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3,673 results for “Temporal”
Fig. 5 in Environmental influences on the spatial and temporal distribution of the puffer fish Sphoeroides greeleyi and Sphoeroides testudineus in a Brazilian subtropical estuary
Fig. 5. Monthly distribution of juvenile and adult individuals of S. greeleyi (a) and S. testudineus (b) on the north-south axis of the estuarine complex of Paranaguá, Paraná State. The numbers indicated above the bars refer to absolute frequency.
Fig. 7 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 7. Cluster dendrogram based on similarities of the samples collected in Ibiraquera Lagoon from December 2003 to December 2004. Samples were clustered by Bray Curtis similarity based on log (x+1) transformed abundances of 12 families.
Fig. 6 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 6. Two-way ANOVA interaction results for log-abundance of (a) engraulid and (b) mugilid larvae.
Fig. 5 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 5. Larvae fish families' composition in Ibiraquera Lagoon over 13 months, from December 2003 to December 2004.
Fig. 4 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 4. Fish larvae (a) dominance and (b) frequency of occurrence in Ibiraquera Lagoon, from December 2003 to December
Fig. 2 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 2. Hydrographic conditions in Ibiraquera Lagoon from December 2003 to December 2004. (a) Water temperature (°C), (b) mean salinity variation, (c) total monthly rainfall (mm).
Fig. 1 in Spatial and temporal distribution of fish eggs and larvae in a subtropical coastal lagoon, Santa Catarina State, Brazil
Fig. 1. The location of Ibiraquera Lagoon on the southern Brazilian coast with its four stations in detail (Saco, Baixo, Meio and Cima).
Fig. 1 in Environmental influences on the spatial and temporal distribution of the puffer fish Sphoeroides greeleyi and Sphoeroides testudineus in a Brazilian subtropical estuary
Fig. 1. Map of the estuarine complex of Paranaguá, northern shore of the State of Paraná, Brazil, locating the sampling sites.
Fig. 2 in Environmental influences on the spatial and temporal distribution of the puffer fish Sphoeroides greeleyi and Sphoeroides testudineus in a Brazilian subtropical estuary
Fig. 2. Graphic representation of the Principal Component Analysis (PCA) conducted for the sampling sites and for the seasons of the year on the north-south axis of the estuarine complex of Paranaguá, Paraná State.
Fig. 6 in Spatial and temporal variation of benthic fish assemblages during the extreme drought of 1997-98 (El Niño) in the middle rio Negro, Amazonia, Brazil
Fig. 6. Hybrid multidimensional scaling (HMDS) ordination plot in two dimensions of benthic fish assemblage), River (b; ->7m). This ordination explained ~39% of the variance in the association matrix (r2 = 0,384).
Fig. 5. Estimated species richness E in Spatial and temporal variation of benthic fish assemblages during the extreme drought of 1997-98 (El Niño) in the middle rio Negro, Amazonia, Brazil
Fig. 5. Estimated species richness E(Sn) by strata at rio Negro (a-Sep, b-Nov 1997 and c-Feb 1998) and rio Branco (d-Sep
Fig. 3. Estimated species richness E in Spatial and temporal variation of benthic fish assemblages during the extreme drought of 1997-98 (El Niño) in the middle rio Negro, Amazonia, Brazil
Fig. 3. Estimated species richness E(Sn) by months of collection for (a) rio Negro and (b) rio Branco.
Fig. 4 in Spatial and temporal variation of benthic fish assemblages during the extreme drought of 1997-98 (El Niño) in the middle rio Negro, Amazonia, Brazil
Fig. 4. Temporal and spatial variation of CPUA in number of individuals (ind.m-2.103 - a and c) and biomass (g.m-2.103 - b and d) captured on the rio Negro (a and b) and rio Branco (c and d) for each trawl in: () Sep; () Nov (just in rio Negro) 1997 and () Feb 1998.
Multiscale Temporal Response of Salt Intrusion to Transient River and Ocean Forcing
<p>Model and validation data presented in Payo Payo et al, Multiscale Temporal Response of Salt Intrusion to Transient River and Ocean Forcing (JGR-Oceans, 2021, submitted).</p> <p>We used a 3-dimensional unstructured hydrodynamic model 3-dimensional unstructured hydrodynamic model (FVCOM Finite Volume Community Ocean Model)understand river and tide forcing to disentangle the multiscale temporal pattern of salt intrusion in estuaries subject to transient forcing due to river and tide. We implemented the Pearl River Delta as a case study for 2007/2008.</p> <p>The dataset consists of:</p> <p>·Measured and modelled salinity and elevation data at the validation stations.</p> <p>·River discharge data</p> <p>·SSH data</p> <p>·Salt intrusion length</p>
Automated temporal front tracking toolbox in Matlab
<p>This toolbox provides the Matlab scripts that achieve temporal tracking of coherently evolving density fronts in numerical modes. It consists of three components: (1) scripts to detect density fronts based on the Canny edge detection algorithm at each time step in the model outputs; (2) scripts to automatically track coherently evolving front in time; and (3) scripts to do front pruning and remove the incoherent frontal segment that shows inconsistent frontal propagation direction. A dataset ('G_time_rho.mat') containing modeled density at successive time steps is provided for demonstration. More details of this method can be found in our work that is expected to be published soon (Wu, X., F. Feddersen and S. N. Giddings, 2021, Automated temporal tracking of coherently evolving density fronts in numerical models, Journal of Atmospheric and Oceanic Technology, in revision). Contact Xiaodong Wu (x1wu@ucsd.edu) for any questions. </p>
Data for: Tracking the temporal dynamics of insect defoliation by high-resolution radar satellite data
<p><span>1. Quantifying tree defoliation by insects over large areas is a major challenge in forest management, but it is essential in ecosystem assessments of disturbance and resistance against herbivory. However, the trajectory from leaf-flush to insect defoliation to refoliation in broadleaf trees is highly variable. Its tracking requires high temporal- and spatial-resolution data, particularly in fragmented forests. </span></p> <p><span>2. In a unique replicated field experiment manipulating gypsy moth <i>Lymantria dispar</i> densities in mixed-oak forests, we examined the utility of publicly accessible satellite-borne radar (Sentinel-1) to track the fine-scale temporal trajectory of defoliation. The ratio of backscatter intensity between two polarizations from radar data of the growing season constituted a canopy development index (CDI) and a normalized CDI (NCDI), which were validated by optical (Sentinel-2) and terrestrial laser scanning (TLS) data as well by intensive caterpillar sampling from canopy fogging. </span></p> <p><span>3. The CDI and NCDI strongly correlated with optical and TLS data (Spearman's ρ=0.79 and 0.84, respectively). The ∆NCDI<sub><sub>Defoliation</sub><sub> (</sub><sub>A</sub><sub>-</sub><sub>C</sub><sub>)<i> </i></sub></sub>significantly explained caterpillar abundance (R<sup>2</sup>=0.52). The NCDI at critical time-steps and ΔNCDI related to defoliation and refoliation well discriminated between heavily and lightly defoliated forests. </span></p> <p><span>4. We demonstrate that the high spatial and temporal resolution and the cloud independence of Sentinel-1 radar potentially enable spatially unrestricted measurements of the highly dynamic canopy herbivory. This can help monitor insect pests, improve the prediction of outbreaks, and facilitate the monitoring of forest disturbance, one of the high priority Essential Biodiversity Variables, in the near future.</span></p>
Earthquake catalog in QuakeML format from: "Spatio-Temporal Evolution of Intermediate-Depth Seismicity Beneath the Himalayas: Implications for Metamorphism and Tectonics"
<p>Earthquake catalog of the intermediate-depth seismicity beneath the central Himalayas in QuakeML format. The information included for each event contains location, phase pick, local magnitude information. For more details refer to the Frontiers publication:<a href="https://doi.org/10.3389/feart.2021.742700"> Michailos et al., 2021</a></p>
MUHSIC: An Open Dataset with Temporal Musical Success Information
<p>Music is a volatile industry, where its dynamic nature can directly influence artist career behavior. That is, musical careers can suffer ups and downs depending on the current market moment. This dataset provides data about hot streak periods in musical careers, which are defined by high-impact bursts occurring in sequence.</p> <p>Success in the music industry has a temporal structure, as the audience tastes change over time. Here, we use the Billboard Hot 100 charts with Spotify data to represent success over time. For musical careers, we build their time series from the debut date (i.e., date of the first release obtained from Spotify) to the last chart collected. Thus, each point in the time series represents the success of such an artist in a given week, according to the Hot 100 chart. </p> <p>Therefore, we present <strong>MUHSIC</strong> (<strong>Mu</strong>sic-oriented <strong>H</strong>ot <strong>S</strong>treak <strong>I</strong>nformation <strong>C</strong>ollection), which contains:</p> <ul> <li><strong>Charts:</strong> enhanced data on all weekly Hot 100 Charts</li> <li><strong>Artists:</strong> artist success time series with hot streak information</li> <li><strong>Genres:</strong> genre success time series with hot streak information (the genre is the aggregated of all its artists)</li> <li><strong>Hot Streaks:</strong> summarized hot streak information</li> </ul>
Data for: Spatial and temporal genetic stock composition of river herring bycatch in southern New England Atlantic herring and mackerel fisheries
<p>Anadromous river herring (alewife and blueback herring) persist at historically low abundances and are caught as bycatch in commercial fisheries, potentially preventing recovery despite conservation efforts. We used newly established single-nucleotide polymorphism genetic baselines for alewife and blueback herring to define fine-scale reporting groups for each species. We then determined the occurrence of fish from these reporting groups in bycatch samples from a Northwest Atlantic fishery over four years.Within sampled bycatch events, the highest proportions of alewife were from the Block Island (34%) and Long Island Sound (22%) reporting groups, while for blueback herring the highest proportions were from the Mid-Atlantic (47%) and Northern New England (24%) reporting groups. We then quantified stock-specific mortality in a focal geographic area (~3500 km<sup>2</sup> including Block Island Sound) of high bycatch incidence and sampling effort, where the most accurate estimates of mortality could be made. During this period, we estimate that bycatch took about 4.6 million alewife and 1.2 million blueback herring, highlighting the need to reduce bycatch mortality for the most depleted river herring stocks.</p>
Spatially and temporally varying selection influence species boundaries in two sympatric Mimulus
<p><span>Spatially and temporally varying selection can maintain genetic variation within and between populations, but it is less known how these forces influence divergence between closely related species. We identify the interaction of temporal and spatial variation in selection and their role in either reinforcing or eroding divergence between two closely related <em>Mimulus</em> species. Using repeated reciprocal transplant experiments with advanced generation hybrids we compare the strength of selection on quantitative traits involved in adaptation and reproductive isolation in <em>Mimulus</em> <em>guttatus</em> and <em>Mimulus</em> <em>laciniatus</em> between two years with dramatically different water availability. We found strong divergent habitat-mediated selection on traits in the direction of species differences during a drought in 2013, suggesting that spatially varying selection maintains species divergence. However, a relaxation in divergent selection on most traits in an unusually wet year (2019), including flowering time which is involved in pre-zygotic isolation, suggests that temporal variation in selection may weaken species differences. Therefore, we find evidence that temporally and spatially varying selection may have opposing roles in mediating species boundaries. Given our changing climate, future growing seasons are expected to be more similar to the dry year, suggesting that in this system climate change may actually increase species divergence. </span></p>
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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.