forecom project meeting may 2014 forest cover change modelling: future scenarios

FORECOM Project meeting May 2014

Forest cover change modelling: future scenarios


Map current forest/land cover Identify over-arching processes

– Climate change– Population growth/demographic change– Economic growth– Political change

new energy policy conservation policy, etc

Define storylines for future scenarios Identify drivers of cover change

– Land abandonment– Policy/planning– Urban sprawl

Quantify future ‘demands’ for land use/ forest

Forest cover change scenarios – general approach

Current land cover Forest cover change scenarios

Climate ChangeAgricultural change- Land abandonment, marginal open areas

to forest- Agricultural intensificationUrbanisation- new settlements

Maps of land cover/forest cover change scenarios

Initial StateLand use demand

Dyna-CLUE Modelling framework

(P. Verburg, University of Amsterdam)

Land use suitability

Environmental Data/explanatory variables

Land-use/forest suitability


CLUE (Conversion of Land Use and its Effects) model

one of the most frequently used land use models worldwide

is based on the spatial allocation of demands for different land use types to individual grid cells


Overview of modeling procedure - CLUE

Verburg 2010

Dyna-CLUE – allocation procedure

Verburg & Overmars 2009


Current land use scenario modelling in Switzerland

Focus on land use change in general (not only forest)– 6 land use classes

Whole of Switzerland 5 future scenarios to 2035 Largely focusing on population and agricultural

drivers – no climate change


Land use/land cover classesClosed Canopy

Forest

Pasture Agriculture

Arable Agriculture

Urban Areas

Open Forest/ Scrub

OvergrownAreas

Self-sufficiency, Regionally centered development, high ecological concerns (B2)

¨Driving forcesPopulationEconomy

….

More regionalMore global

Mor

e in

terv

entio

nLe

ss in

terv

entio

n

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)


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’

Quantification of Scenarios

19851997

2009

Swiss land use statistics

Land-use suitability 1ha resolution

Land cover change scenarios

Agricultural change- Land abandonment, marginal open areas

to forest- Agricultural intensificationUrbanisation- high density housing- new settlements

Maps of land-use change scenarios

Initial StateLand use demand

Dyna-CLUE Modelling framework

(P. Verburg, University of Amsterdam)

Land use suitability

Environmental data


Adaptation to forest cover change scenario modelling for FORECOM

Same general approach Re-focus on over-arching processes of relevance to

forest cover change, and in study area (including climate change)

Adapt scenario storylines to reflect processes and drivers important for forest cover change


Adaptation to forest cover change scenario modelling for FORECOMSuitability include long-term forest cover change perspective Incorporate findings from TASK 6Storylines – new aspects Climate change Renewable energy – bio energy and/or infrastructure

construction Tourism – urbanisation/infrastructure


Adaptation to forest cover change scenario modelling for FORECOM

‘Interventions’ Changes to forest protection laws Conservation protections

– Alpine Agriculture or ‘old growth’ forest


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


Questions?

Thanks

Swiss Federal Institute for Snow, Forest and Landscape research, WSL

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

Explanatory variables

forecom project meeting may 2014 forest cover change modelling: future scenarios

Documents

land use change

swiss land use statisticsland

clue conversion of land

different land use types

forest cover change

population growth scenarios

high economic growth

centered growth