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Using spatial multi-criteria decision analysis to develop new and sustainable directions for the future use of agricultural land in Denmark

Vogdrup-Schmidt, Mathias, Olsen, Søren Bøye, Dubgaard, Alex, Kristensen, Inge Toft, Jørgensen, Leif Bach, Normander, Bo, Ege, Christian, Dalgaard, Tommy
Ecological indicators 2019 v.103 pp. 34-42
European Union, agricultural land, carbon, data collection, ecosystem services, environmental indicators, land use change, leasing, models, multi-criteria decision making, soil types, Denmark
Close to 60 per cent of the Danish land area is used for arable farming. EU regulations as well as public preferences create increasing pressures for changing agricultural land use in a more environmentally sustainable direction incorporating the multiple ecosystem services affected by agriculture. In this paper we present a spatially explicit multi-criteria decision analysis model which describes the trade-offs between the rent obtained from land in agricultural use on the one hand and selected ecosystem services on the other. The model is based on an extensive geographical dataset. This include maps on soil types, carbon content, sensitivity to nutrient losses, High Nature Value scores etc., which in combination with environmental criteria facilitates the ranking of all agricultural fields in Denmark according to their current overall worth to society in terms of land rent as well as other ecosystem services. Picking from a ranked list, we identify areas that may be considered efficient candidates for land use change considerations. Subsequently, the model is applied to identify suitable candidate areas for land use change in scenarios attaching different weights to various environmental services. In this way, four scenarios for Danish agricultural land use in 2050 are analysed. The results highlight that the possible realization of each of these mutually exclusive scenarios will require decision makers to consider very different development paths and land use changes for the Danish agricultural area.