Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
20
datasets available to search
ShareScore release 0.9.0
Dataset results
20 results for “Ramsar wetlands”
Figure 4 in Spatiotemporal patterns of ground beetle diversity (Coleoptera: Carabidae) in a Ramsar wetland (Chott Tinsilt) of Algeria
Figure 4. Sample-based rarefaction (solid line) and extrapolation (dashed line) curves of species richness estimated for ground beetle communities living in the halophytic vegetation belts surrounding Chott Tinsilt in northeastern Algeria. White solid circles indicate reference samples. Light gray shaded areas represent lower and upper bounds of 95% confidence intervals for the S. Colored/shaded (est) areas indicate ±SDs.
Figure 3 in Spatiotemporal patterns of ground beetle diversity (Coleoptera: Carabidae) in a Ramsar wetland (Chott Tinsilt) of Algeria
Figure 3. Values of observed and estimated (Chao1) species richness with standard deviations (±SD) as vertical error bars, of ground beetle community sampled at Chott Tinsilt, northeastern Algeria.
Figure 1 in Spatiotemporal patterns of ground beetle diversity (Coleoptera: Carabidae) in a Ramsar wetland (Chott Tinsilt) of Algeria
Figure 1. Geographical location of Chott Tinsilt (northeastern Algeria), positioning of sampled stations (T1 and T2), and the layout of experimental design with pitfall traps at each station.
Figure 2 in Spatiotemporal patterns of ground beetle diversity (Coleoptera: Carabidae) in a Ramsar wetland (Chott Tinsilt) of Algeria
Figure 2. Total number of subfamilies, genera, and species of ground beetles (Coleoptera: Carabidae) for each station (T1 and T2), and for the entire wetland of Chott Tinsilt, northeastern Algeria.
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>
Figure 2 in Ornithofauna and its conservation in the Kuttanad wetlands, southern portion of Vembanad-Kole Ramsar site, India
Figure 2. Status of the birds recorded from the Kuttanad wetlands
Figure 3 in Ornithofauna and its conservation in the Kuttanad wetlands, southern portion of Vembanad-Kole Ramsar site, India
Figure 3. Percentage distribution of feeding guilds of birds in Kuttanad wetland
Figure 1 in Ornithofauna and its conservation in the Kuttanad wetlands, southern portion of Vembanad-Kole Ramsar site, India
Figure 1. Six divisions of Kuttanad wetlands
Renuka Wetlands (Photo: Chandra et al., 2021) in Faunal Composition of Ramsar Wetlands from India: An Analysis
Renuka Wetlands (Photo: Chandra et al., 2021)
Greylag Geese (Photo: Chandra et al., 2021) in Faunal Composition of Ramsar Wetlands from India: An Analysis
Greylag Geese (Photo: Chandra et al., 2021)
Irrawady Dolphin at Chilika Lake (Photo: Chandra et al., 2021). in Faunal Composition of Ramsar Wetlands from India: An Analysis
Irrawady Dolphin at Chilika Lake (Photo: Chandra et al., 2021).
Figure 5 in Faunal Composition of Ramsar Wetlands from India: An Analysis
Figure 5. Faunal species composition in Ramsar Wetlands of India.
Figure 4 in Faunal Composition of Ramsar Wetlands from India: An Analysis
Figure 4. Faunal composition of Ramsar Wetlands in India.
Figure 3 in Faunal Composition of Ramsar Wetlands from India: An Analysis
Figure 3. Distribution of Ramsar Wetlands in states of India.
Figure 1 in Faunal Composition of Ramsar Wetlands from India: An Analysis
Figure 1. Number of designated Ramsar sites with respect to year of declaration.
Data from: Developing state and transition models of floodplain vegetation dynamics as a tool for conservation decision-making: a case study of the Macquarie Marshes Ramsar wetland
1. Floodplain vegetation states (communities) exhibit spatiotemporal dynamics in vegetation structure and composition, which reflect unique hydrological and connectivity patterns. Shifts in inundation regimes can drive succession and establish new stable states, determined by the magnitude and duration of the hydrological perturbation. 2. We aimed to develop a modelling approach that is able to capture ecosystem dynamics, identify and quantify the main drivers of change, and provide a tool for conservation decision-making. We developed state and transition models for floodplain vegetation states based on surveys in 1991 and 2008 in the Macquarie Marshes (Australia), a Ramsar wetland of international importance. We used a Bayesian logistic regression approach to model state and transitions between vegetation states and investigated how flood frequency, distance to stream and fire frequency were associated with vegetation dynamics during this period. 3. During 1991–2008, significant transitions have occurred towards drier states. Semi-permanent wetland vegetation had the lowest persistence probability (ppsis = 0·456) and a significant threshold response of transitioning to terrestrial vegetation (ptran = 0·505). Transition to drier states was driven by lower inundation probabilities followed by increased fire probability, and distance to nearest stream. 4. Using developed models, we predicted persistence probabilities of vegetation states under an unregulated (i.e. no dams or diversions) and regulated water availability system. Under a regulated system, semi-permanent wetland vegetation had an average persistence of ppsis = 0. 67 and 0·08 in the northern and southern sections of the nature reserve, respectively. Under an unregulated system, the predicted persistence of semi-permanent wetland vegetation was considerably higher: ppsis = 0·87 and 0·38, respectively. 5. Synthesis and applications. Developing quantitative models of state transitions significantly improved our understanding of ecosystem dynamics, identifying sensitive indicators for monitoring and thus supporting conservation decision-making. This helps managers understand potential trajectories of change in ecosystems in response to management options. For example, increasing environmental flows in the Macquarie Marshes is predicted to shift the community towards more of a wetland than the terrestrial state, resulting from river regulation. State and transition models identified how key ecological assets respond to drivers of change, particularly where these can be managed. This is critical for ensuring that all ecosystem components are managed and that these do not shift into undesirable states.
Data from: Developing state and transition models of floodplain vegetation dynamics as a tool for conservation decision-making: a case study of the Macquarie Marshes Ramsar wetland
Open the record for dataset details and reuse information.
Figure 5 in Spatiotemporal patterns of ground beetle diversity (Coleoptera: Carabidae) in a Ramsar wetland (Chott Tinsilt) of Algeria
Figure 5. Hierarchical clustering dendrogram illustrating abundance-based similarity of ground beetle species among months in Chott Tinsilt, northeastern Algeria (clustering method = Euclidean paired group, UPGMA).
Figure 2 in Faunal Composition of Ramsar Wetlands from India: An Analysis
Figure 2. Sum of Area (in sq km) of designated Ramsar sites with respect to year of declaration.
Sea Level Rise Impacts on Ramsar Wetlands of International Importance
The Sea Level Rise Impacts on Ramsar Wetlands of International Importance data set represents the results of an analysis using the boundaries for Ramsar sites designated under the Ramsar Convention on Wetlands and intersecting them with different elevation zones in the coastal zone to assess area and percent area that would become inundated under 1 and 2 meter sea level rise scenarios. This data set provides results for 613 sites with defined boundaries that were found to intersect with the 0-5m above mean sea level coastal zone, defined by NASA Shuttle Radar Topography Mission (SRTM) elevation data. In addition to assessing the degree of risk of inundation, the data set provides population density and percent of land that is urban within the site and within 1km and 5km buffers surrounding the site. The data set also reports on infant mortality rates within 1km and 5km buffers around the site, as a measure of poverty levels that may affect adaptive capacity.
ScienceDex guides
Understand access before you commit
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.