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1,133 results for “wetlands”
Fig. 2 in The Importance Of Artificial Wetlands In The Conservation Of Wetland Birds And The Impact Of Land Use Attributes Around The Wetlands: A Study From The Ajara Conservation Reserve, Western Ghats, India
Fig. 2. Total number of wetland and wetland associated birds recorded at five artificial wetlands during 2011– 2015: A —Gavase wetland; B — Dhangarmola wetland; C — Khanapur wetland; D — Erandol wetland; E — Ningudage wetland.
Fig. 2. The most numerous RDB wetland birds species, recorded during August Counts 2018 and 2021 in The Red Data Book Waterbirds In The Coastal Wetlands Of The Azov-Black Sea Region Of Ukraine - The Results Of The August Counts 2018 And 2021
Fig. 2. The most numerous RDB wetland birds species, recorded during August Counts 2018 and 2021 (bar chart — amount of birds, line chart — number of sites were species was recorded).
Fig. 1 in The Red Data Book Waterbirds In The Coastal Wetlands Of The Azov-Black Sea Region Of Ukraine - The Results Of The August Counts 2018 And 2021
Fig. 1. Coverage of wetlands of Azov-Black Sea coast of Ukraine in 2018 and 2021 (yellow — 1 count, red — 2 counts). The numbers of the wetlands (1–40) correspond to those in table 3.
Fig. 3 in The Red Data Book Waterbirds In The Coastal Wetlands Of The Azov-Black Sea Region Of Ukraine - The Results Of The August Counts 2018 And 2021
Fig. 3. The most important wetlands for RDB wetland bird species according to August Counts 2018 and 2021 (bar chart — average amount of birds, line chart — number of the species recorded at the site).
Average monthly backward moisture footprints for 40 Ramsar wetland basins under potential and current vegetation scenarios (2008 - 2017)
<p>The dataset contains the backward moisture footprints of the basins of 40 selected Ramsar wetlands for a base run with ERA5 reanalysis evaporation and precipitation, and two additional runs based on evaporation and precipitation from a potential vegetation and a current land use scenario. The dataset can be used to study the upwind moisture sources of the 40 included wetland basins under 'normal' conditions (ERA5 reanalysis), and under a potential vegetation scenario and a current land used scenario.<br>The data was generated to study the impact of upwind land use changes and hydroclimatic changes on selected wetland basins (Fahrländer et al. (2024) using the UTrack atmospheric moisture tracking database by Tuinenburg et al. (2020) and data inputs from the ERA5 reanalysis dataset (Hersbach et al. 2020) and from Wang-Erlandsson et al. (2018) (see References section).</p> <p>The moisture footprints are stored in individual NetCDF format files for each wetland basin and in separate folders for each run. The files are marked with the according Ramsar Convention ID for each respective wetland. The footprints are saved in a spatial resolution of 0.5° and contain monthly average evaporation flows for the period 2008 - 2017. The backward footprints contain the moisture sources for the precipitation in the wetland basins, whereas the forward footprint contain the locations where the evaporation from the basins rains down again.</p> <p>In addition, the dataset contains the delineated basins of the 40 Ramsar wetlands, which are provided in shapefile format and marked with the individual wetland ID of the Ramsar Convention.</p> <p> </p> <p>References:</p> <p>Fahrländer, S. F., Wang‐Erlandsson, L., Pranindita, A., & Jaramillo, F. (2024). Hydroclimatic Vulnerability of Wetlands to Upwind Land Use Changes. <em>Earth’s Future</em>, <em>12</em>(3). <a href="https://doi.org/10.1029/2023EF003837">https://doi.org/10.1029/2023EF003837</a></p> <p>Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., et al. (2020). The ERA5 global reanalysis. <em>Quarterly Journal of the Royal Meteorological Society</em>, <em>146</em>(730), 1999–2049. <a href="https://doi.org/10.1002/qj.3803">https://doi.org/10.1002/qj.3803</a></p> <p>Tuinenburg, O. A., Theeuwen, J. J. E., & Staal, A. (2020). High-resolution global atmospheric moisture connections from evaporation to precipitation. <em>Earth System Science Data</em>, <em>12</em>(4), 3177–3188. <a href="https://doi.org/10.5194/essd-12-3177-2020">https://doi.org/10.5194/essd-12-3177-2020</a></p> <p>Wang-Erlandsson, L., Fetzer, I., Keys, P., van der Ent, R. J., Savenije, H. H. G., & Gordon, L. J. (2018). Remote land use impacts on river flows through atmospheric teleconnections. <em>Hydrology and Earth System Sciences</em>, <em>22</em>(8), 4311–4328. <a href="https://doi.org/10.5194/hess-22-4311-2018">https://doi.org/10.5194/hess-22-4311-2018</a></p>
Wetlands evolution in the hinterland of Ravenna
<p><strong>GeoPackage database with polygonal file showing the evolution of the wetlands of the hinterland of Ravenna during the last three millennia</strong>, together with related metadata.</p> <p>Chronological periods considered are:</p> <ul> <li>Bronze Age (~1000 BCE)</li> <li>Roman period (~100 CE)</li> <li>Early Middle Ages (~1200 CE)</li> <li>Late Middle Ages (~1400 CE)</li> <li>1598-1600s CE</li> <li>1651-1694 CE</li> <li>1750-1764 CE</li> <li>1853 CE</li> <li>1895 CE</li> <li>2022 CE</li> </ul>
Data for: Drainage impacts on the productivity of wetland species Spartina alterniflora and Salicornia pacifica
<p>Coastal wetlands display ecohydrological zonation such that vertical differences of plant zones are driven by varying groundwater levels over tidal cycles. It is unclear how variable levels of tidal drainage directly impact biotic and abiotic factors in coastal wetland ecosystems. To determine the impacts of drainage levels, simulated tides in mesocosms with varying degrees of drainage were created with <em>Spartina alterniflora</em>, the salt marsh coastal ecosystem dominant species on the United States Atlantic Coast, and <em>Salicornia pacifica</em>, the Pacific Coast dominant. We measured biomass production and photosynthesis as indicators of plant health, and we also measured soil and porewater characteristics to help interpret patterns of productivity. These measures included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, net ecosystem exchange, photosynthesis rate, respiration rate, and methane flux. We found the greatest plant production in soils with intermediate drainage levels, with production values that were 13.7% higher for <em>S. alterniflora</em> and 57.7% higher for <em>S. pacifica</em> in the intermediate flooding levels than found in more inundated and more drained conditions. Understanding how drainage impacts plant species is important for predicting wetland resilience to sea level rise, as increasing water levels alter ecohydrological zonation.</p>
A 5 m wetland suitability map in mainland France
<p>Wetland suitability map with continuous values from 0 (low suitability) to 100 (high suitability) covering mainland France at 5 m spatial resolution.</p> <p>Dataset includes:</p> <ul> <li>280 GeoTIFF raster files (MH_prob_000.tif) projected in the French Lambert-93 system (EPSG code 2154), each file corresponding to a 50 x 50 km tile. The number indicates the tile of interest ;</li> <li>1 vector tile index at Google Earth format (tile_index.kmz) showing the location of each tile. This file has been created to facilitate download layer only on area of interest.</li> </ul> <p>A complete description of the method used to produce this map can be found in the following article https://doi.org/10.1016/j.heliyon.2023.e13482</p>
Data for: Drainage impacts on the productivity of wetland species Spartina alterniflora and Salicornia pacifica
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Application of LiDAR to assess the habitat selection of an endangered small mammal in an estuarine wetland environment
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Data from: Optimization of wetland environmental DNA metabarcoding protocols for Great Lakes region herpetofauna
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Data from: Spatial replication is important for developing landscape genetic inferences for a wetland salamander
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Impact of human disturbance on the abundance of non-breeding shorebirds in a subtropical wetland
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Training data from: Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates
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Increasing marsh bird abundance in coastal wetlands of the Great Lakes (2011–2021) likely caused by increasing water levels
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Prediction data from: Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates
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Functional diversity of macroinvertebrates as a tool to evaluate wetland restoration
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Return of diversity: wetland plant community recovery following purple loosestrife biocontrol
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Diet composition based on stable isotopic analysis of fecal samples revealed the preference of Black-faced Spoonbill (Platalea minor) for natural wetlands and fishponds
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Data from: Looking for compensation at multiple scales in a wetland bird community
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.