Mapping and modelling of changes in agricultural intensity in Europe

• Published in: Agriculture, ecosystems & environment ecosystems & environment, 2011-01, Vol.140 (1-2), p.46-56
• Main Authors: Temme, A.J.A.M., Verburg, P.H.
• Format: Article
• Language: English
• Subjects: agricultural economics; Agricultural intensity; agricultural land; agricultural policy; agroecosystems; Agronomy; Agronomy. Soil science and plant productions; Biodiversity; Biological and medical sciences; econometric models; Farming; Farmlands; Farms; Fundamental and applied biological sciences. Psychology; General agroecology; General agroecology. Agricultural and farming systems. Agricultural development. Rural area planning. Landscaping; General agronomy. Plant production; Generalities. Agricultural and farming systems. Agricultural development; geographical variation; grasslands; intensive farming; Land use; land use change; LUCAS; Mathematical models; nitrogen; nitrogen fertilizers; simulation models; spatial distribution; Spatial variation; Statistics; stocking rate; temporal variation; vegetation cover
• ISSN: 0167-8809; 1873-2305
• DOI: 10.1016/j.agee.2010.11.010

▶ Crop observations and agricultural statistics are combined. ▶ From them, intensity can be calculated at about 100 thousand points in EU27. ▶ Regression connects intensity classes to location factors. ▶ Maps of agricultural intensity for 5 EU-countries have been made. ▶ Heterogeneity of land use intensity is between and within countries and regions. Spatial maps of agricultural intensity are needed for analyses of environmental issues, including biodiversity changes. We present a method to produce such maps for Europe. While most studies beyond farm level focus on land cover change only, this paper focuses on spatial variation in land use intensity and its dynamics. Our method defines agricultural land use intensity in terms of nitrogen input. For arable land, it combines field observations with administrative-level statistics to assess probability of occurrence for three land use intensity classes. For grassland, it uses maps of livestock density to assess probability of occurrence for two intensity classes. Agricultural land is spatially allocated to intensity classes using an algorithm that downscales intensity changes simulated with an agricultural economic model. Our results are 1km2 resolution maps of classified agricultural land use intensity in the year 2000. We illustrate the method by exploring changes in the spatial pattern of land use intensity for a financial policy reform scenario in the year 2025. Results indicate spatial heterogeneity in land use intensity across European countries, including large differences in intensity between countries, between regions, but also within regions. Our method could be improved with smaller-resolution agricultural statistics and broader intensity indicators.