Seeking preconditions for system shifts in agricultural social-ecological systems

Multifunctional farm systems produce ecosystem services for the benefit of the farmer or of other actors. They are considered to be more resilient to changing conditions like economic shocks in the market price or to ecological shocks like weather extremes, compared to farm systems producing only for the world food market. The concept of complex adaptive systems (CAS) is used to learn how economic, social and ecological factors influence farmers to shift from conventional to multifunctional farming or vice-versa. Using a cellular automata model we studied the development of the number and spatial pattern of stylized potato farms investing in green infrastructure (flower strips) for natural pest regulation in a virtual agricultural landscape. Natural pest regulation is assumed to be only effective if sufficient neighbouring farms also invest in flower strips. We also assume that farmers have different mind-sets towards economic, social and sustainability values. Results of a linear forward stepwise regression analysis of 15 runs of 1000 random parameter settings show that low costs of green infrastructure application is a very important factor for farmers to decide to switch or continue to multifunctional farming, both in a conventional or multifunctional landscape. Moreover, in a conventional setting, another important factor to shift to multifunctional farming is the natural drive of farmers towards multifunctional farming, In a multifunctional setting however, the most important factor to stay multifunctional is the strength of the existing social structure of (multifunctional) farms.