1. LAND Statistical Information Systems Exploitation of data from the Community's LUCAS survey Lot 2 State of Progress Gerd Eiden, LANDSIS g.e.i.e. Eurostat Working Group Agri-Environmental Indicators 3rd and 4th December 2002

2. LAND Statistical Information Systems Lucas Lot 2: Aim and Objectives To propose and quantify concrete (agri-) environmental indicators according to COM(2001) 144 and based on LUCAS data To elaborate recommendations for improved LUCAS survey in 2003

3. LAND Statistical Information Systems Focus of LUCAS data analysis (2002): Methodological and conceptual questions:  Indicator 24: Resource depletion: Land Cover change -------------------------  Indicator 35: Impact on landscape diversity (Indicator 32: Landscape state (group b) - LU Matrix) -------------------------  Indicator 33: Impact on habitats and biodiversity -------------------------  Indicator 23: Soil erosion -------------------------  Indicator proposals on Agri-environmental indicators based on LUCAS Phase 2

4. LAND Statistical Information Systems Indicator 35: Impact on landscape diversity LUCAS: Segment (PSU) Transect Approach: Landscape metrics to capture spatial properties of the segment Method of M.F. Slak Crucial Question: Are 10 points (SSU’s) adequate?

5. LAND Statistical Information Systems Indicator 35: Impact on landscape diversity Simulation of LUCAS segments using French TERUTI data How are changes reflected in LUCAS compared to TERUTI?

6. LAND Statistical Information Systems Indicator 35: Impact on landscape diversity Results: From a conceptual point of view landscape metrics can be applied on just 10 points Compared to TERUTI, LUCAS segments do not necessarily reflect the identical structural properties, but the regional pattern is similarly reflected LUCAS segments “over” pronounce changes Segment design: indications that a LUCAS segment composed of 4 lines (20 SSU’s) would be a compromise

7. LAND Statistical Information Systems Indicator 35: Impact on landscape diversity Proposal: (1) Characterisation of structural properties of each PSU by means of four different indices: Number of land cover classes (richness) Shannon Diversity Index (diversity) Interspersion and Juxtaposition Index (spatial arrangement) INT (heterogeneity/homogeneity) (2) Changes of indices values in time as indication of structural changes (3) Further development of method of M.F. Slak

8. LAND Statistical Information Systems Indicator concept: Linear features as elements with several environmental functions: buffer and habitat State and change in linear habitats (boundary features in agricultural landscapes) Potential data source: LUCAS transect data Indicator 33. Impact on habitats and biodiversity (group c)

9. LAND Statistical Information Systems Indicator 33. Impact on habitats and biodiversity (group c) Approach: Analysis of sequences of land cover codes and linear features and their “environmental” significance Transect sequence …. Ba – 2 – Ba …. SSU N° 11 SSU N° 12 Transect Code sequence: Ba 2 Ba SSU N° 13 (arable land) (green linear) (arable land) SSU N° 14 SSU N° 15

10. LAND Statistical Information Systems Indicator 33: Impact on habitats and biodiversity (group c) Example: “environmental beneficial” sequence (good agricultural practice): Ba – 1 or 2 (arable land - green linear features) Number in 2001: 4291 Sequence with negative environmental effects: Ba – 5 or 6 (arable land – water courses) Number in 2001: 2794

11. LAND Statistical Information Systems Indicator 33: Impact on habitats and biodiversity (group c) Proposal: Identification and quantification of environmentally relevant transect sequences  Observation of changes in time Characterisation of transects with regards to presence of linear features (sequences)  Observation of changes in time

12. LAND Statistical Information Systems Indicator 24: Resource depletion: Land Cover change Indicator concept: Matrix of changes in land cover (LC) in order to track developments Proposal: Post classification (combination and aggregation of land use/land cover) Establishing land cover/land use matrices Analysis of stock and flows

13. LAND Statistical Information Systems Indicator 24: Resource depletion: Land Cover change Creation of a post classification by combining Land Cover and Land Use Codes: Land CoverLand Use Combination U11pastures and meadows E01U36public parks U37residential gardens Fully exploitation of LUCAS data Added value for change analysis

14. LAND Statistical Information Systems Indicator 24: Resource depletion: Land Cover change level 1level 2Number of SSU’s % from total SSU’s I.Artificial landI.1built up and non built up areas25683,0 I.2transport infrastructure18062,1 I.3artificial green22552,6 II.Agricultural landII.1arable land1429816,6 II.2permanent crops33343,9 II.3grassland1130213,1 II.4fallow land21632,5 II.5mixed agricultural land 2070,2 III.WoodlandIII.1broadleaved76548,9 III.2coniferous1476917,1 III.3Mixed62267,2 IV.Semi natural landIV.1woodland41224,8 IV.2shrubland55796,5 IV.3grassland10761,2 IV.4wetland30563,5 IV.5bare land22902,7 V.Water bodies35644,1

15. LAND Statistical Information Systems Indicator 24: Resource depletion: Land Cover change Analysis of LC/LU flows Conversion Modification Extensification/ Intensification Afforestation Deforestation Development Reclamation

16. LAND Statistical Information Systems Indicator 23: Soil Erosion Indicator concept: Risk assessment (vulnerability, potential soil erosion risk) LUCAS information: Presence of visible soil erosion damages during field observation Rills Gullies Accumulation

17. LAND Statistical Information Systems Indicator 23: Soil Erosion First results: Validation show that field observation method on visible soil erosion damages is a feasible approach Consistency to be improved Limitation: non-recurring observation of sporadic soil erosion events Time of observation in May/June  Incomplete/partial picture about the current state due Cartography: Eurostat

18. LAND Statistical Information Systems Indicator 23: Soil Erosion Best practice: repeated observation according to occurrence of rainfall events and crop calendar Crucial question: How can the incomplete information provided be used? Proposals are currently under discussion: Long term monitoring of measures against soil erosion Validation of soil erosion models Link between Farmers interview – Soil erosion observation Integration of soil erosion issue in Farmers Interview

19. LAND Statistical Information Systems Elaboration of indicator proposals based on the Farmers Interview Complementary information for the following Agri-environmental indicators: Regional levels of good farming practice (indicator 2, group b) Quantities of nitrogen (N) and phosphate (P) fertilisers used (indicator 8, group a) Soil surface nutrient balance, incl. indicator 8: fertiliser use (indicator 18, group a) Consumption of pesticides (group a/c, indicator 9) Land use: cropping/livestock patterns (group a/c indicator 13) Area under nature protection (indicator 4, group b)

20. LAND Statistical Information Systems Elaboration of indicator proposals Tasks: Review and assessment of the questionnaire regarding information return for Indicators concerned on agricultural practices and their positive/negative effect on the environment Preliminary Results: A set of modifications/ precision of questions are proposed in order to retrieve concrete information on “environmentally friendly” agricultural practices such as: Farming intensity (based on the cultivated crops, rotation system, Nutrient balance Framing practices (conservation tillage, drilling etc, pesticide usage. )

21. LAND Statistical Information Systems Preliminary Conclusions LUCAS provides harmonised and precise data on land cover and land use at EU level and thus a unique data source for: Indicator 24: Resource depletion: Land Cover Change Indicator 32: Landscape State - LU Matrix Indicator 35: Impact on Landscape Diversity … complementary information for: Indicator 23: Soil Erosion Indicator 33: Impact on habitats and biodiversity The farmers interview offers a flexible tool to retrieve information on agricultural practices which is complementary to FSS data. Adaptations and modifications for improvement of the LUCAS survey and farmers interview necessary.