Abstract

Disentangling nutrient acquisition strategies between trees and crops is central to understanding positive nutrient interactions in agroforestry systems for improved low-input agriculture. However, as plants are responsive to a complex soil matrix at multiple scales, generalizable diagnostics across diverse agroforests remains challenging. We synthesize research at various scales of the tree-crop interface that are cumulatively hypothesized to underpin nutrient acquisition strategies in agroforestry systems. These scales span the whole root system to fine-scale sites of acquisition actively engaged in biological and chemical interactions with soil. We target vertical and horizontal dimensions of acquisition patterns; localized root-soil dynamics including biological associations; root-scale plasticity for higher acquisition; and nutrient additions via biological nitrogen fixation and deep soil nutrient uplift. We consolidate methodological advances and the effects of environmental change on well-established nutrient interactions. Root distribution patterns remain one of the most universal indicators of nutrient acquisition strategies in a range of agroforestry systems, while root functional traits are emerging as an effective root-scale indicator of nutrient acquisition strategy. We validate that in agroforestry systems crop root functional traits reveal bivariate trade-offs similar to, but weaker than, crops in monoculture, with mechanistic links to nutrient acquisition strategies. While interspecific root overlap may be associated with nutrient competition, clear cases of enhanced chemically and microbially meditated processes result in species- and management-specific nutrient facilitation. We argue for agroforestry science to use distinct and standardized nutrient acquisition indicators and processes at multiple scales to generate more nuanced, while also generalizable, diagnostics of tree-crop interactions. And extensive research is needed on how agroforestry practices stabilize key nutrient acquisition patterns in the face of environmental change.

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