Ecosystem services (ES) modeling studies typically use a forecasting approach to predict scenarios of future ES provision. Usually, these forecasts do not inform on how specific policy alternatives will influence future ES supply and whether this supply can match ES demand – important information for policy-makers in practice. Addressing these gaps, we present a multi-method backcasting approach that links normative visions with explorative land-use and ES modeling to infer land-use policy strategies for matching regional ES supply and demand. Applied to a case study, the approach develops and evaluates a variety of ES transition pathways and identifies types, combinations and timings of policy interventions that increase ES benefits. By making explicit ES sensitivity towards regional policy strategies and global boundary conditions over time, the approach allows to address key uncertainties involved in ES modeling studies. Integrated backcasting modeling system BackES Sibyl H. Brunner, Adrienne Grêt-Regamey, Simon Peter, Simon Briner, Swiss Federal Institute of Technology; Robert Huber, Swiss Federal Institute for Forest, Snow and Landscape Research. The model version presented in this paper and example input data are offered free of charge from the corresponding author (sbrunner@ethz.ch) Linear Programing Language (LPL), Virtual Optima; ILOG CPLEX Optimization Studio, IBM LPL academic license available on purchase, http://www.virtual-optima.com/en/index.html; CPLEX academic license available at no charge, http://www-01.ibm.com/software/commerce/optimization/cplex-optimizer/index.html NLOGIT 5, Econometric Software Inc. (Education license available on purchase, http://www.limdep.com/products/nlogit/); R x64 3.1.0: A language and environment for statistical computing, R Core Team, Foundation for Statistical Computing (Available at no charge, http://www.r-project.org/) 
A backcasting approach for matching regional ecosystem services supply and demand