Inter-Species Feedbacks Drive Emergent Productivity in Agroforestry Systems - An Agent-Based Analysis

Luis Raul Comolli^1*Hugo Fassola²

• ¹Independent researcher, Basel, CA, Switzerland
• ²Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria Montecarlo, Misiones, Argentina (https://inta.gob.ar/montecarlo), Montecarlo, Misiones, Argentina

Abstract Introduction Conventional agricultural intensification has increased global food production but has also accelerated deforestation, soil degradation, and biodiversity loss. Agroforestry offers a sustainable alternative by integrating trees into farming systems to enhance ecosystem functions. However, predicting how reciprocal interactions between a focal crop species and multiple associated tree species shape long-term productivity under adaptive management remains a major scientific challenge. Methods We developed an empirically calibrated Agent-Based Model (ABM) based on a decade of measurements from a 25-year old multispecies agroforestry experiment integrating Ilex paraguariensis (yerba mate) with nine tree species. The model simulates species-specific growth, canopy shading, harvest, pruning, soil organic matter (SOM) feedbacks, and management interventions. It represents 778 interacting perennial individuals and enables quantitative exploration of reciprocal inter-species feedbacks under fixed and adaptive management strategies. Because the model is deterministic, statistical replication of simulation runs is not applicable. Results Simulations reproduce key field-observed patterns with quantitative agreement. Starting from degraded soil conditions, both management strategies show an initial fertility decline followed by recovery driven by endogenous SOM accumulation. Adaptive management yields a ~56% higher net productivity than fixed management, shortens the recovery time of soil fertility from ~260 weeks to ~88 weeks, and produces nearly threefold higher total biomass. Across species, the model reproduces observed relative Ilex paraguariensis yield differences, correctly predicting that Toona, Cañafístola, Petiribi, Anchico, and Kiri support higher harvest yields than the control (no trees), consistent with experimental field observations over a 10-year period. This quantitative agreement strengthens the model's validity in capturing beneficial inter-species synergies. Conclusion The simulations reveal that the focal crop responds to tree-mediated shade and nutrient inputs while actively reorganizing soil fertility gradients through biomass extraction and residue return, thereby reshaping tree regrowth and competitive structure. Together, these dynamics define a mechanistically transparent and predictive framework linking empirical field data with long-term system forecasting.