Data comprise soil organic carbon (SOC) content from soil simulations in a small agricultural catchment (Sunjia) which is part of the Critical Zone Observatory (CZO) in southeast China (Jianxi province). The simulations were performed using the ECOSSE model (a pool-based carbon and nitrogen turnover model) and soil and climate input data were provided by the research farm at the soil science department of the Chinese Academy of Sciences. Simulations were conducted in 2018. Full details about this dataset can be found at https://doi.org/10.5285/f8955c65-0103-4a26-9078-f34ec6a28676

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

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