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8,375 results for “nationalism”
Long-term dynamics of soil organic matter and aboveground net primary production in a Chihuahuan Desert Grassland at the Sevilleta National Wildlife Refuge, New Mexico (1989-2014)
Drylands contain a third of the organic carbon stored in global soils; however, the long-term dynamics of soil organic carbon and soil organic matter (SOM) in drylands remain poorly understood relative to dynamics of the vegetation carbon pool. We examined long-term patterns in SOM against both climate and prescribed fire in a Chihuahuan Desert grassland in central New Mexico, USA. SOM was measured each spring and fall for 25 years (1989–2014) in unburned desert grassland and from 2003 to 2014 following a prescribed fire. SOM concentration from 0-20 cm depth did not show a clear long-term trend but fluctuated seasonally at both burned and unburned sites, ranging from a minimum of 0.9% to a maximum of 3.3%. SOM concentration declined nonlinearly in wet seasons and peaked in dry seasons. These results not only contrast with the positive relationships between aboveground net primary production and precipitation for this region, but also with previous reports of greater SOM in wetter sites across drylands globally, suggesting that space is not a good substitute for time in predicting the dynamics of dryland SOM. We suggest that declines in SOM in wet periods are caused by increased soil respiration, runoff, leaching, and soil erosion. In addition to tracking natural variability in climate, SOM concentration also decreased by 14% following prescribed fire, a response that magnified over time and has persisted for nearly a decade due to the slow recovery of primary production. Our results document the surprisingly dynamic nature of soil organic matter and its high sensitivity to climate and fire in this dryland ecosystem.
Field-Collected Spectral Reflectance of Dominant Vegetation at the Sevilleta National Wildlife Refuge
This dataset includes field-collected spectral reflectance of dominant vegetation species in grassland and shrubland at the Sevilleta National Wildlife Refuge collected monthly May – September 2019. A spectroradiometer was used to collect the percent spectral reflectance of electromagnetic radiation (range 400-2500nm) of a sample of dominant vegetation species ("spectra"), yielding a spectral curve for each species. At least ten individuals per species were sampled. These data form a spectral library which was used to calibrate a multiple-endmember spectral mixture analysis (MESMA) of satellite imagery of the Sevilleta NWR, as part of an ongoing collaboration between the LTER and the Center for the Advancement of Spatial Informatics Research and Education (ASPIRE). Ultimately, we aim to produce fractional images of green vegetation, non-photosynthetic vegetation, bare soil, and shade to form a synoptic thirty-year record of vegetation dynamics at the Refuge. The spectral library can be referenced by future researchers using remote sensing methods to examine vegetation dynamics at the Sevilleta NWR.
SEV-LTER Mean - Variance Experiment Seasonal Biomass Data at the Sevilleta National Wildlife Refuge, New Mexico
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean - Variance Climate Experiment (MVE) adds three novel elements to prior designs that have manipulated interannual variance in climate in the field (Gherardi & Sala, 2013) by (i) determining interactive effects of mean and variance with a factorial design that crosses reduced mean with increased variance, (ii) studying multiple dryland biomes to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. This data package includes species-level plant cover and biomass data from the Mean - Variance Experiment at five sites comprising the major ecosystems of the Sevilleta National Wildlife Refuge: Chihuahuan Desert shrubland, Chihuahuan Desert grassland, Great Plains grassland, Juniper savanna, and pinon-juniper woodland. Species cover and volume in one-meter-squared quadrats are assessed twice-yearly in spring and fall, and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."
SEV LTER: Tracking Vegetation Phenology Using PhenoCam Imagery at the Sevilleta National Wildlife Refuge, New Mexico, 2014-2024
As of 03/03/2024, the Sevilleta Long-Term Ecological Research Program is equipped with a total of 65 digital RGB cameras, or PhenoCams, across the Sevilleta National Wildlife Refuge. These cameras are installed on eddy covariance flux towers and at a number of precipitation manipulation experiments to track vegetation phenology and productivity across dryland ecotones. PhenoCams have been paired with eddy covariance flux tower data at the site since 2014, while some Mean-Variance Experiment PhenoCams were installed as recently as June 2023. For information on PhenoCam data processing and formatting, see Richardson et al., 2018, Scientific Data (https://doi.org/10.1038/sdata.2018.28), Seyednasrollah et al., 2019, Scientific Data (https://doi.org/10.1038/s41597-019-0229-9), and the PhenoCam Network web page (https://phenocam.nau.edu/webcam/). The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server hosted at Northern Arizona University, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations at various research sites. Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons.
Comparative Bird Community Assessments in Grassland, Shrubland, and Woodland Habitats at the Sevilleta National Wildlife Refuge, New Mexico (1991-1997 and 2022-2023)
Across North America, avifauna abundance has declined by 30% since 1970 (Rosenberg, K.V. et al. 2019). Direct mortality from anthropogenic sources (pets, cars, collisions with building, power lines, wind turbines, etc.) and indirect mortality (habitat loss, disturbance, climate change, etc.) have both been major contributors to these declines (Loss, S.R. et al. 2015 and Calvert, A.M. et al. 2013). Variables such as migration patterns, family, breeding and non-breeding biomes show differing rates of decline (Rosenberg, K.V. et al. 2019). In New Mexico, there are three breeding biomes all classified with declining avian abundance. Avian abundance in grasslands has declined by 53.3% since 1970, western forests by 29.5% and arid lands by 17.0% (Rosenberg, K.V. et al. 2019). All three of these biomes also occur at the Sevilleta National Wildlife Refuge thus temporal declines in species richness and abundance are expected. This project was originally designed to sample the species richness and abundance of birds on the Sevilleta National Wildlife Refuge in three types of habitat: grassland, creosote shrubland and pinyon-juniper woodland. Surveys were conducted between January 1991 and May 1997 (Parmenter, R. 2016). Surveys were re-established in 2022 to document current species richness and abundance and to capture any temporal changes from the 90s data. Avian point count survey stations in grassland, creosote and pinyon-juniper habitats run through existing study sites which have all been subjected to intense research activity. Literature Cited A. M. Calvert, C. A. Bishop, R. D. Elliot, E. A. Krebs, T. M. Kydd, C. S. Machtans, G. J. Robertson, A synthesis of human-related avian mortality in Canada. Avian Conserv. Ecol. 8, art11 (2013). https://www.ace-eco.org/vol8/iss2/art11/ Loss, S. R., Will, T., Marra, P. P. 2015. Direct Mortality of Birds from Anthropogenic causes. Annu. Rev. Ecol. Evol. Syst. 46, 99–120. https://www.annualreviews.org/doi/10.1146/annurev-ecolsys-1124
Small Mammal Mark-Recapture Population Dynamics at Core Research Sites at the Sevilleta National Wildlife Refuge, New Mexico (1989-present)
This file contains mark/recapture trapping data collected from 1989-present on permanently established web trapping arrays at sites on the Sevilleta National Wildlife Refuge in central New Mexico.. The trapping sites are representative of Chihuahuan Desert Grassland, Chihuahuan Desert Shrubland, Pinyon-Juniper Woodland, Juniper Savanna, Plains-Mesa Sand Scrub and Blue Grama Grassland. Not all sites have been trapped for the entire period: goatdraw (1992-2008), blue grama (2002-2004) rsgrass (1989-1998), rslarrea (1989-2009), two2 (1989-1998), savanna (1999-2002). Only 2 sites have been continuously been sampled since 1989 (5pgrass and 5plarrea). At each site 3 trapping webs are sampled for 3 consecutive nights in spring and fall. Each trapping web consists of 145 rebar stakes numbered from 1-145. There are 148 traps deployed on each web: 12 along each of 12 spokes radiating out from a central point (stake #145) plus 4 traps placed at the center of each web. The wide format facilitates community composition and species diversity analyses. Wide format has been reshaped so that the count data for each species are presented in a unique column. Data are summarized for each trapping web X trapping bout to present the mean number of animals per trap per night of the trapping bout. Wide format fills zeros for species that were not captured on a web during a given trapping bout. Long format facilitates filtering the dataset to a particular small mammal species of interest, but this format requires the addition of zeros to be functional for accurate data analysis requiring counts of animals.
Small Mammal Exclosure Study (SMES) Surface Soil Disturbance in the Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2005)
The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time? This is data for animal created soil surface disturbance measured from each of the SMES study plots. Soil surface disturbance was measured from each of the 36 one-meter2 quadrats twice each year when vegetation was measured.
Sila National Park - 3D Point cloud data
<p>This dataset contains 3 types of data.</p> <ul> <li>GPS data (the ones starting with <em>"GPS"</em>) of sampling plot centers collected with a Trimble GPS and post processed to ensure positioning errors lower than 2 meters.</li> <li>TLS data, (the ones starting with <em>"ID_"</em>): such data were collected in the end of August 2019 with a mobile terrestrial laser scanner (mobile ZEB TLS) in a squared area of approximatively 30x30m. Data have been normalized using TreeLS package in R.</li> <li>ALS data collected in the end of July 2019. For the entire study area, we upload 2 different ALS data: "<em>merged.las</em>" is the original point cloud; "<em>myLas_norm_lt22.las</em>" is the normalised point cloud, cut at 22 meters from the ground in order to perform specific analysis (i.e. paper under submission).</li> </ul> <p>Data collection was founded by the <em>AGRIDIGIT Selvicoltura</em> project.</p>
EPA Integrated Planning Model (IPM) National Electric Energy Data System (NEEDS) database
EPA is making the latest power sector modeling platform available, including the associated input data and modeling assumptions, outputs, and documentation.
Annotated checklist of the beetles of beech forests in Matese National Park, Central Italy
<p>The checklist contains 165 species of beetles which belong to 37 families. The species were collected during a field study carried out in the year 2018 and aimed at describing the community of beetles. The collection methods consisted of window flight traps. The study activities were carried out in four distinct beech forest stands based on their altitude (High and Low) and exposure (South and North) and located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT 7222287 “La Gallinola - Monte Miletto - Monti del Matese” and Matese National Park.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, geographic position, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>The discovery of a new species of beetle (Elateridae) for the Italian fauna was based on this dataset (Parisi et al., 2020).</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Annotated checklist of the beetles of three beech forests in Gran Sasso National Park, Central Italy
<p>The checklist contains 163 species of beetles which belong to 36 families. The species were collected during a field study carried out in the years 2013 and 2016 and aimed at describing the community of beetles. The collection methods consisted of window flight traps and emergence traps. The study area included 3 beech forest sites, named Prati di Tivo (42.5096 N, 13.5679 E), Venacquaro (42.4988 N, 13.5139 E) and Incodara (42.5123 N, 13.4735 E) located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT7110202 “Gran Sasso”.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, locality, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>Investigations on stand structure and forest biodiversity (Sabatini et al. 2016) and faunistic analysis (Zanetti and Parisi 2019) have been based on this dataset.</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Shock Ramp Compressions Measurements of Iron on the Sandia National Laboratories' Z-Machine
<p>This data contains 1) the apparent velocity data from Velocity Interferometer System for Any Reflector (VISAR) data analyzed using the PointVISAR program for experiments Z3155 and Z3339 and 2) the equation of state results from analyzing the velocity data using a backward integration -- forward Lagrangian analysis.<br> These experiments were performed on the Sandia National Laboratories' Z-Machine, where the iron samples were dynamically compressed via shocked compression to approximately 275 Gpa and further ramp compression to approximately 400 GPa. This covers pressure-temperature regions near the melt line as well as the interior conditions of terrestrial planets.<br> The Z3155 data include four samples, each with two VISAR traces, and the Z3339 data include six samples, each with two or three VISAR traces.<br> The apparent velocity can be corrected to true velocity using the latest lithium fluoride window correction for a 532 nm wavelength.<br> PointVISAR is available as part of the Sandia Matlab AnalysiS Hierarchy (SMASH) toolbox.<br> Details of the backward integration -- forward Lagrangian anaylsis that was used can be found in the related publication.</p> <p>Example data file interpretation: "Z3155_north_panel_bot_sample_01.txt" is the first VISAR trace from the bottom sample of the north panel on experiment Z3155.<br> "Z3155_EoS_combined.txt" is the sample-averaged Equation of State result from experiment Z3155.</p> <p>Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2020-13961 O</p> <p> </p>
Dataset with the results of the e-infrastructures Austria National Survey about Research Data
<p>This is the dataset accompanying the report with the results of our national survey regarding the management of research data</p>
Bagan, Manadalay, Myanmar. Clay tablet inscription, National Museum of Myanmar, Yangon.
<p>Bagan, Mandalay. Clay tablet inscription in Pāli, referring to an image made by Aniruddha. Now in the National Museum of Myanmar, Yangon. Provisional translation: This [image of] the Lord was made by Mahārāja Śrī Aniruddhadeva for the purpose of liberation by his own hand.</p>
Bagan, Manadalay, Myanmar. Seated Buddha (detail), National Museum of Myanmar, Yangon.
<p>Bagan, Manadalay, Myanmar. Seated Buddha, cast in a copper alloy (detail), now in the collection of the National Museum of Myanmar, Yangon. Probably 11th century.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai (Thai: สุโขทัย) Sukhothai province, Thailand, as documented in 2014,</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai (Thai: สุโขทัย) Sukhothai province, Thailand.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.</p>
Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.
<p>Khao Klang Nai (เขาคลังใน), Si Thep, Si Thep District, Thailand. Lithophone, now in Ramkhamhaeng National Museum, Sukhothai.</p>
National Open Access Monitor, Ireland - Research product metadata
<p>This dataset contains the foundational data for the National Open Access Monitor under an open license. OpenAIRE will routinely provide monthly data dumps to Zenodo, encompassing a comprehensive set of data and indicators related to the Open Access Monitor. This collaborative effort ensures accessibility and openness in sharing the data, promoting transparency and facilitating its use for research and analysis purposes.<br>The dataset comprises of the metadata of the research products metadata stored in the parquet format. The file contains two columns ("id", "xml"), the first of which is the OpenAIRE identifier of the research product and the the second the xml representation of the metadata. The schema of the metadata can be found in https://www.openaire.eu/schema/1.0/oaf-1.0.xsd and a detailed description of the contents can be found in https://graph.openaire.eu/docs/ and https://zenodo.org/records/2643199</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.