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396 results for “Surface water”
Trade-off between vegetation type, soil erosion control and surface water in global semi-arid regions: A meta-analysis
<p>Soil erosion control and water resource protection can closely interact during restoration of terrestrial ecosystems. In semi‐arid ecosystems, an urgent issue is how vegetation restoration can achieve the goal of soil erosion mitigation and water conservation, which in turn, feeds back to ecosystem functioning.</p> <p>We reviewed 78 articles from 22 countries in semi‐arid areas to evaluate the effects of vegetation type (i.e. forest, grassland and scrubland) on runoff and sediment yields across different environmental conditions (i.e. vegetation coverage, rainfall intensity, slope gradient and soil texture).</p> <p>Our meta‐analysis shows that runoff and sediment reduction both increased as the vegetation coverage increased, and tended to be stable when vegetation coverage exceeded 60%. Vegetation provided a greater benefit for sediment reduction than for runoff control under intense rainfall. Grasslands were generally more effective in reducing sediment than other vegetation types. Forests, grasslands and scrublands were most efficient in soil erosion control on 20°–30°, 0°–25° and 10°–25° slopes respectively. Grasslands and scrublands generally performed better with respect to soil erosion control on moderately coarse soils, whereas forests were most effective on medium‐textured and moderately fine soils.</p> <p>Synthesis and applications. Effective restoration and soil erosion control in semi‐arid ecosystems strongly depends on the selection of vegetation type. Our study further indicates that, for land managers, it is critical to consider local slope, and soil texture, and maintain appropriate vegetation coverage to achieve ecosystem sustainability. Grasslands might be particularly suitable to optimize the trade‐off between soil erosion control and surface water resource in semi‐arid regions.</p>
Data from: Surface-water dynamics and land use influence landscape connectivity across a major dryland region
Landscape connectivity is important for the long-term persistence of species inhabiting dryland freshwater ecosystems, with spatiotemporal surface-water dynamics (e.g., flooding) maintaining connectivity by both creating temporary habitats and providing transient opportunities for dispersal. Improving our understanding of how landscape connectivity varies with respect to surface-water dynamics and land use is an important step to maintaining biodiversity in dynamic dryland environments. Using a newly available validated Landsat TM and ETM+ surface-water time series, we modelled landscape connectivity between dynamic surface-water habitats within Australia's 1 million km2 semi-arid Murray Darling Basin across a 25-year period (1987 to 2011). We identified key habitats that serve as well-connected 'hubs', or 'stepping-stones' that allow long-distance movements through surface-water habitat networks. We compared distributions of these habitats for short- and long-distance dispersal species during dry, average and wet seasons, and across land-use types. The distribution of stepping-stones and hubs varied both spatially and temporally, with temporal changes driven by drought and flooding dynamics. Conservation areas and natural environments contained higher than expected proportions of both stepping-stones and hubs throughout the time series; however, highly modified agricultural landscapes increased in importance during wet seasons. Irrigated landscapes contained particularly high proportions of well-connected hubs for long-distance dispersers, but remained relatively disconnected for less vagile organisms. The habitats identified by our study may serve as ideal high-priority targets for land-use specific management aimed at maintaining or improving dispersal between surface-water habitats, potentially providing benefits to biodiversity beyond the immediate site scale. Our results also highlight the importance of accounting for the influence of spatial and temporal surface-water dynamics when studying landscape connectivity within highly variable dryland environments.
Data from: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011
Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands. The Swan Coastal Plain (SCP) with over 1500 wetlands is a global biodiversity hotspot located in the southwest of Western Australia, where more than 70% of the wetlands have been lost since European settlement. SCP is located in an area affected by recent climate change that also experiences rapid urban development and ground water abstraction. Landsat TM and ETM+ imagery from 1999 to 2011 has been used to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP. A mapping method based on the Landsat data and a decision tree classification algorithm is described. Two generic classifiers were derived for the Landsat 5 and Landsat 7 data. Several landscape metrics were computed to summarize the intra and interannual patterns of surface water dynamic. Top of the atmosphere (TOA) reflectance of band 5 followed by TOA reflectance of bands 4 and 3 were the explanatory variables most important for mapping surface water bodies. Accuracy assessment yielded an overall classification accuracy of 96%, with 89% producer's accuracy and 93% user's accuracy of surface water bodies. The number, mean size, and total area of water bodies showed high seasonal variability with highest numbers in winter and lowest numbers in summer. The number of water bodies in winter increased until 2005 after which a decline can be noted. The lowest numbers occurred in 2010 which coincided with one of the years with the lowest rainfall in the area. Understanding the spatiotemporal dynamic of surface water bodies on the SCP constitutes the basis for understanding the effect of rainfall, water abstraction and urban development on water bodies in a spatially explicit way.
PLATE 140. Splendrillia spp. shell surface SEM images, part 1. Figs. 1–2 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 140. Splendrillia spp. shell surface SEM images, part 1. Figs. 1–2: Splendrillia interpunctata (E.A. Smith, 1882), Tourmaline Reef, Mayaguez, Puerto Rico (M. Williams coll.), SEM magnifications of 250x & 1,000x, respectively. Figs. 3–4: Splendrillia coccinata (Reeve, 1845), designated neotype, Chatham Bay, Union I., SVG (USNM 1291358), SEM magnifications of 250x & 1,000x, respectively. Figs. 5–6: Splendrillia masinoi, new species, paratype, WNW off Santa Martha Beach, Curaçao, Netherlands Antilles (USNM 1291363), SEM magnifications of 250x & 1,000x, respectively. All SEM images courtesy the ANSP and Paul Callomon.
PLATE 141. Splendrillia spp. shell surface SEM images, part 2. Figs. 1–2 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 141. Splendrillia spp. shell surface SEM images, part 2. Figs. 1–2: Splendrillia karukeraensis, new species, paratype, 1.6 km NW of Pointe des Chateaux, Grande-Terre, Guadeloupe (ANSP 465005), SEM magnifications of 250x & 1,000x, respectively. Figs. 3–4: Splendrillia karukeraensis, new species, holotype, 1.6 km NW of Pointe des Chateaux, Grande-Terre, Guadeloupe (ANSP 313863), SEM magnifications of 250x & 1,000x, respectively. Figs. 5–6: Splendrillia compta, new species, Holotype, off N Natal, Rio Grande do Norte, Brazil (MZSP 122075), SEM magnifications of 250x & 1,000x, respectively. All SEM images courtesy the ANSP and Paul Callomon.
Pernambuco State, Brazil (MZSP 30975). Fig. 1: ventral, lateral & dorsal views; Fig. 2: apical view, V = varix, L = edge of outer lip. Figs. 3–4: paratype from the type lot (MZSP 122078). Fig. 3: ventral view; Fig. 4: apical view (varix not developed in this immature specimen). Figs. 5–6: shell surface SEM images of holotype (MZSP 30975). Fig. 5: image taken at 500x showing pattern of paired grooves separated by wider region; the thin line is parallel to the axis of shell. Fig. 6: a closer look showing pattern of punctae (1,000x). SEM images by Yolanda Villacampa and courtesy of the Smithsonian. in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
Pernambuco State, Brazil (MZSP 30975). Fig. 1: ventral, lateral & dorsal views; Fig. 2: apical view, V = varix, L = edge of outer lip. Figs. 3–4: paratype from the type lot (MZSP 122078). Fig. 3: ventral view; Fig. 4: apical view (varix not developed in this immature specimen). Figs. 5–6: shell surface SEM images of holotype (MZSP 30975). Fig. 5: image taken at 500x showing pattern of paired grooves separated by wider region; the thin line is parallel to the axis of shell. Fig. 6: a closer look showing pattern of punctae (1,000x). SEM images by Yolanda Villacampa and courtesy of the Smithsonian.
PLATE 51. Decoradrillia spp. shell surface SEM images. Figs. 1–2 in Taxonomic review of tropical western Atlantic shallow water Drilliidae (Mollusca: Gastropoda: Conoidea) including descriptions of 100 new species
PLATE 51. Decoradrillia spp. shell surface SEM images. Figs. 1–2: Decoradrillia pulchella (Reeve, 1845), Anse Bateau Bay, Tobago I., Trinidad & Tobago (ANSP 338495), 240x & 930x, respectively. Figs. 3–4: Decoradrillia harlequina, new species: Fig. 3: Indian Cay, Grand Bahama I. (ANSP 366927), 240x; Fig. 4: holotype, Devil's Bay, Grenada (USNM 1291335), 1,000x. Figs. 5–6: Decoradrillia interstincta, new species, "Big Rocks", Utila I., Bay Is., Honduras (ANSP 464986), 250x & 1,000x, respectively.
Figs. 1–3 in Notes on Flight and Respiration at the Water Surface byHygrotus salinarius (Wallis) (Coleoptera: Dytiscidae)
Figs. 1–3. Hypersaline habitat of Hygrotus salinarius, Wyoming, Natrona County, 12.8 km S Midwest. 1) Site on 2008 collecting date; 2 and 3) Site on 2012 collecting date.
Databases generated for Manuscript titled "Quantifying downward radiative fluxes from nighttime Martian water ice clouds: Applications to thermal modeling of surface temperatures"
<p>Databases generated for manuscript "<strong>Quantifying downward radiative fluxes from nighttime Martian water ice clouds: Applications to thermal modeling of surface temperatures</strong>"</p> <p>There are two zip files containing generated databases:</p> <p>The zip file titled "database.zip" contains generated database for calculated fluxes using the methodology mentioned in the manuscript. The database spans calculated fluxes in one degree bins for latitudes spanning 30° to -10° N and longitudes spanning 0° to 360°. There are 14760 separate .csv files that are for each one by one degree bin. The title of each file contains its coordinates in the format XXXNXXXEtb.csv (e.g. 000N000Etb.csv for 0°N, 0°E). Each .csv file contains four separate columns and variable rows. The columns have headers corresponding to specific values. "ls" corresponds to solar longitude or date based on Mars' orbit around the Sun. "Flux" corresponds to calculated flux based on the methodology presented on the manuscript. "Delta-T" is the difference in temperature comparing modeled temperature compared to Thermal Emission Spectrometer (TES) measured temperature. "Tau" corresponds to calculated Dust visible opacities using the methodology presented in this work. The rows in each file vary based on the temporal observations from TES at each location. </p> <p>The zip file titled "fitdatabase.zip" contains generated database for fitted fluxes using the methodology mentioned in the manuscript. The database spans calculated fluxes in one degree bins for latitudes spanning 30° to -10° N and longitudes spanning 0° to 360°. There are 14760 separate .csv files that are for each one by one degree bin. The title of each file contains its coordinates in the format XXXNXXXEtbf.csv (e.g. 000N000Etbf.csv for 0°N, 0°E). Each .csv file contains six separate columns and three hundred and sixty rows. The columns have headers corresponding to specific values. "ls" corresponds to solar longitude or date based on Mars' orbit around the Sun. "Flux" corresponds to calculated flux based on the methodology presented on the manuscript. "Delta-T" is the difference in temperature comparing modeled temperature compared to measured temperature. The fitting algorithm interpolates points between values in the calculated flux database and applies a rolling mean fit with a window spanning ten degrees in solar longitude centered at each calculated flux point. "FLAG" indicates the amount of points of calculated flux points that exist within the ten degree window centered at each flux point to demonstrate to the user how much data had to be fitted. "From Ls" shows the leftmost edge of the rolling mean fit window. "To Ls" shows the rightmost edge of the rolling mean fit window. The rows in each file correspond to one degree of solar longitude the fitting algorithm was designed to cover each solar longitude bin. </p> <p> </p>
Surface Water Quality Parameters Data of Khadakwasala Reservoir Pune, India
<p>This dataset contains water quality parameters collected from Khadakwasla Reservoir, India, between October 20, 2022, and April 22, 2023. The sampling location coordinates are 18.4390° N and 73.7720° E.</p> <p><strong>Parameters:</strong></p> <ul> <li>Date of sample collection</li> <li>pH</li> <li>Water Temperature (°C)</li> <li>Dissolved Oxygen (DO) (mg/L)</li> <li>Biochemical Oxygen Demand (BOD) (mg/L)</li> <li>Chemical Oxygen Demand (COD) (mg/L)</li> <li>Chlorophyll-a (Chl-a) (µg/L)</li> <li>Turbidity (NTU)</li> </ul> <p><strong>Data collection:</strong></p> <p>Physical water samples were collected from the reservoir. Turbidity was measured onsite using a standard turbidity meter. All the parameters are measured following the American Public Health Association (APHA) protocol. </p> <p><strong>Data format:</strong></p> <p>The data will be provided in a comma-separated values (Excel) file.</p> <p><strong>Quality control:</strong></p> <p>It is not possible to determine the quality control procedures from the information provided.</p> <p><strong>Additional notes:</strong></p> <ul> <li>The data may be useful for researchers studying water quality in Khadakwasla Reservoir or the surrounding area.</li> <li>Users of the data should be aware of the limitations of the dataset, including the relatively short sampling period and the lack of information on quality control procedures.</li> </ul> <p><strong>Acknowledgement:</strong></p> <p>The authors would like to express their sincere gratitude to the Water Resource Department of Maharashtra, Khadakwasala Division for granting permission to collect water samples from the Khadakwasala Reservoir. We appreciate the Department's cooperation and guidance. All security instructions were strictly followed during the sampling process.</p> <p><strong>Contact:</strong></p> <p>[DR.Rushikesh Kulkarni] [rushikeshk@sitpune.edu.in]</p>
A Refined Supply-demand Framework to Quantify Variability in Ecosystem Services Related to Surface Water in Support of Sustainable Development Goals
<p>This database relies on the article entitled "A Refined Supply-demand Framework to Quantify Variability in Ecosystem Services Related to Surface Water in Support of Sustainable Development Goals " to be published in Earth's Future. The file named 'Results' stores the data produced in this study. The file named 'Scripts' stores the python codes used in this study. The file named 'Software' stores the software installation package (Windows 64-bit system). The file named '3basin' stores the shapefile data of Level 3 basin in Xinjiang. The file named "Supplementary Data" contains the necessary Water Bulletin and Statistical Yearbook data.</p>
Bonneville Salt Flats saline pan ground and surface water fluctuations, geochemical, and well construction data
<p>Data archive of geochemical, water depth, and brine flux data for the Bonneville Salt Flats.</p> <p> </p>
Inputs and outputs for bilayers simulations in "Accurate Simulations of Lipid Monolayers Require a Water Model With Correct Surface Tension"
<p>Inputs and outputs file for simulations of POPC and DPPC Bilayers at various temperatures. For details see:</p>
Data-set of CO2, CH4, N2O dissolved concentrations and ancillary data in surface waters of 24 African lakes.
<p>Geo-referenced and timestamped data-set of water temperature, Specific conductivity (SpCond), oxygen saturation level (%O<sub>2</sub>), dissolved methane (CH<sub>4</sub>) concentration, dissolved nitrous oxide (N<sub>2</sub>O) concentration, partial pressure of carbon dioxide (pCO<sub>2</sub>), carbon stable isotope composition of dissolved inorganic carbon (δ<sup>13</sup>C-DIC), dissolved organic carbon (DOC) concentration, chlorophyll-a (Chl-a) concentration, cyanobacteria abundance (CHEMTAX), nitrate (NO<sub>3</sub><sup>-</sup>) and ammonia concentration (NH<sub>4</sub><sup>+</sup>), coloured dissolved organic matter slope ratio (CDOM SR) in surface waters of African 24 lakes (Victoria, Tanganyika, Albert, Kivu, Edward, Mai Ndombe, Tumba, George, Kamohonjo, Alaotra, Ndalaga, Nyamusingere, Kyamwinga, Mbita, Lukulu, Yandja, Mbalukira, Nkugute, Nyamunuka, Kitagata, Mrambi, Kyashanduka, Katinda, Lac Vert).</p>
Direct and indirect effects of anthropogenic forcing on lake surface water temperature
<p>Here are the data from this paper (Direct and indirect effects of anthropogenic forcing on lake surface water temperature)</p>
data&result of Time Series Surface Water Reconstruction Method (TSWR) based on Spatial Relationship of Multi-stage Water Boundaries
<p>It is a dataset for a paper of Time Series Surface Water Reconstruction Method (TSWR) based on Spatial Relationship of Multi-stage Water Boundaries.</p>
Data used in "Marine heatwaves make more contribution to changing air–water exchange of semi-volatile organic compounds than mean sea surface temperature raising"
<p>Data used in "Marine heatwaves make more contribution to changing air–water exchange of semi-volatile organic compounds than mean sea surface temperature raising"</p>
Spatial impact of urban expansion on lake surface water temperature based on the perspective of watershed scale
<p>This is the original data from the article "Spatial impact of urban expansion on lake surface water temperature based on the perspective of watershed-scale"</p>
Ultrafast water permeation through nanochannels with a densely fluorous interior surface
Ultrafast water permeation in aquaporins is promoted by their hydrophobic interior surface. Polytetrafluoroethylene has a dense fluorine surface, leading to its strong water repellence. We report a series of fluorous oligoamide nanorings with interior diameters ranging from 0.9 to 1.9 nanometers. These nanorings undergo supramolecular polymerization in phospholipid bilayer membranes to form fluorous nanochannels, the interior walls of which are densely covered with fluorine atoms. The nanochannel with the smallest diameter exhibits a water permeation flux that is two orders of magnitude greater than those of aquaporins and carbon nanotubes. The proposed nanochannel exhibits negligible chloride ion (Cl – ) permeability caused by a powerful electrostatic barrier provided by the electrostatically negative fluorous interior surface. Thus, this nanochannel is expected to show nearly perfect salt reflectance for desalination.
An Observational and Modeling Study of Inverse-Temperature Layer and Water Surface Heat Flux
<p>The data are used for an observational and modeling analysis of water temperature distribution and water surface energy budget. </p>
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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.