A conceptual modelling approach to identify the adequacy of existing models to simulate dynamics and productivity of tropical agroforestry systems

Tropical agroforestry systems are examples of ecological intensification. They represent a transition from short-term exploitation and destruction of tropical rain forest to sustainable land use and conservation of biodiversity (Garrity, 2004). However, such systems are complex and their production capacity has been poorly studied. Agroforestry research has focused on the incorporation of trees in agricultural cropping systems, with less attention to incorporation of crops into forest systems. There is a need for specific tools with which system productivity can be assessed and evaluated at any stage of the system during the evolution of its structure over its lifetime (several decades). Modelling the dynamics of these multi-strata and multi-species cropping systems is thus a major challenge in agronomic research. Crop models are useful as analytical and predictive tools, to test effects of structure and input changes on productivity and environmental impacts of the systems. Some agroforestry models have been developed which take into account spatial heterogeneity, in these systems (Malézieux et al, 2009). The models are often based on fundamental crop modelling concepts of resource capture and allocation under `potential growth' and `stressed' conditions. The objective of this paper is to assess the potential use of existing agroforestry models in the context of tropical agroforestry systems for purposes such as: (i) relating architectural and physiological traits of components to system-level resource capture and use for harvestable products, and thus the `strategic' choices of farmers in selecting components for the agroforestry system; (ii) exploring management options for farmers to adjust growth and performance of the components to achieve overall productivity goals; (iii) assessing `robustness' (or `vulnerability') and `resilience' of the agroforestry system under variable external (e.g. climatic) conditions.