Both woody crops and multispecies systems are considered key characteristics of sustainable agroecosystems, yet these two approaches have rarely been applied together for food production, particularly in temperate regions. Diverse food-producing agroforestry systems (DFAS) dominated by fruit and nut trees/shrubs could transform agriculture by restoring ecosystem services while simultaneously producing staple food crops. Optimizing the species composition and arrangement of practical woody multispecies designs is a central hurdle to adoption of DFAS. In particular, DFAS design needs to balance yield and ecosystem service production with practical considerations, such as implementation, management, and harvesting. Alley cropping, a standard agroforestry practice that integrates an herbaceous ‘alley crop’ in between rows of woody crops, adds a linear constraint that may make designs more scalable and easier to mechanize. Here we explore alley crop designs using the spatially explicit SORTIE model, demonstrate the utility of such a model for evaluating DFAS designs, and propose a framework for design optimization using multi-objective hybrid optimal control.
Results/Conclusions
Results from SORTIE reveal that between row tree spacing, within row tree spacing, and tree height were the dominant factors that determine light availability in an alley cropping system. Row orientation, row staggering, latitude, and tree bole height had much smaller effects. When used to evaluate specific multispecies designs, SORTIE showed an approximately 10% increase in light capture for each additional canopy layer added into the design, demonstrating a clear advantage of multispecies systems. While this approach ignores belowground interactions, it still serves as a good method for generating quantitative hypothesis and upper bounds for comparisons of DFAS. Finally, we conclude that future work in DFAS design optimization will require the use of multi-objective hybrid optimal control, an optimization framework specifically intended for complex systems with both discrete (e.g. species composition) and continuous (e.g. species arrangement) variables.