Agent-based Modelling of an Ontario Agricultural Watershed in Transition to Organic Agriculture
Martin Bunch, Alireza Ghaffari, Rod MacRae, and Shuilin Zhao
A Research Report of the SpEAR Lab, Faculty of Environmental and Urban Change, York University
January, 2015
Abstract
Land-use changes are typically modeled using geographic information systems (GIS) because of the spatial nature of the data. But the complexity of coupled human and natural systems, and the fourth dimension of change over time and time-series data, exposes some limitations of GIS. In this paper, we present the application of a free and open source geospatial multi-agent model (REPAST), to the dynamic simulation of greenhouse gas (GHG) emissions associated with theoretical wholesale conversion of farms to organic production in an Ontario sub-watershed with predominantly agricultural land use. The combination of geospatial analysis and use of an Agent-based Model (ABM) is a relatively new way to approach complex problems involving multiple decision makers on the landscape, and helps to address the time dimension in geospatial modeling problems. ABM can model dynamic systems, their evolutionary changes and importantly, can identify options for sustainable system configurations. As a part of this research project, open source tools were developed to integrate ABM and GIS environments. In this paper, we present scenarios to estimate the GHG emissions in an agricultural watershed, and the ABM tools we have adapted and developed. Preliminary results indicate that our loosely coupled GIS-ABM is able to run land use change scenarios that can help decision makers configure policy environments to encourage transition to organic farming systems.
Key words: organic farming, transition, Agent-based Model, Greenhouse gas emissions, complexity modeling, agricultural systems.
