introelpen systemdata statisticaldata fadn fss regio relationtables geographicdata admregions...

IntroELPENSystemData StatisticalData FADN FSS REGIO RelationTables GeographicData AdmRegions DesignatedAreas LandCover Elevation Soil, Climate EnvironmentFarm TypologyReferenceFarmsSchemesCases AllocationFss AllocationElpFarmGroups Economic Social

File Edit View Insert Tools Window Help

ELPEN

Summary of the ELPEN project results, May 2003



ELPEN

Introduction to the ELPEN

project



ELPEN

The

Consortium



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

What is ELPEN?



ELPENThe 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 systems initial focus on dairy systems (DG Agri)

• A flexible expert tool, not a desktop tool



ELPEN

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

The ELPEN system is:



ELPEN

An expert who supports policy makers to answer 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:

The ELPEN system user is:



ELPENPolicy Impact Assessment with the ELPEN system

Spatially explicit socio-economic and environmental impacts

Policyquestion

Statistical and Geographic data

Farm typologies,simple models and expert rules

Spatially explicit modeling results (maps, tables)



ELPEN

Explanation of

The ELPEN System



ELPEN

Explanation of

The ELPEN System

System data (e.g units)

ELPEN Farm typology

Statistical data

Reference Farms (examples of ELPEN farm types)

Schemes (knowledge rules)

Cases (results, obtained by applying schemes on data)

Geographic data



ELPEN

Browser

Table view

Mapview

Meta data viewand technical details

ELPEN system: User interface



ELPEN

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 tables Stored relations between different data sets



ELPEN

Statistical Data: Relation tables

Stored relations between different data sets:

e.g:

The geographic relations between the different statistical data sets is established by:

Harmonised regions (Harm)



ELPEN

Geographic relations: harmonised regions

HARMonised regions make it possible to integrate data from different statistical sources by applying them to the same geographic entities



ELPEN

HARMonised regions make it possible to integrate data from different statistical sources by applying them to the same geographic entities

Geographic relations: harmonised regionsHarm1Harm2



ELPEN

Geographic relations: harmonised regions

ELPEN regions: 23

Harm1 Region

Harm1 Region

Harm1 RegionCountry12 & 15

EU

Other geographic regions in ELPEN:

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



ELPEN

Example data

Example of stored data:Subsidies on livestocktotal in kEuro per Harm1 (1999)

Note: Switzerland is not EU member



ELPENExample of computed data:Subsidies on livestockper Livestock Unitin kEuro per Harm1 (1999)

Note: Switzerland is not EU member



ELPEN

Example data

Nr of livestock unitsof Total Bovineper Harm2 (1990)

Note:Finland, Sweden,Eastern Germany and Austriawere not EU members in 1990

Switzerland is not EU member



ELPENInhabitants per HARM2 (1999)



ELPEN

Geographic Data: overview

Administrative Regions

Designated areas

Land cover: Corine & Pelcom

Elevation

Soil, Climate

Environment (Nitrogen Vulnerable Zones, N-leaching)

Landscape (not yet available)



ELPENELPEN Regions: cluster of administrative regions



ELPENDesignated areas:Less Favoured Areas1997



ELPENCorine Land Cover e.g: pastures (grid map: 1.1x1.1km)

An extract 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.”



ELPENPelcom Land Cover: e.g: grass(grid map: 1.1x1.1km)

An extract 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.”



ELPEN

Elevation



ELPEN

Elevation Elevation: classifiedbelow 300m300-600mabove 600m

This classification corresponds with the FADN data



ELPEN

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



ELPEN

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



ELPEN

ELPEN Farm typology: result

Sector: Grazing livestock farms(>50% production value from grazing livestock)

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 grazingOff farm produced

fodder systemsPermanent

grass systemsGrassland

systemsArable systems

Dairy Mixed BeefDairy

grazingMixed

Dairy&meat Dairy Mixed Dairy Mixed MeatMeatMeat

grazing

Grazing livestocksectors(% cattle and % milk in production value)

Cattle Sheep Goat

Size(Livestock Units (LU) grazing livestock)

Small scale < 20 LU Medium scale 20-100 LU Largel scale > 100 LU

All farms in EUELPEN Farm typology



ELPEN

How many and what ELPEN farm types are located in what regions?

Number of farm types per region

Click on region



ELPEN

What ELPEN farm types are in what regions?

Number of farm types per regionSector:Grazing livestock

Production type:Meat

Livestock type:Cattle

Land use type:Permanent grass

Intensity:Low input

Size:Medium scale



ELPEN

example time-series

Example time series:Change in LU on dairy cattle farms 1990 - 1999 (Index 1990=1)

decrease

Increase

< 15 dairy cattle farms or missing data





ELPENExample time series:Change in nr of dairy cattle farms 1990 - 1999

(Index 1990=1)


decrease

Increase

< 15 dairy cattle farms or missing data




ELPEN

For 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



ELPEN

Profiles of farms per region e.g:arable medium input system

Nr of represented farms per region

Click on region



ELPEN

Profiles of farms per region e.g:arable medium input system


Click on region

Structuralprofile

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



ELPEN

Profiles of farms per region e.g: arable medium input system


Click on region

Structuralprofile

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

Environmentalprofile

Stocking density on grassland, being 6.6% under EU average for this farm type



ELPEN

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

Reference farms are:Real example farms of ELPEN farm types

The data are gathered using a questionnaire with 93 questions about 10 aspects ofthe farm and 7 policy questions



ELPEN

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

Reference farms are:Real example farms of ELPEN farm types

The data are gathered using a questionnaire with 93 questions about 10 aspects ofthe farm and 7 policy questions

K) LIVESTOCK HOUSING / WELFARE86) type of livestock87) duration of housing88) housing type89) housing90) grazing management91) transport 92) visits by 93) main health problem

B) LAND RELATED QUESTIONS18) altitude < 300m, 300-600m, > 600m 19) gradient of land (estimate20) soil quality (1 excellent - 5 poor) 21) layout of farmland (scattered - consolidated)22) farm size23) policy status24) use of land25) ownership of farm: land owned/rented/leased26) types of crops (excluding fodder and grass)27) fodder production (roughage other than grass)28) conservation of grass29) arable land with vegetation cover 30) fertiliser use31) pesticide use



ELPEN

Data on reference farms can be viewed as follows

Data on reference farms per region (HARM1)

Nr. of reference farms per region

Click on region



ELPEN

Data on reference farms can be viewed as follow



Click on region

Data on Sheep



ELPEN

Data on reference farms can be viewed as follow



Click on region

Data on Sheep

Data on land



ELPEN

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:



ELPEN

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:

Suppliers Scheme: Allocation of Dairy Cows(automatically generated by the system)

FSS data: nr. lu dairy cows / Harm2 (1990)

Corine / grid cellPelcom / grid cell

% grazing area / grid cell

Result: nr LU Dairy cows / grid cell (1990)



ELPEN

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:



ELPEN

• Allocation of Livestock basis: FSS / HARM2 and Land cover on 1km2

• Allocation of ELPEN Farm type groups basis: FADN / HARM1, Land cover, LFA, Altitude on 1km2 • Economic Impacts of milk price reduction basis: economic model, input: FADN data / farm type group

• Environmental impacts of milk price reduction

• Social: who stops and who continues decision path for LFA regions, input: reference farms

Cases: overview



ELPEN

Case: Allocation of livestock per grid cell

Grazing livestockin LU / ha, 1997

Allocation of livestock per grid cell



ELPEN

Case: allocation of farm type groups

Small scale farms: harm1 level

less farms < 15 small scale farms (left)

more farms

and desaggregated to grid

no grazing area available (right)



ELPEN

Case: Economic impact of milk price reductionExample: specialised dairy cattle farms

1) Computation of full costs of milk:

input: 250 FADN variables, e.g:

labour land capital feed

Full production costs ofmilk of spec. dairy cattlefarms in €/dt per Harm1

< 15 spec. dairy farms

(or non EU member Switserland)



ELPEN

Case: Economic impact of milk price reductionExample: specialised dairy cattle farmsFull production costs ofmilk of spec. dairy cattle farms in €/dt per Harm1


Average herd size of specialist dairy cattlefarms per Harm1


Small herd size

(or non EU member Switzerland)

High production costs

The results show that there is a correlation between production costs and herd size



ELPEN

Case: Economic impact of milk price reduction

2) Computation of surplus:

surplus = milk price - costs

In our example: costs on long term:

Cash costs + depreciation + full opportunity costs (land, labour, capital, feed, etc)

A large surplus is an incentive to expand production, and it provides capital for more investment

Economic impactof milk price reduction

Surplus:

stop

continue

increase

negative

small

large

Milk production



ELPEN

Nitrate vulnerable zones

Environmental Impact of milk price reduction

This is a political map, which is not very useful for the impact assessment of milk price reduction.

Instead, we used the following map…



ELPEN

Nitrate vulnerability expressed as leaching fraction ≈ sensitivity to leaching

This map was computed outside the ELPEN system

Fragment of the meta data on Nitrate vulnerability

To determine the nitrate leaching fraction the Burns model is used (Burns, 1976). This model, defined in 1975, calculates a nitrate leaching fraction (f) on nitrate present in the soil, using soil and climate factors.

f = (Ed / (Ed + Vm/100))x

f = nitrate leaching fraction (-)Ed = amount of water drain-ing to the sub soil(cm/yr)Vm = volumetric soil moisture content at field capacity (%)x = depth factor depending on the nitrate repartition considered in the soil (cm)

Environmental Impact of milk price reduction



ELPEN Environmental Impact of milk price reduction

Nitrate vulnerabilityexpressed as leaching fraction ≈ sensitivity to leaching

Grazing livestock in LU / ha, 1997

Surplus after 20% reduction of milk priceExpected increase of

milk production

EnvironmentalHotspots



ELPEN

Economic impact of milk price reduction on farm types with environmental consequences

All dairy cattlefarms

Low-input dairycattle farm

Germany -5 -10Spain -3 11France -3 -10Italy 1 -20Austria -32 -35Portugal -12 -31Sweden -7 -12Surplus = (Future price – production cost)

Low-input systems will come under pressure

Surplus in €cent / l milk



ELPEN

All dairy cattlefarms

Low-input dairycattle farm

Germany -5 -10Spain -3 11France -3 -10Italy 1 -20Austria -32 -35Portugal -12 -31Sweden -7 -12Surplus = (Future price – production cost)

Low-input systems will come under pressure

Surplus in €cent / l

Economic impact of milk price reduction on farm types with environmental consequences

% Low intensity dairy cattle farmsof total dairy cattle farms 1997per ELPEN region



ELPEN

Economic impact of milk price reductionon farm type with environment consequences

% Low intensity dairy cattle farmsof total dairy cattle farms 1997per ELPEN region

0 25 50 75 100 125 150

Crop protection use

Fertiliser use

Permanent grassland

Stocking density

Grassland pressure

%

1,1

0,7

31

11

52

Environmental profile of low-input system

EU average forall dairy cattle

farmsindex = 100



ELPEN

Assumption of previous cases:

Only dairy farmers with a surplus income from milk productionwill continue farming, but...

Social and cultural aspects mayhave a big influence on decisionsof farmers.

An example of rules that simulate social behaviour is the following…



ELPENPluriactivity

High

No /Low

Self Processing

PDO YesYes

No

Self marketing

YesNoNetworks

No

High

No / Low

Support

Age<55 >55

Yes

No

Continue farmingMight continue farming Stop farming Might stop farming Added value

Social factors influencing farmers decisions in LFAs

Input:

Reference Farm data



ELPEN

The previous social scheme uses as input stored reference farm data in the ELPEN system.

Unfortunately the number of reference farms in the current system is too limited to apply social schemes like these to predict representative social behaviour.

We need to interview more farmers in order to gather representative data to be able to assess social impacts.



ELPENConclusions

The ELPEN consortium offers:

Support for integrated and targeted policy development by:• Making available integrated statistical and bio-geographical

data for the whole EU in one system• Providing regionally differentiated information in maps

(using expert knowledge for desegregation)• Differentiating farm responses using a flexible typology that

can be associated with reference farms in the field• Enabling a better understanding of linkages between

economic, environmental and social impacts of policy measures

• Maintaining and improving the utility of the ELPEN system for policy impact assessment



ELPENAccessing ELPEN

The ELPEN software is available free of charge at:http://www.objectvision.nl

For general information on the ELPEN project visitthe ELPEN website: http://macaulay.ac.uk/elpen

If you are interested in using our services or the ELPEN system, please contact us…



ELPENIf you are interested in using our services or the ELPEN system, please contact us:

Organisation Country Contact person Coordinates: Macaulay Institute Scotland Iain Wright Project Coordinator,

Reference Farm Collection

Alterra, Green World Research Netherlands Berien Elbersen Geographic Data,

Regional Indicators, Desaggregation Procedures

Agricultural Economics Research Institute (LEI) Netherlands Frans Godeschalk FADN data provision, preparation

of Eurostat data FSS and Regio

Danish Forest and Landscape Research Institute (FSL) Denmark Erling Andersen Elpen Farm Typology,

Environmental Indicators Federal Agricultural Research Centre (FAL) Germany Peter Hinrich Farm Cost Model, Economic Farm

Behaviour Model, Economic Indic. Agricultural University of Athens (AUA) Greece Leonidas Louloudis Socio-cultural indicators and

farmers' behaviour Object Vision Netherlands Maarten Hilferink DMS and Elpen system software



ELPEN

introelpen systemdata statisticaldata fadn fss regio relationtables geographicdata admregions...

Documents