Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and conse- quently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use Electronic supplementary material The online version of this article (doi:10.1007/s10980-009-9362-8) contains supplementary material, which is available to authorized users. T. Houet (&) GEODE—UMR CNRS 5602, Universite ´ Toulouse 2, 5 alle ´e Antonio Machado, 31058 Toulouse Cedex 9, France e-mail: email@example.com T. R. Loveland ? K. Sayler U.S. Geological Survey Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198-0001, USA L. Hubert-Moy COSTEL—UMR CNRS 6554 LETG/IFR 190 CAREN, Universite ´ Rennes 2, Place du recteur Henri Le Moal, 35043 Rennes cedex, France and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape model- ling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and back- casting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.
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