Find research datasets worth reusing

opencc-zeroDec 2017View details →

Data from: Landscape history confounds the ability of the NDVI to detect fine-scale variation in grassland communities

1. The NDVI is a remotely-sensed vegetation index that is frequently used in ecological studies. There is, however, a lack of studies that evaluate the ability of the NDVI to detect fine-scale variation in grassland plant community composition and species richness. Ellenberg indicators characterize the environmental preferences of plant species – and community-mean Ellenberg values have been used to explore the environmental drivers of community assembly. 2. We used variation partitioning to test the ability of satellite-based NDVI to explain community-mean Ellenberg nutrient (mN) and moisture (mF) indices, and the richness of habitat-specialist species in dry grasslands of different ages. The grasslands represent a gradient of decreasing soil nutrient status. 3. If community composition is determined by the responses of individual species to the underlying environmental conditions and if, at the same time, community composition determines the optical characteristics of the vegetation canopy, then positive relationships between the NDVI and mN and mF are expected. Many grassland specialists are intolerant of nutrient-rich soils. If specialist richness is negatively related to soil-nutrient levels, then a negative association between the NDVI and specialist richness is expected. However, because grassland community composition is not only influenced by abiotic variables but also by other spatial and temporal drivers, we included spatial variables and grassland age in the statistical analyses. 4. The NDVI explained the majority of the variation in mF, and also contributed to a substantial proportion of the variation in mN. However, variation in specialist richness and the lowest values of mN were explained by grassland age and spatial variables – but were poorly explained by the NDVI. 5. Synthesis and applications. The NDVI showed a good ability to detect variation in plant community composition, and should provide a valuable tool for assessing fine-scale environmental variation in grasslands or for monitoring changes in grassland habitat properties. However, because the concentration of grassland specialists not only depends on environmental variables but also on the age and spatial context of the grasslands, the NDVI is unlikely to allow the identification of grasslands with high numbers of specialist species.

opencc-zeroDec 2014View details →

Data from: Identification of migratory bird flyways in North America using community detection on biological networks

Migratory behavior of waterfowl populations in North America has traditionally been broadly characterized by four north-south flyways, and these flyways have been central to the management of waterfowl populations for more than 80 years. However, previous flyway characterizations are not easily updated with current bird movement data and fail to provide assessments of the importance of specific geographical regions to the identification of flyways. Here, we developed a network model of migratory movement for four waterfowl species —mallard (Anas platyrhnchos), northern pintail (A. acuta), American green-winged teal (A. carolinensis), and Canada goose (Branta canadensis) — in North America using bird band and recovery data. We then identified migratory flyways using a community detection algorithm and characterize the importance of smaller geographic regions in identifying flyways using a novel metric, the consolidation factor. We identified four main flyways for mallards, northern pintails, and American green-winged teal with the flyway identification in Canada geese exhibiting higher complexity. For mallards, flyways were relatively consistent through time. However, consolidation factors revealed that for mallards and green-winged teal the presumptive Mississippi flyway was potentially a zone of high mixing between other flyways. Our results demonstrate that the network approach provides a robust method for flyway identification that is widely applicable given the relatively minimal data requirements and is easily updated with future movement data to reflect changes in flyway definitions and management goals.

opencc-zeroApr 2022View details →

Data from: A new composite abundance metric detects stream fish declines and community homogenization during six decades of invasions

Aim: We developed a new technique, utilizing species-specific counts of individuals from historical fish community samples, to examine landscape-level, spatiotemporal trends in relative abundance distributions. Abundance-based historical distribution analyses are often plagued by data comparability issues, but provide critical information about community composition trends inaccessible to those using analyses based only on species presence-absence. We established trends in native and non-native fish abundance and community homogenization, uniqueness, and diversity to help local conservation managers prioritize targets and motivate similar studies globally to support fish conservation. Location: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA. Methods: We compiled catch data from 61 years of fish community surveys (1958-2019) and tested for community homogenization by comparing data from repeatedly sampled sites (1900s versus 2000s samples) using dispersion analyses. We measured community uniqueness (site contributions to beta diversity) and species diversity (Shannon index) at sampled streams to identify potential conservation hotspots. We then used regression analyses and Wilcoxon signed-rank tests to examine species-specific basin-wide and local abundance trends and identify species of potential conservation concern. Results: Dispersion of sites in species-abundance space was significantly greater in the 1900s compared to the 2000s, indicating homogenization had occurred. Of 36 native species analyzed, 44.4% (16) showed basin-wide declines. Non-native species exhibited mixed patterns; site-level abundance increased in 2 of 15 species analyzed (13%). Main conclusions: Our results indicate basin-wide community homogenization has occurred within the UMNR, but many unique and diverse communities persist. If conserved, these could help maintain regional fish diversity. We found basin-wide declines in four endemic species, as well as spread patterns of non-native and native species that were not detected by a presence-absence analysis applied within the same study area. This finding illustrates the importance of considering both species' abundance and occurrence patterns as separate dimensions of biodiversity to inform conservation planning.

zenodo32/100

Data for "Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure"

New York City contact network data used in the publication “<a href="https://doi.org/10.1016/j.socnet.2024.06.003">Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure</a>” (LA-UR-23-26868). This contact network comes in the form of a weighted edge list. Each row describes an edge, with the first and second column containing the labels of the nodes connected by the edge, and the third column contains the corresponding weight of the edge. In this network, an edge encodes an interaction between two individuals and the weight describes the duration of the interaction in seconds. In total the edge list describes 6,376,729,847 interactions among 6,813,615 individuals; the first 10 interactions are listed below as an example. 2, 1, 84121 4, 3, 83654.4 5, 3, 79591.4 5, 4, 87642 6, 3, 79853 6, 4, 81604 6, 5, 79146 8, 7, 80604 10, 9, 84259.6 12, 11, 68990.8   This work is approved for public distribution under LA-UR-24-25046.

opencc-by-4.0May 2024View details →

opencc-zeroDec 2019View details →

Data from: Comparison of fish detections, community diversity, and relative abundance using environmental DNA metabarcoding and traditional gears

Background Detecting species at low abundance, including aquatic invasive species (AIS), is critical for making informed management decisions. Environmental DNA (eDNA) methods have become a powerful tool for rare or cryptic species detection; however, many eDNA assays offer limited utility for community‐level analyses due to their use of species‐specific (presence/absence) 'barcodes'. Metabarcoding methods provide information on entire communities based on sequencing of all taxon‐specific barcodes within an eDNA sample. Aims Evaluate measures of fish species detections, community diversity, and estimates of relative abundance based on eDNA metabarcoding and traditional fisheries sampling approaches in the context of fish community characterization and AIS survellience. Materials and Methods In 2016, eight limnologically diverse lakes (surface area range: 13 – 1,728 ha) in Michigan, USA were sampled using a variety of traditional fisheries gears to characterize fish community composition. Environmental DNAs from surface (33 ± 6, mean ± 1 SD) and benthic (14 ± 2) water samples from each lake were isolated and amplified for two metabarcoding markers (mitochondrial 12S and 16S rDNA loci) using fish‐specific primers. Fish species detected within each lake were determined by comparing the sequencing data to a database of sequences from native Michigan fish species and 19 AIS on the Michigan's Watch List. Results Analysis of species accumulation curves indicated multi‐locus eDNA metabarcoding assays can enhance species detection capacities and characterize 95% of a fish community in fewer sampling efforts than traditional gear (range: 2 – 62, median: 14). In addition, all AIS detected in traditional gear samples were also detected by eDNA, while some AIS detected by eDNA assays were absent from traditional gear samples. Discussion Results reported here are, in part, driven by the lack of species‐selectivity during eDNA sampling events. Given the efficacy of eDNA assays, we suggest multi‐locus eDNA metabarcoding assays be implemented in early detection efforts.

zenodo32/100

Dataset for the Paper: "Security Defect Detection via Code Review: A Study of the OpenStack and Qt Communities"

This is the dataset for the paper: "Security Defect Detection via Code Review: A Study of the OpenStack and Qt Communities ", including the extracted data and results. The dataset contains the following three folders: 1. RQ1:  <ul> <li>Security defect in Nova.xlsx</li> <li>Security defect in Neutron.xlsx</li> <li>Security defect in Qt Base.xlsx</li> <li>Security defect in Qt Creator.xlsx;</li> </ul> The RQ1 folder contains four files corresponding to the four projects (i.e., Nova and Neutron from OpenStack, Qt Base and Qt Creator from Qt), including 539 security-related review comments, in which security defects were identified by the reviewers. These instances were obtained from manual labelling after keyword-based search. The security defect type of these instances are  presented to answer RQ1. How to Read the MS Excel files in RQ1: Each of the four MS Excel files in this folder contains 6 sheets for six years from 2017 to 2022. Each sheet has 10 columns for recoding 10 data items, among which the last four data items are used in our study to answer the RQs. We list the data items in the following table. <table> <tbody> <tr> <td>Data Item</td> <td>Description</td> <td>Source</td> </tr> <tr> <td>Keyword</td> <td>The corresponding keyword of the comment.</td> <td>Keyword-based Search</td> </tr> <tr> <td>Code_change_id</td> <td>The code_change_id of the comment.</td> <td>Gerrit</td> </tr> <tr> <td>File</td> <td>The file in which the comment is added.</td> <td>Gerrit</td> </tr> <tr> <td>Patchset</td> <td>The patchset of the comment within the code change.</td> <td>Gerrit</td> </tr> <tr> <td>Line</td> <td>The line number in the file at which the comment is added.</td> <td>Gerrit</td> </tr> <tr> <td>Message</td> <td>The text of the review comment.</td> <td>Gerrit</td> </tr> <tr> <td>Security-related</td> <td>Whether the review comment is security-related (i.e., Yes or No).</td> <td>Labelling</td> </tr> <tr> <td>Security defect type</td> <td>The type of the security defect identified in the comment.</td> <td>Labelling</td> </tr> <tr> <td>Consequence</td> <td>The Consequence of the security defect.</td> <td>Extraction</td> </tr> <tr> <td>Resolution Evidence</td> <td>The information about where the identified security defect was resolved in the code</td> <td>Extraction</td> </tr> </tbody> </table> 2. RQ2:  <ul> <li>Extracted data for RQ2.mx22</li> </ul> The RQ2 folder contains the extracted data of 539 security-related review comments in Extracted data for RQ2.mx22, which was encoded and analyzed by the MAXQDA tool, investigating the treatment of security defects by developers and reviewers to answer RQ2. 3. RQ3:  <ul> <li>Extracted data for RQ3.mx22</li> </ul> The RQ3 folder contains the extracted data of 161 review comments in which identified security defects were not resolved by developers in Extracted data for RQ3.mx22. which was also encoded and analyzed by the MAXQDA tool, exploring the causes of not resolving security defects to answer RQ3. Note: The mx22 can be opened by MAXQDA 22, which are available at <a href="https://www.maxqda.com/">https://www.maxqda.com/</a> for download. You may also use the free trial version of MAXQDA 2022, which is available at <a href="https://www.maxqda.com/trial">https://www.maxqda.com/trial</a> for download.

opencc-by-4.0May 2023View details →

Evaluating the Efficacy of a Detection and Prevention Program for Frail Community-dwelling Older Adults

ClinicalTrials.gov study NCT03168204. IPD Sharing: Not stated. Countries: 1. Publications: 3.

Community-led Responses for Elimination: Controlled Trial of Reactive Case Detection Versus Reactive Drug Administration

ClinicalTrials.gov study NCT02654912. IPD Sharing: Not stated. Countries: 1. Publications: 2.

A Stool DNA Test for Detection of Advanced Colorectal Neoplasia in Asymptomatic Chinese Community Population

ClinicalTrials.gov study NCT04786704. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.

Effect of Community Active Case Finding Strategies for Detection of Tuberculosis in Cambodia

ClinicalTrials.gov study NCT04094350. IPD Sharing: NO. Countries: 1. Publications: 13.

NeuroCare Community Project: A Community Based Prospective Observational Study for Early Alzheimer's Detection in HK

ClinicalTrials.gov study NCT07347574. IPD Sharing: NO. Countries: 1. Publications: 2.

Primary Care Detection of Cognitive Impairment Leveraging Health & Consumer Technologies in Underserved Communities: The MyCog Trial

ClinicalTrials.gov study NCT05607732. IPD Sharing: NO. Countries: 1. Publications: 1.

Community-Based Health Education Programs for the Early Detection of, and Vaccination Against, COVID-19 and the Adoption of Self-Protective Measures of Hong Kong Residents

ClinicalTrials.gov study NCT05539482. IPD Sharing: Not stated. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →

Implementation Study of the ICOPE Program for the Detection of Frailty in the Elderly Within the Territorial Health Professional Communities (CPTS) of Brest Region

ClinicalTrials.gov study NCT05541731. IPD Sharing: YES. Countries: 1. Publications: 1.

Detection of Clinical-functional Changes Following Exercise Therapy and Neuroscience Education in Institutionalised and Community-dwelling Older Adults Diagnosed With Sarcopenia

ClinicalTrials.gov study NCT05875597. IPD Sharing: NO. Countries: 1. Publications: 8.

A Community Population Screening Cohort Study Based on Polygene Methylation Detection for Colorectal Cancer in Yangzhou

ClinicalTrials.gov study NCT05336539. IPD Sharing: NO. Countries: 1. Publications: 2.