Module 3000
Integrated land use modelling

Instructors

Erwin Schmid (erwin.schmid@boku.ac.at),
Martin Schönhart, Hermine Mitter, Mathias Kirchner

Course Description

The course aims at strengthening skills in advanced land use optimization modelling by integrating disciplinary concepts, data, methods and scenarios. The students shall be able to build bottom-up land use optimisation models at farm to landscape scale as well as at regional to global scale and to perform integrated impact analysis of climate change, trade, and policy on agricultural land use, production and environment.

Course Outline

1. Basic concepts of integrated land use modelling
   • Introduction to integrated land use modelling
     • Model types, research aims and contexts
     • Typical structure of integrated quantitative land use studies
     • Model linkages and interfaces: bio-physical simulation models, bottom-up land use optimization models, PE, CGE, I/O models, etc.
     • Impact chains in land use models
   • Scenario development
     • Representative Concentration Pathways (RCPs)
     • Shared Socio-economic Pathways (SSPs)
     • Price, market, policy forecasts /projections /baselines
   • Tools and concepts to facilitate integrated land use model development
     • Generic model development
     • Organization of data transformation, processing and model integration
     • Concept of homogenous response units
     • Linking and analysing bio-physical and economic land use data
   • Integrated land use indicators
     • Economic indicators
     • Biotic and abiotic environmental indicators
     • Biodiversity assessment
     • Landscape assessment
     • Ecosystem service indicators
2. Stakeholder participation in land use modelling
   • Transdisciplinary theory
   • Stakeholder communication
3. Applied land use model building and analysis with GAMS
   • Examples of land use models at different scales
     • Field, farm and landscape modelling
     • Regional to global land use modelling
   • Use of grid-computing facilities
4. Sensitivity and uncertainty analysis
   • Basic concepts of uncertainty in quantitative land use modelling
   • Monte Carlo Simulation
   • Surface Response Function Estimation
5. Reporting
   • Scientific paper preparation

Teaching Method

Lectures (30%), exercises (30%), seminar (40%)

Grading: seminar paper (80%), participation (20%). Registered participants will get an graded certificate from BOKU as well as the certification of participation in the ”Doctoral Certificate Program in Agricultural Economics”.

Credit points: 3 ECTS, Category: Empirics

Language: English

Prerequisites: Basics in GAMS, R, mathematical programming, regression analysis, and scientific writing.

Software: GAMS, R

Organization

The course is held at BOKU University, Vienna, in one week. The course will take place in March or April. To participate in the course it is necessary to register at the Promotionskolleg Agrarökonmik AND at BOKU. You will receive detailed instructions on how to register at BOKU a month before the start of the module by email.

Literature:

• Kirchner, M., J. Schmidt, G. Kindermann, V. Kulmer, H. Mitter, F. Prettenthaler, J. Rüdisser, T. Schauppenlehner, M. Schönhart, F. Strauss, U. Tappeiner, E. Tasser, and E. Schmid (2015) Ecosystem Services and Economic Development in Austrian Agricultural Landscapes - The Impact of Policy and Climate Change Scenarios on Trade-offs and Synergies. Ecological Economics 109, 161-174.
• Mitter, H., C. Heumesser, and E. Schmid (2015). Spatial modelling of robust crop production portfolios to assess agricultural vulnerability and adaptation to climate change. Land Use Policy 46, 75-90.
• Mitter, H., M. Kirchner, E. Schmid, and M. Schönhart (2014).The participation of agricultural stakeholders in assessing regional vulnerability of cropland to soil water erosion in Austria. Regional Environmental Change 14(1), 385-400.
• Kirchner, M., and E. Schmid (2013). Integrated regional impact assessment of agricultural trade and domestic environmental policies. Land Use Policy 35, 359-378.
• Havlík, P., H. Valin, M. A. Mosnier, M. Obersteiner, J.S. Baker, M. Herrero, M.C. Rufino, E. Schmid (2013) Crop Productivity Growth: A way to reduce land use change and greenhouse gas emissions from the livestock sector. American Journal of Agricultural Economics 95(2) 442-448.
• Stürmer, B., J. Schmidt, E. Schmid, and F. Sinabell (2013). Implications of agricultural bioenergy crop production in a land constrained economy – the example of Austria. Land Use Policy 30, 570-581.
• Strauss, F, E. Schmid, E. Moltchanova, H. Formayer, and X. Wang (2012). Modelling climatic change and biophysical impacts of crop production in the Austrian Marchfeld region. Climatic Change 111, 641-664.
• Havlík P., A.U. Schneider, E. Schmid, H. Böttcher, St. Fritz, R. Skalský, K. Aoki, St. de Cara, G. Kindermann, F. Kraxner, S. Leduc, I. McCallum, A. Mosnier, T. Sauer, and M. Obersteiner (2011). Global land-use implications of first and second generation biofuel targets. Energy Policy 39(10), 5690-5702.
• Schneider, U.A., P. Havlík, E. Schmid, H. Valin, A. Mosnier, M. Obersteiner, H. Böttcher, R. Skalsky, J. Balkovic, T. Sauer, and St. Fritz (2011). Impacts of population growth, economic development, and technical change on global food production and consumption. Agricultural Systems 104(2), 204-215.
• Schönhart, M., T. Schauppenlehner, E. Schmid, and A. Muhar (2011). Integration of bio-physical and economic models to analyze management intensity and landscape structure effects at farm to landscape level. Agricultural Systems 104(2), 122-134. 
• Schönhart, M., T. Schauppenlehner, E. Schmid, and A. Muhar (2011). Analyzing maintenance and establishment of orchard meadows at farm and landscape levels applying a spatially explicit integrated modeling approach.  Journal of Environmental Planning and Management 54(1), 115-143.
• Schönhart, M., E. Schmid, and U.A. Schneider (2011). CropRota – A crop rotation model to support integrated land use assessments. European Journal of Agronomy 34(4), 263-277.
• Van Vuuren, D., et al. (2011). The representative concentration pathways: an overview. Climatic Change 109, 5-31.
• Moss, R., et al. (2010). The next generation of scenarios for climate change research and assessment. Nature 463/11, 747-756.
• Schneider, U.A., B.A. McCarl, and E. Schmid (2007).  Agricultural Sector Analysis on Greenhouse Gas Mitigation in U.S. Agriculture and Forestry. Agricultural Systems 92, 128-140.
• Salhofer, K., E. Schmid, and G. Streicher (2006).  Testing for Efficiency of a Policy Intended to Meet Objectives: General Model and Application. Journal of Agricultural and Resource Economics 31/2, 151-172.