Berien Elbersen Maarten Hilferink Wim Nieuwenhuizen Marta Pérez-Soba Janneke Roos Alterra, The Netherlands Udine, 22 nov 2002 allocation of ELPEN farm systems

To determine environmental and socio-economic impacts we need: real farm data grouped in farm systems (survey information from representative farms to understand and model the farming practices and their behaviour) to locate the farm systems (to connect them to the environment they influence, e.g. social and (a)biotic circumstances, landscape, biodiversity) to determine how farm practices have impact on the environment (employment, eutrophication, acidification, habitat maintenance etc.)

Allocation exercises at a national level Objective: validation and improving the methods for allocation of animal categories Using: collecting statistical data on a lower regional level than NUTS 2, e.g. canton in France, grids of 5 km² in Denmark Countries: Denmark, France, The Netherlands, Portugal, Spain, UK (England & Wales and Scotland)

Method: 1) Regression analyses to estimate the influence (weight) of different variables on the number of animals 2) Use the regression formula to improve the allocation approach 5 in ELPEN 3) Compare these results with national data on the number of livestock on a lower territorial level 4) Compare the results of the old approach 5 with the national data and find out whether the new approach has better results.

CORINE Land cover classes Climate Altitude Soil type Accessibility (Denmark) Spatial variables Dairy cows Suckler cows Sheep dairy Sheep meat Goats Animal categories (nr per sub-region) Selection of relevant variables Multivariate Regression Analyses Regression formula Estimation of animal numbers at grid level Configuration in ELPEN system National data on grid level Conclusions on accuracy Conclusions on allocation in ELPEN

Dairy Cows France 1 Pastures 2 Complex cultivation patterns 3 Discontinuous urban fabric 4 Broad-leafed forest Dairy Sheep France 1 Natural grassland 2 Complex cultivation patterns 3 Transitional woodland/shrub 4 Non-irrigated arable land 5 Pastures Meat Sheep France 1 Pastures 2 Land principally occupied by agric. 3 Broad-leafed forest 4 Sclerophyllous vegetation Results France Cantons in France

Dairy Denmark: 1 Non-irrigated arable land 2 Complex cultivation patterns 3 Pastures 4 Land principally occupied by agric. Sheep Denmark 1 Pastures 2 Land principally occupied by agric. 3 Complex cultivation patterns 4 Non-irrigated arable land Conclusions of comparison: Approach 5: 50% of grid cells correct Using results regr analysis: 55 to 60% 5km grid data Results Denmark

The allocation should be improved The allocation rules must be: spatially and farm-/livestocktype specific Use of national data is not practical So: Use all the specific spatial and farm/livestock data we have in the ELPEN system for the allocation Conclusion for the allocation in ELPEN:

How to allocate (groups of) ELPEN farm systems on grid cell level? The available statistical data on the ELPEN farm systems are: FADN data on land use and livestock on HARM1 or ELPEN region level But also: LFA & altitude level + relation with EU farm type So: Use FSS data on corresponding EU farm types to desaggregate to HARM2 level Use Corine/Pelcom land cover data in correspondence with the land use data to desaggregate to grid cell level Use LFA & Altitude geodata on grid cell level to allocate the in FADN provided # of LU, UAA within these regions

Total of HARM regions: 11 farm systems (6 are missing) 56% of LU in ELPEN region 49% of UAA in ELPEN region HARM region 7c: 2 farm system types Livestock units 45308ha of UAA HARM region 7d: 2 farm system types Livestock units ha of UAA HARM region 7a: 3 farm system types Livestock units ha of UAA HARM region 7b: 4 farm system types Livestock units ha of UAA ELPEN region 7: 17 farm system types Livestock units ha of UAA Why do we need ELPEN regions?

Data Aggregation level Allocated ELPEN farm systemLU, UAA / Grid cell ELPEN farm system LU, UAA / HARM1 region LU, UAA / ELPEN region FADN Corine Pelcom Ha / Grid cellcorr.landcover groups Corr. EU farm types UAA / HARM2 regions FSS Allocation items FADN Landuse groups /ELPEN farmsystem UAA / HARM1 region UAA / ELPEN region FADN LFA, Altitude /ELPEN farmsystem LU, UAA / LFA,Alt in HARM1 LFA & Altitude Ha / Grid cellLFA, Altitude regions

Efs D in HARM1-y 14% + 18% = 32%21% + 9% = 30%35% + 3% = 38% 20% UAA in Harm2-a x 0.7=14% 30% UAA in Harm2-b x 0.7=21% 50% UAA in Harm2-c x 0.7=35% 60% UAA in Harm2-a x 0.3=18% 30% UAA in Harm2-b x 0.3=9% 10% UAA in Harm2-c x 0.3=3% 32% x LU Efs in HARM2-a 30% x LU Efs in HARM2-b 38% x LU Efs in HARM2-c Allocation of ELPEN farm system (group)s (EFS) 1) Desaggregate to HARM2 level using FSS data 70% UAA of EU farmtype A 30% UAA of EU farmtype B

Efs D in HARM1-y Allocation of ELPEN farm system (group)s (EFS) 2) Desaggregate to GRID level using Corine/Pelcom 600 ha perm grass 200 ha rough grazing 1000 ha fodder 5000 ha other crops 50 LU >150 d off farm grazing Corine/Pelcom land cover groups in HARM1-y 1200 ha pasture 200 ha extensive grazing areas 2000 ha compl cult pattern ha agr. area grid cell: 0.5 x ha pastures grid cell: 1 x ha extensive grazing areas Grid cell: 0.5 x ha compl cult pattern Gridcell: 0.1 x ha agr. area

Efs D in HARM1-y Allocation of ELPEN farm system (group)s (EFS) 3) use LFA & Altitude geodata to complete the allocation 32% x LU Efs in HARM2-a 30% x LU Efs in HARM2-b 38 x LU Efs in HARM2-c 200 LU LFA > 300m 300 LU non LFA < 300m 0.5 x ha pastures grid cell: 1 x ha extensive grazing areas Grid cell: 0.5 x ha compl cult pattern Gridcell: 0.1 x ha agr. area Allocation ELPEN farms system (group) D in HARM1-y on grid level