The provided data presents a list of greenhouse gas removal practices for soil organic carbon sequestration, which are suitable under biophysical, economic and social consideration. The list is the result of the first step in analysing the potential of agricultural soils to sequester carbon globally and is part of the NERC funded project Soils-R-GGREAT (NE/P019455/1). The work is based on literature research and expert panel and judgements. The work was supported by the Natural Environment Research Council (NE/P019455/1) Full details about this dataset can be found at https://doi.org/10.5285/e0acc105-e13e-4c1f-b275-f7518b823aad

Global spatial data on yields of wheat, sugarcane and maize at 0.25 and 0.5 degrees resolution for 2000-2014. Annual data on wheat, sugarcane and maize yield have been extracted from agricultural statistics, which are recorded annually at regional and national scale depending on the country. The yield data were spatially disaggregated to produce gridded maps (0.25 and 0.5 degrees spatial resolution) of yields per crop type. The earthstat dataset, which provides gridded data on crop distribution (i.e. a crop mask for 2000q), was used to obtain information on the spatial distribution of wheat, sugarcane and maize across the world. The spatial disaggregation process was repeated for every year between 2000 and 2014. The data were produced to constrain agro-ecosystem carbon cycling estimates used in large-scale atmospheric CO2 inversion studies and to be used as inputs in agro-ecosystem biogeochemistry models. The data are provided in netcdf4 (.nc) format. Full details about this dataset can be found at https://doi.org/10.5285/3fa5921b-244a-4944-ab90-e690dbc05a7e

The data set shows the modelled change of soil organic carbon under different managements in agriculture for different climate scenarios globally. Dataset includes the change to a business as usual scenario for different soil managements for each decade from 2030 to 2100. The work was supported by the Natural Environment Research Council (NE/P019455/1) Full details about this dataset can be found at https://doi.org/10.5285/fbb03aba-ad1c-438a-a3b3-2a99bc1baaf8