Modelling Farm Growth and Its Impact on Agricultural Land Use: A Country Scale Application of an Agent-Based Model

• Published in: Land (Basel) Vol. 7; no. 3; p. 109
• Main Authors: Beckers, Veronique, Beckers, Jeroen, Vanmaercke, Matthias, Van Hecke, Etienne, Van Rompaey, Anton, Dendoncker, Nicolas
• Format: Journal Article Web Resource
• Language: English
• Published: Basel MDPI AG 01.09.2018; Multidisciplinary Digital Publishing Institute (MDPI)
• Subjects: ADAM model; agent-based modelling; Agent-based models; agricultural dynamics; Agricultural economics; Agricultural land; Agricultural management; Agriculture; Business competition; Common Agricultural Policy; Computer simulation; country scale; Decision making; Earth sciences & physical geography; Economic conditions; Economic models; Environmental conditions; farm evolution; farmer population; Farmers; Farms; Food; Land use; Physical, chemical, mathematical & earth Sciences; Physique, chimie, mathématiques & sciences de la terre; Population; real-world application; Scale (ratio); Sciences de la terre & géographie physique; Trends; Belgium; United States > US; Europe
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land7030109

The ongoing economic pressure on farmers has resulted in lower gross margins, lower income, and a continuous decrease in the number of farmers in large parts of the world. Most remaining farmers upscale their activities by taking over the land of their former competitors, resulting in a decrease in agricultural employment and an increase in average farm size, accompanied by specialisation and new management techniques. Understanding these significant trends and their impact on the land use and environment requires a deeper knowledge of the mechanisms involved and the impacts of different policy measures. These processes are ideally represented through agent-based modelling. Currently, agent-based models are rarely for larger regions. This paper presents ADAM (Agricultural Dynamics through Agent-based Modelling), using it for the case study of Belgium. ADAM was created to obtain insights in past and current agricultural trends and to explore possible effects of policy measures. ADAM simulates the evolution of a farmer population and their farms at a fine scale on the country level. It produces yearly outputs on the number of farms, their size, and the type of farming activity on every parcel. Results show that ADAM is capable of adequately modelling a farmer population according to past trends and that it can be used to explore the results of a business-as-usual scenario, therefore showing the possibility of creating agent-based models for larger scale real-world applications.