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253 results for “Santa Catarina”
Harmfull algae bloom monitoring program dataset; ERDDAP, ERA5 and ONI datasets; and R script for multicriteria analisys in Santa Catarina coastal zone, Brazil.
<p>Project Harmful Algae Bloom (HAB) Monitoring Network in Santa Catarina, Brazil - Database and R script with data analysis. This project was funded by the Foundation for Research Support of the State of Santa Catarina – FAPESC and generated a database combining a HAB monitoring dataset with oceanographic (from ERDDAP) and climatic (from ERA5 and ONI) data which was submitted to multicriteria analysis using R. The HAB monitoring dataset was obtained from Cidasc/SC State Government (http://www.cidasc.sc.gov.br/defesasanitariaanimal/monitoramento-de-algas-nocivas/) and contains results of phytoplankton counts in water samples and toxin levels in shellfish samples obtained from 39 points located in shellfish farms distributed along the SC coastline. Oceanographic data were obtained from the ERDDAP/NOAA website (https://coastwatch.pfeg.noaa.gov/erddap/index.html), including the variables mean chlorophyll concentration (mg.m-3) and mean sea surface temperature (ºC); Climate data were obtained from Copernicus/ERA5 (https://cds.climate.copernicus.eu/) including the variables mean air temperature (ºC), mean pressure (Pasc.), mean cloud cover (%), mean precipitation (kg.m-2), radiation (Einsteins.m-2.day-1), mean U wind (m.s-1), and mean V wind (m.s-1).; Oceanic Niño Index (ONI) data were obtained from the NOAA website (https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php); The R script involves a pre-processing routine aimed at summarizing and integrating all datasets and the subsequent data analyses carried out to evidence temporal patterns related to different type of algal blooms. Detailed methods will be provided in a scientific article.</p>
Stranded marine mammals, sea turtles and seabirds in Paraná and Santa Catarina from August 2018 to August 2023
<p><span class="fontstyle0">To assess the potential impacts from oil and gas production in deep waters of Brazil's Santos Basin, the Brazilian environmental agency (IBAMA) required PETROBRAS, the main oil company in the basin, to implement the "Projeto de Monitoramento de Praias da Bacia de Santos" (Santos Basin Beach Monitoring Project - PMP-BS). This project has been operating along the</span> <span class="fontstyle0">states of Santa Catarina, Paraná, São Paulo, and Rio de Janeiro, since August 2015, collecting data from stranded seabirds, turtles, and marine mammals. This dataset includes records from August 2018 to August 2023, along the Paraná and Santa Catarina coastlines. During this period, 58151 animals of at least 93 species were recorded (883 unidentified animals). From this total, 88.6% were dead and 11.4% alive when first observed. This dataset complements previous ones from the same area, and is a high-intensity monitoring effort essential to understand temporal and geographical variation of stranded animals. This data will allow future works aimed at understanding the impacts of human activities on marine ecosystems and environmental changes over time.</span> <br><br></p>
Figigure 1. Phyla nodiflora var. nodiflora. A - B in Increasing the knowledge on the distribution of Phyla (Verbenaceae): a new record for the state of Santa Catarina, Southern Brazil
Figigure 1. Phyla nodiflora var. nodiflora. A - B. Habitat and habit; C. Leaves; D - F. Florescences; G. Map showing the new record (red circle) for the state of Santa Catarina, Brazil (Wegener & Garcia 138 - LAG). Acronyms (map): PR = Paraná; SC = Santa Catarina; RS = Rio Grande do Sul.
Figure 4 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil
Figure 4. Temperature variation along the seasons of the year. Samples were taken from July 2010 through June 2011, in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil.
Figure 3 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil
Figure 3. Quotient between the carcino-bycatch and Xiphopenaeus kroyeri abundance. Samples were taken from July 2010 through June 2011 in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil. Black circles indicate deviations from a 1:1 expected proportion (Binomial test, p<0.05).
Figure 5 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil
Figure 5. Biplot of the axes from the Redundancy Analysis (RDA). Spatial variation of the biological and environmental variables from July 2010 through June 2011 in the adjacent area from Babitonga Bay, SC. Arrows indicate the strength of the relation between the axes and the environmental factors (O.M= Organic matter content; Phi=Substrate granulometry).
Figure 2 in Decapod abundance and species richness in the bycatch of Xiphopenaeus kroyeri (Heller, 1862) fishery, Santa Catarina, southern Brazil
Figure 2. Relative composition (%) of individuals comprised in the carcino-bycatch, sorted by different taxonomic categories, from the artisanal Xiphopenaeus kroyeri fishery. Samples were taken from July 2010 through June 2011 in the adjacent area from the Babitonga Bay, Santa Catarina State, Brazil.
Mapa de Santa Catarina com Graus de Convergências e Divergências territoriais entre a Regionalização das Associações dos Municípios com a Regiões Geográficas Imediatas do IBGE
<p>TALASKA, Alcione. Mapa de Santa Catarina com Graus de Convergências e Divergências territoriais entre a Regionalização das Associações dos Municípios com a Regiões Geográficas Imediatas do IBGE. Concórdia: IFC, 2023. Mapa. Color.</p>
Fig. 9 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 9. Profile the temperature and salinity of the water column (Diagram TS) recorded in Arvoredo Biology Marine Reserve (Brazil) region during winter/2007 (a), winter/2008 (b), summer/2008 (c), and summer/2009 (d).
Fig. 8 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 8. Temperature and salinity of the water column (Diagram TS) recorded in Arvoredo Biology Marine Reserve (Brazil) region during winter/2007 (a), winter/2008 (b), summer/2008 (c), and summer/2009 (d). CW = Coastal Water; SACW = South Atlantic Central Water; STSW = Subtropical Shelf Water.
Fig. 5 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 5. Relative abundance (%) of larvae collected in Arvoredo Biology Marine Reserve (Brazil) during winter (a) and summer (b). In campaign 1 (1997/1998), 2 (2007/2008) and 3 (2008/2009).
Fig. 1 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 1. Location of sampling stations in the Arvoredo Biology Marine Reserve region and adjacent areas in campaign 1 (1997/ 1998) (stations 7-12), campaign 2 (2007/2008) (stations 1-12) and campaign 3 (2008/2009) (stations 1-12).
Fig. 10 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 10. Canonical Correspondence Analysis of the (a) eight most abundant families, and (b) stations in Arvoredo Biology Marine Reserve (Brazil) region in relation to temperature, salinity and chlorophyll-a. Note: W-07 - Winter/2007; S-08 - Summer/ 2008; W-08 - Winter/2008 and S-09 - Summer/2009
Fig. 6 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 6. Cluster analysis of 59 samples collected in theArvoredo Biology Marine Reserve (Brazil) region during the summer (1998, 2008 and 2009) and winter (1997, 2007, and 2008), based on relative abundance of the different taxa fish larvae identified. Note: w - Winter; s - Summer
Fig. 7 in Ichthyoplankton of Arvoredo Biological Marine Reserve, Santa Catarina, Brazil
Fig. 7. Rarefaction curve of larval fish species collected during six sampling periods in the Arvoredo Biology Marine Reserve (Brazil) region.
Euterpe edulis potential model Santa Catarina
<p>FISC dataset for presence of E. edulis and biophysical data. R code for data analysis.</p>
Fig. 5 in Peculiarities of Trypanosoma rangeli KP1(-) Strains Isolated from the Wild Rodent Phyllomys dasythrix (Santa Catarina, Brazil): Comparisons with T. rangeli KP1(+) strains and Trypanosoma lewisi (Kinetoplastea, Trypanosomatidae)
Fig. 5. kDNA minicircle amplicons presented by all KP1(+) and KP1(–) Trypanosoma rangeli strains examined in this study, and obtained by polymerase chain reaction using the primers 121/122. (M) molecular marker (100-bp DNA ladder).
Fig. 4 in Peculiarities of Trypanosoma rangeli KP1(-) Strains Isolated from the Wild Rodent Phyllomys dasythrix (Santa Catarina, Brazil): Comparisons with T. rangeli KP1(+) strains and Trypanosoma lewisi (Kinetoplastea, Trypanosomatidae)
Fig. 4. Isoenzyme profiles at IDH locus presented by KP1(+) and KP1(–) Trypanosoma rangeli strains and T. lewisi.
Fig. 3 in Peculiarities of Trypanosoma rangeli KP1(-) Strains Isolated from the Wild Rodent Phyllomys dasythrix (Santa Catarina, Brazil): Comparisons with T. rangeli KP1(+) strains and Trypanosoma lewisi (Kinetoplastea, Trypanosomatidae)
Fig. 3. Diagrammatic representation of the electrophoretic patterns of malate dehydrogenase (MDH), phosphoglucomutase (PGM), glucose phosphate isomerase (GPI) and malic enzyme (ME) displayed by KP1(–) and KP1(+) Trypanosoma rangeli strains, and T. lewisi.
Fig. 1 in Peculiarities of Trypanosoma rangeli KP1(-) Strains Isolated from the Wild Rodent Phyllomys dasythrix (Santa Catarina, Brazil): Comparisons with T. rangeli KP1(+) strains and Trypanosoma lewisi (Kinetoplastea, Trypanosomatidae)
Fig. 1. Camera lucida drawings of representative bloodstream trypomastigotes of Trypanosoma rangeli KP1(–) and KP1(+) strains from experimentally infected mice by metacyclic trypomastigotes grown in DMEM medium. The position of the nucleus in each trypomastigote is indicated by arrowheads. Parasites were from Giemsa-stained smears of each strain, as seen under optical microscopy (×1,000). In a trypomastigote of the strain SC-61 are indicated the reference points for taking measurements: anterior end (A), posterior end (P), nucleus (N) and free flagellum (F).
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.