Geir Inge Gundersen Pilot study on developing statistics on grassland production from registers

Transcription

1 Documents 2016 Geir Inge Gundersen Pilot study on developing statistics on grassland production from registers EUROSTAT GRANT FOR 2014 EUROSTAT UNIT E.1 Objective: 08.4 Provide quality agriculture, fisheries and forestry statistics Module (DTM): Investigation through pilot studies for improving and further developing the agri-environmental statistics Title: Pilot studies to develop methodological improvements to agri-environmental statistics and statistics on grassland production Grant Agreement No Title of project: Pilot study on developing statistics on grassland production from registers Statistisk sentralbyrå Statistics Norway Oslo Kongsvinger

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3 Preface The purpose of this report is to give a presentation of a pilot study on the possibilities of developing statistics on grassland production from administrative registers. According to the findings in the project, recommendations on the way forward have been given. In May 2014, Eurostat invited the National Statistical Institutes of the 28 EU Member States as well as Liechtenstein, Iceland and Norway to participate in a call for proposals on the following action; Pilot studies to develop methodological statistics and statistics on grassland production. A grant application was send from Statistics Norway to the European Commission DG Eurostat. The application was accepted, and the contract was signed by both parties by the 20 th October The project period was set to last for 18 months, which means that the closing day of the project will be 20 th April This report represents the final report from the project to be delivered to the European Commission DG Eurostat. Senior Statistics Adviser Geir Inge Gundersen (Mr.) has prepared this publication. Special thanks to the Reference Group composed of Senior Statistics Adviser Ole Rognstad (Mr.) and Senior Adviser Berit Bjørlo (Mrs.). Last, but not forgotten, thanks to the Steering Committee and Head of Division for Primary Industry Statistics Ole O. Moss (Mr.) for giving advices and valuable feedback during the project. Statistics Norway, Oslo/Kongsvinger 14 th April 2016 SSB 3

4 Abstract Temporary and permanent grasslands constitute the main part of the agricultural area in Norway. Statistics on grasslands are therefore important and very much needed for many reasons e.g. yield statistics and indicators on nutrient flows. Statistics Norway s current statistics on grassland yield is based on a yearly sample survey. There is an acknowledgement in Statistics Norway that the quality of the existing production statistics ought to be enhanced. At the same time, we know that it is exists registers with information on grassland yield that possibly could replace our current yield statistics, or be used to rise the quality of it. The main objectives of this project were to identify possible administrative registers, and second, to evaluate the register by quality, coverage and usefulness, and finally, to give recommendations on how to exploit these registers to set up a system for improved statistics on net grassland production. It should be emphasised that net grassland production compromise the harvested yield removed from grassland, i.e. harvested mechanically, and by grazing. Several registers were identified and evaluated. It is important to bear in mind that a replacement of today s yield statistics has to be based on a persistent and stable data collection system and the principles in The European Code of Practice. In that sense, none of the evaluated registers could fully replace the current yield statistics on forage plants. Of the more positive findings, one of the registers could be suitable of making estimates on grazing by domestic animals. Adding up the harvest from grazing with the yield statistics will give Statistics Norway the opportunity to compile statistics on the net grassland production. This statistics will be of particularly interest while drawing up regional nutrient budgets. Furthermore, there are a number of registers that may be used to facilitate the editing and imputation of missing values in the sample survey. Among these are the coarse fodder model that can be run for different regions and predict yields based on local weather data. Another conclusion from this project is that some of the questions in the form used in the current sample survey should be revised. Methods for storage of forage fodder have changes significantly during the last decades, as round bales amount to 77 per cent of the stored fodder. The dry matter content of round bales should be included in the questionnaire since field experiments has revealed a great variance in both weight and dry matter content of round bales. 4 SSB

5 Contents Preface... 3 Abstract... 4 Contents Introduction Background Grass production assessment methods Statistics Norway s current statistics on grassland yield Objectives Definitions Methodology Identify potential registers Evaluation of registers Results Farm Accountancy Data Network (FADN) Metadata and variables Coverage Assessment Registers from the diary industry Assessment Applications for governmental grants Metadata and variables Coverage Assessment Coarse fodder model Assessment Field observations of yield Assessment New ley seed testing Metadata and variables Coverage Assessment Remote sensing Assessment Conclusions and further work Conclusions from the pilot study Recommendations and further work References Appendix A: A method for estimating grazing List of figures List of tables SSB 5

6 1. Introduction 1.1. Background Statistics on agriculture and its impact on the environment are needed for many reasons. Commission Communication COM (2006) 508 final on the Development of agri-environmental indicators, analyses the need to develop such indicators in relation to the reforming of the CAP, reviews the progress made with their development, and identifies key challenges and actions for future work. The Communication identified several limitations in a number of indicators. Among these are deficiencies in the data sets related to certain indicators, in terms of harmonisation, data quality, geographical coverage and/or availability of data series. In recent years, a lot of projects and call for tenders have been launched by DG Eurostat in order to develop methodology and sound statistical data as input to the indicators. In the 2014-call for tender, Norway was provided grants to accomplish a project to improve statistics on grassland production. These data are important in many ways, especially as input to indicators on nutrient flows i.e. Gross Nutrient Budgets and Economy Wide Material Flow Accounts. Grasslands are important sources and sinks of green house gasses. Monitoring information on grasslands is important for a better accounting of emissions and removals of nutrients from agricultural soils and land use. Enhanced information on grassland management which may have important effects on the grassland productivity and on the level of mitigation is therefore needed. The Gross Nutrient Budgets are one of the most important agri-environmental indicators, and it brings together at multitude of data related to different parts of the nutrient flows (Eurostat, 2011). Statistics Norway will during 2016 develop calculations of regional nutrient budgets, and input data will be needed at both national as regional level. Accurate data on grassland area, grassland production and nutrient content are very important for calculating of Gross Nutrient Budgets and other agri-environmental indicators (e.g. greenhouse gas emissions) and policies (Shils et al., 2013). Harvested yield on grasslands is the most important output data for calculation on nutrient budgets, and efforts in better estimation on grassland production is therefore of great importance Grass production assessment methods Crop yield can be estimated using several methods. In a review of methods, Schils et al. (2013) distinguished six main categories for production estimates: 1. Cutting and weighing is the most direct assessment method. It is carried out on experimental plots to determine gross production. It may also be carried out on farm field to determine the harvested net yield of a complete field or farm. 2. Height and density measurements are carried out on experimental plots and complete fields. They are estimates of the standing crop (gross production). 3. Visual estimates are usually carried out on a standing crop and thus give an estimate of gross production of plots and fields. However, 6 SSB

7 visual estimates may also be performed on hay stacks or silage heaps in which case they are an estimate of net production on farm level. 4. Crop modelling is a powerful tool to estimate gross and net production over all possible scales. In combination with farm and livestock modelling it is also possible to estimate net feed intake. 5. Remote sensing in combination with crop modelling supplies estimates of gross production at larger scales. 6. The feed balance is in fact a simple model that estimates net feed intake, based on the feed requirements of livestock. It may be applied at farm or regional level. The statistical offices in Europe usually gather yield information directly from the farmer through a sample survey (e.g. directly as yield, indirectly through volume of cut grass, number of cut etc.). Many of the member states in the EU also use expert estimates Statistics Norway s current statistics on grassland yield Temporary and permanent grassland constitute 65 per cent of the total utilized agricultural area in Norway, of which rough grazing come to 16 per cent. Grassland and grazing livestock are thus an important part of Norwegian agriculture, and statistics on fodder production are of interest for a number of reasons. Statistics Norway has compiled fodder production statistics based on a random sample of holdings since From the outset, the questionnaire covered the following crops; potatoes, cereal and oil-seed crops, forage crops other than grass and temporary and permanent grassland for mowing. Based on a review of the data collection method in 1990, it was decided to replace survey of cereal and oil seeds by data from an administrative source. Sample survey was still necessary for the other crops. The area of the grassland solely grazed is recorded, but not the corresponding yield. Statistics on the yield of potatoes and forage plants are based on a yearly sample survey. The target population of this survey is holdings referring to these crops when applying for governmental grants. The register of holders applying for governmental grants provides information on persons associated with the holding and the size of areas used for potatoes, coarse fodder and meadows for mowing. Data on area harvested, and of total yield of each crop are provided by holders who fill in the forms of the annual survey. Each year a sample is drawn from the register of holders applying for governmental grants. The size of the sample is about 3 100, which represent about 10 per cent of the population (table 1.1.). All types of holdings with combinations of areas of potatoes, coarse fodder and meadows for mowing are included in the sample survey of agricultural yields. To provide a better representation in certain counties with few holdings a higher percentage of holdings are selected in these areas. SSB 7

8 Table 1.1. Holdings represented in the sample survey on forage plants as part of all holdings growing forage plants in 2014, by size of agricultural area in use. Counties. Per cent By size of agricultural area in use, hectares Holdings 0,1-9,9 10,0-19,9 20,0-29,9 30,0-49,9 50,0- in total The whole country 10,2 5,4 7,5 8,2 16,8 25,1 NUTS3 (counties) Østfold 17,0 11,7 25,3 15,4 14,0 18,1 Akershus/Oslo 25,8 6,3 45,2 18,1 29,0 27,8 Hedmark 19,8 6,9 10,4 7,5 31,4 47,5 Oppland 8,4 4,5 4,7 7,9 17,9 21,9 Buskerud 19,8 4,3 6,2 11,3 51,0 70,3 Vestfold 30,5 21,1 13,4 26,7 50,0 53,3 Telemark 10,3 5,0 7,6 11,2 25,0 33,3 Aust-Agder 11,8 5,8 11,9 11,0 25,0 30,8 Vest-Agder 7,2 4,3 7,3 9,9 13,4 6,5 Rogaland 6,2 4,3 4,8 5,9 7,5 12,6 Hordaland 4,7 3,8 4,8 5,9 7,3 8,6 Sogn og Fjordane 5,5 4,6 5,5 6,0 9,2 10,0 Møre og Romsdal 5,8 4,7 4,7 5,3 8,7 12,3 Sør-Trøndelag 7,6 5,5 6,7 6,3 8,8 13,2 Nord-Trøndelag 10,4 5,3 8,0 6,0 15,9 17,6 Nordland 6,9 4,1 5,1 7,0 10,1 10,7 Troms 14,7 11,6 11,3 15,5 18,1 22,2 Finnmark 28,8 27,5 17,3 35,8 32,8 33,9 Source: Statistics Norway Data on area harvested and total yield of the different crops, are provided by the holders. Average yield is calculated regarded to this information. Total yield for the entire county is calculated by the use of average yield from the sample survey, and area of the different crops in each county based on information from the total population of agricultural holdings. Yield may of course vary significantly among plots, holdings, regions and years. Many factors will affect the harvested yield of forage plants, and the main factors in Norway are (Lunnan and Todnem, 2015): Climatic factors (temperature, rainfall, radiation, winter conditions). Soil conditions (drainage, porosity, fertility). Plant cover (botanical composition, condition of plants). Management (fertiliser use, grazing practice, time of harvest, yield losses from harvest to feeding) Objectives There are several reasons for examining alternative data sources and methods for the estimation of production from grassland: The quality of the existing production statistics ought to be enhanced. Fodder statistics are important as input for the calculation of regional gross nutrient budgets. An action for implementing the calculation of regional gross nutrient budgets started in SSB

9 The possible exploitation of alternative data sources would lead to reduced response burden for farmers. The main objectives of the project will be to: Identify possible administrative registers, governmental as well as nongovernmental, that could be suitable for the calculation of grassland fodder production. Evaluate the coverage, quality and usefulness of these registers as compared to the existing data collection on fodder production. Give recommendations on how to exploit these registers in order to set up a system for improved statistics on grassland fodder production Definitions Agricultural holding A single unit both technically and economically, which has a single management and which produce agricultural products. The holding is independent of municipality boundaries. The agricultural holding s headquarter must be located to an agricultural property. Agricultural area in use Agricultural land that is harvested at least once during a year, including planted area of permanent crops where no harvest has been produced so far. Includes also arable land included in the crop rotation system with no intention to produce a harvest during the year, but which will be harvested next year. Meadows for mowing Include fully-cultivated meadow and surface-cultivated meadow. Fully-cultivated meadow is area that is cultivated at normal plough depth and can be renewed by ploughing. Surface-cultivated meadow is area that is mostly cleared and superficially levelled to enable harvesting by machine. Infield pasturelands are areas used for pasture or harvested by other means than machines. Different types of grass should cover at least 50 per cent of the area. The area should be bounded by fences unless it has natural boundaries such as rivers, lakes, mountains, etc. Coarse fodder crops Include area of rye-grass, grain for silage, fodder rape, fodder kale and fodder roots. Fodder roots Include area of swedes and turnips for feed and fodder beets. Grassland Fully-cultivated meadow, surface-cultivated meadow and infield pastureland are defined as grassland areas in Norway. According to the FSS nomenclature the total area of fully-cultivated meadow are reported as temporary grass despite a larger part of the fully-cultivated meadow is older than five years. Surfacecultivated meadows is similar to permanent grassland for pasture and mowing SSB 9

10 while infield pastureland is similar to the FSS definition of permanent grass for rough grazing. Gross grassland production The total amount of biomass produced on grasslands. This is the potential amount of biomass available for harvesting and/or grazing. Net grassland production The total amount of biomass removed from grasslands. Not the entire potential amount of biomass is removed by harvesting and/or grazing, a part flows back to the soils. For instance not all of the biomass produced on grazed grasslands is actually grazed by animals; a part of the biomass gets trampled and is therefore not grazed. Other losses occur during harvesting, conservation of hay and silage and with the feeding of animals with fresh grass, hay and silage. The net grassland production is calculated from the gross grassland production corrected for these losses. Temporary grass (FSS definition) Grass plants for grazing, hay or silage included as a part of a normal crop rotation, lasting at least one crop year and less than five years, sown with grass or grass mixtures. The areas are broken up by ploughing or other tilling or the plants are destroyed by other means such as by herbicides before they are sown again Permanent grassland (FSS definition) Land used permanently (for five years or more) to grow herbaceous forage crops, through cultivation (sown) or naturally (self-seeded), and that is not included in the crop rotation on the holding. The land can be used for grazing or mown for silage, hay or used for renewable energy production. Permanent grassland can further be divided into: Pasture and meadow Permanent pasture on good or medium quality soils. These areas can normally be used for intensive grazing. Rough grazing Low yielding permanent grassland, usually on low quality soil, for example on hilly land and at high altitude, usually unimproved by fertiliser, cultivation, reseeding or drainage. These areas can normally be used only for extensive grazing and are normally not mown or are mown in an extensive manner. 2. Methodology 2.1. Identify potential registers Phase I Identify potential registers It was anticipated that in recent years, registers that may be used to extract information on fodder production have probably risen in both quality and coverage. The first phase of the project was to identify potential registers that could be used for this purpose. The dairy industry operates an advisory service for dairy holdings (cow milk). Data collected include inter alia information on fodder production and fodder quality. 10 SSB

11 This advisory service covers 98 per cent of all dairy holdings. Similar services also exist for sheep holdings and goat holdings. The coverage for these is 84 per cent of all holdings with goat milk production and 29 per cent of holdings with sheep. Another register or database of interest is data collected by the Norwegian Agricultural Extension Service, whose main task is to give advice to farmers based on local research. Local fodder production and fodder quality is an important work area, and if information is located in a central database, it may be useful for our purpose. Other registers to be investigated were the applications for governmental grants. Recently, the agricultural authorities have introduced the possibility to apply grants for grazing domestic animals, and this register can give information on e.g. type of grazing animals and duration of grazing period. During the project, a special attention was paid to the harvest of grazing by domestic animals. One of the challenges is to find coefficients on fodder needs for grazing animals. Data on grazing time for different livestock, together with coefficient for intake of fodder will give estimates on harvest by grazing. At the moment there is no statistics in Norway over this topic, and if we succeed to make estimates, results will be essential for the calculation on regional nutrient budgets. Except for the application for governmental grants, the registers mentioned above are owned by private enterprises/organisations. However, according to the Statistics Act, Statistics Norway may require access to third part information Evaluation of registers Having identified the potential registers, the next step was to contact register owner to get copy of the register. When the register was received by Statistic Norway, the evaluation of the register could start, which was the second part of the project. Several quality aspects of alternative data sources had to be analysed: What are the statistical unit and the corresponding identifier? Would it be possible to match with registers used by Statistics Norway? What is the coverage? Which variables can be found, and what is their completeness? Are data of sufficient quality? (If possible, variables should be checked against other sources). Are metadata available? (All variables should be documented, and all modifications in data registration should be described). Are data on fodder production directly available, or can other variables be used to estimate fodder production? A detailed assessment following the quality criteria listed above was done for each register. Strengths and weaknesses were described, as well as why a specific register was chosen or rejected in chapter 3. SSB 11

12 3. Results All the identified registers that possibly could be used for our purpose are described in this chapter. Further, the results of the analysis according to the quality and coverage criteria described in chapter 2.2., as well as an assessment of each register, are also given. For some of the identified registers, the part describing metadata, variables and coverage is missing. This is due to the fact that the actual register for different reasons was not received by Statistics Norway. More details have been given under the discussion of each register in the following chapter Farm Accountancy Data Network (FADN) In Norway, the Norwegian Institute of Bioeconomy Research is responsible for the Farm Accountancy Data Network. A questionnaire is filled in by the respondents and combined with the holding s annual accounts. In this context, two parts of the questionnaire are of interest; the part with information on areas and yields from grasslands, and the part with information on grazing by different domestic animals. According to the register owner, questionnaire-data for 2014 was not finally revised before December 2015 because they had to wait for the annual accounts. These data had to be seen together when data from the questionnaire was revised and approved. With basis in this information, and since we would have to wait for several months for 2014-data, we decided to ask for approved data for 2013 for our analysis since the survey year was of secondary importance in this context Metadata and variables Only variables on grassland yield and grazing will be mentioned here since the FADN-form also contains other variables that are not relevant. Of relevance for our purpose, the form has the following variables: Yield of meadows for mowing and pastures divided on: o Hay (loose) o Hay in square bales o Hay in round bales o Silage in silage silo o Silage in round bales (large size) o Silage in round bales (small size) o Other green fodder o Other coarse fodder Grazing, number of livestock and grazing period (from date, to date): o Beef cows o Diary cows o Other cattle, 1 year and older o Other cattle, below 1 year Coverage A data file with a selection of FADN-data covering holdings growing coarse fodder was received in October Before we received the file, business register 12 SSB

13 number was connected to the holding. This was essential since it would make it possible to connect the holdings and the corresponding yield to other registers used by Statistics Norway. The file consisted of 766 agricultural holdings. This file was merged with Statistics Norway s population over holdings and holders for A total of 748 holdings were found in both registers. It is not known why 18 holdings were not found in Statistics Norway s agricultural population, but it may be caused by errors in the business register number made by register owner or use of different business register number in cases were the holder is connected to several enterprises. A total of holdings were mowing coarse fodder in 2013 according to Statistics Norway s population over holdings and holders, which indicate that 2.2 per cent of these holdings were represented in the FADN-data. The FADNholdings are well distributed by counties, as well as by agricultural area in use. The representation among small holdings is poor, whereas the bigger holdings are quite good represented in both by size of agricultural area and by counties. Table 3.1. Holdings represented in FADN as part of all holdings growing coarse fodder in 2013, by size of agricultural area in use. Counties. Per cent By size of agricultural area in use, hectares Holdings in total 0,1-9,9 10,0-19,9 20,0-29,9 30,0-49,9 50,0- The whole country 2,2 0,4 1,3 2,9 4,8 4,1 NUTS3 (counties) Østfold 2,3 0,6 1,1 2,0 4,7 3,0 Akershus/Oslo 1,7 0,0 0,0 2,3 3,6 3,2 Hedmark 2,3 0,2 1,7 2,7 4,8 2,8 Oppland 1,3 0,6 0,8 1,2 3,2 2,8 Buskerud 2,0 0,2 1,1 2,1 5,4 4,0 Vestfold 3,5 0,0 1,3 4,2 7,5 7,8 Telemark 2,3 0,2 3,1 4,0 5,0 6,0 Aust-Agder 3,5 0,9 3,3 4,4 9,4 9,7 Vest-Agder 2,7 0,5 2,5 3,3 6,2 13,2 Rogaland 2,3 0,3 1,1 2,5 4,9 5,1 Hordaland 1,7 0,2 1,9 3,1 8,2 7,5 Sogn og Fjordane 1,9 0,9 1,6 3,1 6,9 2,9 Møre og Romsdal 1,9 0,4 1,4 3,1 3,1 5,6 Sør-Trøndelag 2,6 0,0 0,1 4,7 5,3 4,2 Nord-Trøndelag 2,3 0,6 0,8 3,1 3,9 2,9 Nordland 2,8 0,4 1,5 4,1 4,1 5,3 Troms 3,5 0,5 3,5 2,2 7,3 6,0 Finnmark 4,0 0,0 0,0 4,5 9,2 7,7 Source: Statistics Norway and NIBIO When considering farm typology, the FADN-data are best represented among holdings with mixed livestock, cattle - dairying and cattle - mix. Among other important groups growing coarse fodder, the surveyed holdings are weakly SSB 13

14 The whole country Holdings in total Other field crops represented (about 1 per cent) within holdings dominated by sheep and various grazing livestock. When it comes to area represented in the FADN, 3.3 per cent of the total agricultural area in use is found in the sample. Again, grasslands on holding defined by the typology classes mixed livestock, cattle - dairying and cattle - mix are best represented with more then 4 per cent of the temporary grass area in the population. Table 3.2. Horticulture and permanent crops Holdings represented in FADN as part of all holdings growing coarse fodder in 2013, by Community typology. Counties. Per cent Cattle, dairying Cattle, rearing and fattening By Community typology Cattle, Sheep mix Various grazing livestock Granivores Mixed cropping Mixed livestock Mixed crops and livestock 2,2 1,3 0,3 2,9 4,6 2,3 4,2 1,2 1,0 3,8 0,0 5,0 2,4 Cereals and oilseeds NUTS3 (counties) Østfold 2,3 2,3 1,4 0,0 3,5 4,5 8,3 0,0 0,0 4,3 0,0 8,3 1,2 Akershus/Oslo 1,7 1,9 0,0 0,0 6,2 0,0 3,7 0,9 0,0 3,3 0,0 7,7 2,2 Hedmark 2,3 0,0 1,0 0,0 4,9 2,6 2,9 2,5 0,0 2,0 0,0 2,6 2,2 Oppland 1,3 0,0 0,3 0,0 2,6 1,3 3,3 0,9 0,0 2,3 0,0 3,3 3,7 Buskerud 2,0 0,8 0,0 0,0 3,5 5,4 8,0 1,5 1,2 4,5 0,0 0,0 1,6 Vestfold 3,5 2,2 0,0 0,0 11,5 0,0 0,0 1,9 0,0 11,9 0,0 0,0 7,6 Telemark 2,3 0,0 0,4 0,0 6,7 3,1 0,0 2,1 1,2 7,1 0,0 20,0 6,3 Aust-Agder 3,5 0,0 1,1 20,0 11,8 0,9 16,7 1,2 1,5 7,7 0,0 0,0 7,1 Vest-Agder 2,7 0,0 0,0 12,5 5,6 3,9 4,2 1,0 0,8 0,0 0,0 12,5 5,9 Rogaland 2,3 0,0 0,0 2,0 4,3 1,0 4,1 1,1 1,1 3,8 0,0 4,7 2,4 Hordaland 1,7-0,0 4,2 4,5 1,9 6,3 0,7 1,4 2,3 0,0 6,3 0,0 Sogn og 1,9-0,0 5,1 3,3 1,9 4,8 0,8 1,9 6,9 0,0 16,7 1,7 Fjordane Møre og 1,9 0,0 0,2 0,0 4,5 1,3 3,7 0,7 0,5 5,9 0,0 18,8 0,0 Romsdal Sør-Trøndelag 2,6 2,5 0,3 0,0 4,6 4,3 2,1 1,8 0,0 0,0 0,0 3,7 1,6 Nord- 2,3 0,6 0,0 0,0 3,8 3,8 2,9 1,9 0,0 4,8 0,0 0,0 0,0 Trøndelag Nordland 2,8 0,0 0,0 0,0 7,3 1,8 5,9 1,2 2,3 1,5 0,0 2,4 0,0 Troms 3,5-0,0 0,0 6,5 3,3 7,4 2,1 6,3 0,0 0,0 0,0 0,0 Finnmark 4,0-1,6 0,0 9,3 7,7 0,0 1,9 0,0 0,0 0,0 - - Source: Statistics Norway and NIBIO Agricultural area in use Crops for green fodder and silage Temporary grass Permanent grassland Holdings in total Cereals and oilseeds Other field crops Table 3.3. Horticulture and permanent crops Agricultural area in use and grassland areas in FADN as part of area on holdings growing coarse fodder in 2013, by Community typology. Counties. Per cent By Community typology Cattle, dairying Cattle, rearing and fattening Cattle, mix Sheep Various grazing livestock Granivores Mixed cropping Mixed livestock Mixed crops and livestock 3,3 1,7 0,9 1,2 5,0 3,4 4,1 2,0 1,5 3,8 0,0 4,9 4,2 4,4 0,7 1,0 0,0 6,0 3,8 3,8 3,9 0,1 2,2 0,0 4,7 4,8 3,3 1,8 0,4 1,0 5,1 3,4 4,1 2,0 1,3 2,1 0,0 4,7 3,2 3,1 1,7 0,5 2,4 4,3 3,2 3,5 2,0 2,1 2,1 0,0 7,2 5,6 Source: Statistics Norway and NIBIO 14 SSB

15 Assessment Data from the Farm Accountancy Data Network (FADN) has a suitable identifier, metadata is available and finally it has the requisite variables. When evaluating the FADN-data, we also found several weaknesses: Data from a harvest year (for grassland the harvest year generally ends by the latest at the end of October) is not finally revised before more than a year after the information is obtained from the farmers (in December i.e. 13 months after the end of the harvest year). The timeliness will therefore be exceedingly low. Statistics on yields of coarse fodder, with today s production line, is published by Statistics Norway three months after the harvest year ends (preliminary figures). The sample size is generally too small. Yields of coarse fodder will vary by many gradients whereas the most important is farm management, farm size, typology and region (climate gradients south-north and lowlandalpine area). The distribution of holdings growing coarse fodder in the FADN is quite good according to counties, but weak when it comes to small holdings and holdings with mainly sheep or various grazing livestock. Holdings with less than 20 hectares agricultural area in use contributed to 57 per cent of all holdings growing coarse fodder in Only 167 holdings with less than 20 hectares agricultural area in use, or 0.9 per cent of the holdings in the population, are represented in the FADN. Further, holdings classified by the Community typology Sheep and Various grazing livestock amounted to 1.2 and 1.0 per cent of the population. These holdings are an important part of the Norwegian agriculture, and represent a more marginal use of grassland than for instance holdings with dairy cows. Several researchers in agronomy has criticised the coarse fodder yield statistics from FADN to be unreliable (Johansen, 2014 and personal memo from Bakken). Based on these findings, it is not recommendable that yield data from the FADN should replace the current sample survey carried out by Statistics Norway. The sample size in the FADN is too small, and the distribution of the holdings in the network classified among important typology classes and among size of agricultural area in use does not meet the necessary quality demands. Statistics Norway had to send several reminders to NIBIO to ask for data on grazing from the FADN form. In an assessment over these data together with the register owner it was reviled that the registrations were poor. There were lack of recourses in the FADN, and ask the farmer once more to get information about grazing was not an option. Therefore, data on grazing were in many cases based on an inaccurate estimate from previous observations and common practice. The conclusion was that Statistics Norway would probably not be able to produce useful statistics based on these data. SSB 15

16 3.2. Registers from the diary industry The dairy industry operates an advisory service for dairy holdings (cow milk). Data collected include inter alia information on fodder production and fodder quality. This advisory service covers 98 per cent of all dairy holdings. Similar services also exists for sheep holdings and goats holdings. The coverage for these is 84 per cent of all holdings with goat milk production and 29 per cent of holdings with sheep. Contact with the diary industry (TINE SA) and its advisory service revealed that there had been major modifications in their registrations for each holding. Earlier, uptake by forage plants were estimated based on milk yield and grain feed for each diary cow. Estimates on grazing were also made if it was not given by the farmer. During a review of the registration used by the advisory service some years ago, it was decided to omit registrations on uptake by coarse fodder, grain feed and grazing. The decision was correlated to the fact that the registrations done by the farmers were to poor, likewise was the system for estimation when registrations were missing. When we were in contact with TINE SA in July 2015, we were told that their Economy Program for milk producers had registrations on forage fodder yield. These registrations were done by the farmer. The Economy Program covers 20 per cent of the diary holdings, and data was stored in a central data base. Contact with the advisory service for goats and sheep unveiled that there were no registrations on grazing or forage fodder yield stored in a common data base Assessment A request to TINE SA for a copy of their data base on forage fodder yield was send in October After several reminders, we got an answer in January In their answer we were told that the Economy Program did not have actual harvested yield, but only estimated grassland yield. Further, Statistic Norway could receive data from the Economy Program, but only to a labour cost for extracting and prepare the data. The cost was estimated to around The project group in Statistics Norway assessed different ways of dealing with the situation. One alternative was to pay the actual costs for a copy of the data base; a second was to ask the Director Meeting in Statistics Norway to agree on a disclosure requirement, while a third was to leave this path. Based on the following assessments we decided not to investigate the data from the Economy Program: This project is a pilot with reduced resources. Scientists that have looked at yield data from the Economy Program has stated the estimates on forage fodder as unreliable. Yield is not based on observed data, but predicted yield from a feed balance model based on milk yield and use of grain fodder Applications for governmental grants The applications for governmental grants are an important register for both area use and livestock. This register, in combination with some additional registers, enables Statistics Norway to create and maintain a total population over agricultural holdings with individual information about the holder, crop area and number of heads per livestock type. Recently, the agricultural authorities have 16 SSB

17 introduced the possibility to apply grants for grazing domestic animals, and the corresponding register can give information on e.g. type of grazing animals and duration of grazing period. This register, together with coefficients, may give us the possibility to better estimate forage fodder yield from grazing Metadata and variables Each year, Statistics Norway receives two data files from the register owner, the Norwegian Agricultural Agency. The first data file is preliminary, while the second covers the final registrations. Metadata is available, and the two main identifiers used by Statistics Norway are included in the file, i.e. business register number and title number of rural property. The first section on the application form covering grazing is the number of animals on pasture with durability of at least 12 or 16 weeks during a year. The number of weeks is connected to different climatic zones. The pasture area may be all kind of agricultural grassland areas (i.e. infield pastureland, surface-cultivated meadow and fully-cultivated meadow), as well as outfield pasture. The form does not give information on area type that is grazed, or the exact number of weeks of grazing. The following livestock types are divided on the form: Diary cows and beef cows Other cattle Sheep, 1 year and older Lambs, below 1 year Goats, adults and kid Horses (both stalled and owned) Llama Alpaca Deer The second section of variables is for pasture on outfield pastureland (i.e. not agricultural land) with duration of at least five weeks. It is possible to fill in animals on both sections as long as the demand according to area, duration and fodder uptake by grazing is secured. An example for a domestic animal that fills the criteria for both sections could be a sheep that is grazing 10 weeks in the outfield area and 6 weeks on infield pastureland (i.e. the total time on pasture is at least 16 weeks and in addition, at least five weeks on outfield pasture). The second part of the form is divided on the following livestock types: Diary cows and beef cows Other cattle Sheep, 1 year and older Lambs, below 1 year Goats, adults and kid Horses (only owned horses) Coverage More or less all holdings with a production that is more than a hobby or small size farming for own consumption applies for governmental grants. About 3-4 per cent of the holdings do not apply for governmental grants due to low production or other reasons. For most of these holdings, agricultural area in use and livestock SSB 17

18 are derived from data on deliveries of cereals and oil seeds, and delivered animals to the slaughterhouses etc. The register will not give information on grazing animals for these few holdings Assessment Statistics Norway does not publish yearly regular statistics about grazing domestic animals. However, this topic was surveyed as part of the farm structure survey (FSS) in 2001 and the survey on agricultural production methods (SAPM) in Results from the FSS 2001 gives pasture time for the main livestock groups, but only for grazing area as a total, which in this case denotes both agricultural area and outfield area. Data from the SAPM will meet our purpose far better. The questionnaire was designed to get information on pasture time for the livestock types: Diary cows Beef cows Other cattle Sheep over 1 year Goats over 1 year Horses Pasture for the above mentioned groups was divided on the areas of: Fully-cultivated meadow Surface-cultivated meadow Infield pastureland The use of outfield area for pasture is a deeply practice in Norway. It is common to let sheep and goats graze in the mountain region during the summer. Normally, most farmers will let the sheep graze on infield grassland for some weeks when the sheep has been taken home from the mountain region. Further, a part of the beef cows and other cattle will also graze in the forest during a part of the summer or most of the summer. More or less all sheep, goats and cattle that are let loose on pasture in the outfield area are registered in a common register for pasture societies. These societies apply for governmental grants, which denote the number of heads, geographical grazing area and owner is accounted for in the register. The number of sheep, goats and cattle that is set to be on outfield pasture may be checked against the grant registrations for pasture societies. As described in chapter 3.3.1, it is not possible to produce statistics on pasture directly from the applications for governmental grants. First, it is not possible to give the exact number of weeks of pasture, and secondly, it is not possible to get information on what type of area that is grazed. At last, the area grazed may in many cases be outfield area, or a mix by infield and outfield areas. The actual distribution between infield and outfield areas can not be extracted from the applications. In order to get an estimate of the grazing on outfield area and on different infield areas, a merge between the applications for governmental grants and the SAPM- 18 SSB

19 data were analysed. A more detailed account of the method is given in Appendix A, and results are given in table Using this information together with the yearly applications for governmental grants, and corresponding coefficients, it should be possible to estimate a yearly yield harvested by grazing animals. It should be emphasised that grazing by livestock (i.e. duration and area distribution) should be surveyed at least every fifth year. The ideal would be to include these questions as part of the yearly yield survey for forage plants. Table 3.4. Livestock with subsidies for grazing by type of pasture areas Per cent Share of animals with subsidies for grazing In total Only on Only on On both outfield infield outfield and pasture pasture infield pasture Without subsidies for pasture Sheep>1 year Diary cows Beef cows Other cattle Goats Horses Source: Statistics Norway The number of heads found in the population over agricultural holdings should be multiplied with the percentage in table 3.4. The animals set to be on pasture on infield areas should then be multiplied with the corresponding number of weeks given in table 3.5 to get the duration of pasture on infield area. Further, the different infield area categories should be multiplied with the number of heads. Livestock without subsides for pasture should be evaluated separately. For example, it is not unlikely that 20 per cent of the diary cows are not on pasture at all during the summer time. Guidance in this assessment could be to use pasture time in mean from the SAPM. Although, the number of week of pasture for livestock without subsidies should at least be less than 12 weeks or 16 weeks according to climatic zone. Otherwise the animals should be found on the applications for governmental grants. SSB 19

20 Table 3.5. Number of weeks grazed on infield area, and infield area per grazing animal given in the SAPM Weeks on infield pasture, in mean per holding Infield area per grazing animal, in mean (decares) Pasture on fullycultivated meadow Pasture on infield pasture land Sheep>1 year, pasture only on infield areas 25,3 0,7 0,3 1,5 Sheep>1 year, pasture on both infield and outfield areas 20,2 0,7 0,2 0,7 Diary cows, pasture only on infield areas 14,9 1,8 0,3 1,4 Diary cows, pasture on both infield and outfield areas 13,1 1,9 0,6 2,5 Beef cows, pasture only on infield areas 18,6 2,5 1,0 2,5 Beef cows, pasture on both infield and outfield areas 19,4 2,1 1,1 4,0 Other cattle, pasture only on infield areas 17,0 0,6 0,3 1,0 Other cattle, pasture on both infield and outfield areas 17,8 0,7 0,4 1,5 Goats, pasture only on infield areas 20,7 0,4 0,1 0,7 Goats, pasture on both infield and outfield areas 22,4 0,3 0,1 2,7 Horses, pasture only on infield areas 17,3 1,8 0,9 3,3 Horses, pasture on both infield and outfield areas 20,4 2,4 1,5 5,0 Source: Statistics Norway Table 3.6. Share of infield area type grazed by livestock given in the SAPM Per cent Share of infield area types grazed (per cent) Pasture on surfacecultivated meadow Fullycultivated meadow Surfacecultivated meadow Infield pasture land Sheep>1 year, pasture only on infield areas Sheep>1 year, pasture on both infield and outfield areas Diary cows, pasture only on infield areas Diary cows, pasture on both infield and outfield areas Beef cows, pasture only on infield areas Beef cows, pasture on both infield and outfield areas Other cattle, pasture only on infield areas Other cattle, pasture on both infield and outfield areas Goats, pasture only on infield areas Goats, pasture on both infield and outfield areas Horses, pasture only on infield areas Horses, pasture on both infield and outfield areas Source: Statistics Norway 3.4. Coarse fodder model The Norwegian Institute of Bioeconomy Research (NIBIO) has developed a coarse fodder model as a decision tool for farmers according to time of harvest. The model estimates gross yield and fodder quality in meadows day by day through the growing season based on weather data and soil types from a network of weather stations. This model has also been used to estimate net yield of meadows for mowing in a weather-based normal year for different regions in Norway. Data from the period as well as soil type has been put into the model to estimate yields for the latter mentioned purpose. After the model had 20 SSB

21 estimated the potential yield in a normal year, several steps were used to reduce the potential yield to an excepted harvested (net) yield (Bakken A. K. et al., 2014) Assessment Statistics Norway contacted the researchers behind the model to get an appreciation of the possibility to use the model for our purpose. The questions asked were: 1. Could the model alone (or with some adjustments) estimate net yield at NUTS3 level based on yearly weather data? 2. Could the model estimate net yield at NUTS3 level based on yearly weather data, calibrated against net yield found in a small sample survey or against net yield found in field measures? Written consultancy with the NIBIO researcher Anne Kjersti Bakken unveiled that the model had some limitations. It is adapted to timothy dominated meadow, and predicts more unsecure estimates for rye grass. The model will not intercept local climatic conditions. Nor will the model consider winter damage in meadow, which locally may influence the yield significantly. During the discussion, Bakken first made some remarks on factors, in addition to weather conditions, that significantly will influence the production of forage plants: Damages in meadow caused by winter conditions. Damages in meadow caused by soil pressure from large machines. Farm management (e.g. use of fertilisers, use of pesticides, harvesting system, grazing, reconditioning, seed-mixture etc.). Losses during harvest, ensiling and storage. Since the model does not implement the above mention factors, Bakken evaluated the model not to be a good enough basis in order to meet our purpose. Our conclusion is that the coarse fodder model could not be able to predict the net yield harvested from meadows. On the other hand, the model may be used as a supplement when our sample survey is revised. If about three climatic stations per county are used to run the model by using a standard harvest system, estimates on yield per county can be made. The estimates will only cover the yield variation caused by weather, but it may be an important tool for edit and imputation in our sample survey on the production of forage plants Field observations of yield The Norwegian Agricultural Extension Service collects coarse fodder yield based on local research. The service has about members, and 800 small field trials are executed each year at the farmer s land (all type of crops). The Extension Service s task is mainly to give advice to farmers within agronomy, farm constructions, machineries, hydro technic, greenhouses, business development, economy, climate and environment. A total of 39 Extension Service Offices are located throughout the country, and several of these have coarse fodder test trials where yield is measured. SSB 21

22 Assessment When it comes to coarse fodder, the main task for the Norwegian Agricultural Extension Service is to give individual advice to farmers in order to get better quality of the coarse fodder yield and give advises according to priority of the farmer s work tasks. Experimental plots are established by initiative of the local office, and it is not part of a general plan. Results from the trials are not gathered in a common database; they are only maintained and used by the local office. Based on these facts, it seems extremely difficult to use yield data from the Extension Service. When it comes to the positive sides, the trials will represent many localities over the country, and will be close to real farm yields as the trials are small areas within a plot and managed as part of the holding s agricultural area. On the other hand, it seems that these yield data will be difficult to use for our purpose as they are not part of stable trials within a comprehensive plan for the whole country, which means that the yield data are not comparable over geography or time. Finally, it will be difficult to collect the yield data in a uniform way as they are not gathered in a common database New ley seed testing The Norwegian Institute of Bioeconomy Research (NIBIO) carries out the variety testing of new ley seeds on behalf of The Norwegian Food Safety Authority. The aim is to obtain results for approval of new varieties to the Norwegian official list of varieties Metadata and variables The metadata as well as the results are described in a yearly report and covers varieties that have completed the testing program. The results from each trial could be available for Statistics Norway, and could be connected to the business register number. All tests are carried out on experimental farms belonging to NIBIO. The varieties are grown in squares of 1.5 x 7.0 metres (10.5 m 2 ). All the varieties in trails are grown in pure stand. None of the trials are harvested in the year of sowing. Further, the trails are fertilised according to species, soil type and climate at the location. The testing is done continuous and new ley seeds will be sown each year, and varieties that have finished the test period are taken out. There will therefore be a great variance in the year of sowing for the varieties under testing (Nesheim and Langerud, 2014) Coverage The test plots take place in five main geographic areas; Eastern Norway, Western Norway, Central Norway, North Norway and high altitude areas. A total of 21 varieties within five species had completed the testing in 2014, of which none varieties were recommended for approval Assessment The official variety testing program gives extremely precise measures of the harvest in five main regions in Norway. On the other hand, it must be emphasised that yield of new lay seeds should not be used for the estimation of yield from 22 SSB