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Dataset results
753 results for “metrics”
Data from: Macrofaunal diversity patterns in coastal marine sediments: Re-examining common metrics and methods
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Data from: Measuring nestedness: a comparative study of the performance of different metrics
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Repository Analytics and Metrics Portal (RAMP) 2020 data
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Data for: Emigration and survival correlate with different precipitation metrics throughout a grassland songbird's annual cycle
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Data from: The article Euclimatch: An R package for climate matching with Euclidean distance metrics
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A globally influential area-condition metric is a poor proxy for invertebrate biodiversity
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Piecewise continuous sampling: a method for minimizing bias and sampling effort for estimated metrics of animal behavior
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Data from: Scoutknife: A naïve, whole genome informed phylogenetic robusticity metric
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Effects of supplemental feeding on nesting success and physiological metrics in Eastern Bluebirds (Sialia sialis)
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Ambient nutrients, carbon, and DOM absorbance metrics along with experimental dissolved oxygen decay rates for 5-day incubations of water within the Waccamaw River Watershed, SC, Summer 2020.
Dissolved oxygen (DO) impairment within coastal waters is widespread. Rising temperatures may exacerbate low DO levels by enhancing organic matter (OM) degradation. Here, the temperature sensitivity of OM degradation was investigated as DO decay rates determined during standard five-day biochemical oxygen demand (BOD) measurements conducted under different incubation temperatures. Sampling was conducted in the Waccamaw River watershed, South Carolina, a blackwater river with extensive forested wetland that also receives drainage from stormwater detention ponds associated with coastal development, thus providing contrasting sources of OM composition. Temperature sensitivities were measured as Q10 temperature coefficients, which define how DO decay rates change with 10 degrees of warming. The average Q10 value for the wetland sites (2.14 ± 0.41) was significantly greater (p = 0.004) than those measured in either the river (1.49 ± 0.36) or stormwater ponds (1.41 ± 0.21). Furthermore, using Intergovernmental Panel on Climate Change intermediate-to-very high temperature estimates for 2100 of +2.7 – 4.4 °C, average predicted increases in DO decay rates for wetlands (~22-39 %) are more than double the River (~11-18 %) and stormwater pond rates (~9-16 %). Our findings for inland, coastal waters agree with previous results for soils, suggesting that temperature sensitivities are variable across sites and increase with more complex, lower quality OM. Future modeling scenarios of DO utilization must therefore consider the influence of OM heterogeneity and the temperature sensitivity response of OM degradation across sources and region to better predict how climate change may impact oxygen impairment in aquatic ecosystems.
California Wildfire Resilience Core Metrics Rating Process and Results
The California Wildfire & Forest Resilience Task Force (Task Force) is producing a toolkit that can support organizations to prioritize, plan and implement actions to lessen wildfire risk to communities and improve broader statewide ecosystem resilience. As part of this effort, a core set of metrics needed to be identified to report resilience progress. The Task Force's Science Advisory Panel engaged in a rapid Delphi process, collecting expert opinion via surveys to provide content knowledge and science support for this process. This data archive provides content 1) for transparency, to share as much of our workflow as is feasible; 2) for others to pull from as an example if they want to do a similar process; 3) to provide all the detailed results on metrics if a reader wants to look into the ratings for and definition of a particular metric. The archive supports a report and paper summarizing and describing our Delphi method and the results regarding the specific metrics considered by our experts.
Warming effects of spring rainfall increase methane emissions from thawing permafrost: Site-level data from bog complex II - Carex Metrics 2014-2016
Methane emissions regulate the near-term global warming potential of permafrost thaw, particularly where loss of ice-rich permafrost converts forest and tundra into wetlands. Northern latitudes are expected to get warmer and wetter, and while there is consensus that warming will increase thaw and methane emissions, effects of increased precipitation are uncertain. At a thawing wetland complex in Interior Alaska, we found that interactions between rain and deep soil temperatures controlled methane emissions. In rainy years, recharge from the watershed rapidly altered wetland soil temperatures, warming the top ~80 cm of soil in spring and summer, and cooling it in autumn. When soils were warmed by spring rainfall, methane emissions increased by ~30%. The warm, deep soils early in the growing season likely supported both microbial and plant processes that enhanced emissions. Our study identifies an important and unconsidered role of rain in governing the radiative forcing of thawing permafrost landscapes. All site-level data from the studied bog, eddy covariance and micrometeorological data referenced in the published manuscript are available in the LTER data repository. These data are related to the following data package: Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest 2013-2016 (http://dx.doi.org/10.6073/pasta/4fabab3846113a1866b06f1b3d6d52a3).
Plant diverity and richness metrics across inter-annual precipitation variability treatments at a grassland site in the Jornada Basin, 2009-2014
This ongoing dataset contains metrics of plant diversity, evenness, and richness from a study at the Jornada Experimental Range (JER) in southern New Mexico. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009, has five precipitation treatments (see Methods) and contains 50 plots (10 per treatment). This data package contains 6-year (2009 to 2014) means of metrics per plot. Annual and more recent data are available and will be released pending an upcoming publication.
McMurdo Dry Valleys Soil Apatite Grain Weathering Metrics from Taylor Valley, Antarctica
Mineral apatite is the ultimate source of the essential nutrient phosphorus to the soil ecosystem. In order to assess the biogeochemical weathering of apatite grains in the dry, basic soils of the McMurdo Dry Valleys, we collected nine surface soil samples from the Fryxell and Bonney Basins of Taylor Valley. After separating more than 50 individual soil apatite grains from each sample, we used scanning electron microscopy to quantify the morphology and surface etching of apatite grains to determine the degree of weathering. We developed three metrics to quantify the degree of weathering: aspect ratio, percent crystal faces, and a qualitative pitting index. This dataset contains the raw data from analyzing the morphology of more than 600 grains using the software ImageJ. Samples were collected during January 2013. The samples from the Bonney Basin (LB) were collected 21 Jan 2013, and the samples from the Fryxell Basin (LF) were collected 18 January 2013. Samples were processed and analyzed 2014-2016.
Dataset - How do you propose your code changes? Empirical Analysis of Affect Metrics of Pull Requests on GitHub
<p>This package contains the raw open data for the study </p> <p>Marco Ortu, Giuseppe Destefanis, Daniel Graziotin, Michele Marchesi, Roberto Tonelli. 2020. How do you propose your code changes? Empirical Analysis of Affect Metrics of Pull Requests on GitHub. Under Review.</p> <p>The dataset is based on GHTorrent dataset:</p> <p>Georgios Gousios. 2013. The GHTorent dataset and tool suite. In Proceedings of the 10th Working Conference on Mining Software Repositories (MSR ’13). IEEE Press, 233–236</p> <p>And released with the same license (CC BY-SA 4.0).</p>
Privacy metrics suites for genomic privacy, vehicular communications privacy, and graph privacy
<p>This dataset contains optimized suites of privacy metrics for three application domains: genomic privacy, vehicular communications privacy, and graph privacy.</p> <p>The dataset also contains the data we have used as input for the evolutionary optimization algorithms.</p>
Common field data limitations can substantially bias sexual selection metrics
<p>Sexual selection studies widely estimate several metrics, but values may be inaccurate because standard field methods for studying wild populations produce limited data (e.g., incomplete sampling, inability to observe copulations directly). We compared four selection metrics (Bateman gradient, opportunity for sexual selection, opportunity for selection, and <em>s'<sub>max</sub></em>) estimated with simulated complete and simulated limited data for 15 socially monogamous songbird species with extra-pair paternity (4-54% extra-pair offspring). Inferring copulation success from offspring parentage creates non-independence between these variables and systematically underestimates copulation success. We found that this introduces substantial bias for the Bateman gradient, opportunity for sexual selection, and <em>s'<sub>max</sub></em>. Notably, 47.5% of detected Bateman gradients were significantly positive for females, suggesting selection on females to copulate with multiple males, though the true Bateman gradient was zero. Bias generally increased with the extent of other sources of data limitations tested (nest predation, male infertility, and unsampled floater males). Incomplete offspring sampling introduced bias for all metrics except the Bateman gradient, while incomplete sampling of extra-pair sires did not introduce additional bias when sires were a random subset of breeding males. Overall, our findings demonstrate how biases due to field data limitations can strongly impact the study of sexual selection.</p>
Metrics by commit for Android
<p>This dataset is a set of csv files. Each file contains the metrics by commit of all android code samples analyzed in the paper. </p>
WEGE: A new metric for ranking locations for biodiversity conservation
<p>Aim Effective policy making for biological conservation requires the identification and ranking of the most important areas for protection or management. One of the most frequently used systems for selecting priority areas is Key Biodiversity Areas (hereafter KBAs), developed by the International Union for Conservation of Nature (IUCN). However, KBAs cannot be used to rank areas, potentially limiting their use when limited funding is available. To tackle this shortcoming and facilitate spatial prioritization, here we develop and validate the "WEGE index" (Weighted Endemism including Global Endangerment index), consisting of an adaptation of the EDGE score (Evolutionarily Distinct and Globally Endangered). WEGE allows the ranking of any set of locations according to the KBA guidelines and on a continuous scale. Location Global. Methods We calculated the EDGE score, Weighted Endemism, Evolutionary distinctiveness, Extinction risk and our newly developed WEGE index for all terrestrial species of amphibians, mammals and birds accessed by IUCN. We then compared the performance of each of those five indices at prioritizing areas according to the KBA guidelines. Results We found that for all taxa surveyed, WEGE was consistently better at identifying areas that trigger KBA status. Main conclusions In our analyses, WEGE outperformed all other methods and metrics designed for similar purposes. It can therefore serve as a robust evidence-based methodology to prioritize among otherwise equally qualified sites according to the KBA categories. WEGE can therefore support transparent, evidence-based and biologically meaningful decision-making for conservation priorities.</p>
2019 EMDataResource Model Metrics Challenge Dataset
<p>This is the full dataset of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource (<a href="http://www.emdataresource.org">www.emdataresource.org</a>, <a href="http://challenges.emdataresource.org">challenges.emdataresource.org</a>, <a href="http://model-compare.emdataresource.org">model-compare.emdataresource.org</a>). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers and users, and (3) compare the performance of current metrics used for evaluation of models. The focus was on near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution series (1.8 to 3.1 Å) from the same specimen and imaging experiment. Tools developed in previous challenges were expanded for managing, visualizing and analyzing the 63 submitted coordinate models, and several new metrics were introduced.</p> <p>File Descriptions:</p> <ul> <li>2019-EMDataResource-Challenge-web.pdf: Archive of News, Goals, Timeline, Targets, Modelling Instructions, Process, FAQ, Submission Instructions, Submission Summary Statistics source from the <a href="https://challenges.emdataresource.org">EMDR Challenges</a> website</li> <li>correlation-images.tar.gz: Pairwise correlation tables for selected metric scores from the <a href="https://model-compare.emdataresource.org">EMDR Model Compare</a> website</li> <li>maps.tar.gz: The maps used for Fit-to-Map analyses in the Challenge</li> <li>models.tar.gz: The 63 models submitted by the modelling teams</li> <li>results.tar.gz: The output logs for all of the analysis methods</li> <li>Scores.xlsx: Scores for each model and analysis method, compiled into spreadsheet format</li> <li>targets.tar.gz: The reference models used in the analysis</li> </ul> <p>Post submission correction to the web archive PDF document: The full list of EMDataResource members on the model committee is as follows: Cathy Lawson, Andriy Kryshtafovych, Greg Pintilie, Mike Schmid, Helen Berman, Wah Chiu.</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.