This project seeks to quantify the performance of the Maryland Winter Cover Crop Program (MWCCCP) from multiple criteria. First, we will estimate the amount of cover crop biomass on growers’ fields at two critical timings during winter: at the onset of dormancy and prior to termination. The dormancy-onset estimate serves as a surrogate for measuring soil N prevented from leaching into the Chesapeake Bay, which is the stated goal of the MWCCP. The at-termination estimate provides information about other ecosystem services that could potentially be provided by cover crops. These estimates will be generated from satellite imagery through our collaboration with the USGS and USDA-ARS Remote Sensing Laboratory.
Second, we will determine the association between agronomic factors of cover crop management and these biomass estimates. This association will be conducted by joining a database of enrollment in the MWCCP (provided by the Maryland Department of Agriculture) and our satellite imagery biomass estimates using geospatial analysis.
Third, we will test whether the incentive structure provided by the MWCCP provides a return-on-the-dollar commensurate with the performance of the cover crop. Additionally, we will test whether the incentives have increased adoption of management practices associated with improved performance over the lifetime of the program.
1) Connect existing datasets to develop a model that predicts cover crop biomass (as estimated from satellite imagery) based on agronomic management (as reported to the Maryland Department of Agriculture by farmers) as a function of thermal time (as calculated from historical weather data).
2) Given the model developed in Objective 1), determine how much the variability in cover crop biomass is due to each agronomic management category relative to landscape variables: soil texture, drainage class, and local topography.
3) Develop a return-on-investment index that scales cover crop biomass to the incentives paid to growers and evaluate each agronomic management category based on performance on this index.
The data will be collected from two primary sources:
- satellite imagery at field-scale resolution, used to calculate cover crop biomass estimates from NDVI for Talbot County and some adjoining parts of the Lower Choptank River watershed
- enrollment database of the Maryland Department of Agriculture, listing management practices and geospatial references for each farmer in the program
The enrollment data will be dimensionally reduced using partitioning-around-k-medoids to identify clusters of farms substantially similar management practices, such as species choice, tillage, and planting date.
The biomass data will be analysed by multiple linear regression, to predict performance from interactions of growing degree days and management clusters.
Education & Outreach Activities and Participation Summary
The only outreach conducted to date on this project has been a pair of talks at the Northeast Cover Crop Council’s Annual Meeting, held in Ithaca NY. Approximately 30 people attended the talks, a combination of growers, extension agents, and researchers. These talks presented the data available for the project, our plans for analysis, and initial findings.