Objective 1: Understanding agricultural decision-making in New Zealand
We will understand the decision-making processes of New Zealand’s pastoral farmers and investigate the cultural heterogeneity of approaches to farming. We will produce decision rules for use in the multi agent simulation (MAS) and provide a case study of coterminous farms to aid in MAS development.
Objective 2: Farm system responses
We will create a robust model of a farm system that will allow simulation of farm production and environmental emissions given farm physical resources and in the face of multiple future pressures on the farm system. The model will allow representation of realistic management of a pastoral farm within a dynamic simulation model.
Objective 3: Interventions, responses and consequences
We will create an industry level Multi Agent Simulation (MAS) model of New Zealand’s pastoral industries that describes the strategic decisions and behaviours of individual farmers in response to changes in their operating environment, and links to the production, economic and environmental impacts of their management. The MAS will represent the complex adaptive system of farm businesses and the human and biophysical responses to market and non market pressures; and to interventions and structural changes imposed along the value chain. The MAS will represent the heterogeneity that exists in farmers, their systems, their responses to interventions and the resultant consequences. We will integrate “decision-rules” used by pastoral farmers (Objective 1) and biophysical responses to different farm management developed in Objective 2. The MAS will provide an objective tool to assist strategy and policy setters to learn about the behaviour of this complex socio-economic/bio-physical system before they intervene.
Objective 4: Integrated framework for Rural Futures
We will create a framework for end-users to explore the biophysical and economic consequences of farmer behaviours, plan alternative pathways and build the adaptive capability of farmers to develop resilient farming systems.