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261 results for “belowground”
Spartina alterniflora marsh vegetation data along the Georgia coast used in the Belowground Ecosystem Resiliency Model version 2.0
Study plots (1-m2) were established in eight Spartina alterniflora-dominated marshes (7 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia). At three sites, plots were sampled once each during May, July, August, September, and October of 2016. At all sites, plots were sampled once each during June, August, and November of 2021, February, May, August, and November of 2022, and February of 2023. One long-term (quarterly 2013 to 2023) GCE LTER sampling site is also included. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 and -9 pixel footprints, with 3 plots per pixel footprint. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots. This dataset reflects an update to the "PLT-GCED-2106" dataset (doi: 10.6073/pasta/03f4f78c6498aecca34faf4339591129). This project also utilized data from the "PLT-GCEM-1610" dataset doi: 10.6073/pasta/9746c71b35e9f8c544ea12c601c33949). Those data utilized in this project are duplicated here for completeness.
Spartina alterniflora above- and belowground biomass predictions and inundation intensity as estimated by the Belowground Ecosystem Resiliency Model for U.S. Georgia marshes from 2014 to 2023.
We applied the Belowground Ecosystem Resiliency Model (BERM) to estimate monthly aboveground biomass (AGB) and belowground biomass (BGB) in U.S. Georgia Spartina alterniflora marshes from 2014 to 2023 at 30 m scale. This application involved BERM version 2.0 (https://doi.org/10.5281/zenodo.13306821), which was built using data in the PLT-GCET-2308 dataset (https://dx.doi.org/10.6073/pasta/4a0b715104849d98320fcc34e7cd63a4). Data sources for BERM application included Landsat-8/9, NOAA CO-OPS Station ID: 8670870, Daymet, and USGS 3DEP 2018 DEM. Download and processing steps are described in the BERM code and in metadata methods section. Specific descriptions of data processing are available in model code: https://doi.org/10.5281/zenodo.13306821. Data provided here include model output of AGB estimates, BGB estimates, and calculated inundation intensity. See "Data reporting" method in the metadata for description of data files. For logisitical purposes here we present only select data from the model input and output. All model input data sources as listed in the abstract are publicly available. Model calibration data and code are published as well. Additional predictions not published here include foliar chlorophyll, foliar nitrogen, and leaf area index.
Belowground biomass measurements from the GCE-LTER Seawater Addition Long-Term Experiment (SALTEx) Project
SALTEx (Seawater Addition Long-Term Experiment) is a field experiment designed to simulate saltwater intrusion in a tidal freshwater wetland to predict how chronic (Press) and acute (Pulse) salinization will affect this and other tidal freshwater ecosystems. The SALTEx experiment was initiated in 2012 and consists of 31 field plots, each 2.5 m on a side. There are three treatments (Press, Pulse, and Fresh) and two types of controls (with and without sides), each consisting of six replicates. The Press treatment plots receive regular (4 times each week) additions of a mixture of seawater and fresh river water. Pulse plots receive the same mixture of seawater and river water during September and October, which is historically a time of low flow in the river when natural saltwater intrusion occurs. The Fresh treatment plots receive regular additions of fresh river water. Treatment water is added during low tide to facilitate its infiltration into the soil, and all plots are inundated by astronomical tides at high tide. Belowground biomass was sampled from in each plot in March 2017 after 3 years of dosing.
Predator Contributions to Belowground Responses to Climate Warming at Harvard Forest 2014
Identifying the factors that control soil CO2 emissions will improve our ability to predict the magnitude of climate change-soil ecosystem feedbacks. Despite the integral role of invertebrates in belowground systems, they are excluded from climate change models. Soil invertebrates have consumptive and non-consumptive effects on microbes, whose respiration accounts for nearly half of soil CO2 emissions. By altering the behavior and abundance of invertebrates that interact with microbes, invertebrate predators may have indirect effects on soil respiration. We examined the effects of a generalist arthropod predator on belowground respiration under different warming scenarios. Based on research suggesting invertebrates may mediate soil CO2 emission responses to warming, we predicted that predator presence would result in increased emissions by negatively affecting these invertebrates. We altered the presence of wolf spiders (Pardosa spp.) in mesocosms containing a forest floor community. To simulate warming, we placed mesocosms of each treatment in ten open-top warming chambers ranging from 1.5 to 5.5° C above ambient at Harvard Forest, MA. As expected, CO2 emissions increased under warming and we found an interactive effect of predator presence and warming, though the effect was not consistent through time. The interaction between predator presence and warming was the inverse of our predictions: mesocosms with predators had lower respiration at higher levels of warming than those without predators. Carbon dioxide emissions were not significantly associated with microbial biomass. We did not find evidence of consumptive effects of predators on the invertebrate community, suggesting that predator presence mediates response of microbial respiration to warming through non-consumptive means. In our system we found a significant interaction between warming and predator presence that warrants further research into mechanism and generality of this pattern to other systems.
Belowground Carbon Observatory Network (BeCON) at Harvard Forest since 2020
A central goal of the recent Harvard Forest C Synthesis activity was to identify high-priority needs for C-cycle research at the forest. While there were a number of areas needing follow-up research, belowground C pools and fluxes remain the single largest gap in the C budget and therefore our understanding of the C cycle of the forest. To this end, we developed the Belowground Carbon Observatory Network (BeCON) as a part of the LTER-VI grant proposal. The long-term goal of BeCON is to understand temporal and spatial variations in belowground C pools in response to the various environmental changes the forest now faces [e.g., rising CO2, changes in atmospheric N, S and O3 chemistry, invading insects, land-use change, immigrating (large) herbivores]. There are two great challenges in achieving this goal: (1) excessive spatial heterogeneity in belowground C pools; and (2) lack of automated systems for analysis. These characteristics make it very difficult to quantify changes because the work is intrinsically labor intensive with low replication and the noisy data lead to low statistical power. Here, we measured soil carbon content, root biomass and carbon content, and annual root productivity following the protocols for BeCON.
Above ground plant, belowground stem and root biomass in Arctic Long-term Ecological Research's 2006 moist acidic tussock tundra experimental sites, 2012, Toolik Lake, Alaska.
Above ground plant, belowground stem and root biomass was measured in moist acidic tussock tundra experimental sites established in 2006 by the Arctic Long-term Ecological Research site (ARC-LTER. Control plots and plots amended with three different levels of nitrogen(N) and phosphorus(P), F10 (10 g/m2 N and 5 g/m2 P); F5 (5 g/m2 N and 2.5 g/m2 P); F2 (2 g/m2 N and 1 g/m2 P), were sampled.
Soil nitrogen availability and acidity: effects on aboveground production and belowground carbon allocation in mid- and late-successional mixed temperate forests (2009-2021)
In 2011, an experimental nitrogen x pH manipulation study was initiated in mid- and late-successional mixed temperate forests in central New York, USA to disentangle the often-confounded roles of nitrogen (N) and soil pH in driving various ecosystem processes. This data package contains forest productivity (wood, litterfall, and aboveground net primary production), total belowground carbon flux (TBCF), and leaf litterfall and fine root chemistry (C and N concentration) data collected from all experimental plots. It also includes plot-level, species-weighted estimates of measured and modeled photosynthesis (Anet) for the late-successional stands. Wood production, litterfall production, and litterfall chemistry data were collected between 2009 and 2019. Aboveground net primary production data are reported for a pre-treatment interval (2009-2011) and the interval including years 6-9 of experimental treatment (2016-2019). All other properties were measured between years 9 and 11 of the experiment (2019-2021).
Monthly Spartina alterniflora marsh vegetation data for additional sites along the Georgia coast used in the Belowground Ecosystem Resiliency Model
Study plots (1-m2) were established in three Spartina alterniflora-dominated marshes - 2 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia, and sampled once each during May, July, August, September, and October of 2016. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 pixel footprints, with 3 plots per pixel foot print. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height, flowering status and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots.
OMS01 Microbial and soil data in the Belowground Plot Experiment at konza prairie since 2017
Data describe soil chemistry collected during the 2017-2021 growing seasons at the Belowground Plot Experiment to assess for legacies. Whole plot-scale nitrogen fertilization at the Experiment ceased in 2017. Four subplots within each historically fertilized plot were set up to continue the annual fertilization treatment for soil chemistry.
Belowground responses to altered precipitation regimes in two semi-arid grasslands
Predicted climate change extremes, such as severe and prolonged drought, may profoundly impact biogeochemical processes like carbon and nitrogen cycling in water-limited ecosystems. To increase our understanding of how extreme climate events impact belowground ecosystem processes, we investigated the effects of five years of severe growing season drought and two-month delay in monsoon precipitation on belowground productivity and biogeochemical processes in two semi-arid grasslands. This experiment takes place during the fifth year of the Extreme Drought in Grassland Experiment (EDGE) at the Sevilleta National Wildlife Refuge (SNWR), a Long-Term Ecological Research in central New Mexico, USA. The two grassland sites a Chihuahuan Desert grassland dominated by Bouteloua eriopoda and Great Plains grassland dominated by B. gracilis are ~5km apart in the SWNR. The EDGE platform was established in the spring of 2012 (pre-treatment). Each site contains three treatments (ten replicates): ambient rainfall, extreme growing season drought, and delayed monsoon. The extreme drought treatment reduces growing season rainfall (April through September) each year by 66%, which equates to a 50% reduction of annual precipitation while maintaining natural precipitation patterns. There are 10 replicates per treatment within each site. All plots are 3 x 4 m in size and are paired spatially into blocks with treatments assigned randomly within a block. We measured an array of belowground and biogeochemical variables. Each variable was measured either once, twice, or three times (specific information on sampling scheme for each measured variable in methods section). Belowground net primary productivity, standing crop root biomass, total organic carbon, and total nitrogen were measured once. Extractable organic carbon, extractable total nitrogen, microbial biomass carbon, microbial biomass nitrogen and extracellular enzymes were measured twice. Available soil nitrate, available soil ammonium,
Data and R code for Tansley review New Phytologist 2021: "An integrated framework of plant form and function: The belowground perspective"
<p>The files in this archive are related to the paper of Weigelt, Mommer, Andraczek et al. (2021) An integrated framework of plant form and function: The belowground perspective. Tansley Review New Phytologist. The paper developed and tested a new conceptual framework of plant form and function linking above and belowground traits of 2510 species. We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow ‘conservation’ gradient on which leaf and fine-root traits were well aligned, and the ‘collaboration’ gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth.</p> <p>This archives contains four files:</p> <ol> <li><strong>Weigelt et al.2021RCode.DataCleaning.txt</strong> - RCode for the complete data processing starting with the downloaded database files from the Plant Trait Database version 5.0 (TRY, Kattge et al. 2020), the Global Root Trait database (GRooT, Guerrero-Ramirez et al. 2020) and a small number of additional data files listed in Table S2 of the original paper. Additional information was later incorporated using FungalRoot Database (Soudzilovkaia et al. 2020), nodDB Database (Tedersoo et al. 2018) and a compiled dataset on rooting depth (Fan et al. 2017). The code processes, cleans and merges the data and produces a final table for PCA analysis of species specific mean traits. This final table is provided as a second file in this archive (Weigelt_et_al_2021_Main.PCA.Matrix.xlsx). A second part of the RCode.DataCleaning extracts species-specific individual trait data where root and shoot traits were measured on the same plant individual or plot. This data was compiled from 43 studies identified in Table S2 of the original publication. The final table for individual trait data is the third file in this archive (Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx).</li> <li><strong>Weigelt_et_al_2021_Main.PCA.Matrix.xlsx</strong> – Datafile with species-specific global mean trait data for 17 traits of 2510 species with at least one root and one shoot trait available. Meta-data is provided in the data file.</li> <li><strong>Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx</strong> – Datafile with species-specific trait data where root and shoot traits were measured on the same individual or plot for 6 traits of 455 species. Meta-data is provided in the data file.</li> <li><strong>Weigelt et al.2021RCode.Analysis.txt – </strong>RCode for all analyses and figures provided in the paper for both the species mean and individual based dataset. The Code is annotated to help reproducibility of the analysis.</li> </ol>
Belowground nitrogen cycling in a montane grassland exposed to elevated CO2, warming and drought
<p>#### Data description<br> Data from a multi-factorial global change experiment (elevated CO<sub>2</sub>, warming and drought) in a montane grassland experiment in Austria (ClimGrass). Variables presented are soil nitrogen cycling rates measured using isotope pool dilutions.</p> <p>Companion paper will be linked following manuscript publication.</p> <p>#### Metadata<br> climgrass_soil_N_cycling.csv data description</p> <p>Year: 2017<br> Harvest: three harvests (May 30, July 25, October 3)<br> Season: numerical column for harvest number<br> Plot: location of plot within the ClimGrass experiment<br> Treatment: eight treatment levels<br> c0t0 (ambient CO<sub>2</sub>, ambient temperature)<br> c0t1 (ambient CO<sub>2</sub>, + 1.5°C)<br> c0t2 (ambient CO<sub>2</sub>, + 3°C)<br> c1t1 (+150 ppm, +1.5°C)<br> c2t0 (+300 ppm, ambient temperature)<br> c2t2 (+300 ppm, +3°C)<br> c0t0-d (ambient CO<sub>2</sub>, ambient temperature, extended drought)<br> c2t2-d (+300 ppm, +3°C, extended drought)<br> CO2_ppm: three values of carbon dioxide enrichment treatment (+0, +150, or +300 ppm)<br> Temp_C: three values of elevated temperature treatment (+0, +1.5, +3°C)<br> Drought: two levels (control, drought)<br> Prot_depoly: gross protein depolymerization rates (micrograms nitrogen per grams dry soil per day = µg N g-1 d-1)<br> FAA_uptake: gross free amino acid uptake rates (µg N g-1 d-1)<br> MRT_FAA_hrs: mean residence time of free amino acids (hours)<br> FAA: free amino acids (µg N g-1)<br> Mineralization: gross mineralization rates (µg N g-1 d-1)<br> Nitrification: gross nitrification rates (µg N g-1 d-1)</p> <p>#### References<br> Additional information on the experimental design can be found in the following paper:<br> Piepho, H.-P., Herndl, M., Pötsch, E.M., Bahn, M., 2017. Designing an experiment with quantitative treatment factors to study the effects of climate change. Journal of Agronomy and Crop Science 203, 584–592. doi:https://doi.org/10.1111/jac.12225</p> <p>More information on the isotope pool dilution method used can be found in the following paper:<br> Wanek, W., Mooshammer, M., Blöchl, A., Hanreich, A., Richter, A., 2010. Determination of gross rates of amino acid production and immobilization in decomposing leaf litter by a novel 15 N isotope pool dilution technique. Soil Biology and Biochemistry 42, 1293–1302. doi:10.1016/j.soilbio.2010.04.001</p>
Coastal Foredune Belowground Biomass, Aboveground Biomass, and Species Cover
<p>We collected data from cross-shore transects at seven sites; three categorized as unmanaged (i.e., Corolla Reserve, the northern dunes of the US Army Engineer Research and Development Center [ERDC] Field Research Facility [FRF North], and dunes in the southern reaches of that same site [FRF South]) and four categorized as managed (i.e., Southern Shores, Nags Head, Pine Island and Duck). Sediment vibracores (n = 15 managed, 10 unmanaged) were collected between September and December 2020 at the dune toe, dune face, crest and back along a single transect at each site. Cores were stored at 4 °C and processed within one week of collection to prevent root degradation. Cores were bisected longitudinally and the sediment from each half was segmented into 30 cm sections from the ground surface (i.e., 0–30 cm, 31–60 cm, 61–90 cm, 91–120 cm, 121–150 cm). To separate belowground biomass, core sections were wet sieved using stacked 3.36 mm, 1.0 mm and 0.5 mm mesh-size sieves. Living belowground biomass was characterized as the sample portions with roots, rhizomes and belowground stems that were still flexible and did not exhibit signs of decomposition. All other biotic material was classified as non-living biomass (e.g., decayed plant material, twigs, seeds, wrack). Within the living belowground biomass component, live roots were separated from other belowground structures (rhizomes, belowground-stems) and scanned using an Epson Perfection V800 Photo electric scanner calibrated for image analysis with WinRhizo™ Pro 2019a by Regent Instruments (Regent Instruments Inc, Quebec City, Quebec, Canada). Images were analyzed to quantify root surface area by diameter size class. Fine roots were defined as those with < 1 mm diameter. All living and non-living belowground biomass was oven-dried at 60 °C for 72 hours and weighed. </p> <p>Soil organic matter content was quantified by loss-on-ignition following manual removal of roots. Samples (1 g of sediment from each core section) were baked in a muffle furnace at 550 °C for 5 hours and reweighed to estimate soil organic matter content (%). Aliquots (300 mg) of each core segment were submitted to the Cornell Stable Isotope Laboratory for % carbon (C) and % nitrogen (N) analysis. Due to cost, only the top 90 cm of soils were sent for C and N analysis.</p> <p>Vegetation surveys were conducted during Summer 2021. We established vegetation survey plots (0.25 m­­2 plot size) centered on each exact coring location. We estimated vegetation cover by species (within 0.25 m2 plot), cover of bare ground, dead plant cover. Adjacent to the coring plots, aboveground biomass (within a 0.1 x 1 m plot) was collected to complement belowground biomass sampling at all sites except Duck, where grasses had been manually planted and permission to harvest aboveground biomass was not granted to maintain the vegetation on the dune face. Aboveground biomass was oven-dried at 60 °C for 72 hours, weighed and scaled to g m-2.</p> <p><strong>More details can be found in the manuscript: </strong></p> <p>White AE, Cohn N, Davis EH, Hein CJ, Zinnert JC. Coastal dune management affects above and belowground biotic characteristics. Scientific Reports (in press).</p>
Long-term above- and belowground net primary production (NPP) measurements from a grassland-shrubland transition zone in the Sevilleta National Wildlife Refuge, New Mexico, USA
Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to large-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground NPP (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground NPP (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. This data package accompanies an associated manuscript in which we used sixteen years (2005-2020) of annual NPP measurements, derived from three ongoing long-term research sites, to investigate spatiotemporal responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert.
Predicting aboveground and belowground processes in diverse forest ecosystems using remote sensing and in-situ measurements
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. This data package examines the connections between aboveground and belowground processes in FAB2. This data package includes information on tree diversity and community composition, forest structure, forest understories, soil microbes, net nitrogen mineralization, and canopy nitrogen. A wide variety of data types are included, such as data from hyperspectral and LiDAR remote sensing, percent cover analysis, soil microbial analyses, and soil assays including C:N, pH, and net nitrogen mineralization. This data package is included in the submission of the manuscript entitled “Predicting aboveground and belowground processes in diverse forest ecosystems using remote sensing and in-situ measurements.”
BGPVC Plant species composition in the Belowground Plot Experiment at Konza Prairie
Two permanent plant composition plots were marked with conduit in each of the 64 plots. Canopy cover was recorded in a 5 m2circular area surrounding each of the plots. At approximately 5-year intervals, coverage is assessed in late July, using visual estimates of cover by species, based on a modified Daubenmire scale. In 1989, sampling was done once in early July after mowing using one 10 m2 plot placed randomly in the approximate center of each plot. In 1994, plant composition sampling was done in early June in the unmowed plots; sampling in the mowed plots occurred in August. In 1999, two permanent conduits were placed in each plot, and sampling was conducted in June, before mowing, and again in August using 5 m2 plot sizes. In 2005 and afterward, sampling was reduced to one time in late July. Sampling occurred once every five years until 2015. Plots have been sampled annually since 2016. Two of the long-term unburned plots in a wildfire in 1994 and 1995. Those plots and years of the fire are indicated on the linked plot map. The mowing treatment was discontinued after 2002 due to invasion of the mowed plots by old world bluestem grasses. Data users should check for exotic species impacts on specific mowed subplots prior to this. In addition, fertilization in all plots ceased in 2017 as part of recovery from chronic N enrichment experiment.
SEA01 Soil extracellular enzyme activity data from the Belowground Plot Experiment
Data describe the activity of soil extracellular enzymes collected approximately every month in 2015 from the Belowground Plot Experiment. The measured enzymes depolymerize soil organic matter to release labile carbon, nitrogen, and phosphorus. Soil carbon and nitrogen were measured in July 2015 only, since these soil variables are not expected to change monthly.
BMS01 Mycorrhizae spore density and composition in the Belowground Plot Experiment at Konza Prairie
Spore densities of 14 groups (13 species + unknown) were measured the 64 belowground plots (record type 1). Effects of burning, mowing, and N + P additions on spore densities (an index of AM fungi infection rates). Community indices and percent root colonization (record type 2). Effects of burning, mowing, and N + P additions on mycorrhizal community composition and root colonization.
BNS01 Nematodes density and composition in the Belowground Plot Experiment at Konza Prairie
The effects of burning, mowing, and nitrogen (N) and phosphorus (P) fertilization on the trophic structure of a tallgrass prairie nematode community were examined in a long-term field experiment established in 1986. Nematode densities and trophic composition were determined in October of 1987, 1989, and 1994 following 2, 4, and 9 years of treatment, respectively.
GIS35 GIS Coverages Defining Sample Locations for Belowground Datasets on Konza Prairie (1982-present)
These data show the locations of research conducted at the below ground plots near Konza Headquarters. Record type 1 (GIS350) describes the 64 belowground plots receiving a variety of nutrient, burn, and mowing treatments. Data for BMS01, BMS02, and BNS01 are collected on these plots. Record type 6 (GIS355) describes the locations of the Micro-Rhizotrons. Two spatial datasets lie on the belowground plots, but are classified separately. These are the Lysimeters on belowground plots (GIS455) and Aboveground biomass on belowground plots (GIS505) datasets. GIS505 may be used alongside the BGPVC dataset, because it shares sample locations with PBB01. These data are available to download as zipped shapefiles (.zip), compressed Google Earth KML layers (.kmz), and associated EML metadata (.xml).
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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.