase and the Catchment Characterisation and Modelling (CCM2) – River and Catchment Database v2.1. It is, as far as the authors know, the most up-to-date and comprehensive database on the presence of freshwater-dependent fish species for European river basins. The structure of the database is also prepared to deal with future alterations in species taxonomy, as well as new records of species occurrence in river basins.</p>
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Fish Abundance and Species Richness
These data describe the annual estimates of density of wetland fish (all species combined) and the species richness (as the number of unique species) in six main channel and six tidal creek locations at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetland in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Tijuana Estuary in San Diego County was added in 2013. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
North Temperate Lakes LTER: Fish Species Richness 1981 - current
This data set is a derived data set based on fish catch data. Data are collected annually to enable us to track the fish assemblages of eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, bog lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra and Fish). Sampling on Lakes Monona, Wingra, and Fish started in 1995; sampling on other lakes started in 1981. Sampling is done at six littoral zone sites per lake with seine, minnow or crayfish traps, and fyke nets; a boat-mounted electrofishing system samples three littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two sites per lake. In the bog lakes only fyke nets and minnow traps are deployed. Parameters measured include species-level identification and lengths for all fish caught, and weight and scale samples from a subset. Derived data sets include species richness, catch per unit effort, and size distribution by species, lake, and year. Species richness for a lake is the number of fish species caught in that lake during the annual fish sampling. Hybrids captured are only included in the richness value if neither of the two hybridized species are caught in the lake that year. Fish identified only to genus or higher taxonomic level are not included if any fish identified to species within that genus or higher taxonomic level are caught. E.g., Unidentified Chub would be only included in the richness value if no other chub is caught in that lake that year. Sampling Frequency: annually. Number of sites: 11 Notes: Beach seining was discontinued after 2019. 2020 data does not exist due to insufficient sampling. In 2021, sampling in Fish Lake was suspended due to significant lake level changes. Data is missing for the two bogs in 2022. Please consult NTL's website for information on experimental lake manipulations and the DNR's website for management activities
Adelie penguin diet composition, fish species and number, 1991-2024
The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness. No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
Perceived increases of fish species in the Mediterranean sea: data from a joint LEK initiative.
<p>The dataset was collected with the the Mediterranean LEK initiative. The initiative was initially conceived by the international basin-wide monitoring program <em>CIESM Tropical Signals</em> (funded by the Albert II of Monaco Foundation) and subsequently adopted by the projects BALMAS (Ballast Water Management System for Adriatic Sea Protection, IPA Adriatic Cross-Border Cooperation Programme; <em>FAO-AdriaMed</em> and <em>FAO-MedSudMed</em>. This action was recently supported by the Interreg Med Programme (Grant number Pr MPA-Adapt 1MED15_3.2_M2_337) 85% co-funded by the European Regional Development Fund, which implemented the use of standard LEK protocols for Marine Protected areas and partially supported the writing of this publication.</p> <p>Data refers to self-reported trends of various fish species, which were regarded as increaseing by a sample of fishermen from various Mediterranean countries. Interviews were elicited from fishermen through semi-structured protocols (see Azzurro et al., 2011).</p>
Model projection of the effect of climate change and fishing pressure on key species of the South East Asia Seas
<p>The dataset contain Projection from the Size-Spectra Bioclimatic Envelop Model (SS-DBEM), this work was part of the GCRF Blue communities Programme (www.blue-communities.org). The model provides distribution and abundance and/or biomass of fish and other species of commercial interest under climate change and fishing pressure. The model outputs are yearly abundance/biomass on a 0.5-by-0.5 degree grid, covering the period from 2000 to 2098. Further description of the model and relevant references are listed in the following file: Guide-fish-model-output-use.docx</p> <p>The model was run under two climate scenario: RCP4.5 and RCP8.5, with different combinations of fishing pressure expressed as the Maximum Sustainable Yield (MSY) for the following values: 0 (no fishing, climate change alone will cause variation in fish biomass), 1 (sustainable fishing), 2, 3 (overfishing), and, 4 (overfishing with destructive practice). The intent is not to reproduce current fishing level but to provide a range of scenarios with which the future of fisheries can be explored.</p> <p>We projected fish species that were identified as key in the South East Asia seas region by our regional partners.The full list is provided in document: Fish-list-modelguide.xlsx</p> <p>There are 4 zip files that contain the model outputs of in either abundance (number of fish) or biomass grams of fish) for the two climate scenario. For example Biomass-RCP45.zip will contain model outputs in biomass for projections under RCP4.5 and all MSY. within the zip files are .csv files of the outputs for each species under the 5 MSY (0 to 4), the individual file names identify the species (identified by a 6digit code), the output provided (abundance or biomass), the RCP (8.5 or 4.5), and the MSY (0, 1, 2, 3, or 4). For example the file labelled 600107-Abundance-rcp85-msy4.csv contains the outputs for species 600107 (Skipjack tuna, <em>Katsuwonnus pelamis</em>), as abundance, under RCP8.5 with MSY4. Headers indicate what is in each column (latitude, longitude and year).</p> <p> </p> <p>Note: some knowledge of Python, R, or a similar software is recommended to ensure easy of use.</p>
The raw data of Souma, Katano, Doi et al. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology
<p>The raw data of Souma, Katano, Doi, Takahara, and Minamoto. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology.</p>
Data from: Identifying priority areas for spatial management of mixed fisheries using ensemble of multi-species distribution models. Panzeri D. et al., 2023, Fish and Fisheries
<p>Panzeri D.<sup>1</sup>, Russo T., Arneri E., Carlucci R., Cossarini G., Isajlović I., Krstulović Šifner S., Manfredi C., Masnadi F., Reale M., Scarcella G., Solidoro C., Spedicato M.T., Vrgoč N., W. Zupa, Libralato S<sup>2</sup>.</p> <p><sup>1 </sup>dpanzeri@ogs.it<br> <sup>2 </sup>slibralato@ogs.it</p> <p>Spatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e-SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient-boosting machine methods in a training and testing protocol. The e-SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three-dimensional physical-biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e-SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e-SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.</p> <p>Data (csv) for Panzeri et al. 2023</p> <p>1. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Ensemble_density_F&F_D.Panzeri_et_al_2023.csv: CSV file with density values (column pred) in terms of number of individuals (log N/km2) for each species (column sp) and life stage (column age) for each grid cell (X = longitude and Y = latitude).</a> </p> <p>2. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Getis_hotspot_F&F_D.Panzeri_et_al_2023.csv: CSV file with Getis ord Gi* values (column Gi) derived from the previous file 1, developed for each species and life stage for each grid cell (X = longitude and Y = latitude).</a></p> <p>3. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Multispecies_HotSpot_F&F_D.Panzeri_et_al_2023.csv: Frequency map expressed as the number of species for each grid cell (column freq) that has the hotspot (previous file 2) above the third quartile.</a></p> <p> </p> <p> </p>
MCR LTER: Coral Reef: Community Dynamics: Abundance and Species Richness of Fishes Associated with the Coral Porites rus 2000 thru 2011
These data describe the species richness and abundance as part of MCR LTER's reef fish monitoring program to track long-term patterns in species abundance and diversity. This study began in 2000 in the lagoons off of the north shore of the island of Moorea, French Polynesia and the dataset is updated annually. The abundance and life history stage (adults, juveniles or recruits) of all taxa of fishes associated with selected colonies (5-16 colonies per site) of the mound forming coral Porites rus are recorded at seven reef sites located along the north shore of Moorea. These sites are characterized by differences in water depth, distance to the fore reef and the number and types of neighboring corals. Counts are performed by a pair of divers using SCUBA and include semi-cryptic species. The collection of these data was suspended following the last survey conducted in July 2011 due to the extremely low abundance of live P. rus at these locations.
Fig. 4 in Physical habitat simulation for small-sized characid fish species from tropical rivers in Brazil
Fig. 4. The velocities and depth comparison between the field measurement and the numerical model for points in 50% cros- s-section width of the Velhas reach (a-b) and in 50% width of the Curimataí reach (c-d).
Fig. 3. Karyotypes after FISH with 5S in Contributions to the systematic of Pimelodidae (Osteichthyes, Siluriformes): basic and molecular cytogenetics on seven species of Pimelodus from three Brazilian hydrographic systems
Fig. 3. Karyotypes after FISH with 5S rDNA probes (red) and 18S rDNA probe (green). a. Pimelodus absconditus; b. Pimelodus britskii; c. Pimelodus maculatus; d. Pimelodus microstoma; e. Pimelodus mysteriosus; f. Pimelodus ortmanni; g. Pimelodus paranaensis. Scales bar = 10 μm.
Fig. 3 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 3. Monthly variation of Cyphocharax voga GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Fig. 5 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 5. Monthly variation of Oligosarcus jenynsii GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Fig. 2 in Defining the reproductive period of freshwater fish species using the Gonadosomatic Index: a proposed protocol applied to ten species of the Patos Lagoon basin
Fig. 2. Monthly variation of Astyanax fasciatus GSI values (adult females only) in Guaíba Lake (white) and Casamento Lake (dark gray), Rio Grande do Sul, Brazil (median, 25- 75% quartiles and lower-upper GSI limits by month and site). Three GSI cut-off values were tested with respect to the maximum GSI recorded for each species, for delimitation of reproductive months: 20% (G20), 30% (G30) and 40% (G40).
Figs 40-42. Macvicaria kingscotensis n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia
Figs 40-42. Macvicaria kingscotensis n. sp. ex Haletta semifasciata. 40. Whole-mount ventral view. 41. Terminal genitalia. 42. Dorsal distribution of vitelline follicles. Scale bars: 40, 42, 250 µm; 41, 100 µm.
Figs 1-3. Macvicaria shotteri n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia
Figs 1-3. Macvicaria shotteri n. sp. ex Apogon fasciatus. 1. Whole-mount ventral view. 2. Terminal genitalia. 3. Dorsal distribution of vitelline follicles. Scale bars: 1, 3, 250 µm; 2, 100 µm.
Figs 30-32 in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia
Figs 30-32. Macvicaria heronensis Bray & Cribb, 1989 ex Trachinotus coppingeri. 30. Whole-mount ventral view. 31. Terminal genitalia. 32. Dorsal distribution of vitelline follicles. Scale bars: 30, 32, 250 µm; 31, 100 µm.
Figs 7-9. Macvicaria mekistomorphe n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia
Figs 7-9. Macvicaria mekistomorphe n. sp. ex Sillago maculata. 7. Whole-mount ventral view. 8. Terminal genitalia. 9. Dorsal distribution of vitelline follicles. Scale bars: 7, 9, 250 µm; 8, 100 µm.
Figs 19-20. Macvicaria flexuomeatus n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia
Figs 19-20. Macvicaria flexuomeatus n. sp. ex Cheilodactylus rubrolabiatus. 19. Whole-mount ventral view. 20. Dorsal distribution of vitelline follicles. Scale bars: 19, 20, 250 µm.
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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.