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60 results for “stable water isotopes”
Stable Isotopes of Water from the Glacier de Martinets, 14-September-2021
<p>Thirty samples from the Martinets Glacier in Vaud, Switzerland collected on single day in September 2021. Data set includes ice, water flowing on glacier, and old snow. All ice was sampled at a maximum of 10 cm under the surface. Some duplicate samples are included. Dataset includes deuterium, O-17 and O-18. All analyses were completed with a Picarro CRDS at the Geography Institute of the University of Bern. Metadata includes latitude, longitude, elevation, date, time, and notes. </p>
Stable Water Isotopes and Nutrients in the Changjiang (Yangtze River) Estuary and adjacent East China Sea shelf in Winter
<p>The dataset presented here includes the temperature, salinity, stable water isotopes, and nutrients of seawater from the Changjiang Estuary and adjacent East China Sea shelf in March 2013. </p>
Stable Water Isotope Surveys - Muskoka River Watershed ON CA 2015-16
<p>This dataset includes river stable water isotope surveys from the Muskoka River watershed ON CA, conducted from April 2015 through November 2016. Ten river survey sites and one headwater stream site are included with listed site ID, sample date and ratios of oxygen and hydrogen isotope ratios. Data includes location of river survey sites and additional source water sampling sites (precipitation, snowmelt, groundwater). Daily average streamflow records for the 2015-2016 period of surveys originally sourced from the Water Survey of Canada website are included here (but can also be downloaded independently) for four of the six gauging stations referenced with the river survey isotope dataset. Water Survey of Canada gauging station locations are also provided.</p>
Data to accompany "Stable isotope ratios in seawater nitrate reflect the influence of Pacific water along the northwest Atlantic margin".
<p>This dataset accompanies the article by Owen A. Sherwood, Samuel H. Davin, Nadine Lehmann, Carolyn Buchwald, Evan N. Edinger, Moritz F. Lehmann, and Markus Kienast: "Stable isotope ratios in seawater nitrate reflect the influence of Pacific water along the northwest Atlantic margin", Biogeosciences, 18, 1–20, 2021. <a href="https://doi.org/10.5194/bg-2021-45">https://doi.org/10.5194/bg-2021-45</a>.</p> <p>The dataset comprises nutrient concentrations and nitrate isotope ratios for “bottle” samples of seawater collected by CTD/Rosette from 25 stations along the northwest Atlantic Ocean, from the Labrador shelf to northern Baffin Bay. Seawater physical properties measured by CTD are also provided for the depths at which bottle samples were collected. The complete sampling and analytical methods are provided in the accompanying article. </p>
Spatiotemporal variability of stable isotopes in precipitation and stream water in a high elevation tropical catchment in the Central Andes of Colombia
<p>Stable isotopes data set for the manuscript "Spatio-temporal variability of stable isotopes in precipitation and stream water of a high elevation tropical catchment in the Central Andes of Colombia".</p> <p>Data also used by Andrés Tangarife-Escobar for the thesis "Analysis of the spatial and temporal distribution of stable isotopes and their driving factors in the Upper Claro River Basin, Colombian Andes" to obtain the title of MSc in "Tropical Hydrogeology and Environmental Engineering" at the Technische Universität Darmstadt (Germany) in 2019. </p> <p>Samples collected by Jorge Ceballos from IDEAM (Colombia) and analyzed by the Servicio Geologico Colombiano. </p> <p> </p> <p> </p> <p> </p> <p> </p>
McMurdo Dry Valleys Gas, Tritium, Stable Isotope, and Major Ion data for lake waters: 2005-2006 Antarctic Season
Data of dissolved gas, tritium, stable isotopes, and major ion for Lake Vanda (Wright Valley), Lake Fryxell (Taylor Valley), Lake Hoare (Taylor Valley), and Lake Joyce (Pearce Valley): 2005-2006 Antarctic Season
Raw stable water isotope measurements in water vapour at 13.5 m a.s.l., made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset includes the raw data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements taken in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2130. This data has to be calibrated using the calibration runs and applying an appropriate calibration procedure following the IAEA guide lines.</p> <p>Two similar datasets also measuring stable water isotopes (SWIs) in water vapour were collected during the same expedition and can be distinguished from this dataset due to the height of the measurement collection (8 m a.s.l rather than 13.5 m a.s.l). The three ACE datasets of SWIs in water vapour are described and compared in Thurnherr et al. (2020).</p> <p>The calibrated dataset can be found with DOI: 10.5281/zenodo.3250790.</p> <p><strong>Dataset contents</strong></p> <ul> <li>year/month/day/HIDS2054-${year}${month}${day}-${time:Hhmmss}Z-DataLog_User.dat, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <p><strong>v1.1</strong> - Added 13.5 m a.s.l to title of dataset to distinguish it from other similar datasets collected during the expedition. Added calibrated dataset DOI and information about other SWI datasets from ACE, to abstract. Added reference to Thurnherr et al. (2020) to README.txt. Updated citation of dataset in README.txt.</p> <p><strong>v1.0</strong> - Initial release of raw stable water isotope measurements in water vapour dataset.</p> <p><strong>Dataset license</strong></p> <p>This stable water isotope measurements in water vapour dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw stable water isotope measurements in water vapour at 8 m a.s.l. on the starboard side of the ship, made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset includes the raw data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at a height of approximately 8 meters above sea level taken in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2130-i mounted on the starboard side of the ship. L2130-i was operated only during two months in February and March 2017 from Hobart (Australia) to Cape Town (South Africa). This data has to be calibrated using the calibration runs and applying an appropriate calibration procedure following the IAEA guide lines.</p> <p>Two similar datasets also measuring stable water isotopes (SWIs) in water vapour were collected during the same expedition and can be distinguished from this dataset due to the height of the measurement collection (at 8 m a.s.l and 13.5 m a.s.l). The three ACE datasets of SWIs in water vapour are described and compared in Thurnherr et al. (2020).</p> <p><strong>Dataset contents</strong></p> <ul> <li>leg*/HIDS2018-yyyymmdd-hhmmssZ-DataLog_User.dat, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw stable water isotope measurements dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full description can be found at https://creativecommons.org/licenses/by/4.0</p>
Calibrated data of stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>This data set includes the calibrated data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at approximately 8 m a.s.l. on the port of the ship, taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometers L2120. The data provide continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle.</p> <p>The raw data from which this calibrated dataset originates has been published separately (Kozachek, 2020; DOI 10.5281/zenodo.3667535).</p> <p>Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the starboard side (DOI: 10.5281/zenodo.3739335) and 13.5 m a.s.l (DOI: 10.5281/zenodo.3250790).</p> <p><strong>Dataset contents</strong></p> <p>Measurements on portside:</p> <ul> <li>ACE_watervapour_isotopes_SWI8-ps_1h.csv, data file, comma-separated values</li> <li>ACE_watervapour_isotopes_SWI8-ps_5min.csv, data file, comma-separated values</li> <li>cal_runs_SWI8-ps.csv, metadata, comma-separated values</li> <li>cal_flag_times_SWI8-ps.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p>NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations.</p> <p><strong>Dataset license</strong></p> <p>This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Variability in tree water uptake determined with stable water isotopes in an African tropical montane forest
<p>Dataset supporting the study <strong>Variability in tree water uptake determined with stable water isotopes in an African tropical montane forest.</strong></p> <p>We investigated relative contributions of different soil depths to tree water uptake of 83 trees and possible species-specific differences in a 50x50 m forest plot at four dates in a tropical montane forest in Kenya using stable water isotopes and the Bayesian mixing model framework MixSIAR.</p> <p>The dataset contains raw isotope data of tree xylem, soil and throughfall water sampled on different dates in a tropical montane forest in Kenya as well as interpolated model input data for the Bayesian mixing model.</p> <p>Further information can be found in the soon to be published article in Ecohydrology.</p> <p> </p>
Water Stable Isotopes in the Holthedalfonna Shallow Cores
<p><span>In the dataset, you will find the depth profile of stable oxygen isotopes taken from surface cores of the Holthedhalfonna glacier at Svalbard (79°09′N, 13°23′E; 1150 m a.s.l.). These samples were collected at a spatial resolution of 5 to 7 cm and retrieved in 2012, 2015, 2017, and 2019. The depth is converted to centimeters of water equivalent using density measurements. To align and merge the various cores, depth data from mass balance records available at <a href="http://www.mosj.com" target="_new">www.mosj.no</a> were used. All isotopic measurements were conducted utilizing a Picarro L1102-i analyzer coupled with a CTC Pal autosampler. Data for the 2012 cores are available in Spolaor et al. 2013, the 2015 core in Ruppel et al. 2017, and the 2017 core in Burgay et al. 2021. For additional information contact <a href="mailto:andrea.spolaor@cnr.it">andrea.spolaor@cnr.it</a>. </span></p> <p><span>This work has been supported by the “Programma di Ricerca in Artico” (PRA, project number PRA2019-0011, Sentinel); by the Svalbard Science Forum/Research Council of Norway through the Arctic Field Grant call (project ASIHAD, ISSICOS, BIOMASS), by French Polar Institute IPEV (Institut Polaire Français Paul-Emile Victor) science funding (programs 399 and 1192) and the Svalbard Strategic Grant (project C2S3, nr. 257636, SnowNet nr. 295779 and BC3D nr. 283466). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 689443 via project iCUPE (Integrative and Comprehensive Understanding on Polar Environments). This research has been partially funded by <span>the University of Perugia Research Action no. 5 “Climate, Energy, and Mobility”.</span> Cryogrid simulations have been supported by the Nansen Legacy project (Research Council of Norway grant 276730) and SIOS infraNor (Research Council of Norway grant 269927).</span></p>
Stable Water Isotopes in Fresh Snow Along 2 Slopes in the canton of Grisons/Graubünden, Switzerland: the "Chruez", Praettigau and Eastward ascent to the Vilan Peak
<p>This bachelor thesis concerned itself with the composition of <span class="math-tex">\(\delta\)</span>2H (or deuterium), <span class="math-tex">\(\delta\)</span>18O and <span class="math-tex">\(\delta\)</span>17O in fresh snow. Stable water isotopes have been proven to be useful tracers for hydrological processes, such as air mass sources of regional precipitation or the residence time of snowmelt in a catchment (Beria et al., 2018). Whereas different isotopic compositions of precipitation in the form of rain is well documented for different environments in networks such as the NISOT (The Swiss National Network for the Observation of Isotopes in the Water Cycle), the same knowledge about snow is more limited due to the influences of different isotope fractionation processes and lack of onsite snow accumulation and melt observation (Cooper, 1998; Michelon et al., 2018). The aim of this thesis was therefore to analyse and characterize the spatial variability of <span class="math-tex">\(\delta\)</span>2H, <span class="math-tex">\(\delta\)</span>18O and <span class="math-tex">\(\delta\)</span>17O in freshly fallen snow. This was done by sampling fresh snow on six different snowfall events in the month of March over an elevation gradient of 1000m along the southside slope of the mountain Chruez. 2H throughout four sampling days had <span class="math-tex">\(\delta\)</span>-values ranging from −50‰ to −70‰, with two days being more depleted in 2H, showing <span class="math-tex">\(\delta\)</span>-values from −80‰ down to −160‰. <span class="math-tex">\(\delta\)</span>18O showed the same pattern where of six, four days showed similar -values ranging from −8‰ to −12‰ and two days with a stronger depletion of the isotope with <span class="math-tex">\(\delta\)</span>-values ranging from −14‰ to −20‰. It is known that the enrichment of <span class="math-tex">\(\delta\)</span>17O in a water molecule is about half of <span class="math-tex">\(\delta\)</span>18O, which was also seen in the results of this thesis (Nyamgerel et.al, 2021).</p> <p>In this thesis, two out of six sampling days were examined with statistically significant positive altitude gradients of 0.19‰/100m and 0.64‰/100m for <span class="math-tex">\(\delta\)</span>18O. Additionally, on one of the six sampling days, a statistically significant negative altitude gradient of −0.15‰/100m was observed. The altitude gradients for <span class="math-tex">\(\delta\)</span>17O were about half of <span class="math-tex">\(\delta\)</span>18O. Two statistically significant positive and one negative altitude gradients for <span class="math-tex">\(\delta\)</span>2H were observed during the same days with lapse rates of 1.7‰/100m, 5.5‰/100m and −1.25‰/100m. Having both positive and negative altitude gradients was attributed to the varying amounts of solar radiation and wind direction during different sampling days. However, further research must be done in order to make a valid statement, since additional factors such as water vapor pressure, turbulent fluxes in the air and relative humidity strongly affect fractionation of stable water isotopes.</p> <p>The aim of this work is to characterize and analyze the elevation effect of water isotopologues in fresh snow at Vilan. By analyzing fresh snow, the influence of fractionation processes, after the precipitation event can be minimized and helps the understanding of snow-melt water transformation. For this purpose, a total of five fresh snow events in March and April 2021 were analyzed. Samples were taken from the eastern slope of Vilan between 1100 m a.s.l. and 2300 m a.s.l. and were collected at 100-meter elevation intervals. The altitude effect was determined with a linear regression. The analysis shows that the altitude has only a small effect on the d-values of the new snow, because for the <span class="math-tex">\(\delta\)</span>18O only one snow event shows a statistically significant altitude effect. For the <span class="math-tex">\(\delta\)</span>2H, it is their two. The statistically significant new snow events show an elevation gradient of + 0.155 ‰ <span class="math-tex">\(\delta\)</span>18O/100 m and + 1.211 ‰ <span class="math-tex">\(\delta\)</span>2H/100 m and + 0.677 ‰ <span class="math-tex">\(\delta\)</span>2H/100 m, respectively. The observed positive gradients can be explained by four effects. First, a lee effect is likely due to the prevailing weather conditions. Second, the top snow layer accumulates heavy isotopologues with increasing time (time effect). Third, an inverse height effect can be observed when water vapor of different origins mixes. Fourth, the amount of precipitation (quantity effect) can have an impact on isotopic composition. The work shows that further research in the analysis of water isotopes in fresh snow is necessary to better identify and quantify possible influencing parameters.</p> <p> </p> <p> </p>
Aircraft profiles of stable isotope ratios in atmospheric total and condensed water from the NASA ORACLES mission.
<p>Aircraft in-situ measurements of water concentration and heavy water isotope ratios D/H and 18O/16O of cloud water and total water (water vapor plus condensed water) were collected during the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project. Aircraft sampling took place in the southeast Atlantic marine boundary layer and lower troposphere (equator to 22 degrees south) over the months of Sept. 2016, Aug. 2017, and Oct. 2018. Isotope measurements were made using cavity ring-down spectroscopic analyzers integrated into the Water Isotope System for Precipitation and Entrainment Research (WISPER). The WISPER data are processed into mean latitude-altitude curtains and individual vertical profiles for each sampling period.</p> <p> </p> <p>The WISPER data accompanied a suite of other variables including standard meteorological quantities (wind, temperature, moisture), trace gas and aerosol concentrations, radar, and lidar remote sensing, which can be accessed through the DOIs listed further down. The ORACLES campaigns are described by Redemann et al., (2021). The water isotope measurements are further described in Henze et al., (2021). The absolute error with respect to the SMOW-SLAP scale is explained in detail by Henze et al., (2021).</p> <p> </p> <p>Total water concentration and isotope ratios were binned and averaged onto latitude-altitude grids using a kernel estimation approach, with weighting designed to estimate the mean during the approximate month-long duration of each sampling period. Standard deviations for each bin are also computed using kernel density estimation.</p> <p> </p> <p>Time intervals during aircraft vertical profiling are isolated and averaged onto 50-meter vertical levels. The files include water concentration and isotope ratios for both total water and cloud water in addition to temperature, pressure, latitude, and longitude.</p> <p> </p> <p>See included file README.txt for additional details.</p> <p> </p> <p>References</p> <p>---------------</p> <p>Henze, D., Noone, D., and Toohey, D.: Aircraft measurements of water vapor heavy isotope ratios in the marine boundary layer and lower troposphere during ORACLES, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-238, in review, 2021.</p> <p> </p> <p>Redemann, J., Wood, R., Zuidema, P., Doherty, S. J., Luna, B., LeBlanc, S. E., Diamond, M. S., Shinozuka, Y., Chang, I. Y., Ueyama, R., Pfister, L., Ryoo, J.-M., Dobracki, A. N., da Silva, A. M., Longo, K. M., Kacenelenbogen, M. S., Flynn, C. J., Pistone, K., Knox, N. M., Piketh, S. J., Haywood, J. M., Formenti, P., Mallet, M., Stier, P., Ackerman, A. S., Bauer, S. E., Fridlind, A. M., Carmichael, G. R., Saide, P. E., Ferrada, G. A., Howell, S. G., Freitag, S., Cairns, B., Holben, B. N., Knobelspiesse, K. D., Tanelli, S., L'Ecuyer, T. S., Dzambo, A. M., Sy, O. O., McFarquhar, G. M., Poellot, M. R., Gupta, S., O'Brien, J. R., Nenes, A., Kacarab, M., Wong, J. P. S., Small-Griswold, J. D., Thornhill, K. L., Noone, D., Podolske, J. R., Schmidt, K. S., Pilewskie, P., Chen, H., Cochrane, S. P., Sedlacek, A. J., Lang, T. J., Stith, E., Segal-Rozenhaimer, M., Ferrare, R. A., Burton, S. P., Hostetler, C. A., Diner, D. J., Seidel, F. C., Platnick, S. E., Myers, J. S., Meyer, K. G., Spangenberg, D. A., Maring, H., and Gao, L.: An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin, Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, 2021.</p> <p> </p> <p>The complete archive of ORACLES data are accessible via the digital object identifiers (DOIs) provided under ORACLES Science Team references as follows:</p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2018, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V3, 2020a. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2017, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V3, 2020b. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2016, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V3, 2020c. </p> <p> </p> <p>ORACLES Science Team: Suite of Aerosol, Cloud, and Related Data Acquired Aboard ER2 During ORACLES 2016, Version 3, NASA Ames Earth Science Project Office, https://doi.org/10.5067/Suborbital/ORACLES/ER2/2016_V3, 2020d.</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>
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>
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: Assessing fish movement and physiological traits along a salinity gradient by measuring stable oxygen isotope values in fish blood water and muscle water
Open the record for dataset details and reuse information.
Stable water isotopes reveal the onset of bud dormancy in temperate trees, whereas water content is a better proxy for dormancy release
Open the record for dataset details and reuse information.
Water stable isotope data for the Ogooué River (Gabon) at Lambaréné, 2012-2014.
<p>This dataset contains hydrogen and oxygen stable isotope data on surface water samples collected on the Ogooué River at Lambaréné (Gabon) between April 2012 and April 2014.</p>
Data from: City life alters the gut microbiome and stable isotope profiling of the eastern water dragon (Intellagama lesueurii)
Urbanisation is one of the most significant threats to biodiversity, due to the rapid and large-scale environmental alterations it imposes on the natural landscape. It is, therefore, imperative that we understand the consequences of, and mechanisms by which, species can respond to it. In recent years, research has shown that plasticity of the gut microbiome may be an important mechanism by which animals can adapt to environmental change, yet empirical evidence of this in wild non-model species remains sparse. Using an empirical replicated study system, we show that city life alters the gut microbiome of a wild native non-model species – the eastern water dragon (Intellagama lesueurii). City dragons exhibit a more diverse gut microbiome than their native riparian counterparts and show gut microbial signatures of a high fat and plant rich diet. These results highlight the role that gut microbial plasticity plays in an animals' response to human-altered landscapes.
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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.