Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6,175
datasets available to search
ShareScore release 0.7.1
Dataset results
6,175 results for “composition”
Dataset of "A Monte Carlo Approach for Simulating Electrical Conductivity in Highly Porous Ceramic Composites: Impact of Internal Structure"
<p>3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).</p>
Raw data mzXML and MATLAB code for Variation in chemical composition of dissolved organic matter during the winter to spring transition in the northern Barents Sea
<p>MATLAB code and raw data mzXML for Variation in chemical composition of dissolved organic matter during the winter to spring transition in the northern Barents Sea.</p> <p>Seawater samples were collected during three distinct periods: early winter (December 2019), late winter (March 2021), and spring (May 2021). The sampling transect extended from the northern Barents Sea into the Nansen Basin (76°N – 83°N) as part of <em>The Nansen Legacy</em> project (Research Council of Norway, RCN #276730). The molecular composition of dissolved organic matter (DOM) was analyzed using an Orbitrap mass spectrometer.</p>
Dataset of "Balancing Activity and Stability through Compositional Engineering of Ternary PtNi–Au Alloy ORR Catalysts"
<p>A systematic comparative analysis of the activity-stability relationship for compositionally tuned PtNi-Au model layers, prepared by magnetron co-sputtering, was conducted using a diverse range of complementary characterization techniques and electrochemistry, supported by density functional theory calculations. Our study reveals that progressively increasing the Au concentration in the Pt50Ni50 alloy from 3 to 15 at.% leads to opposing catalyst activity and stability trends. Specifically, we observe a decrease in ORR activity accompanied by an increase in catalyst stability, manifested in the suppression of both Pt and Ni dissolution. Despite the reduced activity compared to PtNi, the PtNi–Au alloy with 15 at.% Au still exhibits nearly three times the activity of monometallic Pt. It also demonstrates a significantly improved dissolution stability relative to the PtNi alloy and even monometallic Pt. These findings provide valuable insights into the intricate balance between activity and stability in multimetallic ORR catalysts, paving the way for the design of cost-effective and durable materials for PEMFCs.</p>
Seawater dissolved chromium concentration, redox speciation, and stable isotope composition in the North Pacific Ocean
<p>Dissolved seawater chromium concentrations, redox speciation, and stable isotope composition were measured on samples collected in the North Pacific Ocean. Samples were collected over diel cycles (2 for stations 1-5, 1 for station 6) on board the RV Kilo Moana cruise KM1713 from Seward Alaska to Honolulu Hawai’i. Sampling stations spanned the subarctic North Pacific (stations 1 & 2), the dynamic subarctic-subtropical convergence zone (stations 3 and 4) and the subtropical North Pacific (stations 5 and 6). Chromium was enriched from filtered samples by Mg(OH)<sub>2</sub> co-precipitation and analyzed by MC-ICP-MS using either isotope dilution (Cr redox speciation) or double spike methodology.</p>
Dataset of "Hydrogen Evolution Reaction Activity in Mo₂TiC₂Tₓ MXene Derived from Mo₂TiAlC₂ MAX Phase: Insights from Compositional Transformations"
<p>MAX phases represent a crucial building block for the synthesis of MXenes, which constitute an intriguing class of materials with significant application potential. This study investigates the catalytic properties of Mo₂TiAlC₂ MAX phase and the corresponding Mo₂TiC₂Tₓ MXene for hydrogen evolution reaction (HER). Characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) revealed that despite the presence of secondary phases, the HER catalytic activity is primarily influenced by the MAX phase and its derived MXene. Interestingly, the catalytic activity of the MXene improves over time, attributed to the formation of MoO₂ as identified by XPS. This work enhances the understanding of MXene-based materials for electrochemical applications, highlighting crucial structural and chemical transformations that optimize their performance in sustainable energy technologies.3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).</p>
Spectral reflectance data of Mercury's surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015 resampled to a [55399 × 396] tabular data format.
<p>MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm.<br> Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury.<br> The final dataset has dimension [N×M] where N is the number of grid cells (360 × 180 = 64, 800) and M is the number of spectral features (396).<br> Due to the incomplete coverage and data filtering, some grid cells are empty.<br> After removing these empty cells, the size of the dataset is [55399 × 396].</p> <p>This specific product is stored as a gzip compressed json, where each element is a grid cell.<br> We are in the process to publish a complete pipeline to produce this product from RAW data on https://github.com/epn-ml/MESSENGER-Mercury-Surface-Cassification-Unsupervised_DLR/ .</p> <p>Spectral reflectance data of Mercury’s surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015.<br> MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm.<br> Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury.<br> The final dataset has dimension [N×M] where N is the number of grid cells (360 × 180 = 64, 800) and M is the number of spectral features (396).<br> Due to the incomplete coverage and data filtering, some grid cells are empty.<br> After removing these empty cells, the size of the dataset is [55399 × 396].</p> <p>0. Pre-filtering<br> We used the most recent dataset that had large-scale photometric corrections and thus was almost free from observation geometry effects.<br> However, extreme geometry are still present and are typically associated with high noise and some residual instrumental effects.<br> Based on our empirical tests, we filtered out observations with an emission/incidence angle ≥80∘.<br> We also calculated the median value per wavelength and per cell grid when constructing the global hyperspectral data cube and filtered out observations falling under the 2nd percentile and above 99.9th percentile to clean some residual geometry effects.<br> With this approach we create an effective noise filter while retaining enough observations to be able to analyse the entirety of the surface of the planet.</p> <p>1. Spectral resmpling<br> Unprocessed MASCS spectra could have 512 or 256 channes, depending on binning.<br> We resampled the data in the spectral dimension to a common wavelength range from 260 nm to 1052 nm with a 4 nm resolution (2 nm spectral sampling), resulting in 396 spectral channels.<br> This approach slightly oversamples the original 4.77 nm spectral resolution and removes some points from the original 200-1050 nm range.<br> The resulting data matrix is expressed in tabular form, with each row representing a single grid cell or pixel on the surface.<br> The elements of each row are the spectral reflectance values from the VIS instrument at 396 (resampled) wavelengths.</p> <p>2. Spatial resmpling<br> The whole dataset of ∼ 5 million spectra is resampled to a planet-wide rectangular grid of 1×1deg in the latitudinal band between ± 80.<br> The cell longitudinal size varies between ∼ 40 km at the equator to a minimum of ∼ 10 km at ±80∘.<br> Thus, the area spanned by each grid cell depends on the latitude. However, the same is true for the acquisition process, where higher spatial resolution is reached near the equator and lower resolution at the poles.</p>
Summer water chemistry, high frequency sensors, zooplankton and benthic macroinvertebrate community composition, periphyton, fish, and macrophyte biomass, along with lake metabolism and greenhouse gas dynamics in six experimental ponds in central Iowa, USA (2020)
This data product contains physical, chemical, and biological data ranging from the minute to daily to weekly scale in six artificial ponds (400 square meter surface area, 2m depth) in central Iowa (USA) 2020. Ponds were paired into three sets of treatment and reference with treatment ponds receiving two nutrient pulses designed to increase ambient phosphorus concentrations ~ 3 - 5%. Nitrogen and phosphorus were added as NH4NO3 and H3PO4, respectively, at a 24:1 molar ratio. The first nutrient pulse occurred on Julian day of year (DOY) 176 corresponding to a 3% increase and the second nutrient pulse occurred on DOY 211 to a 5% increase. Each treatment-reference set had a different food web structure established ranging between low, intermediate, and high complexity based on trophic connectivity and food chain length. Added to this data package is a document titled "2020 Iowa State University Horticultural Farm Experimental Ponds Nutrient Addition Experiment". For experimental set up, context, and a summary table of the data tables archived herein with available variables please review this document. It is added to aid in successful interpretation and to increase ease-of-use. Please email Tyler Butts (tyler.james.butts@gmail.com) for any and all questions regarding context or use of this dataset!
The Sierra Lakes Inventory Project: Non-Native fish and community composition of lakes and ponds in the Sierra Nevada, California
The Sierra Lakes Inventory Project (SLIP) was a research endeavor that ran from 1995-2002 and has supported research and management of Sierra Nevada aquatic ecosystems and their terrestrial interfaces. We described the physical characteristics of and surveyed aquatic communities for > 8,000 lentic water bodies in the southern Sierra Nevada, including lakes, ponds, marshes, and meadows. We also created digital map layers for these water bodies when such layers did not exist. The original objective of SLIP was to describe impacts of non-native fish on lake communities, but SLIP data has subsequently enabled study of additional ecological issues, including regional amphibian declines and their impacts on communities, and impacts of non-native fish on terrestrial species. In addition, these data are being used to develop fish removal efforts to restore aquatic ecosystems and recover endangered amphibians. The SLIP data is stored in a relational database that collectively describes water bodies (e.g., depth, elevation, location), surveys (conditions, effort), and communities (including approximately 170 fish, amphibian, reptile, benthic macroinvertebrate, and zooplankton taxa).
Composited land surface temperature of the greater Phoenix, Arizona, USA metropolitan area and surrounding Sonoran desert derived from cloud-free, summer (June, July, and August) Landsat imagery: 1985-2020
This project calculates land surface temperature (LST) from remotely sensed imagery. The intent is to extend the previous version of the LST data for the CAP LTER study area in central Arizona, USA to include 2020 and update the products so that they are based on a composite of images from each year (all available cloud-free acquisitions from June, July, and August) in the analysis to reduce the potential for outlier images or pixels to impact analyses. The aim is to make updated LST data accessible to stakeholders and researchers studying the greater Phoenix, Arizona, USA metropolitan area. LST is calculated from cloud-free Landsat 5 and 8 imagery (30m resolution) from summer months (June, July, and August) in 1985, 1990, 1995, 2000, 2005, 2010, 2015, and 2020. All images are cropped to the CAP LTER study area boundary.
Long-term composited Modified Normalized Difference Water Index (MNDWI) for the greater Phoenix, Arizona, USA, metropolitan area and the surrounding Sonoran desert derived from annual and seasonal Landsat imagery, 1998 to 2023
Abstract ======== This data package consists of multiple decades of modified normalized difference water index (MNDWI) raster data across the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) study area within metropolitan Phoenix, Arizona (USA), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). By providing a metric by which to reliably identify bodies of open water, these MNDWI data are intended to facilitate analyses of land-based environmental variables (e.g., urbanization, vegetation, land surface temperature) and can also be used to track long-term and seasonal change in the coarse extent of open water as a land-cover type. MNDWI was derived, following the methods of Xu (2006), from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of the spectral index, can be found in the data package metadata (see \'Methods and Protocols\') and accompanying Javascript code. **Citations:** - Gorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202:18--27. <https://doi.org/10.1016/j.rse.2017.06.031> - Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. *International Journal of Remote Sensing*, *27*(14), 3025--3033. <https://doi.org/10.1080/01431160600589179>
Biomarker assessment of spatial and temporal changes in the composition of flocculent material (floc) in the subtropical wetland of the Florida Coastal Everglades (FCE) from May 2007 to December 2009
Flocculent material (floc) is an important energy source in wetlands. In the Florida Everglades, floc is present in both freshwater marshes and coastal environments and plays a key role in food webs and nutrient cycling. However, not much is known about its environmental dynamics, in particular its biological sources and bio-reactivity. We analysed floc samples collected from different environments in the Florida Everglades and applied biomarkers and pigment chemotaxonomy to identify spatial and seasonal differences in organic matter sources. An attempt was made to link floc composition with algal and plant productivity. Spatial differences were observed between freshwater marsh and estuarine floc. Freshwater floc receives organic matter inputs from local periphyton mats, as indicated by microbial biomarkers and chlorophyll-a estimates. At the estuarine sites, the floc is dominated by mangrove as well as diatom inputs from the marine end-member. The hydroperiod (duration and depth of inundation) at the freshwater sites influences floc organic matter preservation, where the floc at the short-hydroperiod site is more oxidised likely due to periodic dry-down conditions. Seasonal differences in floc composition were not consistent and the few that were observed are likely linked to the primary productivity of the dominant biomass (periphyton in the freshwater marshes and mangroves in the estuarine zone). Molecular evidence for hydrological transport of floc material from the freshwater marshes to the coastal fringe was also observed. With the on-going restoration of the Florida Everglades, it is important to gain a better understanding of the biogeochemical dynamics of floc, including its sources, transformations and reactivity.
Dissolved Organic Matter Composition in Doboy Sound and the Altamaha River near Sapelo Island, Georgia in 2012-2013
The composition of dissolved organic matter (DOM) in the Altamaha River estuary and Doboy Sound near Sapelo Island, Georgia, was investigated at the molecular level using ultrahigh-resolution mass spectrometry and stable carbon isotope analyses. DOM samples were collected in November 2012, May 2013, and September 2013 representing different hydrological regimes, including anomalously low-discharge conditions. DOM was also collected from water as it flooded and ebbed from an extensive marsh area at Sapelo Island in May 2013. The untargeted approach used allowed for identifying the DOM molecular signatures associated with different DOM sources in the estuary.
DOM composition changes in Altamaha River and Sapelo Sound estuaries measured by FT-ICR mass spectrometry from September 2015 to September 2016
Dissolved organic matter (DOM) is a large and complex mixture of compounds with source inputs that differ with location, season and environmental conditions. Here, we investigated drivers of DOM composition changes in a marsh-dominated estuary off the southeastern U.S. Monthly water samples were collected at a riverine and estuarine site from September 2015 to September 2016, and bulk, optical, and molecular analyses were conducted on samples before and after dark incubations. Results showed that river discharge was the primary driver changing the DOM composition at the mouth of the Altamaha River. For discharge higher than ~ 150 m3 s-1, DOC concentrations and the terrigenous character of the DOM increased approximately linearly with river flow. For low discharge conditions, a clear signature of salt marsh-derived compounds was observed in the river. At the head of Sapelo Sound, changes in DOM composition were primarily driven by river discharge and possibly by summer algae blooms. Microbial consumption of DOC was larger during periods of high discharge at both sites, potentially due to the higher mobilization and influx of fresh material to the system. The Georgia coast was hit by Hurricane Matthew in October 2016, which resulted in a large input of carbon to the estuary. The DOC concentration was ~ 2 times higher and DOM composition was more aromatic with a stronger terrigenous signature compared to the seasonal maximum observed earlier in the year during peak river discharge conditions. This suggests that extreme events notably impact DOM quantity and quality in estuarine regions.
DOM composition in Altamaha River and Sapelo Sound estuaries measured by FT-ICR mass spectrometry in 2017 (April, July, October) and 2018 (January and October)
Extreme events such as hurricanes and tropical storms often result in large fluxes of dissolved organic carbon (DOC) to estuaries. Precipitation associated with tropical storms may be increasing in the southeastern U.S., which can potentially impact dissolved organic matter (DOM) dynamics and cycling in coastal systems. Here, DOM composition at the Altamaha River and Estuary (Georgia, U.S.A.) was investigated over multiple years capturing seasonal variations in river discharge, high precipitation events, and the passage of two hurricanes which resulted in substantial storm surges. Optical measurements of DOM indicate that the terrigenous signature in the estuary is linearly related to freshwater content and is similar after extreme events with or without a storm surge and during peak river flow. Molecular level analysis revealed significant differences, however, with a large increase of highly aromatic compounds after extreme events exceeding what would be expected by freshwater content alone. Although extreme events are often followed by increased DOC biodegradation, the terrigenous material added during those events does not appear to be more labile than the remainder of the DOM pool that was captured by ultrahigh-resolution mass spectrometry analysis. This suggests that the added terrigenous organic matter may be exported to the coastal ocean, while a fraction of the organic matter that co-varied with the terrigenous DOM may contribute to the increased biomineralization in the estuary, with implications to carbon processing in coastal areas.
The effects of changing vegetative composition on the abundance, species diversity and activity of birds at the Jornada Basin LTER site, 1997
This data package contains bird abundance data collected in plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected in an effort to distinguish the differential effects of plant community biomass, plant community functional groups, and biodiversity within functional groups on plant community function, including effects on animals. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. Following treatments, bird abundance and habitat preference data was collected in 1997. This data set consists of plot number, treatment type, and time of bird presence by taxa and by habitat and behavior. This study is complete.
NGE01 Chronic Addition of Nitrogen Gradient Experiment (ChANGE): Assessing threshold responses of plant community composition and ecosystem processes at Konza Prairie
Chronic nutrient additions can lead to drastic shifts in the plant community through time, both within tallgrass prairie in other grassland ecosystems worldwide. Nutrient addition experiments have answered many questions about patterns of diversity loss and community shifts; however, the level of nutrients which must be added to cause community shifts is unknown. To date, all nitrogen (N) addition experiments at Konza have added 10 g m-2 (e.g., NutNet Plots; Phosphorus (P) Plots; Belowground Plots), yet current rates of N deposition are one-tenth of that level. Even predicted rates of future N deposition in grasslands are not expected to exceed 5 g m-2 by the year 2050 and will likely be around 2 g m-2 for most of the US. This mismatch begs the question will 10 g/m2 affect grasslands the same way 2 or 5 g m-2 will? There are two main goals for this long-term experiment (1) to identify the nutrient threshold needed to drive plant community change with nutrient additions, and (2) to determine what factors underlie those threshold responses (build up of nutrients, mycorrhizal loss, invertebrate herbivory). Konza ChANGE is part of a multi-site experiment spanning grasslands on two different continents: North America – tallgrass prairie (KNZ) and shortgrass steppe (SGS), and China – three sites in Inner Mongolia. By including multiple grasslands, we expand our ability to make generalizations about how grasslands are affected by N additions, and whether thresholds, if they exist, vary with precipitation, natural nutrient availability, and species identity/composition. Research Questions: (1) Do ecosystems have N tolerance thresholds above which community composition will change, and does that differ between grassland types (i.e. mesic and xeric grasslands)? (2) Does adding a large amount of nutrients in one season result in an equivalent community change as adding a small amount over multiple years? (For example does 5 g m-2 for 6 years create the same community change as
Diet composition for small pelagic fishes across the Northeast U.S. Continental Shelf for NES-LTER, ongoing since 2013
These data represent the diet composition of small pelagic fishes assessed by the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) project. The six species of fish in this dataset represent a subset of the species collected in bottom trawls conducted by the NOAA Fisheries Northeast Ecosystems Surveys from Cape Hatteras to the Gulf of Maine. Sampling occurred in the Spring and Fall seasons. Fish were frozen and stomach content analyses were conducted by the Fisheries Oceanography and Larval Fish Ecology Lab at the Woods Hole Oceanographic Institution. Data are counts and length measurements for prey items examined under a dissecting microscope. Prey species were matched to the lowest taxonomic level in the Integrated Taxonomic Information System (ITIS) for scientific name and taxonomic serial number. The dataset was supplemented with geospatial and temporal information from NOAA Fisheries trawl databases.
Plant species composition and aboveground biomass data for Saddle snowfence, 1996 - ongoing.
Bowman et al. (1993) have demonstrated that alpine tundra is sensitive to nitrogen and phosphorus additions. Changes in productivity and species composition (belatedly) follow chronic fertilization. Exactly how this response is mediated by changes in precipitation is unknown but can be addressed using the snowfence experiment. Moreover, replication of the experiment will allow for additional sampling of biotic and abiotic components and processes not possible with the size of the Bowman plots. In 1993, 64 2x2m plots were placed in dry and mesic sites both within and outside of the snowfence area, so that 4 replicates of each treatment (nitrogen addition, phosphorus addition, nitrogen and phosphorus addition, and control) could be established in each meadow type with and without snowpack augmentation. 16 additional plots were established on a wet meadow site, but since a corresponding type site did not exist in the snowfence area, there was no snowpack manipulation for the wet meadow plots. In 2016, 9 existing plots were selected and 6 control plots added for assessing recovery from augmented snowpack treatment. Aboveground biomass, species richness, and species composition have been collected periodically since 1996.
Shrub influence on soil moisture, nutrients, temperature and species composition, 2019 - 2020.
Shrubification, the expansion and densification of shrubs, is occurring in arctic and alpine zones across the globe (Myers-Smith et al., 2011). This alteration is primarily driven by warming temperatures (Elmendorf et al., 2012b, 2012a), and can have major consequences for the existing vegetation (Anthelme et al., 2007; Pajunen et al., 2011; Venn et al., 2014) and for nutrient pools (Sturm et al., 2005; DeMarco et al., 2014) due to the abiotic and biotic effects of shrubs. Shrubs accumulate snow which insulates the ground during the winter and provides more moisture later in the season (Liston et al., 2002). During the summer, shrubs provide shade and wind protection. Additionally, shrubs can increase the soil nitrogen (N) pool through their high input of plant material into the soil (DeMarco et al., 2014). These small-scale climatic and soil alterations have important consequences for plant community dynamics in the arctic and alpine. References: Anthelme, F., Villaret, J.-C., and Brun, J.-J., 2007: Shrub encroachment in the Alps gives rise to the convergence of sub-alpine communities on a regional scale. Journal of Vegetation Science, 18(3):355–362. DeMarco, J., Mack, M. C., and Bret-Harte, M. S., 2014: Effects of arctic shrub expansion on biophysical vs . biogeochemical drivers of litter decomposition. Ecological Society of America, 95(7):1861–1875. Elmendorf, S. C., Henry, G. H. R., Hollister, R. D., Björk, R. G., Bjorkman, A. D., Callaghan, T. V., Collier, L. S., Cooper, E. J., Cornelissen, J. H. C., Day, T. A., Fosaa, A. M., Gould, W. A., Grétarsdóttir, J., Harte, J., Hermanutz, L., Hik, D. S., Hofgaard, A., Jarrad, F., Jónsdóttir, I. S., Keuper, F., Klanderud, K., Klein, J. A., Koh, S., Kudo, G., Lang, S. I., Loewen, V., May, J. L., Mercado, J., Michelsen, A., Molau, U., Myers-Smith, I. H., Oberbauer, S. F., Pieper, S., Post, E., Rixen, C., Robinson, C. H., Schmidt, N. M., Shaver, G. R., Stenström, A., Tolvanen, A., Totland, Ø., Troxler, T., Wahren, C. H
Arthropod species composition in the black sand extended growing season experiment, 2021 - 2024.
Understanding overall arthropod diversity in alpine systems will help us determine how diverse our biota is and what functional ecological roles these animals can provide to ecosystem maintenance and stability. And ultimately, how these services are altered with climate change. Arthropod diversity and functional roles will be altered with climate change, and understanding these interactions will teach us how to protect alpine systems and make predictions for the impacts to other ecosystems. Understanding impacts on pollinators will help us predict the quality of pollinator services at lower elevations, which species need support/protection, and any policies and food management strategies that need to be implemented to adapt to changes in food production.
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.