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Forest cover change modelling: future scenarios

Forest cover change modelling: future scenarios. Forest cover change scenarios – general approach. Map current forest / land cover Identify over-arching processes Climate change Population growth / demographic change Economic growth Political change new energy policy

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Forest cover change modelling: future scenarios

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  1. Forest cover change modelling: future scenarios

  2. Forestcoverchangescenarios – generalapproach • Mapcurrentforest/landcover • Identifyover-archingprocesses • Climatechange • Population growth/demographicchange • Economicgrowth • Political change • newenergypolicy • conservationpolicy, etc • Definestorylinesforfuturescenarios • Identifydriversofcoverchange • Land abandonment • Policy/planning • Urban sprawl • Quantifyfuture ‘demands’ forlanduse/ forest

  3. Forestcoverchangescenarios • Climate Change • Agriculturalchange • Land abandonment, marginal open areastoforest • Agriculturalintensification • Urbanisation • newsettlements Currentlandcover Land usedemand Initial State Land-use/forestsuitability Dyna-CLUEModellingframework (P. Verburg, University of Amsterdam) Land usesuitability Mapsoflandcover/forestcoverchangescenarios Environmental Data/explanatory variables

  4. CLUE (Conversion of Land Use and its Effects) model • one of the mostfrequently used land use models worldwide • is based on the spatial allocation ofdemands for different land use types to individualgrid cells

  5. Overview of modelingprocedure - CLUE Verburg 2010

  6. Dyna-CLUE – allocation procedure Verburg & Overmars 2009

  7. Current land use scenario modelling in Switzerland • Focus on landusechange in general (not onlyforest) • 6 landuseclasses • WholeofSwitzerland • 5 futurescenariosto 2035 • Largelyfocusing on populationandagriculturaldrivers – noclimatechange

  8. Land use/land cover classes Closed Canopy Forest Open Forest/ Scrub Overgrown Areas Urban Areas PastureAgriculture ArableAgriculture

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

  10. Quantification of Scenarios • Population growth scenarios defined by the Swiss Federal Statistics Office • Per capita urban demand (Swiss Federal Statistics Office) • 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’

  11. Land coverchangescenarios • Agriculturalchange • Land abandonment, marginal open areastoforest • Agriculturalintensification • Urbanisation • high densityhousing • newsettlements Swiss landusestatistics 1985 1997 Land usedemand Initial State 2009 Land-usesuitability 1ha resolution Dyna-CLUEModellingframework (P. Verburg, University of Amsterdam) Land usesuitability Mapsof land-usechangescenarios Environmental data

  12. Adaptation to forest cover change scenario modelling for FORECOM • Same generalapproach • Re-focus on over-archingprocessesofrelevancetoforestcoverchange, and in studyarea (includingclimatechange) • Adaptscenariostorylinestoreflectprocessesanddriversimportantforforestcoverchange

  13. Adaptation to forest cover change scenario modelling for FORECOM Suitability • includelong-term forestcoverchangeperspective • Incorporatefindingsfrom TASK 6 Storylines – newaspects • Climatechange • Renewableenergy – bioenergyand/orinfrastructureconstruction • Tourism – urbanisation/infrastructure

  14. Adaptation to forest cover change scenario modelling for FORECOM ‘Interventions’ • Changestoforestprotectionlaws • Conservationprotections • Alpine Agricultureor ‘oldgrowth’ forest

  15. Implementation of the Dyna-CLUE model in the Polish Carpathians: STEPS • tests of simple scenarios of future forest change with Dyna-CLUE (variables like elevation, radiation, distance to roads, distance to built-up areas, population, employment , distance to forest boundary, neighbourhood) • development of full storylines for possible future forest cover change with full list of variables – 5 to 6 possible scenarios • comparison with Swiss models/storylines • simplification of the Polish models (data availability) – 2-4 final scenarios • implementation of scenarios in Dyna-CLUE

  16. Swiss Federal Institute for Snow, ForestandLandscaperesearch, WSL Thanks Questions?

  17. Explanatory variables • Biogeographical (Static, 1ha) • Continentality index CSD/DEM25 (Zimmermann & Kienast 1999) • Yearly moisture index CSD/DEM25 (Zimmermann & Kienast 1999) • Yearly direct solar radiation CSD/DEM25 (Zimmermann & Kienast 1999) • Precipitation average growing season CSD/DEM25 (Zimmermann & Kienast 1999) • No. of summer precipitation days CSD/DEM25 (Zimmermann & Kienast 1999) • Elevation DEM100 • Slope DEM100 • Sine of aspect (east) DEM100 • Cos of aspect (north) DEM100 • Soil permeability Soil suitability maps BLW 2012 • Soil stoniness Soil suitability maps BLW 2012 • Soil suitability for agriculture Soil suitability maps BLW 2012 • Socio-economic (temporally variable, per Gemeinde) • Taxable income per tax paying resident Federal Office for Statistics • Percentage inhabitants employed in primary sector Federal Office for Statistics • Public Transport accessibility Federal Office for Spatial Planning • Infrastructure (temporally variable, 1ha) • Distance to major roads Vector25 • Distance to access roads Vector25 • Neighbourhood variables • No. of neighbours in classes (Urban, closed forest, agriculture) • Distance to forest

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