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Summary of the ELPEN project results, May 2003

Summary of the ELPEN project results, May 2003. Introduction to the ELPEN project. The. Consortium. What is ELPEN ?. A network that: can answer specific questions about the economic, environmental and social impacts of policy related to livestock systems

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Summary of the ELPEN project results, May 2003

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  1. Summary of the ELPEN project results, May 2003

  2. Introduction to the ELPEN project

  3. The Consortium

  4. What is ELPEN? A network that: • can answer specific questions about the economic, environmental and social impacts of policy related to livestock systems • uses state of the art technology: the ELPEN system

  5. The ELPEN system was developed on the basis of the End User Group requirements, which were: • Integrating economic, environmental and social impacts (DG Agri & Env) • Spatially explicit (DG Agri & Env)regional scale • Focus on land dependent systemsinitial focus on dairy systems (DG Agri) • A flexible expert tool, not a desktop tool

  6. The ELPEN system is: A decision support system containing: • EU statistical and geographical data • An ELPEN farm typology • A reference farm database • Expert knowledge (simple rules and models) • Meta data explaining data and knowledge • Fast procedures to process large amounts of data • Procedures to display output maps and tables

  7. The ELPEN system useris: An expert who supports policy makers by answering specific questions by: • Adding and combining the stored EU statistical and geographic data • Adding relevant expert knowledge and meta data for each new policy question • Generating output maps and tables • Reporting on the results • Maintaining and improving the utility of the system for policy impact assessment:

  8. Statistical and Geographic data Farm typologies, simple models and expert rules Spatially explicit modeling results (maps, tables) Policy Impact Assessment with the ELPEN system Policyquestion Spatially explicit socio-economic and environmental impacts

  9. Explanationof The ELPEN System

  10. System data (e.g units) Explanation of The ELPEN System Statistical data Geographic data ELPEN Farm typology Reference Farms (examples of ELPEN farm types) Schemes (knowledge rules) Cases (results, obtained by applying schemes on data)

  11. ELPEN system: User interface Mapview Meta data view and technical details Browser Table view

  12. Statistical Data:A part of the following EU data sets are incorporated in the ELPEN system: • Farm Accountancy Data Network (FADN) Commission of the European Communities, DG Agriculture in ELPEN (March 2003): 1990-91, 1997-98, 1999-2000 • Farm Structure Survey (FSS/Eurofarm) Eurostat in ELPEN (March 2003): 1990, 1997 • Regional data bank (REGIO) Eurostat: in ELPEN (March 2003): 1980 - 2001 • Relation tablesStored relations between different data sets

  13. Statistical Data:Relation tables Stored relations between different data sets: e.g: The geographic relations between the different statistical data sets is established by: Harmonisedregions (Harm)

  14. Geographic relations: harmonised regions HARMonised regions make it possible to integrate data from different statistical sources by applying them to the same geographic entities

  15. Harm1 Harm2 Geographic relations: harmonised regions HARMonised regions make it possible to integrate data from different statistical sources by applying them to the same geographic entities

  16. ELPEN regions: 23 Harm1 Region Harm1 Region Harm1 Region Geographic relations: harmonised regions ELPEN regions: a clustering of Harm regions, a pragmatic solution to enlarge regions in order toprevent disclosure problems when displaying data concerning less than 15 farmsin one region Country12 & 15 EU Other geographic regions in ELPEN:

  17. Example of stored data:Subsidies on livestocktotal in kEuro per Harm1 (1999) Note: Switserland is not EU member Example data

  18. Example of computed data:Subsidies on livestockper Livestock Unitin kEuro per Harm1 (1999) Note: Switserland is not EU member

  19. Nr of livestock unitsof Total Bovineper Harm2 (1990) Note: Finland, Sweden, Eastern Germany and Austria were not EU members in 1990 Switserland is not EU member Example data

  20. Inhabitants per HARM2 (1999)

  21. Geographic Data: overview Administrative Regions Designated areas Land cover: Corine & Pelcom Elevation Soil, Climate Environment (Nitrogen Vulnerable Zones, N-leaching) Landscape (not yet available)

  22. ELPEN Regions:cluster of administrative regions

  23. Designated areas:Less Favoured Areas1997

  24. CorineLand Cover e.g: pastures (grid map: 1x1km) A fragment of the meta data on Corine Land Cover (CLC): “CLC was elaborated based on the visual interpretation of satellite images (SPOT, LANDSAT TM and MSS). Ancillary data (aerial photographs, topographic or vegetation maps, statistics, local knowledge) were used to refine interpretation and the assignment of the territory into the categories of the CORINE Land Cover nomenclature. The smallest surfaces mapped (mapping units) correspond to 25 hectares. Linear features less than 100 m in width are not considered. The scale of the output product was fixed at 1:100.000. Thus, the location precision of the CLC database is 100 m.”

  25. PelcomLand Cover: e.g: grass(grid map: 1x1km) A fragment of the meta data on Pelcom: “The Pelcom land cover database is calculated from Earth Observation images using an algorithm that computes the first and second minimum distances for each AVHRR image pixel based on the spectral signatures, and as a result, it derived the first best class ('highest probability') and the second best class ('second highest probability') for each pixel.”

  26. Elevation

  27. Elevation: classifiedbelow 300m300-600mabove 600m Elevation This classification corresponds with the FADN data

  28. ELPEN Farm Typology: why? to differentiate farms according to: • responses to policy • impact on the social and bio-physical environment and: • to aggregate FADN farm level data into farm types that: • can be associated with reference farms in the field

  29. ELPEN Farm Typology: how? • Selection of classifying variables using expert knowledge of systems in the field(e.g. CEAS-study 2000) • Cluster analysis on FADN-data to determine usefulness of variables and threshold values

  30. All farms in EU ELPEN Farm typology Grazing livestocksectors (% cattle and % milk in production value) Dairy Mixed Beef Dairygrazing MixedDairy&meat Meatgrazing Dairy Mixed Meat Dairy Mixed Meat Size (Livestock Units (LU) grazing livestock) Cattle Sheep Goat Small scale < 20 LU Medium scale 20-100 LU Largel scale > 100 LU Intensity (input costs for fertilizers, pesticides and concentrates) Low input (< 150 €/ha) Medium input (150-600 €/ha) High input (>600 €/ha) Land use(% grass in total Utilised Agricultural Area (UAA), LU per ha and grazing outside UAA) Off farm grazing Off farm produced fodder systems Permanent grass systems Grassland systems Arable systems Sector: Grazing livestock farms(>50% production value from grazing livestock) ELPEN Farm typology: result

  31. Number of farm types per ELPEN region Click on region How many and what ELPEN farm types are located in what regions?

  32. Number of farm types per ELPEN region Sector: Grazing livestock Production type: Meat Land use type: Permanent grass Intensity: Low input Size: Medium scale Livestock type: Cattle

  33. Example time series:Change in LU on dairy cattle farms 1990 - 1999 (Index 1990=1) decreaseIncrease < 15 dairy cattle farms or missing data Note: Finland, Sweden, Eastern Germany and Austria were not EU members in 1990 Switserland is not EU member example time-series

  34. Note: Finland, Sweden, Eastern Germany and Austria were not EU members in 1990 Switserland is not EU member Example time series:Change in nr of dairy cattle farms 1990 - 1999 (Index 1990=1) decreaseIncrease < 15 dairy cattle farms or missing data

  35. Of each (group of) farm type(s) in a region several profiles can be computed that characterise these farm types: • Profiles: • Environmental • Structural • Economic • Social • Regional

  36. Profiles of farms per region e.g:arable medium input system Nr of represented farms per region Click on region

  37. Profiles of farms per region e.g:arable medium input system Structuralprofile Nr of represented farms per region Click on region Total livestock units present on all farms of this type in the region of Acquitaine, being 1.2 % of the total LU of all farms of this type in the EU

  38. Profiles of farms per region e.g: arable medium input system Environmentalprofile Structuralprofile Nr of represented farms per region Click on region Stocking density on grassland, being 6.6% under EU average for this farm type Total livestock units present on all farms of this type in the region of Acquitaine, being 1.2 % of the total LU of all farms of this type in the EU

  39. Reference farms are:Real example farms of ELPEN farm types A) General questions B)Land related questions C) Grass and Fodder D) Mechanisation E) Dairy cows F) Beef cattle G) Sheep H) Goats J) Other grazing livestock K) Livestock housing / welfare L) Questions about Agricultural Policy Changes The data are gathered using a questionnaire with 93 questions about 10 aspects ofthe farm and 7 policy questions

  40. B) LAND RELATED QUESTIONS 18) altitude < 300m, 300-600m, > 600m 19) gradient of land (estimate 20) soil quality (1 excellent - 5 poor) 21) layout of farmland (scattered - consolidated) 22) farm size 23) policy status 24) use of land 25) ownership of farm: land owned/rented/leased 26) types of crops (excluding fodder and grass) 27) fodder production (roughage other than grass) 28) conservation of grass 29) arable land with vegetation cover 30) fertiliser use 31) pesticide use K) LIVESTOCK HOUSING / WELFARE 86) type of livestock 87) duration of housing 88) housing type 89) housing 90) grazing management 91) transport 92) visits by 93) main health problem Reference farms are:Real example farms of ELPEN farm types A) General questions B)Land related questions C) Grass and Fodder D) Mechanisation E) Dairy cows F) Beef cattle G) Sheep H) Goats J) Other grazing livestock K) Livestock housing / welfare L) Questions about Agricultural Policy Changes The data are gathered using a questionnaire with 93 questions about 10 aspects ofthe farm and 7 policy questions

  41. Data on reference farms per region (HARM1) Nr. of reference farms per region Click on region Data on reference farms can be viewed as follows

  42. Data on reference farms per region (HARM1) Data on Sheep Nr. of reference farms per region Click on region Data on reference farms can be viewed as follow

  43. Data on reference farms per region (HARM1) Data on land Nr. of reference farms per region Click on region Data on Sheep Data on reference farms can be viewed as follow

  44. Schemes Schemes contain the knowledge rules that are used to compute results Scheme-displays can be generated automatically by the system e.g. Rules to allocate livestock types per grid cell:

  45. Result: nr of lu dairy cows / grid cell % grazing area / grid cell Pelcom / grid cell Corine / grid cell Suppliers Scheme: Allocation of Dairy Cows(automatically generated by the system) Schemes Schemes contain the knowledge rules that are used to compute results Scheme-displays can be generated automatically by the system e.g. Rules to allocate livestock types per grid cell on the basis of FSS data: FSS data: nr of lu dairy cows / Harm2

  46. Cases: Cases use the schemes to compute results. Different results can be computed,using the same pre-programmed schemes and selecting different input data At the end of the ELPEN project (March 2003) the following cases were stored in the ELPEN system:

  47. Cases: overview • Allocation of Livestock basis: FSS / HARM2 and Land cover on 1km2 • Allocation of ELPEN Farm type groupsbasis: FADN / HARM1, Land cover, LFA, Altitude on 1km2 • Eutrophication risk • Economic Impacts of milk price reductionbasis: economic model, input: FADN data / farm type group • Environmental impacts of milk price reduction • Social: who stops and who continuesdecision path for LFA regions, input: reference farms

  48. Total Dairy cowsin LU / ha, 1990 (FSS) Allocation of FSS livestock data per 1*1 km grid cell Case: Allocation of FSS livestockdata per grid cell

  49. Case: allocation of ELPEN farm type groups • Desaggregation of FADN land use data per ELPEN farm type group from Harm1 or ELPEN region level to grid cell level, using geographic data: • Corine land cover • Altitude class (<300m, 300-600, >600m) • Less Favoured Areas

  50. Case: allocation of farm type groups Data Allocation items Aggregation level ha permanent pastures, rough grazing, fodder&crops/ HARM1 or ELPEN region Landuse groups/ELPEN farmsystem FADN Corine Land cover types ha LC type / grid cell ha UAA / LFA in HARM1ha UAA / Altitude in HARM1 LFA, Altitude/ELPEN farmsystem FADN LFA &Altitude LFA, Altitude regions ha LFA, Alt class / grid cell Allocated ELPEN farm system LU, UAA, nr farms / grid cell

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