Applying Occam's razor to global agricultural land use change. (January 2016)

• Record Type: Journal Article
• Authors: Engström, Kerstin; Rounsevell, Mark D.A.; Murray-Rust, Dave; Hardacre, Catherine; Alexander, Peter; Cui, Xufeng; Palmer, Paul I.; Arneth, Almut
• Is Part Of: Environmental modelling & software. Volume 75(2016:Jan.)
• Page Start: 212
• Page End: 229
• Publication Date: 2016-01
• Subjects: Global agricultural land-use -- Parsimonious models -- Parameter uncertainty -- Sensitivity analysis -- Cereal yields; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.10.015
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We present a parsimonious agricultural land-use model that is designed to replicate global land-use change while allowing the exploration of uncertainties in input parameters. At the global scale, the modelled uncertainty range of agricultural land-use change covers observed land-use change. Spatial patterns of cropland change at the country level are simulated less satisfactorily, but temporal trends of cropland change in large agricultural nations were replicated by the model. A variance-based global sensitivity analysis showed that uncertainties in the input parameters representing to consumption preferences are important for changes in global agricultural areas. However, uncertainties in technological change had the largest effect on cereal yields and changes in global agricultural area. Uncertainties related to technological change in developing countries were most important for modelling the extent of cropland. The performance of the model suggests that highly generalised representations of socio-economic processes can be used to replicate global land-use change. Highlights: The complexity of global agricultural LUC can be represented with simple processes. The approach allows efficient exploration of the parameter uncertainty range. Changes in cereal yields in developing countries are an essential driver of LUC.