Abstract
Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.
Highlights
Agroforestry, the intentional integration of trees with crops or livestock, has gained momentum in temperate regions over the last few decades [1,2,3]
30% of temperate publications on alley cropping field experiments over the last three decades originated from just three sites [5]: the Guelph Agroforestry Research Station (Guelph, Canada; est. 1988) [13], Domaine de Restinclières (Montpellier, France; est. 1995) [14], and the University of Missouri Greenley Memorial Research Center (Novelty, MO, USA; est. 1997) [15]
Process-based rather than empirical models are the ideal choice for agroforestry systems as they better mimic the complex dynamics of tree–crop interactions and allow predictions outside the range of data available for model parameterization [18,19,20]
Summary
Agroforestry, the intentional integration of trees with crops or livestock, has gained momentum in temperate regions over the last few decades [1,2,3]. At the core of agroforestry research are the interactions between trees and crops, which drive differences from monoculture cropping systems and pure forestry stands. Process-based rather than empirical models are the ideal choice for agroforestry systems as they better mimic the complex dynamics of tree–crop interactions and allow predictions outside the range of data available for model parameterization [18,19,20]. CROPGRO [21] and STICS [22] have been used to model agroforestry systems by reducing the amount of light available to crops [23,24]. Yield-SAFE, for example, is a parameter-sparse, one-dimensional (1D) biophysical model developed to simulate the productivity of an agroforestry system for an entire tree rotation [29]. We introduce Hi-sAFe, a three-dimensional (3D), process-based, biophysical model that integrates tree–crop interactions in agroforestry systems.
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