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19,324 results for “westerns”
Survey of Alarka Laurel and Rich Mountain Red Spruce (Picea rubens) Overstory, Saplings, and Seedlings in western North Carolina in 2007, 2022, and 2023
In the southern Appalachians, disjunct red spruce (Picea rubens) populations persist at low latitudes at elevations above 1,370 m. However, research on the condition of these disjunct red spruce populations is limited. This study compared baseline health, recruitment, and stand dynamics of two of the southern-most red spruce populations in eastern North America, the Rich Mountain and Alarka Laurel spruce bog basins in Nantahala National Forest, North Carolina. We collected data on overstory (DBH>10 cm), saplings (DBH< 10 cm, and height >2 m), and seedlings (height<10 cm) from Alarka Laurel in 2007 and 2022. Data from Rich Mountain were collected in 2023. We used 10-m wide belt transects noted the species and diameter at breast height (DBH) of overstory species, counted and noted the DBH of red spruce saplings, and counted and noted the height of red spruce seedlings. In 2022 and 2023, we gave a health score from 0-3 for all three categories of trees (overstory, saplings, and seedlings), with 0 being dead and 3 being healthy with little to no signs of disease or stress. Overall, both stands did not yet appear affected by climatic warming, despite the southern latitude and relatively low elevation. Our findings reveal that red spruce is the dominant overstory species, comprising an average of 25.6% of all measured overstory trees, with seedlings and saplings making up 72.8% of the red spruce population, indicating sustainable recruitment. Red spruce basal area declined by 13.9% from 2007 to 2022 in Alarka Laurel, with a concomitant increase in some hardwood species. However, both Alarka Laurel and Rich Mountain showed high levels of sapling and seedling recruitment. Overall, red spruce trees are healthy, particularly seedlings, representing the healthiest age category. Our results suggest the stands are relatively stable and provide essential baseline data for monitoring of forest conditions in the context of intensifying climate change. This research contributes to b
Western columbine genetics across HJ Andrews Experimental Forest meadow communities
Woody plant encroachment is diminishing meadow and grassland habitat on a global scale. Increased woody cover influences local conditions such as light/shade environments, local soil characteristics, understory plant community structure, and disturbance regimes. Woody encroachment may also affect landscape-scale biological processes, such as herbaceous plant population structure, through reducing the total cover and continuity of open habitat and eroding mutualistic interactions, such as plant-pollinator interaction networks. A major concern is that habitat fragmentation will have a cascading effect if one or more mutualistic partners is adversely affected. For example, if pollinators are sensitive to disturbance, fragmentation may reduce rates of gene flow among sub-populations of plants, which is predicted to decrease effective population sizes and diminish adaptive potential (i.e. the capacity to respond to selective pressures through the evolution of genetically-based and heritable traits). Alpine meadows of the Cascade Mountains, which support diverse wildflower and pollinator communities, have shrunk dramatically over the last century as a result of forest encroachment. We posited that, as meadows become smaller and less connected, pollinators may abandon the smallest meadows and focus foraging efforts on the largest, most connected meadows with the most resources. This could expedite the decline and ultimate collapse of meadow communities through reducing adaptive potential across sub-populations of plants. We focus on a plant-pollinator interaction between a common, nectar-producing plant, Aquilegia formosa (western columbine), and rufous hummingbird (Selasphorus rufus) pollinators in four montane meadow complexes in the H.J. Andrews experimental forest, Oregon, USA (HJA). Using hummingbird movement data from SA028 (see H.J. Andrews project database), we first ask whether further forest encroachment in the HJA may alter hummingbird movement patterns among me
Zooplankton collected with a 2-m, 700-um net towed from surface to 120 m, aboard Palmer Station Antarctica LTER annual cruises off the western Antarctic peninsula, 2009 - 2024.
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton and thus provide a link between primary producers and higher trophic levels. Zooplankton density and biovolume were determined at grid stations on the annual LTER cruises along the western Antarctic Peninsula (WAP). Annual cruises take place between late December to early February, except for the NBP21-13 cruise, which was November and December. Typically, zooplankton were collected with a 2x2 meter, 700um mesh net fitted with a flow meter and towed obliquely to 120m. Zooplankton distributions vary spatially due to water column characteristics, which affect their predators' distributions. As climate change continues to affect the WAP, the relative abundance of the various zooplankton components can also be expected to change.
Standard body length of Euphausia superba collected with a 2-m, 700-um net towed from surface to 120 m, collected aboard Palmer LTER annual cruises off the coast of the Western Antarctic Peninsula, 2009 - 2024.
Antarctic krill, Euphausia superba, are a critical food-web link between phytoplankton primary production and higher trophic levels, such as whales, penguins, and seals. Krill standard length was measured from LTER zooplankton tows along the western Antarctic Peninsula. Annual cruises take place between late December to early February, except for the NBP21-13 cruise, which was November and December. Length data provides estimates of age-class abundance and recruitment. Climate-induced changes in krill recruitment are an important consideration in the management and modelling of krill populations.
Length of Salpa thompsoni collected with a 2-m, 700-um net towed from surface to 120 m, collected aboard Palmer LTER annual cruises off the coast of the Western Antarctic Peninsula, 2009 - 2024.
Salps (Salpa thompsoni) are conspicuous gelatinous zooplankton capable of rapid population increases, enabling them to respond quickly to unpredictable phytoplankton blooms common in the Antarctic. Body length was measured on salps collected from LTER zooplankton tows along the western Antarctic Peninsula. Annual cruises take place between late December to early February, except for the NBP21-13 cruise, which was November and December. Salps have amongst the highest filtration rates of all zooplankton, and package their waste into large, fast sinking fecal pellets. These pellets provide a mechanism to export carbon fixed in the surface waters into the deep ocean. Since filtration rates and pellet size are positively related to the size of a salp, population estimates of grazing and exported carbon can be determined through length data.
Zooplankton collected with a 1.4-m2 frame, 500-μm mesh Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS) aboard Palmer LTER annual cruises off the coast of the Western Antarctic Peninsula, 2009-2017
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton in surface waters and thus provide a link between primary producers and higher trophic levels. Other zooplankton reside in the mesopelagic zone and feed on detritus or on other animals. Depth-discrete density of zooplankton taxa was determined at process study stations on the annual Palmer LTER cruises along the western Antarctic Peninsula. Samples were collected with a 1.4-m2 frame, 500-μm mesh Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS) towed obliquely to the surface from a depth of typically 500 m. MOCNESS tows were conducted in consecutive day-night pairs at each process study station. Zooplankton depth distributions vary between day and night as these animals conduct diel vertical migrations. Depth distributions also vary among zooplankton taxa based on species feeding ecology and life history traits. Zooplankton diel vertical migration contributes to the export of carbon and nutrients from the surface ocean to the mesopelagic zone.
The Neanderthal Niche Space of Western Eurasia - Supplemental Material
<p>The data provided here are the supplemental information accompanying the journal article <strong>The Neanderthal Niche Space of Western Eurasia 145ka to 30ka ago</strong> by Yaworsky, Nielsen, & Nielsen. All analyses were performed in R v4.5.0 and are documented in the HTML document, <strong>Supplemental 9</strong>.</p> <p>List of Supplemental Files:</p> <ol> <li><strong>ROCEEH Archaeological Observations - File name: </strong><em><strong>FaunalData_52923_NOANIMALS.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. The zooarchaeological observations have been removed from the original PHP query.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_Geog.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the Geolayer dates.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_Assem.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the ArchLayer dates.</li> </ol> </li> <li><strong>ROCEEH Dates Data - File name: </strong><em><strong>Dates_ArchLayer.csv</strong></em> <ol> <li>Retrieved from <em>Role of Culture in Early Expansions of Humans Out-of Africa Database (</em>http://www.roceeh.net)</li> <li>Original PHP query is found in Supplemental 9. These are the Assemblage dates.</li> </ol> </li> <li><strong>Spatiotemporal Archaeological Observations - File name: </strong><em><strong>ArchaeologicalData_V1.csv</strong></em> <ol> <li>Derived from Supplemental 1 after removing observations that dated outside of the 145ka to 50ka year range, all NA values, and observations duplicated in time and space (1000-year range).</li> </ol> </li> <li><strong>Spatiotemporal Background Points - File name: </strong><em><strong>AbsencePointData.csv</strong></em> <ol> <li>Randomly generated background points. 100 random points were generated in each millennium.</li> </ol> </li> <li><strong>High-Resolution Spatiotemporal Predictions - File name: </strong><em><strong>SDM_MainGIF.mp4</strong></em> <ol> <li>High-resolution mp4 file showing the predictions of the Neanderthal niche space from 145ka to 30ka ago.</li> </ol> </li> <li><strong>Neanderthal Niche Space 145ka to 30ka ago- File name: </strong><em><strong>Human_Niche_Size.csv</strong></em> <ol> <li>Quantification of the Neanderthal niche space for each millennium.</li> </ol> </li> <li><strong>Analysis Markdown Document - File Name: </strong><em><strong>NeanderEdgeMD_v5.html</strong></em> <ol> <li>Markdown illustrating step-by-step the methods used to organize and analyze the data.</li> </ol> </li> <li><strong>Delta O18 Record - File name: </strong><em><strong>LisieckiRaymod18O.csv</strong></em> <ol> <li>Delta O18 Record from Lisiecki & Raymo, 2005.</li> <li>Used in Figure 1 of the publication to illustrate the relationship between Neanderthal niche size and Delta O18 values.</li> </ol> </li> <li><strong>Neanderthal Niche Space 350ka ago to Present - File name: </strong><em><strong>Human_Niche_Size_350k.csv</strong></em> <ol> <li>Neanderthal niche space estimates from 350ka to the present based on the model constructed around the 145ka to 50ka ago archaeological observations.</li> <li>Not discussed in the main publication.</li> </ol> </li> </ol> <p>The NeanderEDGE Project is funded by the Independent Research Fund Denmark (Danmarks Frie Forskningsfond) case number 9062-00027B.</p>
Downscaled 8km March Snow Water Equivalent Estimates for the Western US, 1901-2010
<p>Downscaled estimates of March mean snow water equivalent at approximately 8km resolution across the western United States for the years 1901-2010. Data downscaled from the CERA-20c reanalysis using UA-SWE daily observations. Downscaled data using both the CERA-20c ensemble mean as well as each individual ensemble member as predictors are included. Units are in millimeters of snow water equivalent.</p>
Scenarios of technical and useful ground-source heat pump potential for building heating and cooling in Western Switzerland
<p>This dataset contains an estimation of the useful and technical potential of shallow ground-source heat pumps (GSHPs) for Western Switzerland, at a spatial resolution of 400 x 400 m<sup>2</sup>. The <strong>technical potential</strong> is hereby defined as the maximum energy that could be extracted from GSHP systems in case of their dense deployment, such as to <em>avoid the over-exploitation</em> of the heat capacity of the ground. We consider GSHPs with <em>vertical closed-loop borehole heat exchangers</em> (BHE) installed at depths of 50 - 200 m. The <strong>useful potential</strong> is defined as the potential that could be delivered to building heating and cooling systems via a water-to-water heat pump.</p> <p>The datasets contains future scenarios of heating and cooling demand, space cooling equipment deployment (service sector only) and climate change models and considers the potential use of DHC. The dataset covers around 80,000 property units (parcels) in the Swiss Cantons of Vaud and Geneva, excluding only the areas of the Alps and the Jura mountains.</p> <p>The data package contains information on the available area for GSHP systems, the heating and cooling demand as well as the resulting technical and useful potentials for all simulated scenarios of future cooling demand (200 Monte Carlo runs), for the case of <strong>direct heat supply</strong> (per pixel of 400 x 400 m<sup>2</sup>) as well as for <strong>district heating and cooling</strong> (DHC). In scenarios without DHC (direct heat supply), the results are summarized by pixel of 400 x 400 m<sup>2</sup>. In scenarios with DHC, the results of potentials <em>within</em> DHCs are summarized by DHC (see <em>*_in_dhc.csv</em>) while potentials <em>outside</em> of DHCs are summarized by pixel (see <em>*_outside_dhc.csv</em>).</p> <p>For details on the methodology applied to obtain the results provided in the data package, please refer to the above-mentioned research articles. A description of all files is provided in<em> Dataset documentation.pdf</em> and metadata is provided in <em>Datapackage.json.</em></p>
Seasonal to decadal western boundary current variability from sustained ocean observations
<p> </p> <p>Cross-transect velocity time series for HR-XBT transects IX21, PX30, and PX40 in support of: <a href="http://doi.org/10.1029/2022GL097834">Chandler et al. (2022). Seasonal to decadal western boundary current variability from sustained ocean observations.</a> </p> <p> </p> <p>Each netcdf file includes the following variables:</p> <ul> <li>time</li> <li>longitude</li> <li>latitude</li> <li>depth</li> <li>vel</li> <li>gvel_LNM</li> <li>long_for_vel_err</li> <li>lat_for_vel_err</li> <li>vel_err</li> <li>wbc_transport</li> </ul> <p> </p> <p>See also <a href="https://github.com/mlchandler/wbc_sustained_obs">https://github.com/mlchandler/wbc_sustained_obs</a></p>
Arctic vegetation cover fractions derived from Landsat time series (1984-2020) for the greater Mackenzie Delta Region (Western Canadian Arctic)
<p>Data to the publication by Nill et al. (2022) "<em>Arctic shrub expansion revealed by Landsat-derived multitemporal<br> vegetation cover fractions in the Western Canadian Arctic"</em></p> <p>The dataset features Landsat-derived fractional cover estimates of Arctic plant functional types (shrub, evergreen trees, herbaceous, lichen) and other land cover (barren, water) in the greater Mackenzie Delta Region, Canada.<br> We utilized regression-based unmixing based on synthetic training data in order to build multitemporal Kernel Ridge Regression (KRR) models for estimating fractional cover and validated our predictions based on independent very-high-resolution imagery (please be referred to publication for details).<br> <br> <strong>Dataset information</strong><br> The fraction cover predictions ("krr-avg") are provided separately for each epoch (1984-1990, 1991-1996, ..., 2015-2020) and class/cover type. The decadal change images ("dec-cng") between 1984 and 2020 are provided separately for each class/cover type. The naming convention of the files is as follows:</p> <p>XXXX-XXXX_YYY-YYY_int16-10e3_class-Z-Z</p> <ul> <li>XXXX-XXXX = epoch, e.g. 2015-2020</li> <li>YYY-YYY = dataset ("krr-avg" = fraction cover, "dec-cng" = decadal fraction cover change)</li> <li>Z-Z = class ID and associated class name (sh = shrub, cf = coniferous, hb = herbaceous, lc = lichen, wt = water, br = barren)</li> </ul> <p>The fraction cover values are % scaled by 10,000. For instance, a value of 1234 refers to 12.34%. Further image metadata:</p> <ul> <li><strong>Datatype:</strong> Signed 16-bit integer (Int16) </li> <li><strong>Data format: </strong>GeoTiff (.tif)</li> <li><strong>No data value:</strong> -9999</li> <li><strong>Projection:</strong> EPSG:3573 with custom central meridian; WKT string: 'PROJCS["WGS 84 / North Pole LAEA Canada",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Lambert_Azimuthal_Equal_Area"],PARAMETER["latitude_of_center",90],PARAMETER["longitude_of_center",-135],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1],AXIS["Easting",EAST],AXIS["Northing",NORTH]]'</li> </ul> <p><strong>Publication</strong><br> Nill, L., Grünberg, I., Ullmann, T., Gessner, M., Boike, J. & Hostert, P. (2022): Arctic shrub expansion revealed by Landsat-derived multitemporal vegetation cover fractions in the Western Canadian Arctic. Remote Sensing of Environment, 2022, 281. https://doi.org/10.1016/j.rse.2022.113228</p> <p><strong>Further information</strong><br> For further information, please see the publication or contact Leon Nill (leon.nill@geo.hu-berlin.de).<br> A web-visualization of this dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/arctic-shrub/">here</a>.</p>
A 30-year high resolution simulation of the ~1980-2010 climate over the Interior Western United States
<p>A high-resolution (4 km) regional climate simulation is conducted in the Interior Western United States (IWUS) using the Weather Research and Forecasting (WRF) model. The IWUS simulation is convection permitting and uses the NoahMP land surface model. The model integration is conducted over a 30-year period from 1 October 1981 through 30 September 2011.</p> <p>This repository contains a 30-year gridded dataset of daily precipitation, and daily minimum and maximum surface (2 m) temperature from the IWUS simulation. Anyone interested in the full dataset of the IWUS simulation is encouraged to contact the lead author at yongganga.wang@gmail.com.</p>
Data in support of 'The deep western boundary current of the Southwest Pacific Basin: insights from Deep Argo'
<p>Data in support of 'Chandler M, Zilberman NV, Sprintall J. (2024). The deep western boundary current of the Southwest Pacific Basin: insights from Deep Argo. <em>Journal of Geophysical Research: Oceans</em>. <a href="https://doi.org/10.1029/2024JC021098" target="_blank" rel="noopener">https://doi.org/10.1029/2024JC021098</a>'</p> <p>There are 4 netCDF files:</p> <ol> <li>swpb_dwbc_deep_argo_profiles_chandler2024.nc</li> <li>swpb_dwbc_deep_argo_trajectories_chandler2024.nc</li> <li>kt_dwbc_deep_argo_time_series_chandler2024.nc</li> <li>kt_dwbc_deep_argo_seasonal_cycles_chandler2024.nc</li> </ol> <p><strong>swpb_dwbc_deep_argo_profiles_chandler2024.nc </strong>contains the delayed-mode profiles of potential temperature and salinity on a 10-dbar pressure grid from the Deep Argo floats profiling within the deep western boundary current of the Southwest Pacific Basin. <em>[pressure; latitude; longitude; time; wmo_id; theta; salinity]</em></p> <p><strong>swpb_dwbc_deep_argo_trajectories_chandler2024.nc </strong>contains delayed-mode trajectories from the Deep Argo floats profiling within the deep western boundary current of the Southwest Pacific Basin. <em>[latitude; longitude; u; v; pressure; wmo_id; time]</em></p> <p><strong>kt_dwbc_deep_argo_time_series_chandler2024.nc</strong> contains the 2021--2022 monthly time series of dynamic height, salinity, and potential temperature between 2000--4000-dbar computed from the spatially-averaged Deep Argo profiles within the deep western boundary current as it travels along the western side of the Kermadec Trench. <em>[time; pressure; theta; salinity; dh; region_long; region_lat]</em></p> <p><strong>kt_dwbc_deep_argo_seasonal_cycles_chandler2024.nc</strong> contains seasonal cycles of dynamic height, salinity, and potential temperature (including the decomposition into heave/spice) between 2000--4000-dbar from the Deep Argo profiles within the deep western boundary current as it travels along the western side of the Kermadec Trench. <em>[pressure; theta; theta_heave; theta_spice; salinity; dh; region_long; region_lat]</em></p> <p>Argo data were collected and made freely available by the International Argo Program and the national programs that contribute to it (<a href="https://argo.ucsd.edu/" target="_blank" rel="noopener">https://argo.ucsd.edu/</a>). The Argo Program is part of the Global Ocean Observing System. A full list of acknowledgements can be found in the affiliated <a href="https://doi.org/10.1029/2024JC021098">publication</a>.</p> <p><code>Version history:</code><br><code>v1.0 First created (06-March-2024)</code><br><code>v1.1 Updated to include accepted publication reference (15-October-2024)</code></p>
Marine heatwaves statistics for the tropical western and central Pacific Ocean
<p>Processed marine heatwave metrics are provided for the tropical western and central Pacific Ocean region (120°E-140°W, 40°S-15°N). The metrics are computed from daily sea surface temperature (SST) data, from both observations and models. The observed marine heatwave data are calculated from NOAA 0.25° daily Optimum Interpolation Sea Surface Temperature (OISST) over the period 1982-2019. The modelled marine heatwave data are from analysis of 18 model simulations as part of the Coupled Model Intercomparison Project, Phase 6 (CMIP6) over the period 1982-2100, where two future scenarios have been analysed. Marine heatwaves are computed with respect to the 1995-2014 climatology. The marine heatwave data are provided on a grid point basis across the domain. Marine heatwave timeseries metrics are also provided for three case study regions: Fiji, Samoa, and Palau.</p>
Data from: Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones
<p>This vcf file contains 7.023.689 SNPs and 870 honey bee samples, as described in the paper "Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones" by Wragg et al., available at https://doi.org/10.1101/2021.09.20.460798 as preprint.</p> <p>Eight hundred and seventy haploid drone samples from several honey bee subspecies hybrids were sequenced and aligned to the HAv3.1 reference genome. Sequence read alignment and genotyping quality filters were used to obtain a selection of 7.023.689 high-quality SNPs. The file Diversity_Study_629_Samples.txt corresponds to the 629 unique samples that were used for the diversity study described in the paper and can be used to recreate the restricted diversity dataset using bcftools or an equivalent software.</p> <p>Having sequenced haploid drones, heterozygous SNPs resulting from duplicated regions could be filtered out and the data is phased.</p>
Geological map of the southern Red Sea & western Gulf of Aden region
<p><strong>Content</strong></p> <p>This dataset contains a geological map of the southern Red Sea & western Gulf of Aden region (1:3’100’000), including all the associated data.</p> <p>This dataset includes:</p> <ul> <li>The map in JPEG, PDF, and GeoTIFF format</li> <li>The shapefiles of the map</li> <li>One document listing all sources used for the compilation of this map (<em>Source_Material_GmsRSwGoAr.pdf</em>)</li> </ul> <p> </p> <p>This database is an additional complement to the paper ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>Note that a larger-scale map of the Afar Depression is available as 'Rime, V., Foubert, A., Atnafu, B. and Kidane, T. (2022) Geological map of the Afar Depression. <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.7351643">https://doi.org/10.5281/zenodo.7351643</a> '</p> <p> </p> <p><strong>References</strong></p> <p>The map was developed by compiling a large number of published maps, descriptions, datings and other studies, complemented by remote sensing. All sources and references are mentioned in the <em>Source_Material_GmsRSwGoAr</em>. Material and methods of mapping have been described in detail within the paper.</p> <p> </p> <p><strong>Citation</strong></p> <p>When using the data, please cite the data as ‘Rime, V., Foubert, A., Atnafu, B. & Kidane, T. (2022) Geological map of the southern Red Sea & western Gulf of Aden region. Zenodo’ and refer to the accompanying paper as ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>The map and additional data are given without any guarantee of correctness. Any use of these are under the user’s full responsibility.The authors decline any responsibility.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This study was funded by the Swiss National Science Foundation (SNF project SERENA – SEdimentary REcord of the Northern Afar 200021_163114). We are grateful to the University of Fribourg (Switzerland), the University of Addis Ababa (Ethiopia), the Ethiopian Ministry of Mines and Energy, the Ethiopian Geological Survey, Circum Minerals, former Allana Potash and Yara Dallol for their support. We particularly acknowledge Samuel Getachew that helped us to access some of the geological maps. We thank David Jaramillo-Vogel, Jean-Charles Schaegis, Haileyesus Negga, Addis Endeshaw, Ermias Gebru, Eva de Boever, Juan-Carlos Braga, Pia Wyler, Xenia Haberditz, the Ethioder team as well as the regional and local administration of the Afar for their help and support during fieldwork.</p>
Dataset containing binominal lexemes in Harakmbut (isolate, Peru), for "The derivational use of classifiers in Western Amazonia" and "When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut"
<p>This is the dataset used, amongst others, in the paper: Van linden, An. Forthcoming. When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut. Special Issue “Re-assessing the explanatory potential of alienability contrasts”, guest-edited by Françoise Rose & An Van linden. <em>Linguistics – An Interdisciplinary Journal of the Language Sciences</em>. [<a href="https://doi.org/10.1515/ling-2022-0039">https://doi.org/10.1515/ling-2022-0039</a>]</p> <p>For more details, see the ReadMe file.</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) January 2014 - December 2014
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from January 2014 to December 2014 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 20 m [°C]; Salinity @ 20 m [psu].</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) March 2015 - December 2015
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from March 2015 to December 2015 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 6 m [°C]; Sea temperature @ 20 m [°C]; Sea temperature @ 36 m [°C]; Salinity @ 6 m [psu]; Salinity @ 20 m [psu], Salinity @ 36 m [psu].</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) July 2016 - May 2017
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from July 2016 to May 2017 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 6 m [°C]; Sea temperature @ 20 m [°C]; Sea temperature @ 36 m [°C]; Salinity @ 6 m [psu]; Salinity @ 20 m [psu], Salinity @ 36 m [psu] </p>
ScienceDex guides
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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.