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107 results for “carbon sequestration”
Comparing vertical accretion, organic carbon (C) sequestration, and nitrogen burial between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia.
Restoration of tidal marshes throughout the 20th century have attempted to bring back important functions of natural tidal systems. In this study, vertical accretion, organic carbon (C) sequestration, and nitrogen burial were compared between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia to examine the impacts of restoration years later. On Sapelo Island there are two marshes near the University of Georgia Marine Institute, one of which is a natural marsh, and one of which is a restored marsh. The restored marsh had been diked in 1948, and the dike was breached, allowing for the marsh to be restored, in 1956. Soil cores were collected from both marshes, and the sediments were analysed for Nitrogen and Carbon concentrations and bulk density. This analysis was used to determine accretion rates for the two marshes as well as changes in the restored marsh since the dike was breached. Nitrogen burial, carbon sequestration, and soil accretion in the restored marsh as compared to the natural marsh were the focus of this study.
Effects of Forest Fragmentation on Carbon Sequestration and Respiration at Harvard Forest since 2016
Forest loss/fragmentation can have profound impacts on the terrestrial carbon (C) cycle by reducing forest uptake of carbon dioxide (CO2; the primary driver of anthropogenic climate change) through photosynthesis and C storage in forest biomass. Relative to intact rural forests, trees growing in forest fragments within developed landscapes typically experience conditions that can enhance growth such as warmer and longer growing seasons (i.e. urban heat island effect) and greater light and nutrient availability (e.g., nitrogen deposition) as well as conditions that can hinder growth such as increased exposure to damaging pollutants such as ozone and higher rates of disturbance. Our research quantifies the impact of fragmentation on C uptake and respiration near forest edges. In 2016 six 600‐m2 plots were installed along forest edges at the HF, measuring 20 m along the forest edge and extending 30 m into the forest perpendicular to the forest edge. Plot biomass was mapped and tree cores were taken in all trees >10cm diameter. The plots were installed at multiple edge aspects and adjacent land cover types (three meadows, two pastures, and one road). Within each plot, a pair of polyvinyl chloride soil respiration collars 20 cm in diameter × 7 cm tall and located 10 m apart was inserted approximately 2 cm into the soil at four distances from the edge (0, 10, 20, and 30m). Each plot had n = 8 collars for a total of n = 48 collars. Following installation, collars were left in the soil for at least 2 weeks to equilibrate. Air temperature, relative humidity, soil temperature, and soil moisture were logged along the center plot transect.
Carbon Sequestration Capacity Groups
<p>Marginal Lands (MLs) as detected by MaiL Project were classified in Carbon Sequestration Capacity (CSC) Groups. The methodology based on multicriteria GIS analysis with data including tree species maps (Brus et al., 2011), land cover maps (Malinowski, et al., 2020) and Aboveground Biomass maps (Spawn, Sullivan, Lark, & Gibbs, 2020). The aim was to estimate potential suitable species for afforestation for each Marginal Land as well species’ Above Ground Biomass Carbon (AGBC) and proceed to classification into CSC groups.<br> In order to estimate CSC for MLs and classify in CSC groups, it is crucial to estimate potential suitable species for afforestation and their Aboveground Biomass Carbon. The MLs as calculated on Task 2.3 of MAIL project is the basemap, where the most frequent species from neighbor forested areas, both dominant 1 and 2 species, and species’ Aboveground Biomass Carbon values are assigned. Dominant 1 and 2 species of neighbor forested areas are adapted to the ecological and climatological conditions and therefore are considered to be the most suitable for afforestation projects. Through classification into CSC groups, we get a better understanding regarding the relative interconnections between groups and each one's potential trend.The frequency distribution of the formula’s results is presented in a histogram. Classification into CSC groups was done by manually defining classes ranges, in such a way so each class to cover approximately the same area across Europe, with the exception of higher and lower sequestration groups, Group A and Group E respectively. Group A represents higher sequestration MLs, covering 5% of Europe’s total MLs and on the other side Group E represents lower sequestration MLs covering 31% of Europe’s MLs.</p>
Knowledge gaps on trade-offs of soil carbon sequestration related to soil management strategies
<p>The database contains 87 unique literature items (29 reviews, 42 meta-analyses, 16 original papers) describing the effect of a soil management strategy (tillage management, cropping systems, water management, cover crops, crop residues, livestock manure, slurry, compost, biochar, liming) on the trade-offs between soil carbon sequestration or SOC change and N2O emission, CH4 emission and nitrogen leaching. Since some literature items describe effects of several SMS categories, the database_summary tab comprises a total of 112 unique inputs. For each input it is indicated in the Database_summary tab if it was used as input for the "Soil management effect assessment" in Maenhout et al. (2024) [Maenhout, P., Di Bene, C., Cayuela, M. L., Diaz-Pines, E., Govednik, A., Keuper, F., Mavsar, S., Mihelic, R., O'Toole, A., Schwarzmann, A., Suhadolc, M., Syp, A., & Valkama, E. (2024). Trade-offs and synergies of soil carbon sequestration: Addressing knowledge gaps related to soil management strategies. European Journal of Soil Science, 75(3), e13515. https://doi.org/10.1111/ejss.13515] and/or to define knowledge gaps ("Knowledge gap in tab"-column). Knowledge gaps and research recommendations are gouped per soil management strategy in different tabs in this database. Per soil management strategy, knowledge gaps are clustered per theme in groups. These themes include: the specific soil management strategy, pedoclimatic conditions, establishment of experiments, other soil management strategies, meta-analysis, modelling and other</p>
Carbon sequestration in riparian forests: a global meta-analysis data set
<p>Data collected for a global meta-analysis of riparian forest biomass and soil carbon stocks. Includes studies estimating the carbon stored in the soil or standing live and dead woody vegetation, or the total biomass of woody vegetation in plots described as "riparian" or "floodplain". Also includes soil carbon metrics for plots considered to be "baseline" plots paired with a riparian plot. Excludes studies focused solely on depressional or tidal wetlands, plots lacking woody vegetation, greenhouse experiments, or those that measured only the biomass or carbon content of individual plants.</p> <p>The data file includes DOIs for all studies included (where available), study area coordinates, descriptions of study plots, vegetation age and soil texture (if known), reported values for woody biomass, biomass carbon stock, soil bulk density, soil carbon concentration, soil carbon stock, and/or soil sampling depth. All field descriptions are provided in the accompanying metadata file.</p>
Unpublished data: Quantifying CO2 Emissions and Carbon Sequestration from Digestate-Amended Soil Using Natural 13C Abundance as a Tracer
<p>Unprocessed data of CO2 evolution measured daily on cavity ring-down spectroscopy analyser (G2201-i CRDS isotopic CO2/CH4 analyser, Picarro, Santa Clara, CA, USA).</p>
scmcclelland/joint-mediation-study: Data, Analysis, and Figure Scripts for "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application"
<p>This repository contains data, analysis, and figure scripts to create findings from the manuscript "Soil organic carbon sequestration jointly-mediated by plants and microbes after compost application" currently under minor revisions.</p> <p>This release includes updated code, primarily improvements to figures, and a new script for a supplementary map figure.</p>
Data used in manuscript Carbon sequestration potential of street tree plantings in Helsinki
<p>Data and model runs used in manuscript "Carbon sequestration potential of street tree plantings in Helsinki". This data set includes model runs for the Surface Urban Energy and Water balance Scheme (SUEWS) and soil carbon model Yasso.</p> <p><br> The data files are:</p> <p><strong>Met_Gapfilling</strong></p> <ul> <li>ConvertMeteorologyInput.m (MATLAB) is the main file and functions gapfilling.m (with other measurements) and gapfillingfill.m (with interpolations) are used in the gap filling</li> <li>Includes files for meteorological measurement data <ul> <li>Airport: Data from Helsinki-Vantaa airport; airportdata.m, where data is cleaned</li> <li>Precipitation: Data from multiple locations; Pres_Gap.m for gap filling precipitation and function PrecipitationGap.m</li> <li>Roof: Data from rooftop</li> <li>SMEARIII: Monthly meteorological data from Kumpula (2003-2016)</li> </ul> </li> <li>SUEWS_met file for the final gap filled meteorological files for SUEWS </li> </ul> <p><strong>Fits</strong></p> <ul> <li>Includes FitCO2_parameter.m for fitting CO2 parameters for SUEWS</li> <li>Includes functions Pho6.m and Resp0.m that have the function forms</li> <li>Includes data files for measurement data <ul> <li>CO2Data: Canopy photosynthesis and canopy respiration estimated with SPP model (KumpulaX.out for Tilia site and Kumpula2X.out for Alnus site)</li> <li>Met_2016: Meteorology from Kumpula for June to August in 2016</li> <li>SWCdata: Soil water content from two streets and three soil types</li> </ul> </li> </ul> <p><strong>ModelRuns</strong></p> <ul> <li>SUEWS model runs separately for Alnus and Tilia sites <ul> <li>Includes input and output files and model codes</li> <li>Alnus site includes both the Baserun and Finalrun</li> </ul> </li> <li>Yasso model runs <ul> <li>Model run in file yasso.f90</li> <li>Output files: DecRate...txt includes three soil types and values for each month from 2002 to 2016</li> <li>Yasso_meteorology_month.m creates meteorological input files for Yasso (Clim_month_xx.txt) using meteorology from SUEWS</li> <li>Lifetimerun: 30 year simulations that includes estimations for leaves and pruned branches</li> </ul> </li> </ul> <p><strong>FigCodes</strong></p> <ul> <li>Includes MATLAB codes for figures and statistics</li> <li>Includes measurement data for CO2, sap flow and SWC</li> </ul> <p> </p>
Realistic soil carbon sequestration considering food security and climate change
<p>This dataset contains soil organic carbon stocks as described in Keel et al. Global Change Biology (submitted)</p> <p>Annual soil organic carbon (SOC) stocks (t C ha-1, 0-30 cm depth) of Swiss agricultural soils simulated with the model RothC for the years 2020-2100. Simulations were performed for 240 strata (regions with similar agricultural production types, climatic conditions and clay content). The SOC stocks are weighted averages across strata for the national scale. <br> Each column contains SOC stocks for a specific combination of a climate model chains (nine in total) and an emission scenario (three in total: RCP 26, RCP 45, RCP 85) (specified in column header). </p> <p>The results include simulated SOC stocks for a baseline scenario and five soil carbon sequestration (SCS) scenarios (cover crops, biochar amendment at two rates, biochar amendment based on biomass from two agroforestry scenarios). <br> The SCS scenarios were only performed on cropland, therefore there is only a single file for grassland (the baseline scenario). <br> All simulations (i.e. baseline as well as the five scenarios) account for changes in crop shares and organic matter additions associated with growing food demand as well as climate change. </p> <p>The scenarios are described in Keel et al. Global Change Biology (submitted)</p> <p>CL_baseline: Baseline scenario for cropland (CL) <br> GL_baseline: Baseline scenario for permanent grassland (GL)<br> CL_cover_crops: Cover crop scenario for cropland <br> CL_biochar_I: Biochar I scenario for cropland <br> CL_biochar_II: Biochar II scenario for cropland <br> CL_agroforestry_I: Agroforestry I scenario for cropland <br> CL_agroforestry_II: Agroforestry II scenario for cropland </p>
Climate-driven shifts in kelp forest composition reduce carbon sequestration potential
<p>The potential contribution of kelp forests to blue carbon sinks is currently of great interest but interspecific variance has received no attention. In the temperate Northeast Atlantic, kelp forest composition is changing due to climate-driven poleward range shifts of cold temperate <em>Laminaria</em> <em>digitata</em> and <em>L</em>. <em>hyperborea</em> and warm temperate <em>L</em>. <em>ochroleuca</em>. To understand how this might affect the carbon sequestration potential of this ecosystem, we quantified interspecific differences in carbon export and decomposition alongside changes in detrital photosynthesis and biochemistry. We found that while warm temperate kelp exports up to 71% more carbon per plant, it decomposes up to 155% faster than its boreal congeners. Elemental stoichiometry and polyphenolic content cannot fully explain faster carbon turnover, which may be attributable to contrasting tissue toughness or unknown biochemical and structural defences. Faster decomposition causes the detrital photosynthetic apparatus of <em>L</em>. <em>ochroleuca</em> to be overwhelmed 20 d after export and lose integrity after 36 d, while detritus of cold temperate species maintains carbon assimilation. Depending on the photoenvironment, detrital photosynthesis could further exacerbate interspecific differences in decomposition via a potential positive feedback loop. Through compositional change such as the predicted prevalence of <em>L</em>. <em>ochroleuca</em>, ocean warming may therefore reduce the carbon sequestration potential of such temperate marine forests.</p>
Data from: Sedimentary organic carbon and nitrogen sequestration across a vertical gradient on a temperate wetland seascape including salt marshes, seagrass meadows and rhizophytic macroalgae beds
<p>Dataset </p> <p> </p> <p>Coastal wetlands are key in regulating coastal carbon and nitrogen dynamics and contribute significantly to climate change mitigation and anthropogenic nutrient reduction. We investigated organic carbon (OC) and total nitrogen (TN) stocks and burial rates at four adjacent vegetated coastal habitats across the seascape elevation gradient of Cádiz Bay (South Spain), including one species of salt marsh, two of seagrasses, and a macroalgae. OC and TN stocks in the upper 1 m sediment layer were higher at the subtidal seagrass <em>Cymodocea nodosa</em> (72.3 Mg OC ha<sup>-1</sup>, 8.6 Mg TN ha<sup>-1</sup>) followed by the upper intertidal salt marsh <em>Sporobolus maritimus</em> (66.5 Mg OC ha<sup>-1</sup>, 5.9 Mg TN ha<sup>-1</sup>), the subtidal rhizophytic macroalgae <em>Caulerpa prolifera</em> (62.2 Mg OC ha<sup>-1</sup>, 7.2 Mg TN ha<sup>-1</sup>), and the lower intertidal seagrass <em>Zostera noltei</em> (52.8 Mg OC ha<sup>-1</sup>, 5.2 Mg TN ha<sup>-1</sup>). The sedimentation rates increased from lower to higher elevation, from the intertidal salt marsh (0.24 g cm<sup>-2</sup> yr<sup>-1</sup>) to the subtidal macroalgae (0.12 g cm<sup>-2</sup> yr<sup>-1</sup>). The organic carbon burial rate was highest at the intertidal salt marsh<em> </em>(91 ± 31 g OC m<sup>-2</sup> yr<sup>-1</sup>), followed by the intertidal seagrass, (44 ± 15 g OC m<sup>-2</sup> yr<sup>-1</sup>), the subtidal seagrass (39 ± 6 g OC m<sup>-2</sup> yr<sup>-1</sup>), and the subtidal macroalgae (28 ± 4 g OC m<sup>-2</sup> yr<sup>-1</sup>). Total nitrogen burial rates were similar among the three lower vegetation types, ranging from 5 ± 2 to 3 ± 1 g TN m<sup>-2</sup> yr<sup>-1</sup>, and peaked at <em>S. maritimus </em>salt marsh with 7 ± 1 g TN m<sup>-2</sup> yr<sup>-1</sup>. The contribution of allochthonous sources to the sedimentary organic matter also decreased with elevation, from 72% in <em>C. prolifera</em> to 33% at <em>S. maritimus</em>. Our results highlight the need of using habitat-specific OC and TN stocks and burial rates to improve our ability to predict OC and TN sequestration capacity of vegetated coastal habitats at the seascape level. We also demonstrated that the stocks and burial rates in <em>C. prolifera </em>habitats were within the range of well-accepted blue carbon ecosystems such as seagrass meadows and salt marshes.</p>
Carbon sequestration potential in hedgerow soils: Results from 23 sites in Germany
<p>Dataset to the manuscript: Drexler, S. & Don, A. (2024). Carbon sequestration potential in hedgerow soils: Results from 23 sites in Germany. Geoderma. <a href="https://doi.org/10.1016/j.geoderma.2024.116878">https://doi.org/10.1016/j.geoderma.2024.116878</a></p> <ul> <li>Drexler_Don_2024_Data: contains the lab data for all samples</li> <li>Drexler_Don_2024_SOC_Stock_Per_Core: contains the calculated SOC stocks per soil core</li> </ul>
Imputation of missing land carbon sequestration data in the AR6 Scenarios Database
<p>This repository is linked to the following research paper:</p> <ul> <li>Prütz, R., Fuss, S., and Rogelj, J.: Imputation of missing land carbon sequestration data in the AR6 Scenarios Database, Earth Syst. Sci. Data, 2025. <a href="https://doi.org/10.5194/essd-17-221-2025">https://doi.org/10.5194/essd-17-221-2025</a> </li> </ul> <p>This repository includes: </p> <ul> <li>An imputation dataset for missing land carbon sequestation data of the AR6 Scenarios Database for global scenarios and R10 scenario variants</li> <li>Code to test, compare and visualize the performance of regression models to predict missing land removal data</li> <li>Code to compare and visualize available AR6 land removal data and existing AR6 data reanalyses</li> </ul> <p>The following two datasets are required to replicate the analysis:</p> <ul> <li>Byers, E., Krey, V., Kriegler, E., Riahi, K., Schaeffer, R., Kikstra, J., Lamboll, R., Nicholls, Z., Sandstad, M., Smith, C., van der Wijst, K., Al -Khourdajie, A., Lecocq, F., Portugal-Pereira, J., Saheb, Y., Stromman, A., Winkler, H., Auer, C., Brutschin, E., … van Vuuren, D. (2022). AR6 Scenarios Database [Data set]. In Climate Change 2022: Mitigation of Climate Change (1.1). Intergovernmental Panel on Climate Change. <a href="https://doi.org/10.5281/zenodo.7197970">https://doi.org/10.5281/zenodo.7197970</a></li> <li>Gidden, M., Gasser, T., Grassi, G., Forsell, N., Janssens, I., Lamb, W. F., Minx, J., Nicholls, Z., Steinhauser, J., & Riahi, K. (2023). Dataset for Gidden et.al. 2023 Updated AR6 Mitigation Benchmarks using National Emissions Inventories (Version v2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.10158920">https://doi.org/10.5281/zenodo.10158920</a></li> </ul> <p>The variable imputation is based on the dataset by Byers et al. (2022). The dataset by Gidden et al. (2023) is used for variable comparison. </p>
Supporting Information for "Deep-Sea Carbonate Carbon Sequestration in the Pacific Ocean since the Early Cenozoic"
<p>This collection of files is supplementary to:</p> <p>Dalvand, F., Dutkiewicz, A., Wright, N.M., Mather, B.R. and Müller, R.D., Deep-Sea Carbonate Carbon Sequestration in the Pacific Ocean since the Early Cenozoic.</p> <p>The archive contains: <br>2 folders of data files: “Backtracked_sites” and “Regional_Cenozoic_carbonate_thickness_grids”<br>1 excel workbook: Table_S1_model_data_summary_for_six_regions_of_the_Pacific.xlsx <br>1 animation: “Movie_S1_compacted_carbonate_thickness_map_of_the_pacific.mp4”</p> <p>“Backtracked_sites” folder</p> <p>This folder has 6 subfolders containing pyBacktrack output files, each corresponding to a single DSDP, ODP or IODP drill site from one of six regions of the Pacific. </p> <p>Files named “Site*_age_depth_waterdepth.txt” contain data on age (Ma), compacted_depth (m), compacted_thickness (m), decompacted_thickness (m), decompacted_density (g/cm^3), water_depth (m), tectonic_subsidence (m), decompacted_depth (m), dynamic_topography (m) and lithology.</p> <p>Files named “Site*_depth_age_waterdepth_dens_DLSR_carb_CAR_filter_width_1my_step_0.5my.txt” contain data on age, depth, paleowater depth, dry bulk density, decompacted linear sedimentation rate (DSLR), carbonate content, and carbonate accumulation rate (CAR).</p> <p>“Regional_Cenozoic_carbonate_thickness_grids” folder</p> <p>This folder has 6 subfolders, each containing NetCDF files of modeled Cenozoic carbonate thicknesses for a different region of the Pacific from 55 Ma to 0 Ma in 1 Myr intervals. The workflow for generating these grids can be found on GitHub at https://github.com/EarthByte/CarbonateSedimentThickness</p> <p>"Table_S1_model_data_summary.xlsx"<br> <br>This workbook contains computed decompacted carbonate sediment volume, decompacted carbonate sediment thickness, carbonate carbon flux, carbonate carbon mass and carbonate compensation depth (CCD) for six regions of the Pacific spanning 55 Ma to 0 Ma in 1 Myr intervals.</p> <p>"Movie_S1_compacted_carb_thick_Pacific_55-0Ma.mp4" </p> <p>This file shows the Cenozoic evolution of the carbonate sediment thickness in the Pacific from 55 Ma to 0 Ma in 1 Myr intervals.</p> <p><br>Reference:</p> <p>Müller, R. D., Cannon, J., Williams, S. and Dutkiewicz, A., 2018, PyBacktrack 1.0: A Tool for Reconstructing Paleobathymetry on Oceanic and Continental Crust, Geochemistry, Geophysics, Geosystems, 19, 1898-1909, https://doi.org/10.1029/2017GC007313.</p>
Data set: Forest management to increase carbon sequestration in boreal Pinus sylvestris forests
<p>Data supporting the results and analyses published in Plant and Soil, "Forest management to increase carbon sequestration in boreal <em>Pinus sylvestris </em>forests".</p> <p>Data from a long-term fertilization (N and N+P) and thinning experiment in <em>Pinus sylvestris </em>stands across Sweden (56–67°N). Carbon stocks in soil and trees, tree growth, soil respiration and soil available nitrogen (ammonium, nitrate) are included.</p> <p>Data (data file + meta data file) include:</p> <p>jorgensen_etal_plantsoil_treesoil_data.csv (site data, carbon stocks: trees and their separate parts and soil, soil available nitrogen)</p> <p>jorgensen_etal_plantsoil_treesoil_data_METADATA.csv</p> <p>jorgensen_etal_plantsoil_resp_data.csv (site data, soil respiration, temperature, moisture)</p> <p>jorgensen_etal_plantsoil_resp_data_METADATA.csv</p> <p>R-script:</p> <p>Jorgensen_etal_plantsoil.R</p>
Climate-driven shifts in kelp forest composition reduce carbon sequestration potential
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Hidden comet-tails of marine snow impede ocean-based carbon sequestration
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Data from: Establishing rates of carbon sequestration in mangroves from an earthquake uplift event
We assessed the carbon stocks (CS) in mangroves that developed after a Magnitude 7.1 earthquake in Silonay, Oriental Mindoro, south Luzon, Philippines in November 1994. The earthquake resulted in a 50 cm uplift of sediment that provided new habitat within the upper intertidal zone which mangroves colonized (from < 2 ha pre-earthquake to the current 45 ha, 23 yrs post-earthquake). The site provided opportunity for a novel assessment of the rate of carbon sequestration in recently established mangroves. The CS were measured in above-ground, below-ground and sediment compartments over a seaward to landward transect. Results showed mean CS of 549 ± 30 Mg C/ha (of which 13% was from the above-ground biomass, 5% from the below-ground biomass, and 82% from the sediments). There was high carbon sequestration at 40-cm depth that can be inferred attributable to the developed mangroves. The calculated rate of C sequestration (over 23 years post-earthquake) was 10.2 ± 0.7 Mg C/ha/yr and is comparable to rates reported from mangroves recovering from forest clearing. The rates we present here from newly developed mangroves contributes to calibrating estimates of total CS from restored mangroves (of different developmental stages) and in mangroves that are affected by disturbances.
Carbon action MULTA Finnish carbon sequestration experimental field dataset 2023
<p>This dataset includes the fifth and final year observations of the Finnish Carbon Action carbon sequestration experiment. In the experiment c.a. 100 farms test carbon farming methods on a test field and an adjacent control plot. Of these 20 farms were chosen for continued sampling 2019-2023 combining field observations and soil sampling. This data will be coupled with satellite imagery, field sensors and carbon cycle modeling to forecast carbon sequestration. Subsequent sampling will track changes in soil carbon stock and soil health.</p> <p>This dataset is an update of the final monitoring year and includes summaries of the previous year measurements. The full measurements for previous years can be found in: https://zenodo.org/communities/carbonaction/ .</p> <p>The 2023 update includes data on:</p> <ul> <li>physical quality: soil structure (VESS), bulk density, porosity, water holding capacity, infiltration rate</li> <li>biological properties: earthworm counts, above ground biomass, plant cover (%), chlorophyll, microbial activity, root biomass</li> <li>chemical properties: soil nutrients, change in nutrient pools over time</li> </ul> <p> </p>
Carbon action MULTA Finnish carbon sequestration experimental field dataset 2021
<p>This dataset includes the third year observations of the Finnish Carbon Action carbon sequestration experiment. In the experiment c.a. 100 farms test carbon farming methods on a test field and an adjacent control plot. Of these 20 farms were chosen for continued sampling 2020-2024 combining field observations and soil sampling. This data will be coupled with satellite imagery, field sensors and carbon cycle modeling to forecast carbon sequestration. Subsequent sampling will track changes in soil carbon stock and soil productivity.</p> <p>The dataset will be updated annually, updates are published as separate datasets in https://zenodo.org/communities/carbonaction/ . The 2021 update includes data on:</p> <ul> <li>physical quality: soil structure (VESS), bulk density, porosity, water holding capacity, infiltration rate, aggregate stability</li> <li>biological properties: earthworm counts, above ground biomass, plant cover (%), chorophyll, microbial activity Solvita CO2 burst</li> <li>chemical properties: change in soil nutrients 2019 to 2021, change in OM </li> </ul> <p>This updated version includes the change in soil nutrients and updated soil infiltration rates as the soil texture was determined more accurately. In addition the biomass calculation was updated to include the row spacing of certain crops (12,5 cm). </p>
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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.