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12,662 results for “linking”
OA-Concepts and Wikipedia-Links for "The different AI of Science and Wikipedia"
<p>The files contain the data for the VosViewer analyses in "The Different Artificial Intelligences of Science and Wikipedia" (Korte et al. 2024).</p> <p>OpenAlex:</p> <p>As described in the paper, all works from OpenAlex from 2001 and 2022 with the concept "Artificial Intelligence" and a concept score > 0.3 were downloaded. In August 23 using the OpenAlex API. The files contain for each work all concepts with a concept score > 0.3 in one line each separeted by dots. This allows co-occurrence analyses of concepts in VosViewer. For the analyses in the paper whitespaces and "(" in the concepts were removed.</p> <p>First line for 2001: <br>Random forest. Mathematics. AdaBoost. Statistics. Tree (set theory). Generalization. Support vector machine. Generalization error. Measure (data warehouse). Artificial intelligence. Pattern recognition (psychology). </p> <p>Wikipedia:</p> <p>As described in the paper, all Wikipedia pages of the category "Artificial Intelligence" and of all direct sibling categories were downloaded. In August 23 with the Wikipedia Periodic Revisions tool of El Baff and Hecking (https://github.com/DLR-SC/wikipedia-periodic-revisions): . The files contain for each page all hyperlinks to other Wikipedia pages for the dates of 12.31.2005 and 12.31.2021 in one line each separeted by dots. This allows co-occurrence analyses of links in Wikipedia.</p> <p>First line of 2006: <br>vehicleregistrationplate. corporation. googlesearch. googleplatform. googol. google(disambiguation). menlopark,california. erice.schmidt. sergeybrin. lawrencee.page. georgereyes. internet. [...]</p>
Data Analysis for Context- and sex-dependent links between sire sexual success and offspring pathogen resistance
<p>Data Analysis for "Context- and sex-dependent links between sire sexual success and offspring pathogen resistance"</p> <p>By Aijuan Liao and Tadeusz J. Kawecki</p>
Supproting Materials for "Cross-Linked Selenoctanoic Acid Nanoplatform Enables Bidirectional Regulation of Intra- and Extracellular ROS: A New Avenue for Enhanced Cancer Immunotherapy" - section A
<p><strong>Table of Content</strong></p> <h1>1. Synthesis and characterization</h1> <h2> 1.1. SeLA</h2> <h3> 1.1.0. Lab book pages</h3> <h3> 1.1.1. NMR</h3> <h3> 1.1.2. HR-MS</h3> <h3> 1.1.3. UV</h3> <h3> 1.1.4. IR</h3> <h2> 1.2. cSeLAN</h2> <h3> 1.2.0. Lab book pages</h3> <h3> 1.2.1. NMR</h3> <h3> 1.2.2. UV</h3> <h3> 1.2.3. IR</h3> <h3> 1.2.4. GPC</h3> <h3> 1.2.5. MALDI-TOF-MS</h3> <h3> 1.2.6. DLS</h3> <h3> 1.2.7. Critical melle cncentration</h3> <h3> 1.2.8. ICP-MS</h3> <h3> 1.2.9. TEM</h3> <h2> 1.3. cLAN</h2> <h3> 1.3.0. Lab book pages</h3> <h3> 1.3.1. NMR</h3> <h3> 1.3.2. UV</h3> <h3> 1.3.3. DLS</h3> <h3> 1.3.4. GPC</h3> <h1>2. <em>In vitro</em> intra- and extracellular ROS regulation</h1> <h2> 2.0. Lab book pages</h2> <h2> 2.1. Raman scattering spectra</h2> <h2> 2.2. HPLC</h2> <h3> 2.2.1. Standard peaking</h3> <h3> 2.2.2. HPLC analysis</h3> <h2> 2.3. ICP-MS</h2> <h2> 2.4. MTT</h2> <h2> 2.5. Intracellular ROS generation</h2> <h3> 2.5.1. Fluorescence images</h3> <h3> 2.5.2. Flow fluorescence quantification</h3> <h2> 2.6. Intracellular pro-oxidation mechanism</h2> <h3> 2.6.1. Quantification of intracellular ATP</h3> <h3> 2.6.2. Quantification of intracellular NADH</h3> <h3> 2.6.3. Quantification of intracellular <strong>·</strong>OH</h3> <h3> 2.6.4. Quantification of intracellular ROS</h3> <h2> 2.7. Quantification of extracellular ROS</h2> <h1>3. <em>In vitro</em> ICD-inducing ability</h1> <h2> 3.0. Lab book pages</h2> <h2> 3.1. ATP release</h2> <h2> 3.2. HMGB1</h2> <h2> 3.3. CRT</h2> <h1>4. T cell proliferation and activation</h1> <h2> 4.0. Lab book pages</h2> <h2> 4.1. Flow cytometry analysis of the T cell proliferation</h2> <h2> 4.2. Quantification of IFN-γ secretions</h2> <h1>5. Biosafety evaluation of cSeLAN</h1> <h2> 5.0. Lab book pages</h2> <h2> 5.1. Hemolytic and hemagglutination assay</h2> <h3> 5.1.1. Hemolytic assay</h3> <h3> 5.1.2. Hemagglutination assay</h3> <h2> 5.2. Acute toxicity test</h2> <h3> 5.2.1. The amounts of dead mice</h3> <h3> 5.2.2. Body weight of mice</h3> <h3> 5.2.3. Hematological assay</h3> <h3> 5.2.4. Blood biochemistry</h3> <h3> 5.2.5. H&E staining of main organs</h3> <h1>6. Pharmacokinetic evaluation of cSeLAN</h1> <h2> 6.0. Lab book pages</h2> <h2> 6.1 Pharmacokinetic evaluation of cSeLAN</h2> <h1>7. <em>In vivo</em> anti-tumor immune response</h1> <h2> 7.0. Lab book pages</h2> <h2> 7.1. Chemiluminescence images</h2> <h3> 7.1.1. Chemiluminescence images of isoluminol</h3> <h3> 7.1.2. Chemiluminescence images of luminol</h3> <h3> 7.1.3. Related quantifications upon various treatments</h3> <h2> 7.2. Immunofluorescence images</h2> <h2> 7.3. T cell proliferation</h2> <h2> 7.4. DC proliferation</h2> <h1>8. <em>In vivo</em> anti-tumor efficacy</h1> <h2> 8.0. Lab book pages</h2> <h2> 8.1. Tumor growth</h2> <h3> 8.1.1. Tumor volume</h3> <h3> 8.1.2. Tumor weight</h3> <h3> 8.1.3. Tumor images</h3> <h2> 8.2. Body weight</h2> <h2> 8.3. Lung tissues with metastatic nodules</h2> <h3> 8.3.1. Lung tissues images</h3> <h3> 8.3.2. Number of pulmonary metastatic nodules</h3> <h3> 8.3.3. H&E</h3> <h2> 8.4. H&E of tumor and main organs</h2> <h2> 8.5. Cytokine secretions</h2> <h2> 8.6. Kaplan−Meier survival curves</h2> <h1>9. <em>In vitro</em> NK cytotoxicity and activity</h1> <h2> 9.0. Lab book pages</h2> <h2> 9.1. NK cytotoxicity</h2> <h2> 9.2. NK activity</h2>
Vortex input files -- Linking habitat and population viability analysis models of a metapopulation of Florida scrub-jays
<p>Vortex input files for manuscript "<span>Linking </span><span><span>habitat and population viability analysis models to account for <span>vegetation dynamics, habitat fragmentation, and social behavior of a metapopulation of Florida scrub-jays</span></span></span>" by R. C. Lacy, D. B. Breininger, et al. </p>
Linked multipoint cotranscriptional RNA chemical probing data for the E. coli SRP RNA, C. beijerinckii pfl ZTP riboswitch, and B. cereus crcB fluoride riboswitch
<p>Cotranscriptional RNA chemical probing data for the <em>E. coli</em> signal recognition particle (SRP) RNA, <em>Clostridium beijerinckii pfl</em> ZTP riboswitch, and <em>Bacillus cereus crcB </em>fluoride riboswitch. Data were generated using the linked multipoint Transcription Elongation Complex RNA structure probing (TECprobe-LM) and variable length Transcription Elongation Complex RNA structure probing (TECprobe-VL) procedures.</p>
Model results and data associated with "Antecedent effect models as an exploratory tool to link climate drivers to herbaceous perennial population dynamics data"
<p>Model results and data (including Bayesian posteriors) associated with "Antecedent effect models as an exploratory tool to link climate drivers to 3 herbaceous perennial population dynamics data".</p> <p>This is a repository created to store the posteriors of the models fit within this project. Because these occupy so much space, it makes sense to store them in a separate repository.</p> <p>There are two directories:</p> <ul> <li><em>model_results/</em> contains all of the posteriors (files with character pattern <em>main_posterior_#.csv</em>). The three types of files contained in this directory are described in <em>metadata_model_results.xlsx</em>. The number # corresponds to column "index" in file <em>raw_data/design_insample.csv</em>.</li> <li><em>raw_data/</em> is mostly not essential: it contains the raw data to fit models, and it replicates folder <em>data/</em> in repository https://dx.doi.org/10.5281/zenodo.13909628.</li> </ul>
PollyXT and COSMO-MUSCAT data for "Investigating the link between mineral dust hematite content and intensive optical properties by means of lidar measurements and aerosol modelling"
<p>The dataset contains 4 different files: </p> <ul> <li>For the single case example on the 24 August 2021 between 2:45 to 5:27 UTC in Mndelo, Cabo Verde: <ul> <li>-Mindelo-PollyXT_CPV-20210824_0245-0527-77smooth-info.txt : contains the information of the vertically retrieved optical properties from PollyXT lidar measurements. The information contained refers to the chosen retrieval times, vertical smoothing, and reference heights</li> <li>-Mindelo-PollyXT_CPV-20210824_0245-0527-77smooth.txt : vertically retrieved optical properties per height.</li> <li>-Mindelo-model_24aug.csv : COSMO-MUSCAT vertical results of dust and mineral mass concentrations per height. The columns that end with "int mass" correspond to the integrated mass per dust layer and columns that end with numbers correspond to different size bins. For reference to the size bins see Table 1 in Gómez Maqueo Anaya et al., 2024</li> </ul> </li> <li>Mutiple case studies: <ul> <li>-Mindelo-lidar-uvvisdiff_model.csv : Twenty-two case studies with the following order: first, the mean values of the lidar-derived optical properties, along with their corresponding retrieval times and heights that define the dust plume. This is followed by the POLIPHON (Mamouri and Ansmann, 2014, 2017) data. The mean values from dust and mineral mass concentrations from the model start with the model heights where the dust plumes were calculated. At the end of the dataset rows, the times from which the modeled mean values are calculated can be found.</li> </ul> </li> </ul>
A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu
<p>Lake Taihu has a history of recurrent harmful cyanobacterial blooms under the pressures of climate change and human activities. Despite efforts to limit nutrient loading, there is a need to better understand the water environment of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. The spatial and temporal characteristics of the water quality, bio-optical parameters, climate, and anthropogenic data of Lake Taihu (THQBCA) could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. The THQBCA dataset is expected to advance research on forecasting and early warning of cyanobacterial blooms, and to support science-based management decisions for sustainable ecological development.</p>
Extreme heat and heatwaves are linked to the risk of unintentional child injuries in Guangzhou city
<p>This repository holds source data for the manuscript figures, which are available as Excel files.</p>
Linking 23 physical activity intensity levels to health-related quality of life in 10-year-old children
<p>This anonymized data is a subset of the ASK study: <br>Resaland, G.K., Moe, V.F., Aadland, E., et al. Active Smarter Kids (ASK): Rationale and design of a cluster-randomized controlled trial investigating the effects of daily physical activity on children’s academic performance and risk factors for non-communicable diseases.BMC Public Health 15, 709 (2015). https://doi.org/10.1186/s12889-015-2049-y</p> <p>The ASK study was approved by the Regional Committees for Medical and Health Research Ethics in Norway (reference number: 2013/1893) and registered at www.Clinicaltrials.gov with ID NCT02132494. </p> <p>The selected cross-sectional baseline data in this file are used in the following unpublished paper: <br>Stai, M., Aadland, E., Andersen, J.R. (Year). *Linking 23 physical activity intensity levels to health-related quality of life in 10-year-old children.</p> <p>The data is stored in Excel. <br><br>Explanations: <br>- #NULL! = missing data<br>- Sex (0 = Girl, 1= Boy) <br>- Overweight or obesity (0 = No, 1 = Yes)<br>- All other data has labeling that is self-explanatory. </p> <p>Corresponding Author: <br>John Roger Andersen, johnra@hvl.no </p> <p> </p>
Supplementary material for the paper: Linking megaliths: A computational approach to the study of movement and mobility in the megalithic complex of Galicia (North-west of the Iberian Peninsula)
<p>Supplementary material for the paper: Carrero-Pazos, M., White, D., Linking megaliths: A computational approach to the study of movement and mobility in the megalithic complex of Galicia (North-west of the Iberian Peninsula). To be appeared in: G. M. Higginbottom, C. Scarre, A. C. González-García, F. Criado-Boado, <em>Megalithic Societies: Old Questions, New Narratives. </em>Oxford: BAR International Series</p>
Data from: Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions
1.Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. 2.Here we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype specific transmission pathways in a social carnivore. 3.We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIVPle) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIVPle molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father and/or mother offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype specific FIVPle co-occurrence networks and assessed what combination of social networks, spatial networks, or co-infection best structured the FIVPle network. 4.While social organization (i.e., pride) was an important component of FIVPle transmission pathways at all scales, we find that FIVPle subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIVPle transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype specific. 5.Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects.
Data from: Split between two worlds: automated sensing reveals links between above- and belowground social networks in a free-living mammal
Many animals socialize in two or more major ecological contexts. In nature, these contexts often involve one situation in which space is more constrained (e.g. shared refuges, sleeping cliffs, nests, dens or burrows) and another situation in which animal movements are relatively free (e.g. in open spaces lacking architectural constraints). Although it is widely recognized that an individual's characteristics may shape its social life, the extent to which architecture constrains social decisions within and between habitats remains poorly understood. Here we developed a novel, automated-monitoring system to study the effects of personality, life-history stage and sex on the social network structure of a facultatively social mammal, the California ground squirrel (Otospermophilus beecheyi) in two distinct contexts: aboveground where space is relatively open and belowground where it is relatively constrained by burrow architecture. Aboveground networks reflected affiliative social interactions whereas belowground networks reflected burrow associations. Network structure in one context (belowground), along with preferential juvenile–adult associations, predicted structure in a second context (aboveground). Network positions of individuals were generally consistent across years (within contexts) and between ecological contexts (within years), suggesting that individual personalities and behavioural syndromes, respectively, contribute to the social network structure of these free-living mammals. Direct ties (strength) tended to be stronger in belowground networks whereas more indirect paths (betweenness centrality) flowed through individuals in aboveground networks. Belowground, females fostered significantly more indirect paths than did males. Our findings have important potential implications for disease and information transmission, offering new insights into the multiple factors contributing to social structures across ecological contexts.
Data from: Linking beaver dam affected flow dynamics to upstream passage of Arctic grayling
Beaver reintroductions and beaver dam structures are an increasingly utilized ecological tool for rehabilitating degraded streams, yet beaver dams can potentially impact upstream fish migrations. We collected two years of data on Arctic grayling movement through a series of beaver dams in a low gradient mountain stream, utilizing radio-telemetry techniques, to determine how hydrology, dam characteristics, and fish attributes impeded passage and movement rates of spawning grayling. We compared fish movement between a "normal" flow year and a "low" flow year, determined grayling passage probabilities over dams in relation to a suite of factors, and predicted daily movement rates in relation to the number of dams each fish passed and distance between dams during upstream migration to spawning areas. We found that the average passage probability over unbreached beaver dams was 88%, though we found that it fell below 50% at specific dams. Upstream passage of grayling was affected by three main characteristics: 1) temperature 2) breach status and 3) hydrologic linkages that connect sections of stream above and below the dam. Other variables influence passage, but to a lesser degree. Cumulative passage varied with distance upstream and total number of dams passed in low versus normal flow years, while movement rates upstream slowed as fish swam closer to dams. Our findings demonstrate that upstream passage of fish over beaver dams is strongly correlated with hydrologic conditions with moderate controls by dam- and fish-level characteristics. Our results provide a framework that can be applied to reduce barrier effects when and where beaver dams pose a significant threat to the upstream migration of fish populations while maintaining the diverse ecological benefits of beaver activity when dams are not a threat to fish passage.
Linking community assembly and structure across scales in a wild mouse parasite community
<p>Understanding what processes drive community structure is fundamental to ecology. Many wild animals are simultaneously infected by multiple parasite species, so host parasite communities can be valuable tools for investigating connections between community structures at multiple scales, as each host can be considered a replicate parasite community. Like free-living communities, within-host parasite communities are hierarchical; ecological interactions between hosts and parasites can occur at multiple scales (e.g. host community, host population, parasite community within the host), therefore both extrinsic and intrinsic processes can determine parasite community structure. We combine analyses of community structure and assembly at both the host population and individual scales using extensive datasets on wild wood mice (<i>Apodemus sylvaticus</i>) and their parasite community. An analysis of parasite community nestedness at the host population scale provided predictions about the order of infection at the individual scale, which were then tested using parasite community assembly data from individuals hosts from the same populations. Nestedness analyses revealed parasite communities were significantly more structured than random. However, observed nestedness did not differ from null models in which parasite species abundance was kept constant. We did not find consistency between observed community structure at the host population scale and within-host order of infection. Multistate-Markov models of parasite community assembly showed that a host's likelihood of infection with one parasite was not impacted by previous parasite infection, suggesting there is not a deterministic order of infection among the species we investigated in wild wood mice. Our results demonstrate that patterns at one scale (i.e. host population) do not reliably predict processes at another scale (i.e. individual host), and that neutral or stochastic processes may be driving the patterns of nestedness observed in these communities. We suggest that experimental approaches that manipulate parasite communities are needed to better link processes at multiple ecological scales.</p>
Data for: Linking behavioural type with cannibalism in Eurasian perch
<p>Behavioural data and prey selection data</p> <p>V3 includes corrected Fulton's K and date of behavioural trials </p>
Nanotate - Annotations linked to ontology terms
<p>The file include the total annotations and the quantity of annotations linked to ontology terms related to 'bio-sample', 'equipment' and 'reagents'.</p>
Novel insights into habitat suitability for Amazonian freshwater mussels linked with hydraulic and landscape drivers
<p><span>Novel insights into habitat suitability for two Unionida freshwater mussels, <i>Castalia ambigua</i> Lamarck, 1819 (Hyriidae) and <i>Anodontites elongatus </i><span>(Swainson, 1823) (Mycetopodidae)</span><i>,</i> is presented on the basis of hydraulic variables linked with the riverbed in six 500 m reaches in an eastern Amazonian river basin. Within the reaches, there was strong habitat heterogeneity in hydrodynamics and substrate composition. In addition, we investigated stressors based on landscape modification that are associated with declines in mussel density. We measured hydraulic variables for each 500 m reach, and landscape stressors at two spatial scales (subcatchment and riparian buffer forest). W<span>e used </span><span>the</span> <span>R</span><span>andom </span><span>F</span><span>orest algorithm,</span> a tree-based model, to predict the hydraulic variables linked with habitat suitability for mussels, and to predict which landscape stressors were most associated with mussel density declines. Both mussel species were linked with low substrate heterogeneity and greater riverbed stability (low Froude and Reynolds numbers), especially at high flow (low stream power). Different sediment grain size preferences were observed between mussel species: <i>Castalia ambigua</i> was associated with medium sand, and <i>Anodontites elongatus</i> with medium and fine sand. Declines in mussel density were associated with modifications linked to urbanization at small scales (riparian buffer forest), especially with percent of and distance from rural settlements, distance to the nearest street, and road density. In summary, the high<span> variance </span><span>explained </span><span>in both hydraulic and landscape models</span><span> indicated </span><span>high predictive power, </span><span>suggesting that our findings</span> <span>may be extrapolated </span><span>and used as a baseline to test </span><span><span>hypotheses of habitat suitability </span></span><span><span>in other Amazonian rivers</span></span><span><span> for </span></span><i><span>Castalia ambigua</span></i><span><span> and </span></span><i><span>Anodontites elongatus</span></i><span><span>, and also </span></span><span><span>for</span></span><span><span> other </span></span><span><span>freshwater </span></span><span><span>mussel species</span></span><span>. </span>Our results highlight the urgent need for aquatic habitat conservation to maintain sheltered habitats during high flow as well as mitigate the effects of landscape modifications at the riparian buffer scale, both of which are important for maintaining dense mussel populations and habitat quality.</span></p>
Using stable isotopes to link biogeochemical processes to biodiversity of conservation concern
<b>Description: </b><p>This data was collected at the SAFE experimental area, and two primary forest sites within the greater SAFE landscape: the Danum Valley conservation area (DVCA; N4.962°, E117.689°) and Maliau Basin conservation area (MBCA; N4.853°, E116.844°), located 36 Km north and 69 Km west of the SAFE project, respectively. DVCA is a 438 Km2 lowland dipterocarp forest reserve close to the Segama River at 210 m elevation. In comparison, MBCA is a 588 Km2 lowland and hill dipterocarp forest reserve, close to the Maliau River and reaching 1, 675 m at the highest point. Both are afforded the highest status as Class I Protected Forest Reserves by the Sabah state government, owing to the value of the areas for conservation and education. <br>In 2015 we sampled all six SAFE sites. In 2016 we did not resample one of the repeatedly logged-forest sites ('F') for logistical reasons, but extended sampling to include primary forest sites Maliau and Danum. In each year, we performed ten nights of trapping using six four-bank harp traps set along existing trails at each site (total: 60 harp trap nights per site). We checked traps late at night and early the next morning (20.30 and 08.30), and moved them each day by at least 20m. For logistical reasons, site F was only sampled using 30 harp trap nights in 2015, and site LFE was sampled three times in 2015 due to low capture rates.<br>Upon capture, we identified each bat to species and, for adult individuals, a wing membrane biopsy was taken using a 3mm punch (Schuco, Walford, UK) for stable isotope analyses and placed in separate tubes for same day processing. Heavily pregnant, highly stressed or recently recaptured bats were not sampled.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/11"><b>Using stable isotopes to link biogeochemical processes to biodiversity of conservation concern</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Research grant, NE/K016148/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 (374) )</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.4 (41))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM.1000-2/2 JLD.5 (153))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=5113429">here</a></p><p><b>Files: </b>This consists of 1 file: 1_Kemp_bat_iso_data.xlsx</p><p><b>1_Kemp_bat_iso_data.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>Carbon and nitrogen natural abundance stable isotope data of insects</b> (described in worksheet Insect_isotope)</p><p>Description: A single year dataset of carbon and nitrogen stable isotope values on volant insects across a gradient of logging disturbance in Sabah, Malaysian Borneo. The data was collected between May – July 2017. </p><p>Number of fields: 15</p><p>Number of data rows: 173</p><p>Fields: </p><ul><li><b>Order</b>: Taxonomic order (Field type: id)</li><li><b>Family</b>: Taxonomic family (Field type: id)</li><li><b>Taxa</b>: Highest taxonomic classification (Field type: taxa)</li><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Site</b>: Sample site (Field type: id)</li><li><b>Plot</b>: Vegetation plot (2 sampled within each site) (Field type: id)</li><li><b>Bottle</b>: Either "top" or "bottom" bottle of the Malaise trap (Field type: categorical)</li><li><b>Feeding_Guild</b>: Feeding Guild (PHY = phytophagous; DET = detritivorous, and PRED = predatory) (Field type: categorical trait)</li><li><b>Weight</b>: Sample weight (Field type: numeric trait)</li><li><b>Beam.Area.N</b>: Measure of the nitrogen peak (uA), i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight (Field type: numeric trait)</li><li><b>ugN</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric trait)</li><li><b>X15N</b>: The delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric trait)</li><li><b>Beam.Area.C</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight (Field type: numeric trait)</li><li><b>ugC</b>: Measure of the elemental carbon content of the sample (Field type: numeric trait)</li><li><b>X13C</b>: The delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric trait)</li></ul></li><li><p><b>Georeferenced bat capture data from three field seasons, 2015-2017 in Sabah, Malaysian Borneo</b> (described in worksheet Bat_data)</p><p>Description: This dataset provides capture data from the SAFE experimental area as well as Danum Valley and Maliau Basin. The dataset covers three field campaigns spanning from 2015 – 2017. The dataset includes species annotation, capture date and time; capture location (latitude and longitude); sex, age; forearm and weight measurement, and reproductive condition. There is also an identifier to match captured individuals with isotope values.</p><p>Number of fields: 19</p><p>Number of data rows: 2490</p><p>Fields: </p><ul><li><b>Bat_no</b>: Unique identifier for each individual bat captured (Field type: id)</li><li><b>Day</b>: The day that individual was captured (Field type: id)</li><li><b>Month</b>: The month that individual was captured (Field type: id)</li><li><b>Year</b>: The year that individual was captured (Field type: id)</li><li><b>Date</b>: Date individual was captured (Field type: date)</li><li><b>TrapName</b>: Unique identifier for each trap which was erected (trap position within sites were not consistent between years, largely due to changes in the trails and vegetation structure) (Field type: location)</li><li><b>Lat</b>: Latitude of the trap in which the bat was captured (Field type: latitude)</li><li><b>Long</b>: Longitude of the trap in which the bat was captured (Field type: longitude)</li><li><b>Site</b>: The site at which the capture was made (Field type: id)</li><li><b>Family</b>: Family classification (Field type: categorical trait)</li><li><b>Species</b>: Species classification (Field type: taxa)</li><li><b>Sex</b>: The sex of each capture (M= Male; F = Female) (Field type: categorical trait)</li><li><b>Age</b>: The age of each capture (A = Adult; J = Juvenile ()) (Field type: categorical trait)</li><li><b>Forearm</b>: Forearm measurement (Field type: numeric trait)</li><li><b>Weight</b>: Weight of bat (Field type: numeric trait)</li><li><b>Reproductive_condition</b>: Reproductive condition of the individual (M= Male; NR = Non reproductive, i.e. not yet born young; L = Lactating, i.e. milk visible below the teet; P = Pregnant; PL = Post-lactating, i.e. not currently pregnant or lactating, but evidence of having born young from distended nipples. (Field type: categorical trait)</li><li><b>Time</b>: Whether the individual was captured PM (traps checked for fly-ins between dusk and ~ 19:30) or AM (traps checked for fly-ins between time of evening check and ~ 08:30) (Field type: categorical trait)</li><li><b>Guild</b>: Echolocation guilds with calls classified as HDC = High-duty-cycle or LDC = Low-duty-cycle (Field type: categorical trait)</li><li><b>Biopsy</b>: Unique identifier to associate the captured individual with the isotope data derived from the wing membrane biopsy. If no biopsy was taken there is a reason given: "RECAPTURE" – recapture as denoted by a fresh biopsy hole; "ESCAPED" – escaped the trap before handling; "BLEEDING" – with any sign of bleeding we avoided handling; "STRESSED" – due to ants in the trap, larger bats in the trap etc.; "NOT HEALED" – biopsy wound not healed from the previous visits ~4 weeks prior; "DEAD" – dead from stress; ants, or extreme weather; "PREGNANT" – heavily pregnant, therefore we avoided handling; "WITH YOUNG" – adult female with young attached; "NO BIOPSY PEN" – no sterile biopsy pens available in the field; "LOST" – biopsy lost after having been taken ; "RELEASED" – due to some kind of stress; "NOT TAKEN" - could be any of the above or another reason. (Field type: id)</li></ul></li><li><p><b>Carbon and nitrogen natural abundance stable isotope data of bat wing tissue, sampled across three field seasons, 2015-2017 in Sabah, Malaysian Borneo.</b> (described in worksheet Bat_isotope)</p><p>Description: This dataset provides carbon and nitrogen stable isotope values of bat wing tissue (3mm punch) from individuals sampled across a gradient of logging disturbance in Sabah, Malaysian Borneo. The data was collected over three discrete field seasons, February – May 2015, March - July 2016 and May – July 2017</p><p>Number of fields: 10</p><p>Number of data rows: 3145</p><p>Fields: </p><ul><li><b>N</b>: Number to show the order in which the samples were run (currently the sheet is ordered in distinct runs (32 in total across the 3 years) (Field type: id)</li><li><b>Name</b>: Unique identifier to associate the isotope data with the captured individuals (matched to "Biopsy" column in "BatData.csv"). (Field type: id)</li><li><b>Weight</b>: Sample weight (Field type: numeric)</li><li><b>Beam.Area</b>: Measure of the nitrogen peak i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight. (Field type: numeric)</li><li><b>N_weight</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric)</li><li><b>X15N</b>: The delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric)</li><li><b>Beam.Area.1</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight (Field type: numeric)</li><li><b>C_weight</b>: Measure of the elemental carbon content of the sample (Field type: numeric)</li><li><b>X13C</b>: The delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric)</li><li><b>Year</b>: Year of sampling (Field type: id)</li></ul></li><li><p><b>Carbon and nitrogen natural abundance stable isotope data of basal resources (living leaves, leaf litter, soil, algae and dead wood), sampled across three field seasons, 2015-2017 in Sabah, Malaysian Borneo.</b> (described in worksheet Basal_resource_data)</p><p>Description: This dataset provides carbon and nitrogen stable isotope values of key basal resources representing the primary and detrital resource bases. The data was collected over three discrete field seasons, February – May 2015, March - July 2016 and May – July 2017.</p><p>Number of fields: 14</p><p>Number of data rows: 647</p><p>Fields: </p><ul><li><b>Source</b>: The type of biological material (Field type: id)</li><li><b>Name</b>: Identifier for each samples, of the format. PlotID_ReplicateNo (Field type: id)</li><li><b>Site</b>: Sample site (Field type: id)</li><li><b>Plot</b>: Vegetation plot (2 sampled within each site) (Field type: id)</li><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Round</b>: In some years some sites were visited twice (at least 1 month between visits) (Field type: replicate)</li><li><b>Weight</b>: Sample weight (Field type: numeric)</li><li><b>Beam.Area.N</b>: Measure of the nitrogen peak i.e. calculated as the area under the nitrogen curve by Calisto software. This value is directly related to N_weight. (Field type: numeric)</li><li><b>ugN</b>: Measure of the elemental nitrogen content of the sample (Field type: numeric)</li><li><b>X15N</b>: The delta value of the sample, which describes the ration of 15N: 14N isotopes (Field type: numeric)</li><li><b>Beam.Area.C</b>: Measure of the carbon peak i.e. calculated as the area under the carbon curve by Calisto software. This value is directly related to C_weight. (Field type: numeric)</li><li><b>ugC</b>: Measure of the elemental carbon content of the sample (Field type: numeric)</li><li><b>X13C</b>: The delta value of the sample, which describes the ration of 13C: 12C isotopes (Field type: numeric)</li><li><b>Year</b>: Year in which the sample was collected (Field type: id)</li></ul></li></ol><p><b>Date range: </b>2015-02-16 to 2017-07-21</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Chiroptera <br> -  -  -  -  -  Hipposideridae <br> -  -  -  -  -  -  <i>Hipposideros</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ater</i> <br> -  -  -  -  -  -  -  <i>Hipposideros bicolor</i> <br> -  -  -  -  -  -  -  <i>Hipposideros cervinus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros diadema</i> <br> -  -  -  -  -  -  -  <i>Hipposideros dyacorum</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ridleyi</i> <br> -  -  -  -  -  Nycteridae <br> -  -  -  -  -  -  <i>Nycteris</i> <br> -  -  -  -  -  -  -  <i>Nycteris tragata</i> <br> -  -  -  -  -  Emballonuridae <br> -  -  -  -  -  -  <i>Emballonura</i> <br> -  -  -  -  -  -  -  <i>Emballonura alecto</i> <br> -  -  -  -  -  -  -  <i>Emballonura monticola</i> <br> -  -  -  -  -  Vespertilionidae <br> -  -  -  -  -  -  <i>Kerivoula</i> <br> -  -  -  -  -  -  -  <i>Kerivoula hardwickii</i> <br> -  -  -  -  -  -  -  <i>Kerivoula intermedia</i> <br> -  -  -  -  -  -  -  <i>Kerivoula lenis</i> <br> -  -  -  -  -  -  -  <i>Kerivoula minuta</i> <br> -  -  -  -  -  -  -  <i>Kerivoula papillosa</i> <br> -  -  -  -  -  -  -  <i>Kerivoula pellucida</i> <br> -  -  -  -  -  -  -  <i>Kerivoula whiteheadi</i> <br> -  -  -  -  -  -  <i>Murina</i> <br> -  -  -  -  -  -  -  <i>Murina aenea</i> <br> -  -  -  -  -  -  -  <i>Murina cyclotis</i> <br> -  -  -  -  -  -  -  <i>Murina peninsularis</i> <br> -  -  -  -  -  -  -  <i>Murina rozendaali</i> <br> -  -  -  -  -  -  -  <i>Murina suilla</i> <br> -  -  -  -  -  -  <i>Myotis</i> <br> -  -  -  -  -  -  -  <i>Myotis muricola</i> <br> -  -  -  -  -  -  -  <i>Myotis ridleyi</i> <br> -  -  -  -  -  -  <i>Pipistrellus</i> <br> -  -  -  -  -  -  -  <i>Pipistrellus javanicus</i> <br> -  -  -  -  -  -  -  <i>Pipistrellus tenuis</i> <br> -  -  -  -  -  -  <i>Pipistrellus</i> <br> -  -  -  -  -  -  -  <i>Pipistrellus javanicus</i> <br> -  -  -  -  -  -  -  <i>Pipistrellus tenuis</i> <br> -  -  -  -  -  -  <i>Philetor</i> <br> -  -  -  -  -  -  -  <i>Philetor brachypterus</i> <br> -  -  -  -  -  -  <i>Scotophilus</i> <br> -  -  -  -  -  -  -  <i>Scotophilus kuhlii</i> <br> -  -  -  -  -  -  <i>Harpiocephalus</i> <br> -  -  -  -  -  -  -  <i>Harpiocephalus harpia</i> <br> -  -  -  -  -  -  <i>Phoniscus</i> <br> -  -  -  -  -  -  -  <i>Phoniscus atrox</i> <br> -  -  -  -  -  -  <i>Hesperoptenus</i> <br> -  -  -  -  -  -  -  <i>Hesperoptenus blanfordi</i> <br> -  -  -  -  -  Pteropodidae <br> -  -  -  -  -  -  <i>Balionycteris</i> <br> -  -  -  -  -  -  -  <i>Balionycteris maculata</i> <br> -  -  -  -  -  Megadermatidae <br> -  -  -  -  -  -  <i>Megaderma</i> <br> -  -  -  -  -  -  -  <i>Megaderma spasma</i> <br> -  -  -  -  -  Rhinolophidae <br> -  -  -  -  -  -  <i>Rhinolophus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus acuminatus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus affinis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus borneensis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus creaghi</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus sedulus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus trifoliatus</i> <br> -  -  Arthropoda <br> -  -  -  Insecta <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Blattodea <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Psocodea <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Trichoptera <br> -  -  -  -  Diptera <br> -  -  -  -  -  Mycetophilidae <br> -  -  -  -  -  Empididae <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  Insecta <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Blattodea <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Psocodea <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Trichoptera <br> -  -  -  -  Diptera <br> -  -  -  -  -  Mycetophilidae <br> -  -  -  -  -  Empididae <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  Insecta <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Blattodea <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  -  Psocodea <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Endomychidae <br> -  -  -  -  -  Bostrichidae <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Erotylidae <br> -  -  -  -  -  Carabidae <br> -  -  -  -  -  Lycidae <br> -  -  -  -  -  Coccinellidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Nitidulidae <br> -  -  -  -  -  Lucanidae <br> -  -  -  -  -  Ptilodactylidae <br> -  -  -  -  -  Anthribidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  -  Scarabaeidae <br> -  -  -  -  -  -  Melolonthinae <br> -  -  -  -  -  -  Ruteliinae <br> -  -  -  -  -  Cantharidae <br> -  -  -  -  -  Mordellidae <br> -  -  -  -  -  Rhipiceridae <br> -  -  -  -  -  Cleridae <br> -  -  -  -  -  Ptinidae <br> -  -  -  -  -  Cerambycidae <br> -  -  -  -  -  Throscidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Histeridae <br> -  -  -  -  -  Cerylonidae <br> -  -  -  -  -  -  <i>Gyrelon</i> <br> -  -  -  -  -  Melolonthidae <br> -  -  -  -  -  -  <i>Apogonia</i> <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Cicadellidae <br> -  -  -  -  -  Cydnidae <br> -  -  -  -  -  Coreidae <br> -  -  -  -  -  Fulgoroidea <br> -  -  -  -  -  Reduviidae <br> -  -  -  -  -  Miridae <br> -  -  -  -  Trichoptera <br> -  -  -  -  Diptera <br> -  -  -  -  -  Mycetophilidae <br> -  -  -  -  -  Empididae <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Ichneumoidea <br> -  -  -  -  -  Vespidae <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  Bethylidae <br> -  -  -  -  -  Apoidea <br> -  -  -  -  -  Braconidae <br> -  -  -  -  -  Pompilidae <br> -  -  -  -  -  Scoliidae <br> -  -  -  -  -  Chalcidoidea <br> -  -  -  Arachnida <br> -  -  -  -  Araneae <br></div><p></p>
Demonstaration of the use of Zenodo website to upload data and link it to the PersonalizeAF project
<p>This video demonstarates the use of Zenodo website to upload data and link it to the PersonalizeAF project</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.