Current approaches for modeling ecosystem services and biodiversity in agroforestry systems: Challenges and ways forward - Rahman, Muhammed Habib ur; Ahrends, Hella Ellen; Raza, Ahsan; Gaiser, Thomas (Frontiers in Forests and Global Change, 2023)
Limited modeling studies are available for the process-based simulation of ecosystem services (ESS) and biodiversity (BD) in agroforestry systems (AFS). To date, limited field scale AFs models are available to simulate all possible ESS and BD together. We conducted an extensive systematic review of available agroforestry (AF), BD, and soil erosion models for the simulation potential of seven most desirable ESS in AFS. Simple to complex AF models have an inherent limitation of being objective-specific. A few complex and dynamic AF models did not meet the recent interest and demands for the simulation of ESS under AFS. Further, many ESS modules especially soil erosion, GHGs emission, groundwater recharge, onsite water retention, nutrients and pesticide leaching, and BD are often missing in available AF models, while some existing soil erosion models can be used in combination with AF models. Likewise mechanistic and process-based BD diversity models are lacking or found limited simulation potential for ESS under AFS. However, further efforts of model development and improvement (integration and coupling) are needed for the better simulation of complex interactive processes belonging to ESS under AFS. There are different possibilities but a proficient modeling approach for better reliability, flexibility, and durability is to integrate and couple them into a process-based dynamic modular structure. Findings of the study further suggested that crop modeling frameworks (MFW) like SIMPLACE and APSIM could be potential ones for the integration and coupling of different suitable modeling approaches (AF, soil protection, GHGs emission, flood prevention, carbon sequestration, onsite water retention, ground recharge, nutrient leaching, and BD modules) in one platform for dynamic process based ESS estimation on daily basis at the field scale.