Farming system models for supporting farm resilience: Research needs, gaps and promising approaches
It is important to increase the resilience of food production systems in the face of a changing climate, land scarcity, and changing demographics and market conditions. As farm resilience is a high level system property emerged from social ecological interactions, its direct measurement is difficult because it requires measuring the thresholds or boundaries that separate alternate stability regimes of the farm system. However, agricultural systems modeling for supporting agricultural resilience is still a very young science. Through critical review of state of the art literature, this study aims at highlighting the new requirements of agricultural system modeling as they apply to management for farm resilience, limitations of contemporary agricultural systems modeling approaches, and promising directions for future research on the field. Although a great deal of knowledge and tools about biophysical or social processes exist, agricultural system model research hardly ever seeks to develop modelling frameworks and tools to support farm resilience management. We conceptualized nine criteria for evaluating models' suitability for farm resilience studies, which include: (1) representing social ecological complementariness) (2) having multiple performance dimensions, (3) explaining human behavioural change, (4) representing flexible multi scale feedbacks, (5) incorporating intra farm heterogeneity, (6) explaining farm's structural changes, (7) being sensitive to key drivers, (8) managing uncertainty, and (9) mediating effective participation. Using these criteria we evaluated a mass primary literature on farming systems models and found that none of developed farming system models are sufficient for supporting farm resilience regarding all criteria. The result of our meta analysis can serve as a reference matrix that helps identifying research directions towards supporting the resilience of agricultural systems. There is an emerging recognition in the scientific community of the capability and utility that multi agent simulations (MAS) offer a platform for understanding the complexity of energy, nutrient and material flows that result from rich interactions and feedback among social and natural processes. Although some great progress has been made in applying MAS to study land use change over the last decade, MAS models for investigating farm resilience and transition scenarios are still in a very early stage of development. Using the above mentioned criteria we also analyzed the current limitations of this model family and elaborate possible future developments as subjects of follow up studies. To better materialize our recommendations, we analyze our MAS modeling framework, entitled MANUS (Multi Agent system model for exploring sustainable smallholders' NUtrient management Strategies) as a demonstration case.