Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales

  1. Schröder, W. 1
  2. Nickel, S. 1
  3. Schönrock, S. 1
  4. Schmalfuß, R. 1
  5. Wosniok, W. 9
  6. Meyer, M. 1
  7. Harmens, H. 8
  8. Frontasyeva, M.V. 15
  9. Alber, R. 4
  10. Aleksiayenak, J. 11
  11. Barandovski, L. 24
  12. Blum, O. 16
  13. Carballeira, A. 2
  14. Dam, M. 3
  15. Danielsson, H. 13
  16. De Temmermann, L. 32
  17. Dunaev, A.M. 12
  18. Godzik, B. 33
  19. Hoydal, K. 3
  20. Jeran, Z. 14
  21. Karlsson, G.P. 13
  22. Lazo, P. 28
  23. Leblond, S. 17
  24. Lindroos, J. 18
  25. Liiv, S. 25
  26. Magnússon, S.H. 7
  27. Mankovska, B. 10
  28. Núñez-Olivera, E. 26
  29. Piispanen, J. 19
  30. Poikolainen, J. 19
  31. Popescu, I.V. 31
  32. Qarri, F. 30
  33. Santamaria, J.M. 27
  34. Skudnik, M. 23
  35. Špirić, Z. 6
  36. Stafilov, T. 24
  37. Steinnes, E. 21
  38. Stihi, C. 31
  39. Suchara, I. 22
  40. Thöni, L. 5
  41. Mostrar todos os autores +
  1. 1 University of Vechta
    info

    University of Vechta

    Vechta, Alemania

    ROR https://ror.org/045y6d111

  2. 2 Universidade de Santiago de Compostela
    info

    Universidade de Santiago de Compostela

    Santiago de Compostela, España

    ROR https://ror.org/030eybx10

  3. 3 Environment Agency, Argir, Faroe Islands
  4. 4 Environmental Agency of Bolzano, Laives, Italy
  5. 5 FUB-Research Group for Environmental Monitoring, Rapperswil, Switzerland
  6. 6 Green Infrastructure Ltd, Zagreb, Croatia
  7. 7 Icelandic Institute of Natural History, Garðabær, Iceland
  8. 8 ICP Vegetation Programme Coordination Centre, Centre for Ecology & Hydrology, Environment Centre Wales, Bangor, United Kingdom
  9. 9 University of Bremen
    info

    University of Bremen

    Brema, Alemania

    ROR https://ror.org/04ers2y35

  10. 10 Institute of Landscape Ecology, Slovak Academy of Sciences, Bratislava, Slovakia
  11. 11 International Sakharov Environmental University
    info

    International Sakharov Environmental University

    Minsk, Bielorrusia

    ROR https://ror.org/05198a862

  12. 12 Ivanovo State University of Chemistry and Technology
    info

    Ivanovo State University of Chemistry and Technology

    Ivánovo, Rusia

    ROR https://ror.org/02fjy3w42

  13. 13 IVL Swedish Environmental Research Institute, Göteborg, Sweden
  14. 14 Jožef Stefan Institute, Ljubljana, Slovenia
  15. 15 Moss Survey Coordination Centre, Frank Laboratory of Neutron Physics, Joint Institute for Nuclear Research, Dubna, Moscow Region, Moscow, Russian Federation
  16. 16 National Botanical Garden, Academy of Science of Ukraine, Kiev, Ukraine
  17. 17 National Museum of Natural History, Paris, France
  18. 18 Natural Resources Institute, Helsinki, Finland
  19. 19 Natural Resources Institute Finland (Luke), Oulou, Finland
  20. 20 Norwegian Institute for Air Research, Kjeller, Norway
  21. 21 Norwegian University of Science and Technology
    info

    Norwegian University of Science and Technology

    Trondheim, Noruega

    ROR https://ror.org/05xg72x27

  22. 22 Silva Tarouca Research Institute for Landscape and Ornamental Gardening, Průhonice, Czech Republic
  23. 23 Slovenian Forestry Institute, Ljubljana, Slovenia
  24. 24 St. Cyril and St. Methodius University of Veliko Tarnovo
    info

    St. Cyril and St. Methodius University of Veliko Tarnovo

    Veliko Tarnovo, Bulgaria

    ROR https://ror.org/027n8z047

  25. 25 Tallinn Botanic Garden, Tallinn, Estonia
  26. 26 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  27. 27 Universidad de Navarra
    info

    Universidad de Navarra

    Pamplona, España

    ROR https://ror.org/02rxc7m23

  28. 28 University of Tirana
    info

    University of Tirana

    Tirana, Albania

    ROR https://ror.org/03g9v2404

  29. 29 University of Vienna, Wien, Austria
  30. 30 University of Vlora, Vlorë, Albania
  31. 31 Valahia University of Targoviste
    info

    Valahia University of Targoviste

    Târgovişte, Rumanía

    ROR https://ror.org/00ywqar95

  32. 32 Veterinary and Agrochemical Research Centre CODA-CERVA, Tervuren, Belgium
  33. 33 W. Szafer Institute of Botany, Polish Academy of Sciences, Kraków, Poland
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Revista:
Annals of Forest Science

ISSN: 1286-4560

Ano de publicación: 2017

Volume: 74

Número: 2

Tipo: Artigo

DOI: 10.1007/S13595-017-0621-6 SCOPUS: 2-s2.0-85017312083 WoS: WOS:000405798400001 GOOGLE SCHOLAR

Outras publicacións en: Annals of Forest Science

Resumo

Key message: Moss surveys provide spatially dense data on environmental concentrations of heavy metals and nitrogen which, together with other biomonitoring and modelling data, can be used for indicating deposition to terrestrial ecosystems and related effects across time and areas of different spatial extension. Context: For enhancing the spatial resolution of measuring and mapping atmospheric deposition by technical devices and by modelling, moss is used complementarily as bio-monitor. Aims: This paper investigated whether nitrogen and heavy metal concentrations derived by biomonitoring of atmospheric deposition are statistically meaningful in terms of compliance with minimum sample size across several spatial levels (objective 1), whether this is also true in terms of geostatistical criteria such as spatial auto-correlation and, by this, estimated values for unsampled locations (objective 2) and whether moss indicates atmospheric deposition in a similar way as modelled deposition, tree foliage and natural surface soil at the European and country level, and whether they indicate site-specific variance due to canopy drip (objective 3). Methods: Data from modelling and biomonitoring atmospheric deposition were statistically analysed by means of minimum sample size calculation, by geostatistics as well as by bivariate correlation analyses and by multivariate correlation analyses using the Classification and Regression Tree approach and the Random Forests method. Results: It was found that the compliance of measurements with the minimum sample size varies by spatial scale and element measured. For unsampled locations, estimation could be derived. Statistically significant correlations between concentrations of heavy metals and nitrogen in moss and modelled atmospheric deposition, and concentrations in leaves, needles and soil were found. Significant influence of canopy drip on nitrogen concentration in moss was proven. Conclusion: Moss surveys should complement modelled atmospheric deposition data as well as other biomonitoring approaches and offer a great potential for various terrestrial monitoring programmes dealing with exposure and effects. © 2017, INRA and Springer-Verlag France.