Are agricultural land-use models able to predict changes in land-use intensity?

Land-use and land-cover change research needs to pay more attention to proc esses of land-cover modification, and especially to agricultural land inten sification. The objective of this paper is to review the different modellin g approaches that have been used in land-use/land-cover change research fro m the perspective of their utility for the study and prediction of changes in land-use intensification. After clarifying the main concepts used, the d ifferent modelling approaches that have been used to study land-use change are examined, case study evidence on processes and drivers of land-use inte nsification are discussed, and a conclusion is provided on the present abil ity to predict changes in land-use intensity. The analysis suggests there a re differences in the capability of different modelling approaches to asses s changing levels of intensification: dynamic, process-based simulation mod els appear to be better suited to predict changes in land-use intensity tha n empirical, stochastic or static optimisation models. However, some stocha stic and optimisation methods may be useful in describing the decision-maki ng processes that drive land management. Case study evidence highlight the uncertainties and surprises inherent in the processes of land-use intensifi cation. This can both inform model development and reveal a wider range of possible futures than is evident from modelling alone. Case studies also hi ghlight the importance of decision-making by land managers when facing a ra nge of response options. Thus, the ability to model decision-making process es is probably more important in land-use intensification studies then the broad category of model used. For this reason, landscape change models oper ating at an aggregated level have not been used to predict intensification. In the future, an integrated approach to modelling - that is multidiscipli nary and cross-sectoral combining elements of different modelling technique s - will probably best serve the objective of improving understanding of la nd-use change processes including intensification. This is because intensif ication is a function of the management of physical resources, within the c ontext of the prevailing social and economic drivers. Some of the factors t hat should be considered when developing future land-use change models are: the geographic and socio-economic context of a particular study, the spati al scale and its influence on the modelling approach, temporal issues such as dynamic versus equilibrium models, thresholds and surprises associated w ith rapid changes, and system feedbacks. In industrialised regions, predict ing land-use intensification requires a better handling of the links betwee n the agriculture and forestry sectors to the energy sector, of technologic al innovation, and of the impact of agri-environment policies. For developi ng countries, better representation of urbanisation and its various impacts on land-use changes at rural-urban interfaces, of transport infrastructure and market change will be required. Given the impossibility of specific pr edictions of these driving forces, most of the modelling work will be aimed at scenario analysis. (C) 2000 Elsevier Science B.V. All rights reserved.