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Project

MonViA: German farmland biodiversity monitoring



© BMEL

German farmland biodiversity monitoring

Far reaching changes in production systems and in farm management have led to a decline in farmland biodiversity. To counteract this decline, a national database is needed that allows conclusions to be drawn about cause-effect relationships.

Background and Objective

In Germany, around 50 percent of the land is used for agricultural purposes. Therefore, agriculture plays an important role in the conservation and promotion of farmland biodiversity. In particular, land-use and farm management, and closely linked to this, the configuration of agricultural landscapes, are mainly responsible for the decline in farmland biodiversity. Since existing monitoring programmes only allow to a limited extent scientifically reliable conclusions on underlying cause-effect relationships and on evaluations of the effectiveness of agri-environmental policy measures to promote farmland biodiversity, a representative nationwide data basis is required.

In the joint project MonViA, scientists want to provide well-founded answers to the following questions:

  • How does agricultural production, changes in land- use and agricultural structure influence farmland biodiversity?
  • How do changes in farmland biodiversity affect the performance and stability of agricultural production systems?
  • How do agri-environmental policy instruments affect farmland biodiversity?

 

Target Group

Agriculture, science, politics

Approach

MonViA is designed to complement existing nature conservation monitoring schemes and starts with a 5-year pilot phase in which standardised sampling methods are developed and feasibility studies for the development of innovative indicator systems are carried out. MonViA consists of three monitoring sections: a nationwide general trend monitoring, a question-based monitoring on specific agricultural issues and a Citizen Science-based monitoring. In the latter case, farmers in particular are to be involved in monitoring activities.
MonViA deals, in addition to the diversity and quality of habitats, with different groups of organisms. The focus is on functional groups (pollinators, pests, beneficial organisms, soil fauna) that are of particular importance for the performance of agricultural production systems.

The scientific conception and development of MonViA is carried out by a total of 12 specialist institutes of the Thünen Institute and the Julius Kühn Institute. The Information and Coordination Centre of Biological Diversity of the Federal Agency for Agriculture and Food is responsible for the presentation of results for politicians and the public. The overall coordination of the joint project is carried out by the Thünen Institute of Biodiversity.

Links and Downloads

More information on MoViA and all projects are available on the website of the joint-project:
www.agrarmonitoring-monvia.de

Involved Thünen-Partners

Involved external Thünen-Partners

Funding Body

  • Federal Ministry of Food und Agriculture (BMEL)
    (national, öffentlich)

Duration

1.2019 - 12.2024

More Information

Project status: ongoing

Publications

  1. 0

    Klaus F, Ayasse M, Classen A, Dauber J, Diekötter T, Everaars J, Fornoff F, Greil H, Hendriksma HP, Jütte T, Klein A-M, Krahner A, Leonhardt SD, Lüken DJ, Paxton RJ, Schmid-Egger C, Steffan-Dewenter I, Thiele J, Tscharntke T, Erler S, Pistorius J (2024) Improving wild bee monitoring, sampling methods, and conservation. Basic Appl Ecol 75:2-11, DOI:10.1016/j.baae.2024.01.003

    https://literatur.thuenen.de/digbib_extern/dn067619.pdf

  2. 1

    Yang J, Schrader S, Tebbe CC (2024) Legacy effects of earthworms on soil microbial abundance, diversity, and community dynamics. Soil Biol Biochem 190:109294, DOI:10.1016/j.soilbio.2023.109294

    https://literatur.thuenen.de/digbib_extern/dn067492.pdf

  3. 2

    Sickel W, Zizka V, Scherges A, Bourlat SJ, Dieker P (2023) Abundance estimation with DNA metabarcoding - recent advancements for terrestrial arthropods. Metabarcoding & Metagenomics 7:e112290, DOI:10.3897/mbmg.7.112290

    https://literatur.thuenen.de/digbib_extern/dn067243.pdf

  4. 3

    Sickel W, Kulow J, Krüger L, Dieker P (2023) BEE-quest of the nest: A novel method for eDNA-based, nonlethal detection of cavity-nesting hymenopterans and other arthropods. Environmental DNA 5(6):1163-1176, DOI:10.1002/edn3.490

    https://literatur.thuenen.de/digbib_extern/dn067323.pdf

  5. 4

    Gönner J von, Herrmann TM, Bruckermann T, Eichinger M, Hecker S, Klan F, Lorke J, Richter A, Sturm U, Voigt-Heucke S, Brink W, Liedtke C, Premke-Kraus M, Altmann C, Bauhus W, Bengtsson L, Büermann A, Dietrich P, Dörler D, Eich-Brod R, et al (2023) Citizen science's transformative impact on science, citizen empowerment and socio-political processes. Socio-ecol pract res 5(1):11-33, DOI:10.1007/s42532-022-00136-4

    https://literatur.thuenen.de/digbib_extern/dn065961.pdf

  6. 5

    Pérez-Sánchez AJ, Schröder B, Dauber J, Hellwig N (2023) Flower strip effectiveness for pollinating insects in agricultural landscapes depends on established contrast in habitat quality: A meta-analysis. Ecol Solut Evid 4(3):e12261, DOI:10.1002/2688-8319.12261

    https://literatur.thuenen.de/digbib_extern/dn066651.pdf

  7. 6

    Kasiske T, Dauber J, Harpke A, Klimek S, Kühn E, Settele J, Musche M (2023) Livestock density affects species richness and community composition of butterflies: A nationwide study. Ecol Indic 146:109866, DOI:10.1016/j.ecolind.2023.109866

    https://literatur.thuenen.de/digbib_extern/dn065917.pdf

  8. 7

    Ayasse M, Fornoff F, Grabener S, Hoiß B, Hopfenmüller S, Hornby G, König C, Mayr A, Rest M, Reininghaus H, Schlager M, Schmid-Egger C, Seitz H, Sommerlandt FMJ, Tschöpe M, Zobel M (2023) Sammeln von Wildbienen in der Natur - Artenschutzfachliche Argumente : Biodiversität. Düsseldorf: VDI, 19 p, VDI Richtl

  9. 8

    Mupepele A-C, Hellwig N, Dieker P, Klein A-M (2023) What evidence exists on wild-bee trends in Germany? Research protocol for a systematic map. PROCEED, 6 p, DOI:10.57808/proceed.2023.2

    https://literatur.thuenen.de/digbib_extern/dn066671.pdf

  10. 9

    Bowler DE, Bhandari N, Repke L, Beuthner C, Callaghan CT, Eichenberg D, Henle K, Klenke R, Richter A, Jansen F, Bruelheide H, Bonn A (2022) Decision-making of citizen scientists when recording species observations. Sci Rep 12:11069, DOI:10.1038/s41598-022-15218-2

    https://literatur.thuenen.de/digbib_extern/dn065060.pdf

  11. 10

    Hellwig N, Schubert LF, Kirmer A, Tischew S, Dieker P (2022) Effects of wildflower strips, landscape structure and agricultural practices on wild bee assemblages - A matter of data resolution and spatial scale? Agric Ecosyst Environ 326:107764, DOI:10.1016/j.agee.2021.107764

    https://literatur.thuenen.de/digbib_extern/dn064248.pdf

  12. 11

    Schmidt A, Kirmer A, Hellwig N, Kiehl K, Tischew S (2022) Evaluating CAP wildflower strips: High-quality seed mixtures significantly improve plant diversity and related pollen and nectar resources. J Appl Ecol 59(3):860-871, DOI:10.1111/1365-2664.14102

    https://literatur.thuenen.de/digbib_extern/dn064671.pdf

  13. 12

    Schubert LF, Hellwig N, Kirmer A, Schmid-Egger C, Schmidt A, Dieker P, Tischew S (2022) Habitat quality and surrounding landscape structures influence wild bee occurrence in perennial wildflower strips. Basic Appl Ecol 60:76-86, DOI:10.1016/j.baae.2021.12.007

    https://literatur.thuenen.de/digbib_extern/dn064531.pdf

  14. 13

    Richter A, Hendriksma HP, Greil H, Gummert A, Kraft M, Ulber L, Redwitz Cv, Chiavassa JA, Lüken DJ (2022) Handreichung : Citizen Science-basiertes Monitoring der Biodiversität in Agrarlandschaften. Braunschweig: Thünen-Institut für Biodiversität, II, 24 p

    https://literatur.thuenen.de/digbib_extern/dn065677.pdf

  15. 14

    Schwieder M, Wesemeyer M, Frantz D, Pfoch K, Erasmi S, Pickert J, Nendel C, Hostert P (2022) Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series. Remote Sens Environ 269:112795, DOI:10.1016/j.rse.2021.112795

    https://literatur.thuenen.de/digbib_extern/dn064247.pdf

  16. 15

    Blickensdörfer L, Schwieder M, Pflugmacher D, Nendel C, Erasmi S, Hostert P (2022) Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sens Environ 269:112831, DOI:10.1016/j.rse.2021.112831

    https://literatur.thuenen.de/digbib_extern/dn064297.pdf

  17. 16

    Richter A (2022) Quality assurance indicators for environmental citizen science : development of indicators for volunteer-based biodiversity monitoring. Fteval journal 53:68-80, DOI:10.22163/fteval.2022.573

    https://literatur.thuenen.de/digbib_extern/dn065474.pdf

  18. 17

    Wolters V, Feindt PH, Dauber J, Bahrs E, Finckh M, Graner A, Jaenicke H, Krämer F, Kreuter-Kirchhof C, Schleip I, Schröder S, Tholen E, Wagner S, Wätzold F, Wedekind H, Weigend S, Wolf H, Zander K (2022) Synergien nutzen: Für die Beteiligung des BMEL an der neuen Nationalen Biodiversitätsstrategie. Kurzstellungnahme des Wissenschaftlichen Beirats für Biodiversität und Genetische Ressourcen beim Bundesministerium für Ernährung und Landwirtschaft. 7 p

  19. 18

    Sietz D, Klimek S, Dauber J (2022) Tailored pathways toward revived farmland biodiversity can inspire agroecological action and policy to transform agriculture. Comm Earth Environ 3:211, DOI:10.1038/s43247-022-00527-1

    https://literatur.thuenen.de/digbib_extern/dn065370.pdf

  20. 19

    Hertzog LR, Röder N, Frank C, Böhner HGS, Kamp J (2022) Village modernization and farmland birds: A reply to Rosin et al. (2021). Conserv Lett 15(2):e12874, DOI:10.1111/conl.12874

    https://literatur.thuenen.de/digbib_extern/dn065540.pdf

  21. 20

    Lobert F, Holtgrave A-K, Schwieder M, Pause M, Gocht A, Vogt J, Erasmi S (2021) Detection of mowing events from combined Sentinel-1, Sentinel-2, and Landsat 8 time series with machine learning. Grassl Sci Europe 26:123-125

  22. 21

    Tetteh GO, Gocht A, Erasmi S, Schwieder M, Conrad C (2021) Evaluation of sentinel-1 and sentinel-2 feature sets for delineating agricultural fields in heterogeneous landscapes. IEEE Access 9:116702-116719, DOI:10.1109/ACCESS.2021.3105903

    https://literatur.thuenen.de/digbib_extern/dn063902.pdf

  23. 22

    Yang J, Wang H, Samad MS, Tebbe CC (2021) Fine-scale temporal monitoring of soil microbial communities at an agricultural field site. Verhandl Gesellsch Ökol 50: 133

  24. 23

    Böhner HGS, Joormann I (2021) Fördermaßnahmen aus Agrarumweltprogrammen. Ökol Wirtschaften 36(4):19-20, DOI:10.14512/OEW360419

    https://literatur.thuenen.de/digbib_extern/dn064290.pdf

  25. 24

    Pérez Sánchez AJ, Dauber J (2021) How beneficial are flower strips for biodiversity in European agricultural landscapes? Verhandl Gesellsch Ökol 50: 316

  26. 25

    Hertzog LR, Frank C, Klimek S, Röder N, Böhner HGS, Kamp J (2021) Model-based integration of citizen science data from disparate sources increases the precision of bird population trends. Diversity Distrib 27(6):1106-1119, DOI:10.1111/ddi.13259

    https://literatur.thuenen.de/digbib_extern/dn063506.pdf

  27. 26

    Lobert F, Holtgrave A-K, Schwieder M, Pause M, Vogt J, Gocht A, Erasmi S (2021) Mowing event detection in permanent grasslands: Systematic evaluation of input features from Sentinel-1, Sentinel-2, and Landsat 8 time series. Remote Sens Environ 267:112751, DOI:10.1016/j.rse.2021.112751

    https://literatur.thuenen.de/digbib_extern/dn064075.pdf

  28. 27

    Schlund M, Lobert F, Erasmi S (2021) Potential of Sentinel-1 time series data for the estimation of season length in winter wheat phenology. In: Institute of Electrical and Electronics Engineers (ed) IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium : proceedings ; 12-16 July 2021, Virtual Symposium, Brussels, Belgium. IEEE, pp 5917-5920, DOI: 10.1109/IGARSS47720.2021.9554454

  29. 28

    Potts SG, Dauber J, Hochkirch A, Oteman B, Roy DB, Ahrné K, Biesmeijer K, Breeze TD, Carvell C, Ferreira C, Fitzpatrick U, Isaac NJB, Kuussaari M, Ljubomirov T, Maes J, Ngo H, Pardo A, Polce C, Quaranta M, Settele J, et al (2021) Proposal for an EU pollinator monitoring scheme. Luxembourg: Publications Office of the European Union, 310 p, JRC Techn Rep, DOI:10.2760/881843

    https://literatur.thuenen.de/digbib_extern/dn063257.pdf

  30. 29

    Kasiske T (2021) Tagfalter in Agrarlandschaften - Einfluss von Landnutzung und Landschaftsstruktur auf verschiedenen räumlichen und zeitlichen Skalen. Oedippus 39:36-38

  31. 30

    Pe'er G, Bonn A, Bruelheide H, Dieker P, Eisenhauer N, Feindt PH, Hagedorn G, Hansjürgens B, Herzon I, Lomba A, Marquard E, Moreira F, Nitsch H, Oppermann R, Perino A, Röder N, Schleyer C, Schindler S, Wolf C, Zinngrebe Y, Lakner S (2020) Action needed for the EU Common Agricultural Policy to address sustainability challenges. People Nature 2(2):305-316, DOI:10.1002/pan3.10080

    https://literatur.thuenen.de/digbib_extern/dn062144.pdf

  32. 31

    Kühl HS, Bowler DE, Bösch L, Bruelheide H, Dauber J, Eichenberg D, Eisenhauer N, Fernandez N, Guerra CA, Henle K, Herbinger I, Isaac NJB, Jansen F, König-Ries B, Kühn I, Nilsen EB, Pe'er G, Richter A, Schulte R, Settele J, et al (2020) Effective biodiversity monitoring needs a culture of integration. One Earth 3(4):462-474, DOI:10.1016/j.oneear.2020.09.010

    https://literatur.thuenen.de/digbib_extern/dn062813.pdf

  33. 32

    Lindermann L, Dieker P (2020) Hohlräume für die wilden Bestäuber. Bauernzeitg 61(30):24-25

  34. 33

    Eichenberg D, Bernhardt-Römermann M, Bowler DE, Bruelheide H, Conze K-J, Dauber J, Dengler J, Engels D, Fartmann T, Frank D, Geske C, Grescho V, Harter D, Henle K, Hofmann S, Jandt U, Jansen F, Kamp J, Kautzner A, König-Ries B, et al (2020) Langfristige Biodiversitätsveränderungen in Deutschland erkennen - mit Hilfe der Vergangenheit in die Zukunft schauen. Natur Landsch 95(11):479-491, DOI:10.17433/11.2020.50153851.479-491

  35. 34

    Sickel W, Dieker P (2020) Neues Werkzeug: Umwelt-DNA. Bauernzeitg 61(46):22-23

  36. 35

    Schlund M, Erasmi S (2020) Sentinel-1 time series data for monitoring the phenology of winter wheat. Remote Sens Environ 246:111814, DOI:10.1016/j.rse.2020.111814

  37. 36

    Sommerlandt FMJ, Dieker P (2020) Wirksam für die Bienen? Bauernzeitg 61(29):26-27

  38. 37

    Dauber J, Dieker P, Beer H, Schröder S (2019) Auf der Suche nach wissenschaftlich belastbaren Antworten : Monitoring der biologischen Vielfalt in Agrarlandschaften. Dt Bauern Korrespondenz(6):14-15

  39. 38

    Geschke J, Vohland K, Bonn A, Dauber J, Gessner MO, Henle K, Nieschulze J, Schmeller D, Settele J, Sommerwerk N, Wetzel F (2019) Biodiversitätsmonitoring in Deutschland : Wie Wissenschaft, Politik und Zivilgesellschaft ein nationales Monitoring unterstützen können. GAIA 28(3):265-270, DOI:10.14512/gaia.28.3.6

    https://literatur.thuenen.de/digbib_extern/dn061966.pdf

  40. 39

    Dieker P, Dauber J (2019) Biodiversity monitoring schemes and indicators - challenges and feasibilities. In: GfÖ 2019 : Science meets practice ; 49th Annual Meeting of the Ecological Society of Germany, Austria and Switzerland ; University of Münster, 9 - 13 September 2019 ; book of abstracts. Berlin: Gesellschaft für Ökologie, p 550

  41. 40

    Dieker P, Beer H, Schröder S, Dauber J (2019) MonViA - a long term farmland biodiversity monitoring for Germany. In: GfÖ 2019 : Science meets practice ; 49th Annual Meeting of the Ecological Society of Germany, Austria and Switzerland ; University of Münster, 9 - 13 September 2019 ; book of abstracts. Berlin: Gesellschaft für Ökologie, p 553

  42. 41

    Dieker P, Kappes H, Klimek S, Dauber J (2019) Progress in farmland biodiversity monitoring in Germany. In: IALE World Congress 2019 - Nature and society facing the Anthropocene: challenges and perspectives for landscape ecology; 10th World Congress of the International Association for Landscape Ecology (IALE); Milan, 1-5 July 2019; book of abstracts. p 18

  43. 42

    Dauber J (2018) Progress towards a national farmland biodiversity monitoring in Germany. Verhandl Gesellsch Ökol 47/48: 402

  44. 43

    Ronnenberg K, Dauber J, Mitschke A, Ludwig J, Klimek S (2018) Regionally differentiated responses of farmland birds to levels of agricultural intensity. Verhandl Gesellsch Ökol 47/48: 403

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