RIKSDeSurvey Module 1.2 Module 1.2 Socio economic drivers Annual meeting 2006 INEA Istituto Nazionale di Economia Agraria UC3MUniversidad Carlos III de Madrid RIKS Research Institute for Knowledge Systems

RIKS DeSurvey Module Objectives of Module 1.2  Socio-economic drivers of desertification;  Development of a land use model:  Estimate socio-economic trends and associated land claims;  Dynamic processes: changes in demography, sectoral economic activity, employment levels, land uses (time dependant forecasts ≈ 30 yrs);  Spatially explicit analysis/representation;  At different embedded spatial entities: EU, National (country), Regional (NUTS2/NUTS3), Local (grid based entities ≤ 1km 2 );  Represent the interlinked processes at the different spatial entities.

RIKS DeSurvey Module Model structure: integrating 3 sub models Regional and national trends in Employment, population and agricultural utilized area Delineation of agricultural land ‘Geographical’ Feedbacks Constraints Pressures Externalities Cellular Automata Land use model WP 2.3 Agricultural land use WP 2.2 Economic growth model WP 2.1 Database development Model development Database development Model development integration

RIKS DeSurvey Module CA Loop WP Model structure: economic trends to land use Regional and national trends modelled by WP Land use at time T Suitability & Zoning & Accessibility & & CA Rules Land use at time T+1 This is a pivoting variable in linking the Bio-physical and the Socio-economic aspects of the problem at stake

RIKS DeSurvey Module Model structure: specification of agricultural land Socio-economic land uses Provided by WP Specification of Agriculture: WP Fully specified land use ? Specification of natural land Scope for further integration

RIKS DeSurvey Module Database development  Sources:  Farm Accountancy Data Network  International databases: EuroStat, OECD  National databases: Spain, Italy, Portugal  Now available:  Macro-population trends and related agricultural labour data, including: Work units (paid & unpaid) Utilized area National labour accounts  Land productivity by year, region, farm type, and farm size

RIKS DeSurvey Module Model development: Economic growth  Economy develops towards equilibrium state  Based on established and robust MOISEES model  Extended to include tourism sector  Extended to include construction sector  Reduced on the basis of relevance  Flexible region definitions: National, NUTS 2/3, Aggregates  Introduces EU / national level policy variables in the Integrated Assessment Model  Tax system, CAP, etc.  Output to Cellular Automata model  Agricultural Utilized Area per region  Employment in main economic sectors  Consistent scenario on population development

RIKS DeSurvey Module Model development: Agricultural land use  Multinomial model of farm level decisions  Dynamic model based on time series of FADN data  Integrate two types of input:  Demographic & organizational: prices, subsidies etc.  Site characteristics: topography, soil, climate etc.  Output is farm practice:  Type of production? (crop/cattle)  Management practices?  Estimated at farm level but transposed to be applied at as 1 km cell based model

RIKS DeSurvey Module Model development: Cellular Automata  The main factor determining locations of land use change is the neighbourhood of all location  The neighbourhood now extends to the whole map, integrating spatial interactions over different scales  The density of activities is determined by the value of a location  Allocation of activity (people, jobs) instead of land use (area)

RIKS DeSurvey Module Preliminary results, population Portugal DATA 1990 DATA 2000 Model 2000 Error null model Error model

RIKS DeSurvey Module Theoretical background in deliverables  Andea Fais & Iraj Namdarian:  Literature review of impact of socio-economic factors on land use dynamics  Ricardo Mora & Carlo San Juan  Literature review on agricultural economic and demographic factors influencing land use dynamics

RIKS DeSurvey Module Current priorities  Progress according to plan  But there are some immediate issues:  What will be the decision variable for the agricultural land use model?  How do we anticipate further model integrations ( )?