This paper reports work using a coupled agent-based model of land use change and species metacommunity model (FEARLUS-SPOMM) to explore biodiversity incentive mechanisms using adaptive control algorithms. Existing work at the Lancaster Environment Centre has shown that such algorithms can help in analysing the adaptive capabilities of climate-related policy interventions under uncertainty. In particular, feedback control is a practical approach that mimics many recognisable features of adaptive decision making processes, including the sequential review of models and policies in the light of new observations. In a companion paper, we show that FEARLUS-SPOMM shows nonlinear dynamics in the relationship between agricultural incentives and biodiversity outcome. In this pilot study, we show that the sequential review implicit in feedback control allows information about unforeseen events to be assimilated such that biodiversity can be maintained at a desired level by adaptively adjusting agricultural incentives. We also find that Simon's 'satisficing' has its limitations in the representation of human decision making.