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Simulating the Effects of Agrochemicals and Other Risk-Bearing Management Measures on the Terrestrial Agrobiodiversity: The RISKMIN Approach

  • Matthias TrappEmail author
  • Mark Deubert
  • Lucas Streib
  • Björn Scholz-Starke
  • Martina Roß-Nickoll
  • Andreas Toschki
Chapter
  • 46 Downloads
Part of the Innovations in Landscape Research book series (ILR)

Abstract

The RISKMIN Model was a research project funded by the German Federal Office of Consumer Protection and Food Safety between 2012 and 2016 to support the development of a landscape-based mitigation approach for assessing different measures and their effects on agrobiodiversity. Conducted by an interdisciplinary cooperation between different research groups in Germany two representative landscapes were chosen as pilot regions. Based on a very high-resolution landscape analysis and a comprehensive survey of the terrestrial agrobiodiversity in these regions a simulation of different risk mitigation measures was realized by reference to potential scenarios. The resulting effects could be analysed, quantified and visualized with the help of geographic information systems (GIS). Main results are that the most effective measure on landscape level is the extensification of the land use, but on the other hand, that the combination of in crop and off crop measures does have the most effects for the landscape elements with the highest ecological values.

Keywords

Landscape classification and analysis Agrobiodiversity Ecological values Risk assessment Mitigation measures GIS 

Notes

Acknowledgements

We thank the German Federal Office of Consumer Protection and Food Safety for funding the research project called “Landschaftsbezogene Risikominderungsmaßnahmen zur Förderung der terrestrischen Agrobiodiversität (RISKMIN)”. The full document can be downloaded by https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/01_Aufgaben/09_GesundheitNaturhaushalt/02_SchutzNaturhaushalt/psm_SchutzNaturhaushalt_RiskMin_basepage.html. We also thank the Land Survey Authorities in Rhineland—Palatinate and in North Rhine—Westphalia for supporting this research project by giving the license of using geodata: © LVermGeo 2019, www.lvermgeo.rlp.de Open.NRW—Das Open Government Portal für das Land Nordrhein-Westfalen, “www.open.nrw”.

References

  1. Adam K, Nohl W, Valentin W (1986) Bewertungsgrundlagen für Kompensationsmaßnahmen bei Eingriffen in die Landschaft. In: Ministerium für Umwelt, Landwirtschaft, Natur- und Verbraucherschutz Nordrhein-Westfalen (ed) Naturschutz und Landschaftspflege in Nordrhein-Westfalen. DüsseldorfGoogle Scholar
  2. Biedermann U, Werking-Radtke J, Woike M (2008) Numerische Bewertung von Biotoptypen für die Eingriffsregelung in NRW. In: Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen (LANUV NRW) (ed.) Recklinghausen. https://www.lanuv.nrw.de/fileadmin/lanuv/natur/lebensr/Num_Bew_Biotyp_Sept2008.pdf
  3. Enzian S, Gutsche V (2005) GIS - gestützte Berechnung der Ausstattung von Agrarräumen mit naturnahen terrestrischen Biotopen auf der Basis der Gemeinden – 2. Ausgabe des Verzeichnisses der regionalisierten Kleinstrukturanteile Biologische Bundesanstalt für Land- und Forstwirtschaft, Institut für Folgen-ab-schätzung im Pflanzenschutz, Kleinmachnow. https://www.julius-kuehn.de/sf/ab/raeumliche-analysen-und-modellierung/verzeichnis-der-regionalisierten-kleinstrukturanteile/
  4. European Environment Agency (EEA) (2013) the European grassland butterfly indicator: 1990–2011. EEA Technical report No 11/2013, p 36Google Scholar
  5. European Food Safety Authority (EFSA) (2016) Recovery in environmental risk assessments (ERA). EFSA J 14(2):4313, 85.  https://doi.org/10.2903/j.efsa.2016.4313
  6. Federal Agency for Natural Conservation (BfN) (2011) Landscapes of conservation importance. https://www.bfn.de/en/activities/protecting-habitats-and-landscapes/landscapes-of-conservation-importance.html
  7. Hallmann CA, Sorg M, Jongejans E, Siepel H, Hofland N, Schwan H et al (2017) More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12(10):e0185809.  https://doi.org/10.1371/journal.pone.0185809CrossRefPubMedPubMedCentralGoogle Scholar
  8. Jahn T, Hötker H, Oppermann R, Bleil R, Vele L (2014) Protection of biodiversity of free living birds and mammals in respect of the effects of pesticides, Federal Environment Agency (Umweltbundesamt), 06844 Dessau-Roßlau. https://www.umweltbundesamt.de/publikationen/protection-of-biodiversityof-free-living-birds, ISSN 1862-4804
  9. Lang S, Blaschke T (2007) Landschaftsanalyse mit GIS. Ulmer, StuttgartGoogle Scholar
  10. Ludwig D, Meinig H (1991) Methode zur ökologischen Bewertung der Biotopfunktion von Biotoptypen. BochumGoogle Scholar
  11. Roß-Nickoll M, Lennartz G, Fürste A, Mause R, Ottermanns R, Schäfer S, Smolis M, Theissen B, Toschki A, Ratte HAT (2004) Die Arthropodenfauna von Nichtzielflächen und die Konsequenzen für die Bewertung der Auswirkungen von Pflanzenschutzmitteln auf den terrestrischen Bereich des Na-turhaushaltes. Umweltbundesamt (UBA), Berlin. FKZ 20063403, p 148Google Scholar
  12. Scholz-Starke B, Trapp M, Streib L, Deubert M, Oellers J, Fürste A, Luther S, Peters S, Toschki A, Roß-Nickoll M (2016) Landschaftsbezogene Risikominderungsmaßnahmen zur Förderung der terrestrischen Agrobiodiversität (RISKMIN). Federal Office of Consumer Protection and Food Safety (BVL). https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/01_Aufgaben/09_GesundheitNaturhaushalt/02_SchutzNaturhaushalt/psm_SchutzNaturhaushalt_RiskMin_basepage.html
  13. Tintrup gen Suntrup G, Jalke T, Streib L, Keck N, Nieland S, Moran N, Kleinschmit B, Trapp M (2014) New methods in acquisition, update and dissemination of nature conservation geodata – implementation of an integrated framework. In: The 36th international symposium ion remote sensing of environment, 11–15 May 2015, Berlin, GermanyGoogle Scholar
  14. Toschki A (2008) Eignung unterschiedlicher Monitoring-Methoden als Grundlage zum Risk-Assessment für Agrarsysteme - Am Beispiel einer biozönologischen Reihenuntersuchung und einer Einzelfall-studie. Phd thesis Institute for Environmental Research, RWTH-Aachen, p 162Google Scholar
  15. Trapp M, Jalke T, Tintrup gen Suntrup G (2015) Automatisierung von Verwaltungsabläufen am Beispiel von Landwirtschaft und Umwelt, LSA VERM 1/2015, pp 25–30Google Scholar
  16. Trapp M, Deubert M, Streib L, Roß-Nickoll M, Scholz-Starke B, Toschki A (2018) Simulating the effects of agrochemicals and other risk-bearing management measures on the terrestrial agrobiodiversity: the RISKMIN approach. J Plant Sci Nov Methods Results Landsc Res Eur Cent Asia Sib 3(2018):228–342.  https://doi.org/10.25680/5187.2018.80.87.264CrossRefGoogle Scholar
  17. Tscharntke T, Klein AM, Kruess A, Steffan-Dewenter I, Thies C (2005) Landscape perspectives on agricultural intensification and biodiversity – ecosystem service management. Ecol Lett. 8:857–874.  https://doi.org/10.1111/j.1461-0248.2005.00782.x
  18. Working Committee of the Surveying Authorities of the States of the Federal Republic of Germany (AdV) (2015) Documentation on the modelling of geoinformation of official surveying and mapping. http://www.adv-online.de/Publications/AFIS-ALKIS-ATKIS-Project/binarywriterservlet?imgUid=8e1708ee-765f-8551-2357-c133072e13d6&uBasVariant=11111111-1111-1111-1111-111111111111

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Matthias Trapp
    • 1
    Email author
  • Mark Deubert
    • 1
  • Lucas Streib
    • 1
  • Björn Scholz-Starke
    • 2
  • Martina Roß-Nickoll
    • 3
  • Andreas Toschki
    • 4
  1. 1.Institute for AgroEcology (IfA), RLP AgroScienceNeustadtGermany
  2. 2.Darwin statisticsAachenGermany
  3. 3.Institute for Environmental Research (Biology V)RWTH Aachen UniversityAachenGermany
  4. 4.Gaiac - Research Institute for Ecosystem Analysis and AssessmentAachenGermany

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