Geospatial Analysis of Crop Production and Publicly-Funded Research Stations to Scale Carbon Markets

Agricultural carbon markets compensate farmers for the implementation of climate smart practices to increase soil organic carbon (SOC) sequestration in agricultural land. To incentivize farmers to enroll in carbon credit contracts, it is necessary to identify model farms with historical crop and land management data from which carbon markets can base their estimations of SOC sequestration. This research utilizes row crop production, SOC sequestration estimations, and Soil Conditioning Index (SCI) values to evaluate the potential for scaling measurement, reporting, and verification (MRV) efforts for carbon markets in Tennessee. Relationships between University of Tennessee Research and Education Centers (RECs) and cropland in surrounding regions across the state were analyzed by developing a geospatial model to relate SOC sequestration potential of fields on private agricultural land to fields at the RECs. The model was developed using ArcGIS Pro software and an iterative self-organizing clustering technique. Model inputs included factors that affect agricultural SOC sequestration: crop system type (corn, soybeans, and cotton), soil texture, average daily temperature, average daily precipitation, and elevation. Model outputs included clusters of geospatially-correlated regions determined by the model that covered the entire state. To determine the model with the best representation of the geospatially-correlated regions based on the input layers, the silhouette coefficient was calculated and compared for each model output. SOC sequestration estimates from COMET-Farm and Soil Conditioning Index values from the Field to Market Fieldprint Platform were also evaluated for current management and future sustainable management scenarios for each field. The comparisons of these scenarios were used to assess the application of the model results to relate SOC sequestration potential on private agricultural land to publicly-funded RECs in West Tennessee. Future work intends to expand this modeling approach to analyze effects of climate smart land management practices across the Southeastern United States. This work also seeks to encourage further utilization of publicly-funded RECs for use in developing standards for carbon market MRV, as well as other conservation efforts.