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.
134
datasets available to search
ShareScore release 0.9.0
Dataset results
134 results for “Ecosystem structure”
Figure 6 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan
Figure 6. Analysis of CCA plot illustrating correlation between calciumcarbonate and plant communities along axis-1 and 2.
Data from: The importance of landscape and spatial structure for hymenopteran-based food webs in an agro-ecosystem
1. Understanding the environmental factors that structure biodiversity and food webs among communities is central to assess and mitigate the impact of landscape changes. 2. Wildflower strips are ecological compensation areas established in farmland to increase pollination services and biological control of crop pests, and to conserve insect diversity. They are arranged in networks in order to favour high species richness and abundance of the fauna. 3. We describe results from experimental wildflower strips in a fragmented agricultural landscape, comparing the importance of landscape, of spatial arrangement, and of vegetation on the diversity and abundance of trap-nesting bees, wasps and their enemies, and the structure of their food webs. 4. The proportion of forest cover close to the wildflower strips and the landscape heterogeneity stood out as the most influential landscape elements, resulting in a more complex trap nest community with higher abundance and richness of hosts, and with more links between species in the food webs and a higher diversity of interactions. We disentangled the underlying mechanisms for variation in these quantitative food-web metrics. 5. We conclude that in order to increase the diversity and abundance of pollinators and biological control agents and to favour a potentially stable community of cavity nesting hymenoptera in wildflower strips, more investment is needed in the conservation and establishment of forest habitats within agro-ecosystems, as a reservoir of beneficial insect populations.
Canopy temperature is regulated by ecosystem structural traits and captures the ecohydrologic dynamics of a semiarid mixed conifer forest site
<p>The data have been used in a published article in the Journal of Geophysical Research: Biogeosciences, titled "Canopy temperature is regulated by ecosystem structural traits and captures the ecohydrologic dynamics of a semiarid mixed conifer forest site". Please check out the published article for more information about the data.<br> <br> Javadian, M., Smith, W. K., Lee, K., Knowles, J. F., Scott, R. L., Fisher, J. B., et al. (2022). Canopy temperature is regulated by ecosystem structural traits and captures the ecohydrologic dynamics of a semiarid mixed conifer forest site. <em>Journal of Geophysical Research: Biogeosciences</em>, 127, e2021JG006617. <a href="https://doi.org/10.1029/2021JG006617">https://doi.org/10.1029/2021JG006617</a><br> <br> There are 5 folders in the main folder as follows:<br> <br> 1."EC_Tower" : The flux tower data over US-MtB eddy covariance site from Jan 2020 to May 2021.<br> 2. "FLIR_Thermometer": The vertical temperature profiles on Nov, 14, 2020.<br> 3."PRI": The photochemical reflectance index (PRI) from Jan 2020 to Feb 2021.<br> 4. "Tree_Sap_Flow": Tree sap flow data from Jan 2020 to May 2021.<br> 5. "UAS": Unmanned Aircraft Systems (UAS) images</p>
Country-wide data of ecosystem structure from the fourth Dutch airborne laser scanning survey (AHN4)
<p>This data repository contains country-wide data products for the ecosystem structure metrics generated from Airborne Laser Scanning (ALS) data across the Netherlands (AHN4). Twenty-five ecosystem structure metrics (at 10-meter resolution, GeoTIFF format) were derived from the AHN4 dataset (<a href="https://www.ahn.nl/ahn-viewer">https://www.ahn.nl/ahn-viewer</a>) using <a href="https://laserfarm.readthedocs.io/en/latest/">Laserfarm</a> workflow (<a href="https://zenodo.org/record/5636773">https://zenodo.org/record/5636773</a>). Laserfarm is a free and open-source workflow that enables efficient, scalable, and distributed processing of multi-terabyte LiDAR point clouds from national and regional ALS surveys into LiDAR metrics of ecosystem structure. All code of Laserfarm is hosted and freely available on GitHub (<a href="https://github.com/eEcoLiDAR/Laserfarm">https://github.com/eEcoLiDAR/Laserfarm</a>).</p> <p>Note that we also published the data products generated from AHN3 (2014-2019), which you can find in the repository here: <a href="https://doi.org/10.5281/zenodo.6421381">https://doi.org/10.5281/zenodo.6421381</a>. Laserfarm workflow was also employed to generate the data products from AHN4 (2020-2022). </p> <p>The twenty-five LiDAR metrics are related to three key dimensions of ecosystem structure (ecosystem height, ecosystem cover, and ecosystem structural complexity). Each GeoTIFF layer represents one LiDAR metric at 10 m resolution covering the whole Netherlands (file name as "ahn4_10m_featrue_name.tiff").</p> <p>A detailed description of all the metrics can be found in the README file (README.pdf). </p> <p>Relevant publications:</p> <p>Kissling, W.D., Shi, Y., Koma, Z., Meijer, C., Ku, O., Nattino, F., Seijmonsbergen, A.C., & Grootes, M.W. (2022). Laserfarm – A high-throughput workflow for generating geospatial data products of ecosystem structure from airborne laser scanning point clouds. <em>Ecological Informatics, 72</em>, 101836 (<a href="https://doi.org/10.1016/j.ecoinf.2022.101836">https://doi.org/10.1016/j.ecoinf.2022.101836</a>)</p> <p>Kissling, W.D., Shi, Y., Koma, Z., Meijer, C., Ku, O., Nattino, F., Seijmonsbergen, A.C., & Grootes, M.W. (2023). Country-wide data of ecosystem structure from the third Dutch airborne laser scanning survey. <em>Data in Brief, 46</em>, 108798 (<a href="https://doi.org/10.1016/j.dib.2022.108798">https://doi.org/10.1016/j.dib.2022.108798</a>)</p> <p> </p>
Millennial-scale change in Caribbean coral reef ecosystem structure and the role of human and natural disturbance
Open the record for dataset details and reuse information.
Data from: How habitat-modifying organisms structure the food web of two coastal ecosystems
Open the record for dataset details and reuse information.
Data from: Eco-evolution in size-structured ecosystems: simulation case study of rapid morphological changes in alewife
Open the record for dataset details and reuse information.
Data from: The importance of landscape and spatial structure for hymenopteran-based food webs in an agro-ecosystem
Open the record for dataset details and reuse information.
Phylogeography and population structure of the tsetse fly Glossina pallidipes in Kenya and the Serengeti ecosystem
Open the record for dataset details and reuse information.
Data from: Population size-structure dependent fitness and ecosystem consequences in Trinidadian guppies
Open the record for dataset details and reuse information.
Global Forest Ecosystem Structure and Function Data For Carbon Balance Research
A comprehensive global database has been assembled to quantify CO2 fluxes and pathways across different levels of integration (from photosynthesis up to net ecosystem production) in forest ecosystems. The database fills an important gap for model calibration, model validation, and hypothesis testing at global and regional scales. The database archive includes: a Microsoft Office Access Database; data files for all tables in the database; query outputs from the database; and SQL script file for re-creating the database from the tables. The database is structured by site (i.e., a forest or stand of known geographical location, biome, species composition, and management regime). It contains carbon budget variables (fluxes and stocks), ecosystem traits (standing biomass, leaf area index, age), and ancillary information (management regime, climate, soil characteristics) for 529 sites from eight forest biomes. Data entries originated from peer-reviewed literature and personal communications with researchers involved in Fluxnet. Flux estimates were included in the database when they were based on direct measurements (e.g., tower-based eddy covariance system measurements), derived from single or multiple direct measurements, or modeled. Stand description was based on observed values, and climatic description was based on the CRU data set and ORCHIDEE model output. Uncertainty for each carbon balance component in the database was estimated in a uniformed way by expert judgment. Robustness of CO2 balances was tested, and closure terms were introduced as a numerical way to approach data quality and flux uncertainty at the biome level.
Effectiveness of Structured Ecosystems Therapy for Reducing HIV Risk Behaviors and Improving Treatment Adherence in HIV Infected Men Released From Prison
ClinicalTrials.gov study NCT00344591. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Phylogenetic structure of an Andean and Amazonian ecosystem
<p><strong>Abstract</strong></p> <p><br> Phylogenetic structures, the relatedness of species based on evolutionary traits, are still hardly studied. Several studies in the last three decades have been performed to examine taxonomic structures in forest and non-forest areas. Based on recent studies of phylogenetic structures in the Amazon forest, we aimed to explore the phylogenetic structure of non-forest areas in tropical South-America. We focused on mechanisms, such as environmental filtering and dispersal on the species composition and phylogenetic structure in these types of regions. We selected two of these non-forest areas, namely Guiana Shield (sandstone plateau in the Amazon) and Páramo (Andean). Vegetation and location data of both areas were analyzed. Our results suggested that these mechanisms play a crucial role in the phylogenetic structure in both regions. A significant negative correlation has been found between phylogenetic similarity and geographical (Euclidean) distance in Guiana Shield and Páramo. An NMDS-ordination showed the similarity between the different communities and substantiate the correlation found. Based on the positive values of the NRI and NTI, both regions were phylogenetically clustered. We concluded that mechanisms of environmental filtering and dispersal are important historical drivers that influence the phylogenetic structure, similarity and clustering in both these non-forest ecosystems.</p>
Phylogenetic structure of an Andean and Amazonian ecosystem
<p><strong>Abstract</strong></p> <p><br> Phylogenetic structures, the relatedness of species based on evolutionary traits, are still hardly studied. Several studies in the last three decades have been performed to examine taxonomic structures in forest areas and non-forest areas. Based on recent studies of phylogenetic structures in Amazonia-forest, we aimed to explore the phylogenetic structure of non-forest areas in tropical South-America. We focused on mechanisms, such as environmental filtering and dispersal on the species composition and phylogenetic structure in these types of regions. We selected two of these non-forest areas, namely Guiana Shield (Sandstone plateau in the Amazon) and Páramo (Andean). y Vegetation and location data of both areas were analyzed. Our results suggested that these mechanisms play a crucial role in the phylogenetic structure in both regions. A significant negative correlation has been found between phylogenetic similarity and geographical (Euclidean) distance in Guiana Shield and Páramo. An NMDS-ordination showed the similarity between the different communities and substantiate the correlation found. Based on the positive values of the NRI and NTI, both regions were phylogenetically clustered. We concluded that mechanisms of environmental filtering and dispersal are important historical drivers that influence the phylogenetic structure, similarity and clustering in both these non-forest ecosystems.</p>
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.