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534 results for “stable isotopes”
Baltic Sea stable isotope ecology meta-data collection
<p>Stable isotope analysis (SIA) has become a pivotal method in food web and ecological research, leading to the establishment of the research field "stable isotope ecology". We conducted the first systematic review of stable isotope studies in this field in the Baltic Sea macro-region (Eglite et al. 2022). The meta-data collection provided here includes the information extracted from all 164 studies identified in the systematic review across various dimensions (topic, space, time, taxonomic, and technical focus), but not primary stable isotope data. The first published version of this meta-data collection represents the status as of July 10, 2021, and was used to filter and extract meta-data to produce the figures and tables in the review by Eglite et al. (2022). The meta-data collection is a resource for both experienced isotope ecologists and newcomers to grasp and access all published Baltic Sea SIA work on any fundamental or applied research topic, sub-region, taxon, or trophic group of interest. It also represents an ideal foundation for an envisioned "Baltic Isobank" database of primary stable isotope data, following the vision outlined in Eglite et al. (2022). We will provide regular updates of the meta-data collection in the Dryad repository, based on new runs of the systematic review query and including any additions of research papers and corrections received from the stable isotope ecology community. For this purpose, we encourage researchers to inform us about newly published research papers employing stable isotopes in the Baltic Sea ecology field by sending an e-mail with the publication reference to baltic-isobank@geomar.de.</p>
Table 1 for Radiocarbon and Stable Carbon Isotope Constraints on the Propagation of Vent CO2 to Fluid in the Acidic Kueishantao Shallow Water Hydrothermal System
<p>This table contains radiocarbon (<sup>14</sup>C) and stable carbon isotope (<sup>13</sup>C) compositions of CO<sub>2</sub> in vent gas, dissolved inorganic carbon and particulates of hydrothermal fluid from Kueishantao shallow water hydrothermal system, offshore northeastern Taiwan.</p>
Data from: New perspectives on soil animal trophic ecology through the lens of C and N stable isotope ratios of oribatid mites
<p>Knowledge of the trophic ecology of soil animals is important for understanding their high alpha diversity as well as their functional role in soil food webs and systems. In the last 20 years, the analysis of natural variations in stable isotope ratios (<sup>15</sup>N/<sup>14</sup>N, <sup>13</sup>C/<sup>12</sup>C) has revolutionized our view on soil animal trophic ecology. Here, we review the state of the art of the trophic ecology of a highly abundant and diverse soil animal taxon, oribatid mites (Oribatida), investigated by stable isotope analyses. The review is based on 25 papers reporting stable isotope data of 292 oribatid mite taxa from 30 different sites. Four main findings emerged. (1) Oribatid mites cluster into six trophic groups, i.e. moss feeders, lichen feeders, primary decomposers, fungal feeders/secondary decomposers, predators/scavengers and marine algal feeders, plus one additional group, which incorporates CaCO<sub>3</sub> in their cuticle for defence but still belongs to the fungal feeders/secondary decomposers group. (2) Of the 292 species studied 43.7% were classified as fungal feeders/secondary decomposers, 27.0% as primary decomposers and 15.7% as predators/scavengers, only few species include CaCO<sub>3</sub> into their skeleton (6.1%), feed on lichens (4.9%), mosses (2.1%) or marine algae (0.7%). (3) In about one-third of the species studied the trophic niche was constant or varied little between sites or habitats, but in two-thirds of the species, their trophic niche varied between habitats, with some species even shifting trophic levels, indicating trophic plasticity. (4) When aggregated at higher taxonomic level oribatid mite species clustered in only three instead of six trophic groups. This indicates that species within the same high-level taxon often belong to different trophic groups, for example, because feeding habits evolved convergently. Therefore, to accurately reflect the trophic ecology of oribatid mites their stable isotope signatures need to be analysed at the species level. However, stable isotope analyses also have limitations, e.g. feeding on bacteria and fungi cannot be separated, and the same is true for feeding on ectomycorrhizal and arbuscular mycorrhizal fungi. Other methods such as fatty acid, amino acid and molecular gut content analyses as well as microbiome analyses may complement stable isotope studies and resolve oribatid mite trophic niche differentiation at a higher resolution. This will contribute to a better understanding of the local coexistence of large numbers of species in soil. Finally, we provide perspectives on how to integrate microarthropods into soil food webs using stable isotope and other methods allowing deeper insight into their<br>trophic structure.</p>
Data for: Two is better than one: Coupling DNA metabarcoding and stable isotope analysis improves dietary characterizations for a riparian-obligate, migratory songbird
<p>While an increasing number of studies are adopting molecular and chemical methods for dietary characterization, these studies often employ only one of these laboratory-based techniques; an approach which may yield an incomplete, or even biased, understanding of diet due to each method's inherent limitations. To explore the utility of coupling molecular and chemical techniques for dietary characterizations, we applied DNA metabarcoding alongside stable isotope analysis to characterize the dietary niche of breeding Louisiana waterthrush (<em>Parkesia motacilla</em>), a migratory songbird hypothesized to preferentially provision their offspring with pollution-intolerant, aquatic arthropod prey. While DNA metabarcoding was unable to determine if waterthrush provision aquatic and terrestrial prey in different abundances, we found that specific aquatic taxa were more likely to be detected in successive seasons than their terrestrial counterparts, thus supporting the aquatic specialization hypothesis. Our isotopic analysis added greater context to this hypothesis by concluding that breeding waterthrush provisioned Ephemeroptera and Plecoptera, two pollution-intolerant, aquatic orders, in higher quantities than other prey groups, and expanded their functional trophic niche when such prey were not abundantly provisioned. Finally, we found that the dietary characterizations from each approach were often uncorrelated, indicating that the results gleaned from a diet study can be particularly sensitive to the applied methodologies. Our findings contribute to a growing body of work indicating the importance of high-quality, aquatic habitats for both consumers and their pollution-intolerant prey, while also demonstrating how the application of multiple, laboratory-based techniques can provide insights not offered by either technique alone.</p>
Long-term dataset of stable isotopes in rainfall at the North American monsoon region in southern Sonora, Mexico
<p>This is an original data set where rainwater samples were collected with a rain bucked prepared to avoid isotopic fractionation following the indication from the International Atomic Energy Agency (IAEA). We use a rainfall collector containing mineral oil, and samples from the collector were extracted within a maximum of 24 hours from the rain event and sometimes soon after precipitation ceased. Isotope analyses were carried with laser spectroscopy using working standards calibrated against the accepted Vienna Standard Meteoric Oceanic Water (VSMOW) for international reference and comparison. We analyzed the isotopic composition of 138 rain samples collected a permanent location with the aid of a rain bucket containing mineral oil. Samples were collected soon after every rainfall event between July 2014 and December 2021. Rainfall was collected at one permanent location at a residential area in Ciudad Obregon, Sonora Mexico within the Cajeme municipality (27.511850, -109.956316) in the transition zone between the urban and agricultural area in the northeastern edge of the city.</p>
The natural abundance of stable water isotopes method may overestimate deep-layer soil water use by trees
<p>The dataset is the basic data of the author's paper 'The natural abundance of stable water isotopes method may overestimate deep-layer soil water use by trees'. The main content of this paper is to study the water use strategy of trees in deep vadose zone regions by first identifying the soil layer depths from which trees derive their water source using isotopic labeling in deep layers and then calculating water sources based on the natural abundance of stable isotopes. We also compared the results with the natural abundance of stable water isotopes method. Taking apple plantation as an example, the data set includes the soil moisture, isotopic value in soil water, xylem water and precipitation.</p>
An in vivo stable isotope labeling method to investigate individual matrix protein synthesis, ribosomal biogenesis, and chondrocyte proliferation in murine articular cartilage
<p>These experiments have used a stable-isotope method using <em>in vivo</em> deuterium oxide labeling and mass spectrometry to measure protein concentration, protein half-life, cell proliferation, and ribosomal biogenesis in a single sample of murine articular cartilage. We hypothesized that a 60-day labeling period would capture age-related declines in cartilage matrix protein content, protein synthesis rates, and chondrocyte proliferation. Knee cartilage was isolated from 25- and 90-week-old female C57BL/6J mice treated with deuterium oxide for 15, 30, 45 and 60 days. We measured protein abundance and half-lives using high resolution accurate mass spectrometry (HRAM) and d2ome data processing software. </p>
Proteomics LC-MS/MS test dataset for protein quantitation via stable isotope labelling
<p>The provided mzML file can be used as a test dataset for protein identification and quantitation software. It was generated from human embryonic kidney (HEK) cells that were either unlabelled or labelled with heavy SILAC (K6R6, unimod accession 188, PSI-MS Name: "Label:13C(6)"). Apart from different labelling, the HEK cells were kept in exactly the same conditions and harvested simultaneously. Light and heavy labelled proteins from HEK cell lysate were mixed in a certain ratio, digested with Trypsin and measured on a ThermoFisher QExactive mass spectrometer. A more detailed description on the generation of the dataset will soon be accessible at PRIDE.</p> <p>The provided mzML file has been converted from Thermo RAW and slightly modified via msConvert (ProteoWizard). To reduce the filesize and to speed up analysis, it has further been filtered to contain only the data measured between 2,000 sec and 3,000 sec of the original LC-MS/MS run.</p>
Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web
<p>This is the data and analysis scripts needed to recreate the analyses shown in "Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web"</p> <p>The abstract of the manuscript summarizes the goal of the paper:</p> <p> </p> <p>Stable isotope tracing is a crucial technique for understanding the metabolic wiring of biological systems, determining metabolic flux through pathways of interest, and detecting novel metabolites and pathways. Despite the potential insights provided by this technique, its application remains limited to a small number of targeted molecules and pathways. Because previous software tools usually require chemical formulas to find relevant features, and the data are highly complex, especially in untargeted metabolomics and when the reactions and metabolites downstream the labeled substrates are poorly characterized. We report here Khipu version 2 and its new user-friendly web application. New functions are added to enhance analyzing stable isotope tracing data including metrics that evaluate peak enrichment in labeled samples, scoring methods to facilitate robust detection of intensity patterns and integrated natural abundance correction. We demonstrate that this approach can be applied to untargeted metabolomics to systematically extract isotope-labeled compounds and annotate the unidentified metabolites.</p> <p> </p> <p>This repository stores the code and data needed to recreate all presented analyses. The code and instructions are in the AnalysisCode.zip. The DDA in the dda_mzML.zip, the MS1 in the dataset_mzml.zip, and the asari results in the AsariResults.zip. The readme is in the AnalysisCode.zip and has more detailed instructions. This directory also has the output data in tabular format for the figures as the figures were mostly made with Excel. </p>
Dataset: Stable oxygen and carbon isotopes in freshwater pearl mussels from ultrastructurally distinct shell portions
<p>Oxygen isotopes in stream water can serve as natural tracers of watershed dynamics. Freshwater pearl mussels provide δ<sup>18</sup>O<sub>water</sub> estimates that overcome temporal and spatial limitations of instrumental records. The reliability of shell‑based δ<sup>18</sup>O<sub>water</sub> reconstructions depends on understanding which shell layer biomineralizes closer to oxygen isotopic equilibrium with ambient water<em>.</em></p> <p>This dataset contains isotope data obtained from freshwater pearl mussel shells<em>,</em> as discussed in the article titled "Biologically driven isotope fractionation in ultrastructurally different shell portions of freshwater pearl mussels <em>(Margaritifera margaritifera):</em> Implications for stream water δ<sup>18</sup>O reconstructions".</p> <p>The dataset includes δ<sup>18</sup>O and δ<sup>13</sup>C values from field-collected and tank-reared bivalve shells, complemented by <em>in-situ</em> δ<sup>18</sup>O<sub>water</sub> measurements from the tanks and shell growth rates of the tank-reared specimens.</p>
Stable water isotopes reveal the onset of bud dormancy in temperate trees, whereas water content is a better proxy for dormancy release
<p><span>Earlier spring growth onset in temperate forests is a visible effect of global warming and affects global water and carbon cycling. Therefore, it is crucial to accurately predict the shift in spring phenology under projected future warming. However, current phenological models lack physiological information and are rarely experimentally validated.</span><span> </span><span>Therefore, twig cuttings of five deciduous tree species were sampled at two climatically different sites throughout the winter of 2019/2020. Twig budburst success, thermal time to budburst, bud water content, and short-term <sup>2</sup>H-labelled water uptake into buds were quantified to link bud dormancy status with vascular water transport efficacy.</span><span> We found strong <sup>2</sup>H-labelled water uptake into buds during leaf senescence, followed by a sharp decrease that we attributed to the initiation of dormancy. However, we did not find increasing <sup>2</sup>H-labelled water uptake into buds with progression of winter, whereas all species showed a linear relationship between bud water content and dormancy status. Our results show that short term <sup>2</sup>H-labelled water uptake appears to be a poor tracer of dormancy release, but could be a promising method to track dormancy induction of deciduous trees, whereas bud water content seems to be an inexpensive and more reliable indicator of dormancy release. </span></p>
Data from: Dissolved nitrogen uptake versus nitrogen fixation: Mode of nitrogen acquisition affects stable isotope signatures of a diazotrophic cyanobacterium and its grazer
<p>Field studies suggest that changes in the stable isotope ratios of phytoplankton communities can be used to track changes in the utilization of different nitrogen sources, i.e., to detect shifts from dissolved inorganic nitrogen (DIN) uptake to atmospheric nitrogen (N<sub>2</sub>) fixation by diazotrophic cyanobacteria as an indication of nitrogen limitation. We explored changes in the stable isotope signature of the diazotrophic cyanobacterium <em>Trichormus variabilis</em> in response to increasing nitrate (NO<sub>3</sub><sup>-</sup>) concentrations (0 to 170 mg L<sup>-1</sup>) under controlled laboratory conditions. In addition, we explored the influence of nitrogen utilization at the primary producer level on trophic fractionation by studying potential changes in isotope ratios in the freshwater model <em>Daphnia magna</em> feeding on the differently grown cyanobacteria. We show that <em>δ</em><sup>15</sup>N values of the cyanobacterium increase asymptotically with DIN availability, from -0.7 ‰ in the absence of DIN (suggesting N<sub>2</sub> fixation) to 2.9 ‰ at the highest DIN concentration (exclusive DIN uptake). In contrast, <em>δ</em><sup>13</sup>C values of the cyanobacterium did not show a clear relationship with DIN availability. The stable isotope ratios of the consumer reflected those of the differently grown cyanobacteria but also revealed significant trophic fractionation in response to nitrogen utilization at the primary producer level. Nitrogen isotope turnover rates of <em>Daphnia</em> were highest in the absence of DIN as a consequence of N<sub>2</sub> fixation and resulting depletion in <sup>15</sup>N at the primary producer level. Our results highlight the potential of stable isotopes to assess nitrogen limitation and to explore diazotrophy in aquatic food webs.</p>
Fig. 3 in A study on benthic molluscs and stable isotopes from Kutch, western India reveals early Eocene hyperthermals and pronounced transgression during ETM2 and H2 events
Fig. 3 (See legend on previous page.)
Holocene and glacial individual foraminiferal analyses (IFA) of stable isotopes in Globigerinoides ruber tests from Line Islands sediment cores (central equatorial Pacific)
<p>This dataset contains individual foraminiferal analyses (IFA) stable isotopic (δ¹⁸O and δ¹³C) measurements of planktic foraminifera <em>Globigerinoides ruber</em> tests from modern and Last Glacial Maximum (LGM; ~20 ka) sediments from offshore the Line Islands, located in the central equatorial Pacific Ocean.</p>
Raw data: Stable isotopes of Hawaiian spiders reflect substrate properties along a chronosequence
<p>Data sets used to analyze N and C stable isotope ratios in spider tissues, leaf litter, and plant leaves originating from three sites along a substrate age gradient in Hawaii.</p>
Stable isotope records and bulk chemical compositions of the early Paleogene intervals of ODP Hole 762C
<p>In this study, we examined marine carbonate sediments of the late Paleocene to middle Eocene interval from the ODP Hole 762C, located on the Exmouth Plateau in the mid-latitude eastern Indian Ocean. This new dataset includes bulk carbonate δ<sup>13</sup>C and δ<sup>18</sup>O records, as well as bulk chemical composition of the sediments. By combining δ<sup>13</sup>C data with previously published magneto-biostratigraphic records, we revised the age model based on the newly identified hyperthermal event layers.</p> <p>Description of files:</p> <ul> <li>Supporting Table S3 : Bulk δ<sup>13</sup>C and δ<sup>18</sup>O data of ODP Hole 762C.</li> <li>Supporting Table S4 : Major and trace element data of ODP Hole 762C</li> </ul>
Stable isotope data for oxygen and hydrogen and electron microprobe data in phyllosilicates and clumped isotopes of carbonates from paleosols, Illinois Basin, USA
<p>Datasets including stable isotope data for oxygen and hydrogen of phyllosilicates, electron microprobe data of phyllosilicates, and clumped isotope data of carbonates from paleosols of the Illinois Basin, accompanying publication.</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>
IsoAnalyst: A System-Wide Stable Isotopic Labeling Aproach for Connecting Natural Products to Their Cognate Biosynthetic Gene Clusters
<p>Processed mass spectrometry data input used to develop and validate the IsoAnalyst program and the output from these analyses. The S_erythraea folder contains all MS input and output data for <em>Saccharopolyspora erythraea</em>. The Micromonospora_RL09050HVFA folder contains MS input and output data for <em>Micromonopora sp.</em> RL09050HVFA, as well as the full antiSMASH output for the <em>Micromonopora sp.</em> RL09050HVFA genome.</p> <p>Version 2 contains updated IsoAnalyst results for both organisms. </p>
Stable Isotope datasets "Late Miocene onset of Tasman Leakage and Southern Hemisphere Supergyre"
<p>Updated age models for isotopic series from ODP Sites 570, 751, 752, 754, 757 and 1172. </p> <p> </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.