1. Martin Schönhart 1, Franz Sinabell 2, Erwin Schmid 1 ‘The spatial dimension in analysing the linkages between agriculture, rural development and the environment’ Edinburgh, UK, October 22-23, 2015 Integrated Assessment of Climate Change Impacts on a Grassland Dominated Austrian Landscape 1 Institute for Sustainable Economic Development, BOKU University of Natural Resources and Life Sciences, Vienna 2 WIFO Austrian Institute of Economic Research, Vienna

2. Global change at landscape level climate change CAP reforms & climate change policies international market developments land use & livestock management farm welfare abiotic environmental impacts biodiversity landscape appearance 3 weeks -70%

3. Up to the 1950ies Wide spread of orchard meadows around farms, on grassland and along field borders Since then... Permanent decrease of fruit trees and orchard meadows History of orchard meadows (Streuobstwiesen)

4. Case study landscape Mostviertel geological transition zone between flat land (Danube valley, N) and alpine region (Nördliche Kalkalpen, S) S 1250mm | 7-8°C Farms: N=118 Strauss et al., 2013. Int. J. of Climat. 33, 430–443.

5. Methods and Data CropRota 1 EPIC 2 FAMOS[space] 3 socio-economic & RD indicators agri-environmental indicators input and output prices CAP production functions farm labor supply livestock – herd sizes observed land use spatially explicit field data landscape elements climate scenarios topography soil characteristics natural & socio-economic data Input Output food production indicators 1 Schönhart et al. (2011). Eur J Agron 34, 263-277. 2 e.g. Izaurralde et al. (2006). Ecol Modell 192, 362-384. 3 Schönhart et al. (2011). J Environ Plann Manage 54, 115-143. 4 Georg Kindermann, BFW (see Kirchner et al., (2015). Ecol Econ 109, 161-174). Models CALDIS VÂTIS 4 farm gross margin public budget spending farm labor demand landscape diversity & appearance agric. & forestry land use change biodiversity SOC soil sediment loss N & P nutrient balances GHG emissions crop & livestock production

6. EPIC – model run settings CS05 +20% CS01 +0% CS09 -20%

7. Impact, mitigation & adaptation scenarios NameCC*AEP*CAP reformMitigation policiesAdaptation policies REF_2040No no dairy quota; no livestock premiums; regional farm payment; greening; LFA payments from 2008 CS[CC]_iYesNolike REF_2040 CS[CC]_mYesNolike REF_2040energy crops on set aside; subsidies for: landsc. elements, SRF, afforestation, cover crops, min. tillage and extensive land use CS[CC]_aYesNolike REF_2040no greening, subsidies for maintenance of steep slope grass land and irrigation CS[CC]_maYesNolike REF_2040like CS[CC]_mlike CS[CC]_a Climate Change [CC] Scenario Name Climate change in 2040 ∆ temperature (°C)∆ precipitation (%) CS01+ 1.50% CS05+ 1.5+20% CS09+ 1.5-20% * CC…climate change, AEP…agri-environmental program

8. Prelim. Results – changes in farm gross margins from climate change and policies Gross margin:+ product sales (plant, livestock) + subsidies + annuities for long-term investment - variable costs (machinery, inputs and services, off-farm labor) Average aggregated at landscape level Farm gross margins at landscape level Farm gross margins – northern landscape Schönhart et al., under review

9. Prelim. Results – land use impacts (ha) from climate change and policies CroplandIntensively managed permanent grassland Orchard meadowsForests impact mitigation adaptation

10. Prelim. Results – soil management (ha)

11. Prelim. Results – changes in soil organic carbon from climate change and policies CroplandPermanent grassland

12. Prelim. Results – changes in nitrogen fertilization and GHG emissions from climate change and policies Nitrogen fertilizationGHG emissions

13. Prelim. Results – changes in vascular plant species richness on farms from climate change and policies Schönhart et al., under review

14. Discussion Increasing productivity from climate change on average in the landscape In line with some of the literature, but not all What about extreme weather events? Declining intensity on grasslands on average counter-intuitive to economic reasoning – may indicate rigidity (in the model) for forage markets and livestock expansion Increasing farm incomes on average from assumed mitigation and adaptation policies Mitigation policy increases environmental quality at the cost of public budgets and agricultural production Flexibility from adaptation shows trade-offs between ag. production and env. protection Location determines impacts Heterogeneous climate change impacts among regions and farms Not only latitude but altitude to be considered as well in impact studies

15. Conclusions & Outlook High spatial resolution creates interfaces to disciplinary models and indicators Challenging data & modelling demand Increasing productivity can increase intensification pressures Threatened permanent (extensive) grasslands and landscape elements, but subject to resource constraints, costs and prices Future RDP and environmental policy design (e.g. WFD) may need to take changing productivity into account Future research: analyze uncertainties & environmental impacts Ensembles of crop and grassland models Sensitivity analysis on economic input parameters Alternative model settings to test model uncertainty

16. Outlook Landscape visualization Source: Schauppenlehner (2015)

17. Outlook indicator for landscape appearance Schönhart et al., under review

18. Martin Schönhart| martin.schoenhart@boku.ac.at This presentation was prepared within the project BiodivERsA/FACCE-JPI Project TALE funded by the Austrian Science Fund (FWF): [I 2046-B25] as well as within the FACCE-JPI MACSUR project supported by BMLFUW.