Our diverse field and in silico research is integrated through a conceptual and quantitative framework: the simulation model. Models are simplifications of a system designed to provide insights into the system functioning.

In our case the models are Cycles, CropSyst, and PIHM. Models are powerful research tools in two different ways. First, building a systems' model requires putting all the pieces together in a coherent way and as a result we not only gain a deeper understanding of how the system of interest work, but also shed light on the knowledge gaps. These knowledge gaps are the seed of many research projects in our lab. Second, the models help us test interactions and scenarios that are experimentally impractical (for example unusual or expensive agricultural management practices or different climate scenarios), or that are simply impossible to accomplish experimentally in a meaningful way (e.g. changes in diffuse radiation, changes in air humidity).

Currently, Cycles, CropSyst and PIHM are part the backbone of a variety of projects:

  • SAMSS, a strategic and adaptive decision support system;
  • watershed scale modeling projects;
  • bioenergy oriented projects;
  • modeling of competition in multi-species communities;
  • N fertilizer management; and
  • applications to several of the Agmip activities (GCB Maize paper).