Belowground resource sharing in mixed tree– crop systems: methods to better understand belowground interactions

  • Research in agroforestry moved from a descriptive stock-taking phase to efforts to understand and quantify processes in the sharing of growth resources, above- and belowground
  • Root distribution and structure are key to understanding of the interactions and processes involved
  • Deployed methods range from basic but labour-intensive invasive approaches (coring, trenching, excavating and rhizotrons) to more sophisticated, expensive but non-invasive methods: X-ray Computed Tomography (CT), Gamma-ray Computed Tomography, Neutron Tomography, Magnetic Resonance Imaging (MRI) and Nuclear Magnetic Resonance (NMR)
  • Despite the advances, root research in mixed crop-tree systems remains challenging because of the difficulty in finding the relevant spatial and temporal scales for real-world high heterogeneity soil conditions

Cropping systems based on carefully designed species’ mixtures over time (in terms of crop sequences) and/or space (within a farm or landscape) reveal many potential advantages under various conditions, both in temperate and tropical agriculture. In general, annual crops are expected to be relatively shallow-rooted while perennial plants, including trees, can have roots extending deep below the crop root zone, giving a foundation to the safety-net hypothesis5. The safety-net hypothesis (intercepting mobile nutrients leaching from crop root zones) complements the nutrient-pump hypothesis (uptake of deep soil resources of relatively immobile nutrients). However, the actual situation of relative root distributions is more complex and dynamic with seasonal shifts in the soil depth from which water and nutrients are taken up. In some situations, trees and crops compete for nutrients and water in the same soil layer even though the impact on crop performance and yield may vary according to rainfall and nutrient availability. Therefore, the potential benefits of trees in mixed systems depends on complex spatial and temporal interactions involving a large number of factors. Strong positive effects (for example, through increased nutrient availability) can be offset by strong negative effects (for example, via shading), making optimization complex and context dependent.

The past decades of agroforestry research have revealed many interacting processes in the sharing of, and competition for, belowground resources, made progress in their quantification and established tools to study mixed tree–crop systems, as this chapter shows. However, the manner in which net effects depend on context still requires empirical verification of simulation models.


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