Data, code and software to reproduce the article entitled "Modelling intercrops functioning to advance the design of innovative agroecological systems"

This is the data, code and software to reproduce the article entitled "Modelling intercropping functioning to support sustainable agriculture". Here is a summary of the paper:

The growing demand for sustainable agriculture is raising interest in intercropping for its multiple potential benefits, including decreasing nitrogen and pesticide inputs while maintaining, or even surpassing the productivity of sole crops. Yet, predicting the existence and magnitude of those benefits remains difficult due to the numerous interactions between plants, their environment and agricultural practices.

Crop models are efficient tools used to understand and predict the trends of crop development, growth and yield, under various pedoclimatic conditions, management practices, and climate change scenarios. However, few of those models are able to simulate bi-specific intercropping systems, mainly because it would break assumptions generally used to simulate homogeneous sole crops, such as spatially homogeneous structure and plant-plant interactions only via density.

In this study, we improved the STICS soil-crop model to account for bi-specific intercrops (STICS-IC), and proposed new formalisms when needed, i.e. to simulate correctly dynamic interspecific plant-plant interactions. We proposed simple, generic formalisms that can readily be calibrated and further integrated into other crop models. The improved formalisms of STICS-IC concern mainly light interception, plant and root density effects, nitrogen (N) uptake and N stress assessment in intercrop.

We provide an example of simulations for bi-specific intercrops with an evaluation of the consistency and genericity of the model to simulate a wide range of species and intercropping designs, and then determine its validity domain. The genotypic parameters of STICS-IC were calibrated using only the sole crops and the model was evaluated independently on intercropping systems with the same parameters’ values. The simulated daily variables representing the soil-crop interactions in intercrops, i.e. LAI, plant height, shoot dry mass, nitrogen uptake, and yield were assessed with a dataset of various types of intercrops. Simulations were close to the observed values over all situations (nRMSE = 30% for LAI, 10% for final height, 22% for final shoot dry mass, and 17% for yield), which showed the consistency of the STICS-IC model despite the relative simplicity of the formalisms and their calibration on sole crops only.