Planning to ‘Hear the Farmer’s Voice’: an Agent-Based Modelling Approach to Agricultural Land Use Planning

Abstract

Agricultural land use is influenced not only by multiple aspects of biophysical and socio-economic processes, but also the cumulative impacts of individual farmer decisions. Farmers’ activities and decisions at farm scale shape land use and water utilisation at regional scale, yet land use planning processes do not take into account farmers’ knowledge and decision-making processes as they respond to, and in turn shape, change. Farmers’ voices are missing in the planning system. In this paper, we address the complexity of agricultural land use planning and examine the possibility of agricultural land use planning from the bottom-up via simulation to integrate environmental, economic and human factors that influence land use change. We present an innovative approach to model the interactions between government policy, market signals, and farmers’ land use decisions, and how the accumulated effects of these individual decisions change agricultural land use patterns at regional scale, using spatial and temporal agent-based modeling. A multi-stage mixed method spatial agent-based modeling (ABM) approach, aligned with the Geodesign framework, can incorporate local knowledge and decision-making into models of regional land use change. To illustrate the new approach, we examine the impact of milk market price on changes in land use in Tasmania, Australia. This approach brings together local knowledge with scientific, planning, and policy knowledge to generate dynamic scenarios for informed agricultural land-use planning decisions.

Relational rationality in land- and water use: facing Mount Kenya in times of change

“…In ABM, environmental factors that affect farmer decisions can be included, for instance weather patterns, soil quality, water availability, and climate change impacts. ABM has been used to explore farmer decisions in response to policies, interventions, market volatility, resource scarcity, climate variability, socio-economic changes, innovations, land, and water management among others (Ambrosius et al, 2022;Kasargodu Anebagilu et al, 2021;Malawska & Topping, 2016;Pacilly et al, 2019;Shahpari & Eversole, 2023;M. Wens et al, 2020).…”