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709 results for “soil carbon”

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zenodo32/100

Detailed global modelling of soil organic carbon in cropland, grassland and forest soils

Supporting information of the paper: Morais, T.G., Teixeira, R.F.M., Domingos, T. 2019. Detailed global modelling of soil organic carbon in cropland, grassland and forest soils. PloS One. Version 2 includes raster files (.tif) for each land use class (including: Attainable SOC stock, mineralization rate, and fator K).

opencc-by-4.0Sep 2019View details →

zenodo32/100

Soil Moisture Active/Passive (SMAP) Level 4 Carbon (L4C) Nature Run version 7.2

The Soil Moisture Active/ Passive (SMAP) Level 4 Carbon (L4C) product is a daily, global, terrestrial carbon budget driven, in part, by soil moisture estimates from the Level 4 Soil Moisture (L4SM) product and, in turn, on brightness temperature observations from the SMAP satellite [1,2]. The SMAP L4C operational product's record begins on March 31, 2015, shortly after the launch of SMAP, and continues to the present, with an average latency of 9 days [3]. SMAP L4C data are posted to a global, 9-km equal-area EASE-Grid 2.0 [4]. In order to improve the longitudinal coverage of the SMAP L4C record, a model-only "Nature Run" was devised, with daily carbon budget estimates beginning January 1, 2000. The Nature Run differs from the SMAP L4C operational product in the following ways: - The SMAP L4C Nature Run uses the MERRA-2 re-analysis dataset for meteorological driver data, instead of the GEOS-5 FP driver data used in the operational product. - The SMAP L4C Nature Run uses soil moisture and soil temperature estimates from the L4SM Nature Run, which is a model-only version of the operational L4SM product that does not assimilate SMAP brightness temperature data. This repository contains the full README for the data. The data can be downloaded from: http://files.ntsg.umt.edu/data/SMAP_L4C_NatureRun/NRv7.2/

opencc-by-4.0Nov 2020View details →

zenodo32/100

Soil organic carbon distribution for 0-3 m soils at 1 km2 scale of the frozen ground in the Third Pole Regions

Soil organic carbon (SOC) is very important in the vulnerable ecological environment of the Third Pole; however, data regarding the spatial distribution of SOC are still scarce and uncertain. Based on multiple environmental variables and soil profile data from 458 pits (depth of 0–1 m) and 114 cores (depth of 0–3 m), this study uses a machine-learning approach to evaluate the SOC storage and spatial distribution at different soil depths (0–30 cm, 0–50 cm, 0–100 cm, 0–200 cm, and 0–300 cm) in the frozen ground area of the Third Pole region. Our results provide information on the storage, patterns, and environmental controls of SOCSs at a 1 km2 scale for areas of frozen ground in the Third Pole region, thus providing a scientific basis for future studies pertaining to Earth system models. Soil organic carbon data is stored in grids format, and the file name is "TP-SOC-d.tif", where d represents soil depth, for example, "TP-SOC-30.tif" represents the spatial distribution of soil organic carbon stocks in the Third Pole regions of the upper 30 cm depth interval.

opencc-by-4.0Nov 2020View details →

dryad32/100

Soil carbon, nitrogen, and phosphorus cycling microbial populations and their resistance to global change depend on C:N:P stoichiometry

Maintaining the stability of ecosystem functions to global change calls for a better understanding the regulatory factors of functionally specialized microbial-groups and their population-response to disturbance. Here, we explored this issue by collecting soils from 54 managed ecosystems in China and building a predictive model of microcosm experiments. Soil carbon:nitrogen:phosphorus (C:N:P) stoichiometry (35%~49%) imparted a greater individual effects on the abundances of microbial-groups associated with main carbon C, N, and P biogeochemical processes in comparison with geographical conditions (7%~10%). Soil total C and N contents were significantly positively correlated with the abundances of diazotrophs (nifH), nitrifiers (bacterial amoA), nitrate reducers (narG) and denitrifiers (nirS/K and nosZ genes). Soil C:N ratio not only exhibited a negative relationship with the abundances of P activators (phoD, phoC and pqqC genes), but also with cellulolytic decomposers (fungcbhIR and GH74 genes). Nitrogen cycling genes, including bacterial amoA, nirS, narG and norB, exhibited higher genetic resistance to N deposition compared with the drying-wetting cycles and warming. Soil total C, N and P contents, and their ratios had a strong direct effect on the genetic resistance of microbial-groups. Soil C:P ratio was selected by random forest analyses as the main predictor of N cycling genetic resistance to N deposition. Soil total C and N contents, and their ratios were the main predictors of the P cycling genetic resistance to three global change drivers. Overall, our work highlights the importance of soil stoichiometric balance for maintaining the ability of microbially-driven ecosystem functions to withstand global change.

opencc-zeroDec 2019View details →

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Data from "Removal of grazers alters the response of tundra soil carbon to warming and enhanced nitrogen availability", Ecological Monograps in October 2019

Here we present the data used in the manuscript "Removal of grazers alters the response of tundra soil carbon to warming and enhanced nitrogen availability", Ecological Monograps, Early view in October 2019 by H. Ylänne, E. Kaarlejärvi, M. Väisänen, M. K. Männistö, S. H. K. Ahonen, J. Olofsson & S. Stark. In this paper we studied, how five years of experimental warming and increased soil nitrogen availability interact with both long- and short-term differences in grazing intensity in shaping ecosystem carbon stocks and the processes underlying the changes. We used an over 50-year-old reindeer fence that separates a lightly grazed shrub-dominated tundra from a heavily grazed graminoid-dominated tundra, where the different grazing histories on the two sides of the fences have created different ecosystem states. In addition to the long-term grazing difference, we also established short-term grazer exclosures on the heavily grazed side of the fence to account for the effect of a sudden grazing cessation. This file includes data of ecosystem carbon stocks, soil properties, and fungal and bacterial copy numbers. It also provides data on development of the vegetation through the course of the experiment (2010-2014) and presents the activities of six extracellular enzymes measured on three occasions in 2013.

opencc-zeroOct 2019View details →

dryad32/100

Soil organic carbon in drylands: shrub encroachment and vegetation management effects dwarf those of livestock grazing

Dryland ecosystems occur worldwide and play a prominent, but potentially shifting, role in global biogeochemical cycling. Widespread woody plant proliferation, often associated with declines in palatable grasses, has jeopardized livestock production in drylands and prompted attempts to reduce woody cover by chemical or mechanical means. Woody encroachment also has the potential to significantly alter terrestrial carbon storage. However, little is known of the long-term biogeochemical consequences of woody encroachment in the broader context of its interaction with common dryland land uses, including "brush management" (woody plant clearing) and livestock grazing. Present assessments exhibit considerable variation in the consequences of these land use/land cover changes, with evidence that brush management may counteract sizeable impacts of shrub encroachment on soil biogeochemical pools. A challenge to assessing the net effects of brush management in shrub-encroached grasslands on soil organic carbon (SOC) and total nitrogen (N) pools is that land management practices are typically considered in isolation, when they are co-occurring phenomena. Furthermore, few studies have assessed spatial patterns in brush management and how these are affected in decades following treatment on sites with contrasting grazing histories. To address these uncertainties and interactions, we quantified the impacts of shrub encroachment and their subsequent mortality resulting from brush management (herbicide application) on SOC and N pools in a Sonoran Desert grassland where long-term grazing manipulations (>100 y) co-occur with shrub encroachment and brush management. Pools of SOC and N associated with herbicided shrubs declined markedly over ~40 years, offsetting 66% of the increases from shrub encroachment. However, spatial patterns in SOC induced by shrubs persisted over the decades following brush management. Century-long protection from grazing did little to change SOC and N pools. Accordingly, shrub encroachment and shrub mortality from brush management each far outweighed livestock grazing impacts. Consideration of the patterns of SOC and N through space (e.g., bole-to-dripline gradients), time (e.g., shrub age/size), land use (e.g., livestock grazing and brush management) and their interactions will position us to improve predictions of SOC and N responses to land use/land cover change, inform C-based management decisions, and objectively evaluate trade-offs with other ecosystem services.

opencc-zeroApr 2020View details →

dryad32/100

Data from: Plant species richness promotes soil carbon and nitrogen stocks in grasslands without legumes

1. The storage of carbon (C) and nitrogen (N) in soil are important ecosystem functions. Grassland biodiversity experiments have shown a positive effect of plant diversity on soil C and N storage. However, these experiments all included legumes, which constitute an important N input through N2-fixation. Indeed, the results of these experiments suggest that N2-fixation by legumes is a major driver of soil C and N storage. 2. We studied whether plant diversity affects soil C and N storage in the absence of legumes. In an 11-years grassland biodiversity experiment without legumes, we measured soil C and N stocks. We further determined above-ground biomass productivity, standing root biomass, soil organic matter decomposition and N mineralization rates to understand the mechanisms underlying the change in soil C and N stocks in relation to plant diversity and their feedbacks to plant productivity. 3. We found that soil C and N stocks increased by 18 and 16% in eight-species mixtures compared to the average of monocultures of the same species, respectively. Increased soil C and N stocks were mainly driven by increased C input and N retention, resulting from enhanced plant productivity, which surpassed enhanced C loss from decomposition. Importantly, higher soil C and N stocks were associated with enhanced soil N mineralization rates, which can explain the strengthening of the positive diversity-productivity relationship observed in the last years of the experiment. 4. Synthesis: We demonstrated that also in the absence of legumes plant species richness promotes soil carbon (C) and nitrogen (N) stocks via increased plant productivity. In turn, enhanced soil C and N stocks showed a positive feedback to plant productivity via enhanced N mineralization, which could further accelerate soil C and N storage in the long term.

opencc-zeroDec 2013View details →

dryad32/100

Data from: Plant economic strategies of grassland species control soil carbon dynamics through rhizodeposition

1. The plant economics spectrum is increasingly recognized as a major determinant of plant species effects on terrestrial ecosystem functioning related to carbon cycling. However, the role of plant economic strategies in the effects of living root activity on soil organic carbon (SOC) dynamics through rhizodeposition remains unexplored, despite SOC being the largest terrestrial carbon pool. 2. Using a continuous 13C-labeling method allowing partitioning of plant and soil sources to carbon fluxes and pools, we studied here the linkages between plant economic strategies and SOC cycling processes in a 'common garden' greenhouse experiment. It includes a panel of 12 grassland species selected along a gradient of economic traits and belonging to three functionnal groups (C3 grasses, forbs and legumes). 3. All species induced an acceleration of native SOC mineralization but this rhizosphere priming effect (RPE) substantially differed across species and varied eleven-fold by the end of the experiment (from +26 to +295 % relative to unplanted soil). Interspecific variation in RPE was primarily linked to plant photosynthetic activity associated to species economic strategies of light and CO2 resource acquisition and processing. Fast-growing acquisitive species, such as legumes, featured large RPE, in relation with their high canopy photosynthesis coupled to high leaf photosynthetic capacity and large net primary productivity allocated aboveground. This large RPE was further associated with high root metabolic activity, rhizodeposition and soil microbial activity. In contrast, fine-root growth and economic traits related to soil resource foraging ability were poor predictors of RPE. 4. The formation of new root-derived SOC varied nine-fold across species and was similarly positively related to the net primary productivity allocated aboveground. Fast-growing acquisitive species with a high photosynthetic activity induced a disproportionately large RPE relative to SOC formation. 5. Synthesis. Overall, our study demonstrates that rhizodeposition is a major mechanism through which plant economic strategies of grassland species control soil carbon dynamics. Acquisitive versus conservative species were associated with high versus low rates of photosynthesis and rhizodeposition, in turn leading to fast versus slow SOC turnover. This emphasizes the importance of considering rhizosphere processes for understanding plant species effects on soil biogeochemistry.

opencc-zeroNov 2019View details →

dryad32/100

Data from: Intensive forest harvesting increases susceptibility of northern forest soils to carbon, nitrogen and phosphorus loss

1. Understanding the impact of forest harvesting is critical to sustainable forest management, yet there remains much uncertainty regarding how harvesting affects soil carbon (C), nitrogen (N) and phosphorus (P) dynamics. 2. Here we conducted a global meta-analysis of 808 observations from 49 studies to test the effects of harvesting on the stocks and concentrations of soil C, N, and P and C:N:P ratios relative to uncut control stands. 3. With all harvesting intensities combined, C stock was unaffected by harvesting in either the forest floor or mineral soil, while harvesting reduced forest floor [C], [N], and [P] and C:N ratio, increased the mineral soil [C] and C:N ratio, but reduced mineral soil N stock,. The impacts of harvesting on forest floor C and N stocks, C:P and N:P and mineral soil [C] and [N] changed from no effects by partial, stem-only and whole-tree harvesting to significantly negative effects by the harvesting coupled with fire. Stem-only and whole-tree harvesting similarly reduced forest floor [P]. The negative effects of harvesting were most pronounced in conifer stands. Soil [C], [N] and C:N decreased with time since harvesting, but soil [P] did not, resulting in an increase in forest floor N:P. 4. Synthesis and applications. Our findings highlight the importance of harvest intensity and rotation length on long-term soil nutrient availability when managing forests. Furthermore, the lag in [P] recovery following harvesting may indicate a decoupling of the P cycle from that of C and N and a potential concern in managed forests.

opencc-zeroDec 2016View details →

dryad32/100

Data from: Soil carbon, nitrogen and phosphorus stoichiometry (C:N:P) in relation to conifer species productivity and nutrition across British Columbia perhumid rainforests

Temperate rainforest soils of the Pacific Northwest are often carbon (C) rich and encompass a wide range in fertility reflecting varying nitrogen (N) and phosphorus (P) availability. Soil resource stoichiometry (C:N:P) may provide an effective measure of site nutrient status and help refine species-dependent patterns in forest productivity across edaphic gradients. We described the nature of soil organic matter for mineral soil and forest floor substrates across very wet (perhumid) rainforest sites of southwestern Vancouver Island (Canada), and employed soil element ratios as covariates in a long-term planting density trial to test their utility in defining basal area growth response of four conifer species. There were strong positive correlations in mineral soil C, N and organic P (Po) concentrations, and close alignment in C:N and C:Po both among and between substrates. Stand basal area after five decades was best reflected by soil C:N but included a significant species-soil interaction. The conifers with ectomycorrhizal fungi had diverging growth responses displaying either competitive (Picea sitchensis) or stress-tolerant (Tsuga heterophylla, Pseudotsuga menziesii) attributes, in contrast to a more generalist response by an arbuscular mycorrhizal tree (Thuja plicata). Despite the consistent patterns in organic matter quality we found no evidence via foliar nutrition for increased P availability with declining element ratios as we did for N. The often high C:Po ratios (as much as 3000) of these soils may reflect a stronger immobilization sink for P than N, which, along with ongoing sorption of PO4-, could limit the utility of C:Po or N:Po to adequately reflect P supply. The dynamics and availability of soil P to trees, particularly as Po, deserves greater attention as many perhumid rainforests were co-limited by N and P, or, in some stands, possibly P alone.

opencc-zeroOct 2019View details →

zenodo32/100

Abrupt loss of soil organic carbon following disturbance in seagrass ecosystems

<h1>Code for running the bifurcation diagrams and the sensitivity analysis of seagrass-soil model</h1>   Contact: antoine.levilain18@gmail.com   This repository contains the code used to conduct the figures of: Abrupt loss of soil organic carbon following disturbance in seagrass ecosystems. Each figure from the related study has its own folder, which includes the necessary scripts to rerun simulations, the output of those simulations, and the code to plot the results. By navigating to any figure’s folder, you can reproduce the simulations and visualise the results. The repository is organised to facilitate reproducibility and further exploration of the ecosystem model and its behavior under various scenarios. We performed our analysis using R version 3.6.3. Do not forget to add your working directory if you want to save the figures.   <h2>Sensitivity analysis (Figure 5, Figure S11, Figure S15 & Figure S16)</h2> The “sensitivity” folder contains subfolders with the scripts required to run the global sensitivity analysis using the Sobol method for each scenario/case, along with the resulting outputs. In this analysis, higher numbers in folder names indicate a more deteriorated meadow, meaning it’s closer to the point of collapse. The analysis was conducted across different scenarios for different cases: “f” denotes the feedback case, while “no_f” represents the no feedback case. To recreate the figures, you can plot the pie charts for each scenario/case by running the sensitivity_plot.R script after setting the working directory to the appropriate subfolder.

opencc-by-4.0Oct 2024View details →

zenodo32/100

Soil dissolved organic carbon (DOC) machine learning model code

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2024View details →

zenodo32/100

Supporting data for Relative increases in CH4 and CO2 emissions from wetlands under global warming dependent on soil carbon substrates

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2023View details →

zenodo32/100

Large grazers suppress a foundational plant and reduce soil carbon concentration in eastern US saltmarshes

Supporting data for the submitted manuscript currently titled "Large grazers suppress a foundational plant and reduce soil carbon in eastern US saltmarshes". "Observational data Spr.Fall 2017.xlsx" contains all data collected for eastern US grazing survey. "Cumberland experiment.xlsx" contains all data collected for grazing experiment on Cumberland Island, GA, USA. Each data workbook contains a metadata tab to help guide users.

opencc-by-4.0Oct 2023View details →

zenodo32/100

Drought may exacerbate dryland soil inorganic carbon loss under warming climate conditions

Data of the Q10 value and soil properties for the study entitled "Drought may exacerbate dryland soil inorganic carbon loss under warming climate conditions".

opencc-by-4.0Jul 2023View details →

zenodo32/100

Data for: Methodological choices in size and density fractionation of soil carbon reserves – A case study on wood fiber sludge amended soils

A myriad of methods is currently being applied in soil carbon research encompassing major variation in the basic principles and minor variation in details. The most proper method is dependent on the research question and soil type, wherefore a consensus will likely never be reached, and it is difficult to label any method inappropriate. Both the fundamental and the subtle choices in methodology affect the results, wherefore increasing the method-related understanding of soil, agricultural and environmental scientists is of utmost importance. In scientific literature, methods are often not thoroughly presented, let alone reasoned. With this data, we discuss methodological choices in soil carbon fractionation. In addition, our case study follows the effects of pulp mill sludge amendments on soil carbon in a Luvic Stagnosol and Dystric Arenosol. Organic materials are being applied to soil to increase productivity and soil carbon storage. Our results show the difficulties of accumulating carbon in the stable, mineral associated pool, when the carbon content is initially relatively high, and the sorption capacity of the mineral phase already largely occupied.

opencc-by-4.0Dec 2023View details →

zenodo32/100

Data for "Misestimation of forest soil carbon and nitrogen stocks due to rock fragments: A case study of large number samples in a boreal forest watershed ecosystem of northeast China"

Here are the data for "Misestimation of forest soil carbon and nitrogen stocks due to rock fragments: A case study of large number samples in a boreal forest watershed ecosystem of northeast China", using the format of"excel".

opencc-by-4.0Mar 2024View details →

zenodo32/100

Lithological controls on soil geochemistry regulate microbial carbon use efficiency and carbon storage

The data supporting the findings of the study titled "Lithological controls on soil geochemistry regulate microbial carbon use efficiency and carbon storage". lithology mediates the effects of soil aggregates and minerals on microbial carbon use efficiency and microbial necromass stability. Furthermore, despite high mineral abundance reduced microbial carbon use efficiency, it enhanced microbial necromass stabilization through organo-mineral associations.

opencc-by-4.0Mar 2024View details →

zenodo32/100

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

This is the data for results shown in the article accepted by Global Change Biology: Convergence in simulating global soil organic carbon by structurally different models after data assimilation

opencc-by-4.0Apr 2024View details →

zenodo32/100

Spatiotemporal prediction of soil organic carbon density (SOCD) for pan-Europe (2000-2022) in 3D+T

<h2>Sub-dataset: SOCD p025, 2020–2022</h2> <h2>Disclaimer</h2> This is the first release of pan-EU predictions of soil health indicators (the Soil Health Data Cube). Use for testing purposes only. A publication describing methods used has been submitted to PeerJ and is in review. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commision. Neither the European Union nor the granting authority can be held responsible for them. The data is provided "as is". AI4SoilHealth project consortium and its suppliers and licensors hereby disclaim all warranties of any kind, express or implied, including, without limitation, the warranties of merchantability, fitness for a particular purpose and non-infringement. Neither AI4SoilHealth project Consortium nor its suppliers and licensors, makes any warranty that the Website will be error free or that access thereto will be continuous or uninterrupted. You understand that you download from, or otherwise obtain content or services through, the Website at your own discretion and risk. <h2>Description</h2> This dataset covers pan-European areas, including Ukraine, the UK, and Turkey. This data cube could be used for applications such as soil property mapping and comprehensive soil health assessment across Europe. The dataset spans four depth ranges and multiple time periods, providing information for studies on soil organic carbon stock and dynamics. This dataset is part of the Spatiotemporal prediction of soil organic carbon density for Europe (2000-2022) in 3D+T dataset. Check the related identifiers section below to access other parts of the dataset. This data set includes: <ul> <li>Soil Organic Carbon Density (SOCD) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 SOCD maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in kg/m3 (scaled 10x). </li> <li>Organic carbon content based on dry combustion weight percentage (WPCT) (2000-2022, 4-year intervals): This data includes mean, p975, and p025 WPCT maps for four depth ranges (0-20cm, 20-50cm, 50-100cm, and 100-200cm) in percentage (scaled 10x). </li> </ul> <h3>Related identifiers</h3> <ul> <li>SOCD mean: <a href="https://doi.org/10.5281/zenodo.13754343">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13771721">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13771841">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13771911">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13771967">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13772054">2020-2022</a> </li> <li>SOCD p025: <a href="https://doi.org/10.5281/zenodo.13779539">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13774064">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13774089">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13774114">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13774167">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13774196">2020-2022</a> </li> <li>SOCD p975: <a href="https://doi.org/10.5281/zenodo.13778472">2000-2004</a> <a href="https://doi.org/10.5281/zenodo.13773396">2004-2008</a> <a href="https://doi.org/10.5281/zenodo.13773765">2008-2012</a> <a href="https://doi.org/10.5281/zenodo.13773828">2012-2016</a> <a href="https://doi.org/10.5281/zenodo.13773953">2016-2020</a> <a href="https://doi.org/10.5281/zenodo.13774003">2020-2022</a> </li> </ul> <h3>Data Details</h3> <ul> <li>Time period: 2000–2022, in 4-year intervals (last period covers 2020–2022).</li> <li>Type of data: Spatiotemporal soil organic carbon data cube, with depth ranges and weighted percentage data for soil carbon assessments.</li> <li>How the data was collected or derived: The data was derived using machine learning models.</li> <li>Statistical methods used: Quantile Random Forest</li> <li>Limitations or exclusions in the data: The dataset does not include data for Svalbard. </li> <li>Coordinate reference system: EPSG:3035</li> <li>Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)</li> <li>Spatial resolution: 30m</li> <li>Image size: 216,700P x 153,400L</li> <li>File format: Cloud Optimized Geotiff (COG) format.</li> </ul> <h3>Support</h3> If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: GitLab Issues (tbc) <h3>Name convention</h3> To ensure consistency and ease of use across and within the projects, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are: <ol> <li>generic variable name: oc = organic carbon</li> <li>variable procedure combination: iso.10694.1995.mg.cm3 = ISO method 10694:1995, with values in mg/cm3 for SOCD | iso.10694.1995.wpct = ISO method 10694:1995, with values in weighted percentage of organic carbon content.</li> <li>Position in the probability distribution/variable type: m = mean | p975 = percentile 97.5 | p025 = percentile 2.5</li> <li>Spatial support: 30m</li> <li>Depth reference: b0cm..20cm = depth range from 0 to 20cm</li> <li>Time reference begin time: 20000101 = 2000-01-01</li> <li>Time reference end time: 20041231 = 2004-12-31</li> <li>Bounding box: eu = pan-Europe</li> <li>EPSG code: epsg.3035</li> <li>Version code: v20240804 = version from 2024-08-04</li> </ol>

opencc-by-4.0Sep 2024View details →

ScienceDex guides

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record