Climate change impacts on and adaptation measures for agriculture in Austria in 2020 and 2050: Linking bottom-up and top-down models

The Austrian agricultural sector is very heterogeneous in natural conditions and farming systems and highly vulnerable to climate change (e.g. alpine farming). The economic assessment of climate change impacts on and adaptation measures for agriculture requires an integrated modeling approach to take account of the cross-cutting nature of adaptation and to cope with the heterogeneity of impacts and response options. Traditionally, agriculture is a highly subsidized and regulated sector in order to meet multiple sectoral and societal objectives (e.g. increasing international competitiveness, food security, conserving biodiversity). The assessment of adaptation measures in response to climate, whether autonomous by farmers or policy induced, needs to take account of these policy objectives as well as of international leakage and unintended regional spill-over effects. The main objective of this paper is thus to present a bottom-up to top-down modeling approach that is able to assess the impacts of and adaptation to climate change for the agricultural sector and the corresponding effects to the national economy.The core of the modeling approach consists of a bottom-up to top-down model interface that couples an agricultural production optimization model (PASMA, Schmid and Sinabell, 2007) with a CGE model for the Austrian economy based on the GTAP 7 database (GTAP, 2007). PASMA has an advantage in its detailed description of the bio-physical system on a spatially high resolution scale (NUTS3 level based on regionally disaggregated farm structure and bio-physical properties) and of agricultural policies and is consistent with the Austrian agricultural statistics. The CGE model has less detail both in terms of agricultural crops and spatial resolution (NUTS 1), but captures the impact of changes in agriculture on the rest of the economy and arising feedback effects on the agricultural sector, and is consistent with international trade. To combine the advantages of both modeling approaches, PASMA and the CGE model are mapped to each other. The main modeling challenges include ensuring consistency of structural and policy parameters, price levels and scenario assumptions. In an integrated manner, climate change impacts are studied with respect to four plant and three livestock sectors. Different options of agricultural adaptation are considered, taking account of the relevant spatial and temporal scales of impacts and adaptation, i.e. autonomous adaptation such as choices on crops and crop management (e.g. tillage, fertilizer, and irrigation) and policy induced measures such as agri-environmental and less favored area measures or investment aids. Different types of adaptation are translated to the CGE model e.g. through a shift in multi-factor-productivities, a change in production technology or different tax/subsidization regimes.First results from PASMA for the year 2020 show impacts of climate change and adaptation effects on agriculture. Compared to a baseline scenario without climate change, increases as well as decreases in production values and farm incomes emerge depending on the underlying climate scenario. Simulation results furthermore report on the arising consequences for upstream and downstream industries. The strength and magnitude of economy wide effects due to the impacts in the plant and livestock sectors depend on their linkage with other sectors. Important suppliers for agriculture in Austria include (petro-) chemicals, food, trade and other business, but also grain and other crops (within agriculture itself). Central downstream industries, i.e. sectors that use agricultural outputs in their production, are primarily food, but also trade as well as milk production and cattle (both using outputs from plant production). Comparing the scope of structural change with the consequences that arise from changed climatic conditions by 2020 (in terms of agricultural sector output), the structural shift is expected to be the dominating effect. As for climate change adaptation, autonomous responses are likely to have minor effects on the overall economy (also given the relatively small share of agriculture in the Austrian GDP), while they are essential for food security and environmental objectives. Policy induced responses such as e.g. investment aids or research subsidies fostering new technologies require public funding and may have stronger economic implications. A comparison across different adaptation options allows identifying the groups which are required to take action (private/farmers, public/governments) to respond to future challenges for agriculture, food and the environment.