Advertisement

Regional Environmental Change

, Volume 11, Issue 3, pp 663–678 | Cite as

How global conditions impact regional agricultural production and nitrogen surpluses in the German Elbe River Basin

  • Horst Gömann
  • Peter Kreins
  • Claudia Heidecke
Original Article

Abstract

Agricultural land use has shifted towards more intensified production because the prices of agricultural products have increased during the past years. Just a few years ago, voluntary area set-aside was a lucrative alternative in some regions. But nowadays, land is re-cultivated again, inter alia with biomass crops. Consequently, this affects the soil and nutrient balances in agriculture. The global changes on the world markets influence agricultural production and thus the water cycle at the regional scale. In this paper, the regional developments and policy alternatives are discussed for the Elbe River Basin. The paper concludes that on average, no substantial effects of nitrogen surpluses are expected for the Elbe River Basin due to a continuing decline in animal herds. However, at the county level, nitrogen surpluses are likely to exceed the maximum threshold of 60 kg nitrogen per hectare (stipulated in the German Fertiliser Regulation) due to regional concentrations of animal production. A halving of the threshold to 30 kg per hectare shows that the marginal costs of nitrogen surplus reduction regionally exceeded 10 Euros per kilogram nitrogen.

Keywords

Agriculture Land use Global change Agricultural sector model Nitrogen surplus 

Notes

Acknowledgments

The authors gratefully acknowledge the financial support of the research project “Impacts of Global Change on the Water Cycle in the Elbe Region—Risks and Options (GLOWA-Elbe)” funded by the Federal Ministry of Research and Education under the GLOWA programme (FKZ: 01 LW 0603A2).

References

  1. Behrendt H, Kornmilch M, Opitz D, Schmoll O, Scholz G (2001) Estimation of the nutrient inputs into river systems–experiences from German rivers. Reg Environ Change 3:107–117. doi: 10.1007/s10113-002-0042-3 CrossRefGoogle Scholar
  2. Blazejczak J, Gornig M, Schulz E, Schäpel C (2008) Szenarien zur Demographie und Ökonomie in der Elbe-Region. Wirkungen des globalen Wandels auf den Wasserkreislauf im Elbegebiet—Risiken und Optionen. Schlussbericht (Final report) zum BMBF-Vorhaben GLOWA-Elbe II, PotsdamGoogle Scholar
  3. BMU (Federal Ministry for the Environment, Nature Conservation and Nuclear Safety) and UBA (Federal Environment Agency) (2005) Die Wasserrahmenrichtlinie—Ergebnisse der Bestandsaufnahme 2004 in Deutschland. BerlinGoogle Scholar
  4. Bouwman AF, Kram T, Klein Goldewijk K (Eds.) (2006) Integrated modelling of global environmental change. An overview of IMAGE 2.4© Netherlands Environmental Assessment Agency (MNP), Bilthoven, October 2006. MNP publication number 500110002/2006. (access in March 2010; http://www.rivm.nl/bibliotheek/rapporten/500110002.pdf)
  5. Britz W, Hertel T (2009) Impacts of EU biofuels directives on global markets and EU environmental quality: an integrated PE, global CGE analysis. Agric Ecosyst Environ, doi: 10.1016/j.agee.2009.11.003
  6. Britz W, Witzke HP (2008) Development of a regionalised EU-wide operational model to assess the impact of current Common Agricultural Policy on farming sustainability, http://www.ilr1.uni-bonn.de/agpo/rsrch/capri/capri-documentation.pdf
  7. Carter TR, Jones RN, Lu X, Bhadwal S, Conde C, Mearns LO, O’Neill BC, Rounsevell MDA, Zurek MB (2007) New assessment methods and the characterisation of future conditions. Climate change 2007. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds), Impacts, adaptation and vulnerability. Contributions of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge, 133–171Google Scholar
  8. Cypris C (2000) Positive mathematische Programmierung (PMP) im Agrarsektormodell RAUMIS. Schriftenreihe der Forschungsgesellschaft für Agrarpolitik und Agrarsoziologie e.V. Bd. 313. Dissertation University of Bonn, BonnGoogle Scholar
  9. DüV (2006) Verordnung über die Anwendung von Düngemitteln, Bodenhilfsstoffen, Kultursubstraten und Pflanzenhilfsmitteln nach den Grundsätzen der guten fachlichen Praxis beim Düngen (Düngeverordnung–DüV). Bundesministerium der Justiz 10.01.2006Google Scholar
  10. Eickhout B, Prins AG (2008) Eururalis 2.0 Technical background and indicator documentation. Wageningen UR and Netherlands Environmental Assessment Agency (MNP) Bilthoven, The NetherlandsGoogle Scholar
  11. European Commission (2003a) Council regulation (EC) No 1782/2003 of 29 September 2003 establishing common rules for direct support schemes under the common agricultural policy and establishing certain support schemes for farmers. OJ L 270, 21.10.2003Google Scholar
  12. European Commission (2003b) Council regulation (EC) No 1784/2003 of 29 September 2003 on the common organisation of the market in cereals. OJ L 270/78, 21.10.2003Google Scholar
  13. European Commission (2003c) Council Regulation (EC) No 1787/2003 of 29 September 2003 amending Regulation (EC) No 1255/1999 on the common organisation of the market in milk and milk products. OJ L 270, 21.10.2003Google Scholar
  14. European Parliament and Council (2003) Directive 2003/30/EC of 8 May 2003 on the promotion of the use of biofuels or other renewable fuels for transport. OJ L 123/42. 17.5.2003Google Scholar
  15. Eurostat (1989) Handbuch zur landwirtschaftlichen und forstwirtschaftlichen Gesamtrechnung, LuxemburgGoogle Scholar
  16. FAPRI (Food and Agricultural Policy Research Institute) (2008) U.S. and World Agricultural Outlook. FAPRI Staff Report 08-FSR 1, ISSN 1534-4533, http://www.fapri.iastate.edu (access in March 2008)
  17. FNR (Fachagentur Nachwachsende Rohstoffe/Agency for Renewable Resources) (2005) Handreichung Biogasgewinnung und -nutzung. GülzowGoogle Scholar
  18. German Parliament (2004) Gesetz zur Neuregelung des Rechts der Erneuerbaren Energien im Strombereich vom 21. Juli 2004. Bundesgesetzblatt Jahrgang 2004 Teil I Nr. 40, ausgegeben zu Bonn am 31. JuliGoogle Scholar
  19. Gödeke K (2006) Entwicklung und Vergleich von optimierten Anbausystemen für die landwirtschaftliche Produktion von Energiepflanzen unter den verschiedenen Standortbedingungen Deutschlands. Präsentation des vom BMELV über die FNR geförderten Verbundprojektes auf dem GFP-Workshop in Freising am 9./10. MärzGoogle Scholar
  20. Gömann H, Kreins P, Herrmann S, Wechsung F (2005) Impacts of global changes on agricultural land-use in the German Elbe region—results of an operational modelling tool for planning, monitoring and agri-environmental policy counselling [CD-ROM]. In: 21st European Regional Conference -ERC 2005- Integrated Land and Water Resources Management: Towards Sustainable Rural Development, 15–19 May 2005–Frankfurt (Oder), Germany -Slubice, Poland. pp 11Google Scholar
  21. Gömann H, Kreins P, Breuer T (2007) Deutschland–Energie-Corn-Belt Europas? Agrarwirtschaft 56(5/6):263–271Google Scholar
  22. Gömann H, Kleinhanß W, Kreins P, Ledebur O von, Offermann F, Osterburg B, Salamon P (2009) Health Check der EU-Agrarpolitik : Auswirkungen der Beschlüsse. Agra Europe (Bonn) 50(18)Google Scholar
  23. Helming K, Perez-Soba M, Tabbush P (Eds) (2008) Sustainability impact assessment of land use changes. Springer,Berlin, pp 507Google Scholar
  24. Henrichsmeyer W, Cypris C, Löhe W, Meudt M, Sander R, Sothen F, von Isermeyer F, Schefski A, Schleef KH, Neander E, Fasterding F, Helmke B, Neumann M, Nieberg H, Manegold D, Meier Th (1996) Entwicklung des gesamtdeutschen Agrarsektormodells RAUMIS96. Endbericht zum Kooperationsprojekt. Forschungsbericht für das BML (94 HS 021). Vervielfältigtes Manuskript, Bonn/BraunschweigGoogle Scholar
  25. Henseler M, Wirsig A, Krimly T (2007) Introduction of ACRE: An agro-economic production model on regional level. Conference proceedings: EcoMod-Network: International Conference of Policy Modeling 2005 (EcoMod 2005), 29.06.–02.07.2005, IstanbulGoogle Scholar
  26. Hertel TW (1997) Global trade analysis: modelling and applications. Cambridge University Press, CambridgeGoogle Scholar
  27. Hofmann J, Behrendt H, Gilbert A, Janssen R, Kannen A, Kappenberg J, Lenhart H, Lise W, Nunneri C, Windhorst W (2005) Catchment–coastal zone interaction based upon scenario and model analysis: Elbe and the German Bight case study. Reg Environ Change 5:54–81. doi: 10.1007/s10113-004-0082-y CrossRefGoogle Scholar
  28. Howitt RE (1995) Positive Mathematical Programming. Am J Agr Econ 77(2):329–342CrossRefGoogle Scholar
  29. Hoymann J (2010, online): Accelerating urban sprawl in depopulating regions: a scenario analysis for the Elbe River Basin. Reg Environ Change, doi: 10.1007/s10113-010-0120-x
  30. IPCC, 2007: Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Core Writing Team, R.K. Pachauri and A. Reisinger, Eds., IPCC, Geneva, 104pGoogle Scholar
  31. Isermeyer F, Brockmeier M, Gömann H, Hargens R, Klepper R, Kreins P, Offermann F, Osterburg B, Pelikan J, Salamon P, Thiele H (2006) Analyse politischer Handlungsoptionen für den Milchmarkt. Braunschweig: FAL, 178 p, Landbauforsch. Völkenrode SH 300Google Scholar
  32. Kaiser F, Diepolder M, Eder J, Hartmann S, Prestele H, Gerlach R, Ziehfreund G, Gronauer A (2004) Ertragspotenziale verschiedener nachwachsender Rohstoffe in landwirtschaftlichen Biogasanlagen. Schriftenreihe der Bayerischen Landesanstalt für Landwirtschaft (LfL). Bd. 13. ISSN 1611–4159. FreisingGoogle Scholar
  33. Kempen M, Heckelei T, Britz W (2006) An econometric approach for spatial disaggregation of crop production in the EU, In: Arfini (ed), Modelling agricultural policies: state of the art and new challenges, proceeding of the 89 th Seminar of the EAAE, pp 810–830Google Scholar
  34. Koch H, Vögele S (2009) Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change. Ecol Econ 68(7):2031–2039CrossRefGoogle Scholar
  35. Kreins P, Gömann H (2008) Modellgestützte Abschätzung regionaler landwirtschaftlicher Landnutzung und Produktion in Deutschland vor dem Hintergrund der „Gesundheitsüberprüfung” der GAP. In: Agrarwirtschaft 57, Heft 3/4, pp 195–206Google Scholar
  36. Kreins P, Gömann H, Herrmann S, Kunkel R, Wendland F (2007) Integrated agricultural and hydrological modeling within an intensive livestock region. Adv Econ Environ Res 7:113–142CrossRefGoogle Scholar
  37. Lambin EF, Rounsevell MDA, Geist HJ (2000) Are agricultural land-use models able to predict changes in land-use intensity? Agric Ecosyst Environ 82:321–331CrossRefGoogle Scholar
  38. Ledoux L, Beaumont N, Cave R, Turner RK (2005) Scenarios for integrated river catchment and coastal zone management. Reg Environ Change 5:82–96. doi: 10.1007/s10113-004-0079-6 CrossRefGoogle Scholar
  39. Mudgal S, Benito P, Koomen E (2008) Modelling of EU land use choices and environmental impacts—scoping study. Funded by EU-Commission DG Env. Contract N° 070307/2007/485312/ETU/G1. Final Report, August 2008 (access in March 2010; http://ec.europa.eu/environment/enveco/others/pdf/landuse_final_report.pdf)
  40. PARCOM (Paris-Konvention zur Verhütung der Meeresverschmutzung) (1993) Dritte Sitzung der Ad-hoc-Arbeitsgruppe zur Reduzierung der Nährstoffeinträge aus der Landwirtschaft—Anlage 1: PARCOM-Richtlinien für die Berechnung von MineralbilanzenGoogle Scholar
  41. Pérez Domínguez I (2006) Greenhouse gases: Inventories, abatement costs and markets for emission permits in european agriculture—a modelling approach, Peter Lang, European University Studies, ISBN 3-631-55082-0, p 213Google Scholar
  42. USDA (United States Department of Agriculture) (2007) USDA Agricultural Projections to 2016. Long-term Projections Report OCE-2007-1. http://www.ers.usda.gov/publications/oce071/oce20071.pdf. Access in February 2007
  43. Van Ittersum MK, Ewert F, Heckelei T, Wery J, Alkan Olsson J, Andersen E, Bezlepkina I, Brouwer F, Donatelli M, Flichman G, Olsson L, Rizzoli A, Van der Wal T, Wien JE, Wolf J (2008) Integrated assessment of agricultural systems–A component-based framework for the European Union (SEAMLESS). Agric Syst 96:150–165CrossRefGoogle Scholar
  44. Van Mejil H, van Rheenen T, Tabeau A, Eickhout B (2006) The impact of different policy environments on agricultural land use in Europe. Agric Ecosyst Environ 114:21–38CrossRefGoogle Scholar
  45. Verburg PH, Overmars KP (2009) Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model. Landscape Ecol 24(9):1167–1181CrossRefGoogle Scholar
  46. Verburg PH, Koning GHJ, Kok K, Veldkamp A, Bouma J (1999) A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecol Model 116:45–61CrossRefGoogle Scholar
  47. Verburg PH, Eickhout B, van Meijl H (2008) A multi-scale, multi model approaches for analysing the future dynamics of European land use. Ann Reg Sci 42(1):57–77CrossRefGoogle Scholar
  48. Vetter A, Reinhold G (2005) Bereitstellung von Biomasse für Biogasanlagen. Tagungsband 2. Mitteldeutscher Bioenergietag am 29. April in Leipzig. Informationsschrift der Sächsischen Landesanstalt für Landwirtschaft des Freistaates SachsenGoogle Scholar
  49. Wechsung F, Kaden S, Behrendt H, Klöcking B (eds) (2008) Integrated Analysis of the impacts of global change on environment and society in the elbe river basin. GLOWA-Elbe. WeißenseeVerlag, Berlin, p 401Google Scholar
  50. Weinmann B, Schroers JO, Sheridan P (2006) Simulating the effects of decoupled transfer payments using the land use model ProLand. Agrarwirtschaft 55(5/6):248–256Google Scholar
  51. Wietze L, van der Veeren RJHM (2002) Cost-Effective Nutrient Emission Reductions in the Rhine River Basin. Integr Assess 3(4):321–342CrossRefGoogle Scholar
  52. Wirsig A (2009) Global change and regional agricultural land use—Impact estimates for the upper danube basin based on scenario data from european studies. Reihe: Europäische Hochschulschriften. Reihe 5: Volks- und Betriebswirtschaft, Band 3344. Peter Lang Internationaler Verlag, Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, p 187Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Institute of Rural Studies, Johann Heinrich von Thünen-InstitutFederal Research Institute for Rural Areas Forestry and FisheriesBraunschweigGermany

Personalised recommendations