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N-flow in Danish agriculture And FarmAC in Amazonas

This study examines nutrient flows and N-leaching in Danish agriculture, focusing on the average farm N balance. The research highlights the development and variation of N surplus in Danish farms from 1990 to 2008. The findings provide valuable insights into the N-flow dynamics in organic dairy farms in Estonia and the impact of different factors on N losses in Danish agriculture.

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N-flow in Danish agriculture And FarmAC in Amazonas

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  1. N-flow in Danish agricultureAnd FarmAC in Amazonas Ib Sillebak Kristensen & Nick Hutchings Aarhus University Dept. of Agroecology Foulum. Denmark 10. Feb. 2015. Campinas, Brazil.

  2. part 1 Principles for Nutrient flows, examplified on average DK agriculture

  3. Farm N balance & N-leaching Hansen et al. Env Sci. Tech. (2011)

  4. N-eff. in Danish Agriculture

  5. Danish Farm N surplusDevelopment and Variation 2008 1990 Dalgaard et al. BiogeoSciences 9 (2012)

  6. N-flow on 4 organic dairy farms in Estonia in 1998 75N/cow in manure from stable

  7. DK agriculture N-balance, 1999 Input Kg N ha-1 year-1 N-fertiliser 94 • Seed 2 • Fodder 79 • N-fixation 13 • Precipitation 16  Output • Milk -9 • Animals -28 • Cash crops -41  los in . -stall -storage = fieldbalance N-surplus 125 - 9 -4 = 112

  8. Field-balance: Un-secure Farm-balance: Reliable

  9. N-losses in DK-agriculture, 1999 Kg N ha-1 year-1 % N-los of input Farm gate N-surplus 125 Amm. los in: • Stall -9 9 % • Storage -4 4 % Field N-surplus 112 Amm. los: • Spreading -8 11 % • Grazing -1 7 % • Fertiliser -5 3 % • Crops -4 4 % Denitrifikation -16 11 % Change in soil-N 0 N-leaching (=difference) - 78

  10. N/ha Farmgate N balancer on arable sandy soil - 250 200 150 100 50 LU/ha 0 0,00 0,50 1,00 1,50 2,00 Svin Konv. mælk Øko. mælk Øko. Plante Konv. plante Dairy conv. Pig conv. Dairy organic Arable organic Arable conv.

  11. FarmAC model – the basics

  12. FarmAC model • Focusses on livestock farming systems • Can be used for arable agriculture • Intended to have wide applicability • Simple enough that demand for inputs and parameters is manageable • Complex enough to describe consequences of mitigation/adaptation measures • Mass flow for C and N • Consistency between GHG and N emissions • Capture knock-on effects

  13. NH3,N20,N2 NH3,N20,N2 NH3,N20,N2 Exported Exported Exported NH NH NH NH NH NH , N , N , N , N , N , N O O O O O O 3 3 3 3 3 3 2 2 2 2 2 2 Deposition Fixation Fertiliser Manure NO NO 3 3 Storage losses NH , N O 3 Runoff NO 3

  14. CO NO 2 Storage losses 3 NH , N O 3 Fertiliser Manure Exported NH , N O 3 2 CH4,CO2 NH , N O 3 2 Exported NH , N O 3 2 Runoff NO 3 CH4,CO2 NH , N O Exported 3 2 NH , N O 3 2 CH4,CO2 NH , N O 3 2

  15. Components • Cattle model (simplified Australian) • energy and protein determine growth/milk • Animal housing and manure storage (mainly IPCC) • Crop model • Potential growth * N limitation * water limitation • Soil model • simple soil water model • simple soil C and N model

  16. How the model sees grain crops 1st product (e.g. grain) 2nd product (e.g. straw) (may or not be harvested) above-ground crop residue root + leaf scenescence

  17. How the model sees forage crops Grazed forage Grazed forage Unutilised forage Ungrazable residue Ungrazable residue root + leaf scenescence root + leaf scenescence

  18. Grazed yield Modelled yield Unutilised (residue) Ungrazable residue Modelled yield Grazed yield Ungrazable residue Enough production More than enough production

  19. Deficit! Grazed yield Modelled yield Ungrazable residue What the cattle thinks they can eat What the pasture can supply Not enough production

  20. Running FarmAC (1) • Define crop sequences • area, soil type, irrigation • crop sequence (crops and bare soil) • Define yield potentials and grazed yields • also define fate of crop residues • Define livestock numbers, feed rations, livestock housing and manure storage • calculates manure production • calculates livestock production • Decide manure and fertiliser applications

  21. Running FarmAC (2) • Simulate! • What can go wrong • grazed yield cannot be achieved • total production of grazed forage does not equal total consumption of grazed forage

  22. Yield modelling • Potential yield (water and N unlimited) • for all crop products • input by users • Calculate water-limited yield (Water balance) • Calculate N uptake at water-limited yield • includes N in above and below-ground crop residues • Calculate mineral N available • Mineral N or maximum uptake determines yield

  23. Calculating mineral N available • Mineral N = mineral N input - losses • N inputs • atmosphere • N fixation • fertiliser • manure • urine • mineralised soil, manure organic N, dung and crop residue N

  24. Calculating mineral N available • N outputs • Ammonia emission, which varies between • fertiliser, manure, urine • application method • N2O and N2 emission • N2O via emission factor (varies between sources) • N2 = N2O * factor • N leaching, which varies with • timing of application of fertiliser/manure • Period with drainage

  25. Growth • Potential crop N uptake = crop N uptake with water-limited yield • If mineral N available >= potential crop N uptake • Modelled growth = water-limited growth • Otherwise • Modelled growth = mineral N available/potential crop N uptake

  26. How to define a permanent crop • The fertilisation necessary to achieve a given yield will change with time • For grazed crops, the fertilisation will be determined by the year with the least mineralisation of soil N • Means that excessive fertiliser will be applied in other years • Break the permanent crop into several crops

  27. Amazonian forest • Simulated here by teak • Main features: • no export of products • deep roots, high rainfall 1000 mm drainage and high temperature • high C:N ration in residues • N input 10 kg/ha/yr from precipitation

  28. Forest Total soil-C Slow degradable ½ time life = 365 years degradeble ½ time life =5 year Quick degradeble ½ time life =1,5 mdr

  29. Bare soil

  30. Grass – no cattle

  31. Grass – few cattle

  32. Grass – more cattle

  33. N inputs – light grazing

  34. N outputs – light grazing

  35. C stored in soil – long term

  36. Dry matter production – long term

  37. N inputs long term

  38. N outputs long term

  39. Losses arecalculated for the wholecropperiod

  40. So it mightbe sensible to divide the crop in two

  41. 130 DK dairy 120 110 Pig C (t/ha) 100 Arable 90 80 70 2000 2020 2040 2060 2080 2100 År Soil-C in farm type

  42. Soil pools never in equilibrium

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