1. Linking land cover change to pressures on biodiversity http://www.creaf.uab.es/biopress/

2. Question: How have past changes in land cover affected Biodiversity ? Why: Legislative imperative to protect the environment. EEA is our key stakeholder How: Measuring land cover change by manual interpretation of aerial photos Pressure – State – Impact Funded by EC – Framework 5: Project coordinator: Dr. France Gerard ffg@ceh.ac.uk Tel: +44(0)1487 773381 Centre for Ecology and Hydrology Monks Wood, Abbots Ripton PE28 2 LS, UK http://www.creaf.uab.es/biopress/

3. CORINE LC Aerial photos From To Land cover Conversion matrix Human Population Census Statistics on agriculture Transport Data Etc… Region Specific Pressures Abandonment Intensification etc… Cause & Effect Pressures Zone Stratification & Extrapolation Biodiversity Semi quantitative Pressure – state model 1950 Phase I Phase II 1990 EO CORINE LC 2000 Aerial photos EO 2000+

4. Key steps – land cover change (1950 – 2000) Quality assessment for pilot sites Transect interpretation: Change matrices (1950,1990,2000) Extrapolating the matrices to produce a European land cover change product Stratification strategy Sampling sites across Europe: 100 windows, 50 transects Location, acquisition, pre-processing of aerial photography Windows: 1950 Transects: 1950, 1990, 2000 Interpreters rules: 2 manuals Windows: CORINE Land Cover backdating Transects: photo to photo interpretation Workshop: Training of interpreters CORINE backdating: Change matrices (1950-1990) Assessment of results by external experts

5. Land Cover Change data Spatial framework for integration, extrapolation & reporting RS of landscape features for quantifying pressures Improve pressure - state model and assessment of impact on biodiversity Error Propagation Integrating with non RS data to quantify pressures Key steps – Pressure-State-Impact

6. Sample of Natura2000 Sites 75 Windows: 30 x 30 km (black) 59 Transects: 2 x 15 km (red) Focussing on 4 Annex-I habitats which are found in main bio- geographical regions: (i) Freshwater habitats, (ii) Natural and semi-natural grassland formations, (iii) Raised bogs and mires and fens and (iv) Forests. Stratification: Biogeographical Regions Map of Europe (BRME)

7. Sampling Area Distribution of window area with respect to biogeographic regions as defined by the Biogeographic Regions Map of Europe (BRME)

8. Sampling Area Area proportion of Europe calculated from the Biogeographic Regions Map of Europe (BRME)

9. Change matrices for ~100 Natura2000 sites Backdating CORINE 1990 with aerial photos of the 1950ies 30 km x 30 km windows = total of 90,000 km 2

10. Backdating CORINE land cover 1990 to 1950ies 30x30km windows centred on Natura2000 site CORINE LC90 on aerial photos of 1950iesCORINE LC 1990 Area around Zaventem airport, Brussels, Belgium

11. Photo to Photo Interpretation 15 x 2 km transects from least intensive to most intensive Catalonia, Spain Semi natural shrub & woodlands Town 1950 1990

12. 1956 1998 Catalonia, Spain

13. Window 185 Czech Republic 231 Pasture 242 AgComplex 243 Ag mosaic 211 Arable 112 Built 131 Minerals 132 Dumps 313 Mixed 324 Transitional 312 Coniferous 322 Moors Marianskolazenske hadce (1659ha) 1950 Change 1990 Fluxes > 100ha Fluxes > 1000ha Fluxes > 5000ha

14. Window 210 Belgium 112 Urban 121 Industrial 124 Airport 142 Sports 242 Agcomplex 231 Pasture 243 Agmosaic 211 Arable 311 Brd wood 313 Mxd wood 324 Scrub Poelbos-Marais de Jette (90ha) Valleigebied tussen Melsbroek... (1445ha) Zoniënwoud (2761ha) Fluxes > 100ha Fluxes > 1000ha Fluxes > 5000ha 1950 Change 1990

15. Germany Transect - De1 All transect and window data are stored in a common database

16. Germany Transect – De8 All transect and window data are stored in a common database

17. The Netherlands: Arable into harbour & build-up: Urbanisation

18. Finland: Peatbogs into arable land: Intensification

19. Germany: First intensification then abandonment 1990 1950 2000

20. Land cover to pressure conversion TO\T1 1.1.1.1.1.2.1.2.1.1.2.2.1.2.3.1.2.4.1.3.1.1.3.2.1.3.3.1.4.1.1.4.2.2.1.1.2.1.2.2.1.3.2.2.1.2.2.2.2.2.3.2.3.1.2.4.12.4.2.2.4.3. 1.1.1. Continuous urban fabric UUUUUUUUUUUU 1.1.2. Discontinuous urban fabric UUUUUUUUUUUUUUU 1.2.1. Industrial or commercial units UUUUUUUUUUUU 1.2.2. Road and rail networks and associated land UUUUUUUUUUUUUUU 1.2.3. Port areas UUUUUUUUUUUUU 1.2.4. Airports UUUUUUUUUUUUUUU 1.3.1. Mineral extraction sites UUUUUUUUUUUUUUUUU 1.3.2. Dump sites U UIIIIIIIIII 6.3.2. Grasslands UUUUUUUUUUUIIIIIIII Priority rules Combination of more than one intensification OR relaxation per case The less natural the process, the more priority (Urbanisation > Intensification > Drainage > Deforestation > Abandonment > Afforestation) in intensification. The less natural the process, the less priority (Urbanisation < Intensification < Drainage < Deforestation < Abandonment < Afforestation) in relaxation

21. FINLAND - Riihimäki-Kytäjä

22. Loss of valuable open habitat types and ecotones Increase of pine forest with no biodiversity value Lake-and riverside fields with scattered farmhouses turned into managed forest Forest area that turn into urban- forest loss clearcuts- loss of valuable forest habitats Forest fragmentation loss a valuable habitat urban sprawl takes over agricultural land and forest IMPACT Impact on Biodiversity decrease of arable land and pastures afforestation-- intensification agricultural areas tuned into forest Forest and transitional woodlands turn into artificial surfaces Forest turned into transitional woodland Increase in artificial surfaces increase of major roads STATE Land Cover Changes IntensificationAfforestationDeforestationUrbanisation PRESSURES Economic trendsAgricultural policies Economic trends Subsidies Economic pressures Urban sprawl Demographic trends Transport network Urban sprawl DRIVING FORCES DPSIR - framework Finland - Riihimäki - Hyvinkää

23. PRESSURES Urbanisation Deforestation Afforestation Land Abandonment Intensification Drainage Why is it so difficult to select indicators? Pressures: How can indicators quantify them ? INDICATORS: Spatial Configuration Semantic Composition Temporal Distribution

24. Select indicators that can be used in the short term (even when imperfect) Identify indicators by pressure, but also by spatial configuration, semantic composition, and temporal distribution. Weighting indicators using a space-time assessment Priority, ranking, or value of indicators BIOPRESSs strategy: Bottom-up approach & use of analytical zoning Suitable spatial scales to tackle habitat information range from 1:5,000 to 1:100,000 and landscape maps are required as input to compute indicators with a spatial component. Suitable temporal scales are not that clear yet.

26. CORINE LC Aerial photos From To Land cover Conversion matrix Human Population Census Statistics on agriculture Transport Data Etc… Region Specific Pressures Abandonment Intensification etc… Cause & Effect Pressures Zone Stratification & Extrapolation Biodiversity Semi quantitative Pressure – state model 1950 Phase I Phase II 1990 EO CORINE LC 2000 Aerial photos EO 2000+ Socio economic Indicators Integration