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9,882 results for “Scale”
Data from: Habitat connectivity is determined by the scale of habitat loss and dispersal strategy
Understanding factors that ameliorate the impact of habitat loss is a major focus of conservation research. One key factor influencing species persistence and evolution is the ability to disperse across increasingly patchy landscapes. Here we ask whether interpatch distance (a proxy for habitat loss) and dispersal strategy can interact to form thresholds where connectivity breaks down. We assayed dispersal across a range of interpatch distances in fruit flies carrying allelic variants of a gene known to underlie differences in dispersal strategy. Dispersal-limited flies experienced a distinct negative threshold in connectivity at greater interpatch distances, and this was not observed in more dispersive flies. Consequently, this differential response of dispersal-limited and more dispersive flies to decreasing connectivity suggests that habitat loss could have important implications on the evolution and maintenance of genetic variation underlying dispersal strategy.
Data from: A cross-scale trophic cascade from large predatory fish to algae in coastal ecosystems
Trophic cascades occur in many ecosystems, but the factors regulating them are still elusive. We suggest that an overlooked factor is that trophic interactions (TIs) are often scale-dependent and possibly interact across spatial scales. To explore the role of spatial scale for trophic cascades, and particularly the occurrence of cross-scale interactions (CSIs), we collected and analysed food-web data from 139 stations across 32 bays in the Baltic Sea. We found evidence of a four-level trophic cascade linking TIs across two spatial scales: at bay scale, piscivores (perch and pike) controlled mesopredators (three-spined stickleback), which in turn negatively affected epifaunal grazers. At station scale (within bays), grazers on average suppressed epiphytic algae, and indirectly benefitted habitat-forming vegetation. Moreover, the direction and strength of the grazer–algae relationship at station scale depended on the piscivore biomass at bay scale, indicating a cross-scale interaction effect, potentially caused by a shift in grazer assemblage composition. In summary, the trophic cascade from piscivores to algae appears to involve TIs that occur at, but also interact across, different spatial scales. Considering scale-dependence in general, and CSIs in particular, could therefore enhance our understanding of trophic cascades.
Symbrain: A large-scale dataset of MRI images for neonatal brain symmetry analysis
Open the record for dataset details and reuse information.
Dataset of "Pore-scale simulation of the impact of CO2-Water-Mineral Interaction on Rock Permeability and Mechanical Properties"
<p>This dataset supports the research study 'Pore-scale simulation of the impact of CO2-Water-Mineral Interaction on Rock Permeability and Mechanical Properties' by B. Yang, T. Xu, Z. Jiang, and H. Zhu.</p>
Hospital Anxiety and Depression Scale (HADS)
<p>Data set</p>
R unmarked dataframe: Fine-scale forest structure, not management regime, drives occupancy of a declining songbird, the Olive-sided Flycatcher, in the core of its range
<p>Encounter history, site covariates, and observation covariates formatted as an unmarkedFrameOccu object for use in program R with the package unmarked to replicate the analyses conducted by Hack et al. in 'Fine-scale forest structure, not management regime, drives occupancy of a declining songbird, the Olive-sided Flycatcher, in the core of its range.'</p>
Personalized Large-scale Functional Networks in the Adolescent Brain Cognitive Development (ABCD) Children
<ul><li>Data for our paper "<strong>Personalized Large-scale Functional Networks in ABCD Children: Linking Functional Network Topography with Socioeconomic Status</strong>".</li><li>This dataset contains personalized functional networks for <strong>3,921</strong> participants (age 9- and 10-year-olds) who had more than 20 min of high-quality (mean motion < 0.2mm) resting-state fMRI data from the Adolescent Brain Cognitive Development (<strong>ABCD</strong>) Study.</li><li>Using regularized non-negative matrix factorization (<strong>NMF</strong>) and preprocessed resting-state fMRI data from the ABCD-BIDS Community Collection (<strong>https://github.com/ABCD-STUDY/nda-abcd-collection-3165</strong>, NDA Collection 3165), we parcellated the cortex (<strong>fsLR_32k space</strong>) into 17 functional networks for each ABCD participant.</li><li>We provided two kinds of atlas data: discrete network parcellation (<strong>IndivAtlasLabel</strong>) and probabilistic network parcellation (<strong>IndivAtlasLoading</strong>). For discrete network parcellation, each value in the dscalar indicates which network this vertex belongs to; for probabilistic network parcellation, each value indicates the probability that this vertex belongs to each network (<strong>17 in total</strong>). We also provided group atlas label and atlas loading for comparison.</li><li>For dscalars contain individual atlas loading, we separated participants into 10 parts, each has nearly 400 individuals for easily uploading and downloading.</li><li>Each value corresponds with the following key for discrete network parcellation: 1=FP1, 2=AU, 3=VS1, 4=DM1, 5=DA, 6=DM2, 7=DA2, 8=DM3, 9=VS2, 10=SM1, 11=TMP, 12=LB 13=VA1, 14=FP2, 15=SM2, 16=SM3, 17=DA3 (VS: visual; AU: auditory; SM: somatomotor; VA: ventral attention; DA: dorsal attention; FP: fronto-parietal; DM: default mode; TM: temporo-parietal; LB: limbic).</li><li>For each participant, we provide his or her subject-key in the ABCD Study. Other related information can be found at <strong>https://wiki.abcdstudy.org</strong>.</li><li>Relevant analysis scripts can be found in <strong>https://github.com/CuiLabCIBR/SingleFuncParcel_ABCD</strong>.</li></ul>
Supplementary material to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" : Pleiades snow depth maps analysis
<p>This Folder contains :</p><p> - necessary codes to reprduce Fig. 5, 12 and 13 of the third version of the submitted manuscript SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme"</p><p> - necessary data to run these codes, including extracts of simulation outputs</p><p> - A readme.txt which explains how to run everything</p><p> </p>
Data and code for Synoptic mechanisms of large-scale extreme precipitation events over southeastern China (Version 1.1.0)
<p>All data generated for the article <em>Synoptic mechanisms of large-scale extreme precipitation events over South China</em> and the code used to reproduce the article analysis and figures.</p>
Structure and scaling of the middle ear in domestic dog breeds
<p>This data-set of 8-bit JPEG files represents CT scans of the ear regions of 17 dog breeds, plus a mongrel and a wolf. Each folder includes a CT parameter settings text file (.xtekct) which contains the voxel size.</p> <p>17 of the 19 JPEG stacks were based on scans of prepared skull specimens from the Veterinary Anatomy Museum and Anatomic Pathology Laboratory at the Queen’s Veterinary School Hospital, University of Cambridge. The mongrel was a preserved teaching specimen, while the Chihuahua was a euthanized animal donated to the Queen's Veterinary School, University of Cambridge, for the purposes of teaching and research.</p> <p>These CT scans were made by Matthew J. Mason as part of a project entitled "Structure and scaling of the middle ear in domestic dog breeds". An original journal article based on reconstructions made from the scan data has been published in Journal of Anatomy (volume 245, issue 2, 2024), co-authored by Matthew J. Mason and Madaleine A. Lewis. The article may be found here: <a href="https://doi.org/10.1111/joa.14049">https://doi.org/10.1111/joa.14049</a>.</p>
55 Block--63k or 50k scale Maps of South Asia--additional 1--20240105
<p>85 new map files to add to the set of 63k/50k Maps of South Asia, Block 55. An updated Index Map for Block 55 is included in this set of maps.</p>
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
<p>Data and checkpoints for 'Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models'</p>
Dataset of current sheets for "Kinetic-scale current sheets in the solar wind at 5 AU"
<p>This is a dataset of current sheets observed aboard Ulysses spacecraft at 5 AU, close to the ecliptic plane and around solar minimum.</p> <p>The current sheets were collecteed in the time interval of 641 days, from DOY 180 / Year 1997 to DOY 90 / Year 1999. DOY = Day Of Year.</p> <p>There are several columns in the txt file:<br>1) Year: 97, 98 and 99 correspond to 1997, 1998 and 1999<br>2) DOY=Day Of Year<br>3) Type: 0 means that a current sheet is non-bifurcated, while 1 means it is bifurcated. There are 15,309 non-bifurcated current sheets and 1,594 bifurcated current sheets in this dataset.</p> <p>4&5) T_left and T_righ are moments of time corresponding to left and right boundaries of a current sheet, the time is in seconds from the beginning of a DOY. </p>
cigFacies: a massive-scale benchmark dataset of seismic facies and its application
<p>cigFacies is a dataset create by the <a href="https://cig.ustc.edu.cn/main.htm">Computational Interpretation Group (CIG)</a> for the AI-based automatic seismic facies classification in 3-D seismic data, <a href="https://cig.ustc.edu.cn/hui/list.htm">Hui Gao</a>, <a href="https://cig.ustc.edu.cn/xinming/list.htm">Xinming Wu</a>, <a href="http://cig.ustc.edu.cn/xiaoming/list.htm">Xiaoming Sun</a> and Mingcai Hou are the main contributors to the dataset.</p> <p>This is the benchmark skeletonization datasets of seismic facies, guided by the knowledge graph of seismic facies and constructed from three different stategies (field seismic data, synthetic data and GAN-based generation).</p> <p>Below are some brief desription of the datasets:</p> <p>1) The "The benchmark skeletonization datasets" file consists of 5 classes of seismic facies.</p> <p>2) The "parallel_class", "clinoform_class", "fill_class", "hummocky_class" and "chaotic_class" consist of 2000, 1500, 1500, 1500, 1500 stratigraphic skeletonization data constructed from field seismic data, synthetic data and GAN-based generation, respectively.</p> <div> <div> <div> <p>The source codes for constructing the benchmark dataset of seismic facies and deep learning for seismic facies classification have been uploaded to Github and are freely available at <a href="https://github.com/huigcig/cigFaciesNet">cigFaciesNet</a>.</p> </div> </div> </div> <p> </p> <p> </p>
Data for research article "European-wide variations in ecosystem-scale strategies to increasing drought"
<div> <p>This repository contains the datasets used in the research article "<strong>European-wide variations in ecosystem-scale strategies to increasing drought</strong>".</p> <p> </p> </div>
Pore-Scale Investigation of MICP in Simplified Pores through Microfluidic Tests
<p>This file contains all raw and binarized images and movies used to analyze the pore filling ratios, count of crystals, size of crystals, and flow fields in pore networks. The processed data used for producing figures also included in the Data Excel. The MATLAB script used for subimage segmentation was also included. The COMSOL models used for calculating flow field.</p>
Italian Children's Hope Scale DATASET
<p>Italian Children’s Hope Scale DATASET for validation and gender differences</p> <p>FILE: <strong>DATASET_CHS</strong> contains data about age, gender, Socioeconomic status (SES), pre CHS score (used for Confirmatory and Exploratory Factor Analysis), post CHS score (used for test-retest reliability).</p> <p> </p>
Laboratory water quality monitoring data from full scale CS#3 DWDN for the DBP prediction model
<p>Lab measurements of water quality based on manual sampling including ordinary monitoring and special monitoring performed in SafeCREW project.</p> <p>Laboratory LIMS database.</p> <p>Provide water quality measurements based on the planned monitoring schedule. Schedule tailored to SafeCREW project needs plus usual legal water sampling.</p>
Identification of beneficial and detrimental bacteria that impact sorghum responses to drought using multi-scale and multi-system microbiome comparisons
<p><strong>Background: </strong>Drought is a major abiotic stress that limits agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere and may lead to enrichment of specific groups of microbes, such as <em>Actinobacteria</em>. How these changes ultimately affect plant health is not well understood. In parallel, model systems have been used to tease apart the specific interactions between plants and single, or small groups of microbes. However, translating this work into crop species and achieving increased crop yields within noisy field settings remains a challenge. Thus, the next scientific leap forward in microbiome research must cross the great lab-to-field divide. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key beneficial and detrimental, root associated microbes that robustly affect drought stressed plant phenotypes.</p> <p> </p> <p><strong>Results: </strong>Fifty-three bacterial strains, originally characterized for association with <em>Arabidopsis</em>, were applied to sorghum seeds and their effect on root growth was monitored for seven days. Two <em>Arthrobacter </em>strains, members of the <em>Actinobacteria </em>phylum, caused root growth inhibition (RGI) in <em>Arabidopsis</em> and sorghum. In the context of synthetic communities, strains of <em>Variovorax</em> were able to protect both <em>Arabidopsis </em>and sorghum from the RGI caused by <em>Arthrobacter</em>. As a transitional system, we tested the synthetic communities through a 24-day high-throughput sorghum phenotyping assay and found that during drought stress, plants colonized by <em>Arthrobacter</em> were significantly smaller and had reduced leaf water content as compared to control plants. However, plants colonized by both <em>Arthrobacter</em> and <em>Variovorax</em> performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across well-watered and drought conditions. Drought responsive microbes were identified, including an enrichment in <em>Actinobacteria</em>, consistent with previous findings. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a newly developed method and were then able to observe that the abundance of <em>Arthrobacter</em> strains negatively correlated with plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of high confidence bacterial taxa that positively associated with plant growth under drought stress.</p> <p> </p> <p><strong>Conclusions: </strong>A three-tiered experimental system connected reductionist and ecological approaches and identified beneficial and deleterious bacterial strains for sorghum under drought stress.</p>
Fig. 2 in First Japanese Record of the Black Margined-scale Sergeant Abudefduf nigrimargo (Perciformes: Pomacentridae) from the Tokara Islands
Fig. 2. Anteroventral region of head of Abudefduf nigrimargo (KAUM–I. 115057, 137.1 mm SL).
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.