Implementation and calibration of the parameter-sparse Yield-SAFE model to predict production and land equivalent ratio in mixed tree and crop systems under two contrasting production situations in Europe

Abstract

Silvoarable agroforestry, the integration of trees and arable crops on the same area, has the potential to offer production, ecological, and societal benefits. However, the uptake of such systems in Europe has been limited by a combination of unsupportive policies and uncertainty concerning their productivity, profitability, and environmental impact. Faced with a lack of experimental data, the parameter-sparse Yield-SAFE model offers one method for generating plausible yield data and improving understanding of production in mixed tree–crop systems under European conditions. The applicability of the model was examined by: (i) selecting two contrasting sites in France and the UK with measured agricultural, silvoarable and/or forestry data, (ii) implementing the model in a software package, and (iii) inputting data and parameters on the climate, soils, management regime, and tree and crop types. Following calibration, Yield-SAFE provided credible descriptions of measured arable and tree (Populus spp.) yields in the monoculture and silvoarable systems at the two sites. An examination of the response of the model to changes in model parameters and environmental and management data showed that silvoarable crop yields were most sensitive to variations in tree parameters. Increased soil depths increased timber yields, and increasing stand density increased stand volume whilst decreasing individual tree volume. In all the simulations, the model predicted greater efficiency in use of land, i.e. greater land equivalent ratios, when trees and crops were combined rather than grown as sole crops. These results, supported by the sparse experimental data available, indicate that agroforestry provides a method of increasing food, timber and biomass production from limited land resources in Europ