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AWU The number of hours to one Annual Work Unit (AWU) corresponds to the number of hours actually worked in a normal full-time job. The System of National Accounts states that full-time equivalent employment in a given country is defined as the total hours worked divided by the average annual number of hours worked in full-time jobs within the economic territory.
Cash crops Crops which are to be sold or traded on the market, unlike crops consumed by the holding (food for human consumption), crops supplied for own use (animal feed, seeds, processing at the farm) on the holding, or non-harvested crops (fallow land and green manure).
Corine Land Cover
Coordination of information on the environment (Community programme) on land cover
Cronos Macroeconomic database for the management of time series
ESU In 1995, the value of one Economic Size Unit (ESU) was equal to one SGM of 1 200.
Deterioration in the quality of inland waters (lakes, ponds, etc.) caused by excessive deposits of minerals (phosphates and nitrates, in particular). The influx of minerals causes the proliferation of algae (cyanophyta and diatoms) which cloud the water. These algae multiply and finally invade the beds of the stretches of water affected. Oxygen and minerals become scarce. Many aquatic plants die and as they decompose they release large amounts of nitrogen and phosphorus, which thus accelerate the eutrophication process. The disappearance of oxygen deep down forces the fish up to the surface, but they cannot survive very long in cloudy water infested with algae, and in the end only microscopic floating algae can exist in eutrophic waters.
FADN The Farm Accountancy Data Network (FADN) is a system of sample surveys, on a Community-wide scale, carried out each year. The FADN survey covers all the different types of activity on farms and also collects data on some of their non-agricultural activities (such as tourism and forestry).
GVA The Gross value added (GVA) is the value created by any unit engaged in an activity involving production. It is a component of an essential aggregate: gross domestic product (GDP), whose value represents the activity of the economic agents on a given economic territory. GVA at market prices is, for each branch of activity, the difference between the value of actual output (goods and services) and that of the intermediate consumption used in the production process. Gross value added excludes subsidies.
LU The Livestock unit (LU) is a unit used to compare or aggregate numbers of animals of different species or categories. Equivalences based on the food requirements of the animals are defined. By definition, a cow weighing 600 kg and producing 3000 litres of milk per year = 1 LU, a calf for slaughter = 0.45 LU, a nursing ewe = 0.18 LU, a sow = 0.5 LU and a duck = 0.014 LU.
Production system based on combining several types of crop production (field crops, perennial crops, horticulture, etc.) on a single holding.
Production system based on combining several types of livestock production (Dairy cows, Cattle, breeding pigs, poultry )
NUTS The Nomenclature of Territorial Units for Statistics was drawn up by Eurostat to be a single, cohesive system of territorial groupings for the compilation of EU regional statistics. The NUTS nomenclature subdivides the economic territory of the EU into 77 regions at NUTS level 1, 206 regions at NUTS level 2 and 1031 regions at NUTS level 3.
Farm type The Community classification of types of farming was established by Commission Decision 78/463/EEC of 7 April 1978. These farm types classify holdings according to their main source of income. Each type of agricultural production, whether crop or livestock, is assigned a standard gross margin (SGM), i.e. a standard income per production unit. The income from each of the holding's production sources can be calculated by multiplying the volume of production by the corresponding standard gross margin. All that then remains is to calculate the proportion of each type of production in the holding's overall standard gross margin. A holding is considered to be specialised if it earns more than two-thirds of its total income from a single type of production:
1. Field crops
3. Permanent crops
4. Grazing livestock
5. Pigs and poultry (granivores)
Otherwise, it is classified as non-specialised:
6. Mixed cropping
7. Mixed livestock
8. Mixed crops-livestock
The eight categories listed here are subdivided into seventeen subcategories.
The change in the structure of crop rotation and the holdings' move towards fewer production types has probably increased the economic size of the holdings and, in a classification by farming type based on standard gross margins, made it easier to categorise the holdings under one or other specialised farming type.
Crop on the same parcel of land for at least 5 years (vines, orchards, etc.)
PG The Permanent grassland (PG) is an area under grass, whether sown for at least five years or natural
SGM The standard gross margin (SGM) is a concept similar to value added. The SGM of a holding, assessing the potential gross margin, is determined by a set of standard coefficients which can be used to value areas under crops and numbers of animals. It is obtained by adding the partial SGMs produced by the holding. It is expressed in hectares wheat-equivalent or Economic Size Units (ESU). Since 1986, 2 ESU have been worth ECU 2 400, which is approximately 3 hectares wheat-equivalent. Above all, SGMs make it possible to allocate holdings to one of the types of farming by virtue of the relative contribution of the different types of farming to the total standard gross margin.
UAA The Utilised
agricultural area (UAA) corresponds to arable land, permanent grassland,
permanent crops (vines, orchards, etc.), kitchen gardens and crops under
Wooded area includes
forest area and other types of wooded land. Eurostat definition of Forest area
is "areas with crown cover (stand density) greater than around 20% of the area.
Continuous forest with trees usually reaching a height of more than 7 metres
and providing a source of wood.
The data used in this work come from various sources.
Some articles are based on a single source, such as Community surveys on the structures of holdings, which provides a homogeneous mass of information. Sample surveys or censuses are carried out regularly among farmers, by means of interviews. The questions asked cover all the types of production (land use for crop production and livestock for animal production) along with management of the holding, the equipment available and the workforce employed. These data, which are very accurate, are available at regional level and form a cohesive overview of European holdings. The various types of holding can then be established on the basis of data collected all at the same time, which makes the analysis of the results even more precise (classification in terms of types of farming or of agricultural production, for example).
Another blanket source is the Farm Accountancy Data Network (FADN), which compiles annual accounts for farms in the European Union and is representative at regional level. Very detailed data on amounts and values of purchases and sales, costs and products as well as balance sheets and profit-and-loss accounts are therefore collected from a stable sample (panel). This source enables an analysis to be made, over time and space and in terms of type of agricultural production, of all financial aspects relating to farms.
The advantage of these blanket sources is that the data are comparable, i.e. figures can be compared with other figures, since the questionnaire covers all variables of interest, and countries can be compared with other countries, since the concepts and definitions are standard across the Community. Although there are not many of these sources, they are a valuable reference for comparisons.
Some articles are based on time series, i.e. annual national information is compiled over a long period of time and in accordance with Community nomenclature. These data are very common at Eurostat, which is responsible for collecting the official figures drawn up by each country, bringing them into line with the common nomenclature and calculating the various aggregates. The amount of information is even greater than that of the blanket sources. However, this information is collected using varying methods and concepts. This in no way reduces its value but does however limit its overall cohesion (comparison of one set of data with another) and its homogeneity over time and space (comparison of data from one country to another).
National data are collected through censuses or sample surveys (based on lists or units of area). They meet a local need and are therefore totally adapted to national characteristics (importance of the agricultural sector, type of agriculture, consideration of environmental constraints, etc.).
Time series are excellent databases capable of serving as a basis for discussion in the long term. In view of their shorter processing time, they are available sooner and detail recent events. Finally, some data are available only through time series (agricultural production, use of fertilisers or pesticides, etc.).
Some articles quote from ad hoc sources: a specific survey (at Community, national or regional level) carried out by statistical institutes or non-statistical sources (administrative files, research carried out outside the European Statistical System, data from professional organisations, etc.). Although these sources are less commonly used in this work, they are sometimes the only information available, that is, they meet needs which are too specific or too recent for the official statistical system to have data, or they offer a different outlook and an original perspective on the subject in question, or they are the response given by the official statistical system to a specific request (follow-up to a regulation or assessment before it is implemented).
The advantage of such sources is that they provide an accurate response to questions asked. However, their scope may be limited, since they are not always reliable or may be too specialised (narrow field, questions directed with one aim in view - regulatory, for example - lack of reference data or of data showing trends over time, etc.).
Different data, depending on source
The results of surveys are sometimes different from those of time series. The sources of discrepancies are numerous: methods of collection, concepts selected, definitions and nomenclatures used, response thresholds, accuracy of information collected, etc.).
For example, in the article «CROP TRENDS AND ENVIRONMENTAL IMPACT», the time series derived from official statistics show a decline in Utilised Agricultural Area while the figures from Community farm structure surveys show an increase. This difference can be explained by the difference in the statistical fields covered: entire territory in the first case, population of holdings in accordance with certain criteria in the second. It is therefore necessary to be cautious when using figures, to cite sources used and, in the present case, to take into account the fact that the analysis is concerned with areas cultivated solely by holdings with a minimum utilised agricultural area (from 1 to 5 hectares depending on the country), instead of looking at all agricultural areas.