1. FORECOM Project meeting May 2014 Land‐use modelling in Switzerland using land use statistic data

2. FORECOM Project meeting May 2014 Socio-economic processes are strong drivers of land-use change across Europe Land abandonment has been a dominant process Urbanisation is increasing at a rapid rate Increasing pushes towards renewable energy sources = Unknown extent and location of land use changes Unknown impact on landscape services Context

3. FORECOM Project meeting May 2014 Over-arching processes – Population growth – Economic growth – Political change new energy policy conservation policy, etc Storylines for future scenarios to 2035 – Related to IPCC storylines for development (A1, A2, B1, B2) Drivers of land cover change – Land abandonment – Urban sprawl – Land use intensification Land cover change scenarios

4. Self-sufficiency, Regionally centered development, high ecological concerns (B2) ¨ Driving forces Population Economy …. More regionalMore global More intervention Less intervention Globalisation, High global economic growth but low Swiss growth (A1) Globalisation but emphasis on services, high ecological concerns. Low Swiss growth (B1) Heterogeneous world, regionally centered growth, (comparatively) high economic growth for Switzerland (A2)

5. Self-sufficiency, Regionally centered development, high ecological concerns (B2) ¨ Driving forces Population Economy …. More regionalMore global More intervention Less intervention Globalisation, High global economic growth but low Swiss growth (A1) Globalisation but emphasis on services, high ecological concerns. Low Swiss growth (B1) Heterogeneous world, regionally centered growth, (comparatively) high economic growth for Switzerland (A2) Low population growth Average technological innovation Increased food importation Low levels of policy-led restrictions on development Very low - no population growth Low technological innovation Increased food importation Policy-led restrictions on development Support for subsidies Medium population growth Average technological innovation Strong support for local agriculture Strong policy-led restrictions on development Strong support for subsidies High population growth High per capita urban demand Low support for subsidies Low to no policy-led restrictions on development

6. FORECOM Project meeting May 2014 Swiss land-use statistics (Arealstatistik der Schweiz) Aerial photography interpretation 100m grid = each point represents 1ha 72 categories of land-use/cover in theme areas – Settlement and urban – Agricultural areas – Wooded areas – Unproductive 3 time points – 1979/85 – 1992/97 – 2004/2009 Base dataset 1985 1997 2009

7. Land use/land cover types classification Closed Canopy Forest Pasture Agriculture Arable Agriculture Urban Areas Open Forest/ Scrub Overgrown Areas

8. 1985 1997 2009 Arealstatistik Land-use suitability 1ha resolution Land cover change scenarios Agricultural change -Land abandonment, marginal open areas to forest -Agricultural intensification Urbanisation - high density housing - new settlements Maps of land-use change scenarios Initial State Land use demand Dyna-CLUE Modelling framework (P. Verburg, University of Amsterdam) Land use suitability Environmental data

9. Biogeographical (Static, 1ha) Continentality indexCSD/DEM25 (Zimmermann & Kienast 1999) Yearly moisture index CSD/DEM25 (Zimmermann & Kienast 1999) Yearly direct solar radiation CSD/DEM25 (Zimmermann & Kienast 1999) Precipitation average growing seasonCSD/DEM25 (Zimmermann & Kienast 1999) No. of summer precipitation daysCSD/DEM25 (Zimmermann & Kienast 1999) ElevationDEM100 SlopeDEM100 Sine of aspect (east)DEM100 Cos of aspect (north)DEM100 Soil permeabilitySoil suitability maps BLW 2012 Soil stoninessSoil suitability maps BLW 2012 Soil suitability for agricultureSoil suitability maps BLW 2012 Socio-economic (temporally variable, per Gemeinde) Taxable income per tax paying residentFederal Office for Statistics Percentage inhabitants employed in primary sectorFederal Office for Statistics Public Transport accessibilityFederal Office for Spatial Planning Infrastructure (temporally variable, 1ha) Distance to major roadsVector25 Distance to access roadsVector25 Neighbourhood variables No. of neighbours in classes (Urban, closed forest, agriculture) Distance to forest Explanatory variables

10. Model suitability for land use type Landcover (AS) Explanatory variables/ Environmental data Logistic Regression Modelling Land use suitability Random Forests Maximum Entropy

11. FORECOM Project meeting May 2014 Cross correlation analysis, removal of highly correlated explanatory variables Sampling within each land-use type Unequal across land cover types ~5% of total points Sampling presence and absence Minimum 1km apart to avoid spatial autocorrelation issues Small classes (overgrown) fewer samples Capturing within class variability – geographical and environmental space Model averaging Every combination of explanatory variables to find best fit model (AIC) Averaging process to determine coefficient for each explanatory variable Logistic regression

12. FORECOM Project meeting May 2014 Population growth scenarios defined by the Swiss Federal Statistics Office Per capita urban demand (Swiss Federal Statistics Office) – Mean – Upper and lower 95% CI bounds Agricultural demand related to population and level of imports Land cover change restrictions representing policy and planning – Conversion restrictions – Spatial restrictions Common to all scenarios – Forests and current National Parks/protected areas are ‘sacred’ Quantification of Scenarios

13. Trend Scenario Linear Interpolation of 1985-1997-2009 trend in growth (or reduction) of land use classes A1 (Global/Low Intervention) BfS ‘Low’ population growth scenario, mean urban area demand per capita No further spatial restrictions A2 (Regional/Low Intervention) BfS ‘High’ population growth scenario, high urban area demand per capita Weighting of urban suitability to reflect improved public transport connectivity in regional areas No further spatial restrictions B1 (Global/High Intervention) ‘Stagnation’ scenario for population growth (no growth), low urban area demand per capita Restrictions on urbanisation through exisiting building zones (‘Bauzone’) Restrictions on conversion from pasture to overgrown above 900m asl Increased demand for Agriculture B2 (Regional/High Intervention) BfS ‘Medium’ population growth scenario, mean per captia urban area demand Restrictions on conversion from pasture to overgrown above 900m asl Weighting of urban suitability to reflect improved public transport connectivity in regional areas Urban growth permitted outside of ‘Bauzone’ -regionalisation

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15. 15 A1 Global/low intervention

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18. 18 Maps

19. FORECOM Project meeting May 2014 Results: land cover transitions UrbanisationLand abandonment Reforestation

20. FORECOM Project meeting May 2014 Strongest scenario is A2 (regionalisation, low intervention) – Strong trend to urban sprawl, especially in lowlands – Land use intensification in lowlands – Land abandonment in Alps – Concentration of growth despite weighting for regionalisation Population growth is key driver of land cover change, but Planning/Policy restrictions can have mitigating control – Conservation policy to prevent land abandonment – Building zone controls Summary Key Results

21. FORECOM Project meeting May 2014 Questions? Thanks Swiss Federal Institute for Snow, Forest and Landscape research, WSL

22. FORECOM Project meeting May 2014