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.
14
datasets available to search
ShareScore release 0.9.0
Dataset results
14 results for “constructed communities”
Differences in mammal community response to highway construction across different levels of human land use
Open the record for dataset details and reuse information.
Online Resources Chapter 3 - Decomposition of standing litter biomass in newly constructed wetlands associated with direct effects of sediment and water characteristics and the composition and activity of the decomposer community using Phragmites australis as a single standard substrate
<p>Online Resources to Chapter 3 "Decomposition of standing litter biomass in newly constructed wetlands associated with direct effects of sediment and water characteristics and the composition and activity of the decomposer community using Phragmites australis as a single standard substrate" of PhD thesis from Ciska Overbeek, "Peat formation on a former landfill - Production and decomposition of aquatic pioneer vegetation". </p> <p>Published by Overbeek et al in 2019 in Wetlands 39(1): 113-125. https://doi.org/10.1007/s13157-018-1081-y. </p>
Spatio-temporal dynamics of insect communities in constructed and natural tidal marshes with distinct landscape positions
Open the record for dataset details and reuse information.
Data from: Hydrological dynamics, wetland morphology and vegetation structure determine riparian arthropod communities in constructed wetlands
Open the record for dataset details and reuse information.
Data from: Constructing more informative plant-pollinator networks: visitation and pollen deposition networks in a heathland plant community
Interaction networks are widely used as tools to understand plant–pollinator communities, and to examine potential threats to plant diversity and food security if the ecosystem service provided by pollinating animals declines. However, most networks to date are based on recording visits to flowers, rather than recording clearly defined effective pollination events. Here we provide the first networks that explicitly incorporate measures of pollinator effectiveness (PE) from pollen deposition on stigmas per visit, and pollinator importance (PI) as the product of PE and visit frequency. These more informative networks, here produced for a low diversity heathland habitat, reveal that plant–pollinator interactions are more specialized than shown in most previous studies. At the studied site, the specialization index Embedded Image was lower for the visitation network than the PE network, which was in turn lower than Embedded Image for the PI network. Our study shows that collecting PE data is feasible for community-level studies in low diversity communities and that including information about PE can change the structure of interaction networks. This could have important consequences for our understanding of threats to pollination systems.
Constructing a social-behavioral association network to study management impact on waterbird community ecology using digital video recording cameras
<p>Studying social behavior and species associations in ecological communities is challenging because it is difficult to observe the interactions in the field. Animal behavior is especially difficult to observe when selection of habitat and activities are linked to energy costs of long-distance movement. Migrating communities tend to be resource specific and prefer environments that offer more suitability for coexisting in a shared space and time. Given the recent advances in digital technologies, digital video recording systems are gaining popularity in wildlife research and management. We used digital video recording cameras to study social interactions and species-habitat linkages for wintering waterbird communities in shared habitats. Examining over 8,640 hours of video footages, we built tetrapartite social behavioral association network of wintering waterbirds over habitat (n=5) selection events in sites with distinct management regimes. We analyzed these networks to identify hub species and species role in activity persistence, and to explore the effects of hydrological regime on these network characteristics. Although the differences in network attributes were not significant at treatment level (<i>p</i> = 0.297) in terms of network composition and keystone species composition, our results indicated that network attributes were significantly different (<i>p </i>= 0.000, <i>r<sup>2</sup></i><sup> </sup>= 0.278) at habitat level. There were evidences suggesting that the habitat quality was better at the managed sites, where the formed networks had more species, more network nodes and edges, higher edge density, and stronger intra- and inter-species interactions. In addition, we also calculated the species interaction preference scores (SIPS) and behavioral interaction preference scores (BIPS) of each network. The results showed that species synchronize activities in shared space for temporal niche partitioning in order to avoid or minimize any potential competition for shared space. Our social network analysis (SNA) approach is likely to provide a practical use for ecosystem management and biodiversity conservation.</p>
Data from: Constructing more informative plant-pollinator networks: visitation and pollen deposition networks in a heathland plant community
Open the record for dataset details and reuse information.
Constructing a social-behavioral association network to study management impact on waterbird community ecology using digital video recording cameras
Open the record for dataset details and reuse information.
Data from: Construction and characterization of synthetic bacterial community for experimental ecology and evolution
Open the record for dataset details and reuse information.
Constructing A Model of Health Promotion and Active Aging for Community-Dwelling Older Adults
ClinicalTrials.gov study NCT03612167. IPD Sharing: NO. Countries: 1. Publications: 0.
Effectiveness of Active Brain Construction Program in Community-Dwelling Older Adults
ClinicalTrials.gov study NCT07282626. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Constructing and Evaluating the Effectiveness of a Community-based Older Adults Dementia Prevention Education Program
ClinicalTrials.gov study NCT06998836. IPD Sharing: NO. Countries: 1. Publications: 0.
Community Intervention and Demonstration Area Construction
ClinicalTrials.gov study NCT05715424. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study of the Construct Validity of Community Walking Speed Data Collected Remotely With the Canary canturioTM te Tibial Extension
ClinicalTrials.gov study NCT05539326. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.