Indicator: Soil Carbon Potential

Indicator	Soil Carbon Potential
Description	Plot-level forecast of future soil carbon stocks under different land management scenarios (e.g., reduced or no-till, applying manure and cover crops). This forecast runs for 20 years.
Unit	Metric tons (total and per hectare)
Temporal Resolution	Projection into the future
Spatial Resolution	field-level model, 250m input data
Input Data	IRSIC SoilGrids v2: organic carbon stock, bulk density, texture
Method	The soil carbon potential is modelled by coupling baseline soil carbon data with anticipated changes due to various land management practices. The baseline is the current status of soil carbon modelled by TLG historical assessment. The CoolFarmTool is utilized to assess the impact of different farm management scenarios on future soil carbon stocks.
Confidence interval	Confidence intervals are derived from two main sources of uncertainty. First, SoilGrid data, which provides quantiles (05, 50, and 95), is not symmetrically distributed around the median or mean. To prevent negative standard deviation values, a log-normal distribution is assumed, leading to confidence intervals that are not perfectly symmetrical around the median. Second, uncertainty arises from land use, tillage, and management practices. The impact of these factors on soil carbon varies due to micro-environmental differences. For example, tillage may increase soil carbon by a factor of 0.02 in a specific climate and soil type, but the actual effect can range between 0.01 and 0.03.
Benchmarking	Benchmarks are created for each combination of climate zones and soil types, treating each combination as a separate group. Within each group, soil carbon levels are analyzed separately for croplands and grasslands. The poor benchmark is set at the lower 25th percentile of SoilGrid estimates, representing low carbon input conditions. The good benchmark is estimated using the CFT model under optimal management practices. The average benchmark is the midpoint between the poor and good values.