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Replacements of small- by large-ranged species scale up to diversity loss in Europe’s temperate forest biome

Nature Ecology & Evolution volume 4, pages 802–808 (2020)Cite this article

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Abstract

Biodiversity time series reveal global losses and accelerated redistributions of species, but no net loss in local species richness. To better understand how these patterns are linked, we quantify how individual species trajectories scale up to diversity changes using data from 68 vegetation resurvey studies of seminatural forests in Europe. Herb-layer species with small geographic ranges are being replaced by more widely distributed species, and our results suggest that this is due less to species abundances than to species nitrogen niches. Nitrogen deposition accelerates the extinctions of small-ranged, nitrogen-efficient plants and colonization by broadly distributed, nitrogen-demanding plants (including non-natives). Despite no net change in species richness at the spatial scale of a study site, the losses of small-ranged species reduce biome-scale (gamma) diversity. These results provide one mechanism to explain the directional replacement of small-ranged species within sites and thus explain patterns of biodiversity change across spatial scales.

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Fig. 1: Spatial distribution of resurvey studies in Europe.
Fig. 2: Species that go extinct from a study site have smaller ranges than persisting and colonizing ones.
Fig. 3: Small-ranged species drive the increase in the average extinction risk from high N deposition.

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Data availability

The community change and environmental site-level data are available on figshare at https://figshare.com/s/45d71eb77c23c11bc857. The species composition data are available from forestreplot.ugent.be, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. These data are, however, available from the authors upon request and with the permission of the forestREplot consortium.

Code availability

The R code for all analyses is available on figshare at https://doi.org/10.6084/m9.figshare.10110713.v1.

References

  1. Barnosky, A. D. et al. Has the earth’s sixth mass extinction already arrived? Nature 471, 51–57 (2011).

    Article  CAS  PubMed  Google Scholar 

  2. Díaz, S. et al. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (Advance Unedited Version) (IPBES Secretariat, 2019).

  3. Pereira, H. M., Navarro, L. M. & Martins, I. S. Global biodiversity change: the bad, the good, and the unknown. Annu. Rev. Environ. Resour. 37, 25–50 (2012).

    Article  Google Scholar 

  4. Vellend, M. et al. Global meta-analysis reveals no net change in local-scale plant biodiversity over time. Proc. Natl Acad. Sci. USA 110, 19456–19459 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Dornelas, M. et al. Assemblage time series reveal biodiversity change but not systematic loss. Science 344, 296–299 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. Vellend, M. et al. Estimates of local biodiversity change over time stand up to scrutiny. Ecology 98, 583–590 (2017).

    Article  PubMed  Google Scholar 

  7. Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).

    Article  CAS  PubMed  Google Scholar 

  8. Damgaard, C. A critique of the space-for-time substitution practice in community ecology. Trends Ecol. Evol. 34, 416–421 (2019).

    Article  PubMed  Google Scholar 

  9. Cardinale, B. J., Gonzalez, A., Allington, G. R. H. & Loreau, M. Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends. Biol. Conserv. 219, 175–183 (2018).

    Article  Google Scholar 

  10. Gonzalez, A. et al. Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity. Ecology 97, 1949–1960 (2016).

    Article  PubMed  Google Scholar 

  11. Magurran, A. E., Dornelas, M., Moyes, F., Gotelli, N. J. & McGill, B. Rapid biotic homogenization of marine fish assemblages. Nat. Commun. 6, 8405 (2015).

    Article  CAS  PubMed  Google Scholar 

  12. Brown, J. H. On the relationship between abundance and distribution of species. Am. Nat. 124, 255–279 (1984).

    Article  Google Scholar 

  13. Gaston, K. J. The multiple forms of the interspecific abundance–distribution relationship. Oikos 76, 211–220 (1996).

    Article  Google Scholar 

  14. Gaston, K. J. et al. Abundance–occupancy relationships. J. Appl. Ecol. 37, 39–59 (2000).

    Article  Google Scholar 

  15. Schoener, T. W. & Spiller, D. A. High population persistence in a system with high turnover. Nature 330, 474–477 (1987).

    Article  Google Scholar 

  16. Kambach, S. et al. Of niches and distributions: range size increases with niche breadth both globally and regionally but regional estimates poorly relate to global estimates. Ecography (Cop.) 42, 467–477 (2019).

    Article  Google Scholar 

  17. Berendse, F. & Aerts, R. Nitrogen-use-efficiency: a biologically meaningful definition? Funct. Ecol. 1, 293–296 (1987).

    Google Scholar 

  18. Galloway, J. N. et al. Nitrogen cycles: past, present, and future. Biogeochemistry 70, 153–226 (2004).

    Article  CAS  Google Scholar 

  19. Aber, J. D. et al. Is nitrogen deposition altering the nitrogen status of northeastern forests? BioScience 53, 375–389 (2003).

    Article  Google Scholar 

  20. Gilliam, F. S. Response of the herbaceous layer of forest ecosystems to excess nitrogen deposition. J. Ecol. 94, 1176–1191 (2006).

    Article  CAS  Google Scholar 

  21. Aber, J. et al. Nitrogen saturation in temperate forest ecosystems: hypotheses revisited. BioScience 48, 921–934 (1998).

    Article  Google Scholar 

  22. Tian, D., Wang, H., Sun, J. & Niu, S. Global evidence on nitrogen saturation of terrestrial ecosystem net primary productivity. Environ. Res. Lett. 11, 24012 (2016).

    Article  CAS  Google Scholar 

  23. Clark, C. M. & Tilman, D. Loss of plant species after chronic low-level nitrogen deposition to prairie grasslands. Nature 451, 712–715 (2008).

    Article  CAS  PubMed  Google Scholar 

  24. Stevens, C. J., Dise, N. B., Mountford, J. O. & Gowing, D. J. Impact of nitrogen deposition on the species richness of grasslands. Science 303, 1876–1879 (2004).

    Article  CAS  PubMed  Google Scholar 

  25. Smith, M. D., Knapp, A. K. & Collins, S. L. A framework for assessing ecosystem dynamics in response to chronic resource alterations induced by global change. Ecology 90, 3279–3289 (2009).

    Article  PubMed  Google Scholar 

  26. Bobbink, R. et al. Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis. Ecol. Appl. 20, 30–59 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Clark, C. M. et al. Potential vulnerability of 348 herbaceous species to atmospheric deposition of nitrogen and sulfur in the United States. Nat. Plants 5, 697–705 (2019).

    Article  CAS  PubMed  Google Scholar 

  28. Ortmann-Ajkai, A. et al. Twenty-years’ changes of wetland vegetation: effects of floodplain-level threats. Wetlands 38, 591–604 (2018).

    Article  Google Scholar 

  29. Hernández, D. L. et al. Nitrogen pollution is linked to US listed species declines. BioScience 66, 213–222 (2016).

    Article  Google Scholar 

  30. Simkin, S. M. et al. Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States. Proc. Natl Acad. Sci. USA 113, 4086–4091 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Sonkoly, J. et al. Do large-seeded herbs have a small range size? The seed mass–distribution range trade-off hypothesis. Ecol. Evol. 7, 11204–11212 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Bartelheimer, M. & Poschlod, P. Functional characterizations of Ellenberg indicator values—a review on ecophysiological determinants. Funct. Ecol. 30, 506–516 (2016).

    Article  Google Scholar 

  33. Grime, J. P. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. Am. Nat. 111, 1169–1194 (1977).

    Article  Google Scholar 

  34. Grotkopp, E., Rejmánek, M. & Rost, T. L. Toward a causal explanation of plant invasiveness: seedling growth and life-history strategies of 29 pine (Pinus) species. Am. Nat. 159, 396–419 (2002).

    Article  PubMed  Google Scholar 

  35. Fenner, M. & Thompson, K. The Ecology of Seeds (Cambridge Univ. Press, 2005).

  36. Van der Veken, S., Bellemare, J., Verheyen, K. & Hermy, M. Life-history traits are correlated with geographical distribution patterns of western European forest herb species. J. Biogeogr. 34, 1723–1735 (2007).

    Article  Google Scholar 

  37. McKinney, M. L. & Lockwood, J. L. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol. Evol. 14, 450–453 (1999).

    Article  CAS  PubMed  Google Scholar 

  38. Hanski, I. Dynamics of regional distribution: the core and satellite species hypothesis. Oikos 38, 210–221 (1982).

    Article  Google Scholar 

  39. Wright, D. H. Correlations between incidence and abundance are expected by chance. J. Biogeogr. 18, 463–466 (1991).

    Article  Google Scholar 

  40. Mason, H. L. The edaphic factor in narrow endemism. I. The nature of environmental influences. Madroño 8, 209–226 (1946).

    Google Scholar 

  41. Sandel, B. S. et al. The influence of Late Quaternary climate-change velocity on species endemism. Science 334, 660–664 (2011).

    Article  CAS  PubMed  Google Scholar 

  42. Hubbell, S. P. The Unified Neutral Theory of Biodiversity and Biogeography (MPB-32) (Princeton Univ. Press, 2001).

  43. Suding, K. N. et al. Functional- and abundance-based mechanisms explain diversity loss due to N fertilization. Proc. Natl Acad. Sci. USA 102, 4387–4392 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Rabinowitz, D., Cairns, S. & Dillon, T. in Conservation Biology: The Science of Scarcity and Diversity (ed. Soulé, M. E.) 182–204 (Sinauer Associates, 1986).

  45. Köckemann, B., Buschmann, H. & Leuschner, C. The relationships between abundance, range size and niche breadth in Central European tree species. J. Biogeogr. 36, 854–864 (2009).

    Article  Google Scholar 

  46. Thompson, K., Hodgson, J. G. & Gaston, K. J. Abundance–range size relationships in the herbaceous flora of central England. J. Ecol. 86, 439–448 (1998).

    Article  Google Scholar 

  47. Verheyen, K. et al. Driving factors behind the eutrophication signal in understorey plant communities of deciduous temperate forests. J. Ecol. 100, 352–365 (2012).

    Article  Google Scholar 

  48. Dirnböck, T. et al. Forest floor vegetation response to nitrogen deposition in Europe. Glob. Change Biol. 20, 429–440 (2014).

    Article  Google Scholar 

  49. Bernhardt-Römermann, M. et al. Drivers of temporal changes in temperate forest plant diversity vary across spatial scales. Glob. Change Biol. 21, 3726–3737 (2015).

    Article  Google Scholar 

  50. Borer, E. T. et al. Herbivores and nutrients control grassland plant diversity via light limitation. Nature 508, 517–520 (2014).

    Article  CAS  PubMed  Google Scholar 

  51. Hautier, Y., Niklaus, P. A. & Hector, A. Competition for light causes plant biodiversity loss after eutrophication. Science 324, 636–638 (2009).

    Article  CAS  PubMed  Google Scholar 

  52. De Frenne, P. et al. Global buffering of temperatures under forest canopies. Nat. Ecol. Evol. 3, 744–749 (2019).

    Article  PubMed  Google Scholar 

  53. De Frenne, P. et al. Microclimate moderates plant responses to macroclimate warming. Proc. Natl Acad. Sci. USA 110, 18561–18565 (2013).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  54. Amann, M. et al. Progress towards the Achievement of the EU’s Air Quality and Emissions Objectives (IIASA, 2018).

  55. Storkey, J. et al. Grassland biodiversity bounces back from long-term nitrogen addition. Nature 528, 401–404 (2015).

    Article  CAS  PubMed  Google Scholar 

  56. Isbell, F., Tilman, D., Polasky, S., Binder, S. & Hawthorne, P. Low biodiversity state persists two decades after cessation of nutrient enrichment. Ecol. Lett. 16, 454–460 (2013).

    Article  PubMed  Google Scholar 

  57. Verheyen, K. et al. Combining biodiversity resurveys across regions to advance global change research. BioScience 67, 73–83 (2016).

    Article  PubMed  Google Scholar 

  58. Peterken, G. F. Natural Woodland: Ecology and Conservation in Northern Temperate Regions (Cambridge Univ. Press, 1996).

  59. Beck, J., Takano, H., Ballesteros-Mejia, L., Kitching, I. J. & McCain, C. M. Field sampling is biased against small-ranged species of high conservation value: a case study on the sphingid moths of East Africa. Biodivers. Conserv. 27, 3533–3544 (2018).

    Article  Google Scholar 

  60. Verheyen, K. et al. Observer and relocation errors matter in resurveys of historical vegetation plots. J. Veg. Sci. 29, 812–823 (2018).

    Article  Google Scholar 

  61. Kopecký, M. & Macek, M. Vegetation resurvey is robust to plot location uncertainty. Divers. Distrib. 21, 322–330 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  62. GBIF Occurrence Download (GBIF, accessed 18 January 2019); https://doi.org/10.15468/dl.l1r0yg

  63. Chamberlain, S. scrubr: clean biological occurrence records (R package v.0.1, 2016).

  64. Gaston, K. J. & Fuller, R. A. The sizes of species’ geographic ranges. J. Appl. Ecol. 46, 1–9 (2009).

    Article  Google Scholar 

  65. Isaac, N. J. B. & Pocock, M. J. O. Bias and information in biological records. Biol. J. Linn. Soc. 115, 522–531 (2015).

    Article  Google Scholar 

  66. Meyer, C., Weigelt, P. & Kreft, H. Multidimensional biases, gaps and uncertainties in global plant occurrence information. Ecol. Lett. 19, 992–1006 (2016).

    Article  PubMed  Google Scholar 

  67. Hultén, E., et al. Atlas of North European Vascular Plants North of the Tropic of Cancer (Koeltz Scientific, 1986).

  68. Meusel, H., Jäger, E. J. & Weinert, E. Vergleichende Chorologie der Zentraleuropaischen Flora (Gustav Fischer, 1965).

  69. Berg, C., Welk, E. & Jäger, E. J. Revising Ellenberg’s indicator values for continentality based on global vascular plant species distribution. Appl. Veg. Sci. 20, 482–493 (2017).

    Article  Google Scholar 

  70. Stevens, C. J. et al. Ecosystem responses to reduced and oxidised nitrogen inputs in European terrestrial habitats. Environ. Pollut. 159, 665–676 (2011).

    Article  CAS  PubMed  Google Scholar 

  71. van den Berg, L. J. L. et al. Evidence for differential effects of reduced and oxidised nitrogen deposition on vegetation independent of nitrogen load. Environ. Pollut. 208, 890–897 (2016).

    Article  PubMed  CAS  Google Scholar 

  72. Dorland, E. et al. Differential effects of oxidised and reduced nitrogen on vegetation and soil chemistry of species-rich acidic grasslands. Water, Air, Soil Pollut. 224, 1664 (2013).

    Article  CAS  Google Scholar 

  73. Gauss, M. et al. EMEP MSC-W Model Performance for Acidifying and Eutrophying Components, Photo-oxidants and Particulate Matter in 2017 (Supplementary Material to EMEP Status Report, 2019).

  74. Asman, W. A. H. Factors influencing local dry deposition of gases with special reference to ammonia. Atmos. Environ. 32, 415–421 (1998).

    Article  CAS  Google Scholar 

  75. Ellenberg, H., Weber, H. E., Düll, R., Wirth, V. & Werner, W. Zeigerwerte von Pflanzen in Mitteleuropa (Goltze, 2001).

  76. Diekmann, M. Species indicator values as an important tool in applied plant ecology—a review. Basic Appl. Ecol. 4, 493–506 (2003).

    Article  Google Scholar 

  77. McElreath, R. Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman and Hall, CRC, 2018).

  78. Peterson, R. A. bestNormalize: normalizing transformation functions (R package v.1.2.0, 2018).

  79. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth: a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51, 933–938 (2001).

    Article  Google Scholar 

  80. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article  CAS  PubMed  Google Scholar 

  81. Pearl, J. Causality 2nd edn (Cambridge Univ. Press, 2009).

Download references

Acknowledgements

This paper is an outcome of the sREplot working group supported by sDiv, the Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FZT 118). P.D.F. and P.V. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC Starting Grant FORMICA 757833). K.V. received funding through ERC Consolidator Grant PASTFORWARD 614839. M.K. and M. Macek were supported by the Czech Academy of Sciences (grant no. RVO 67985939). F.M. was supported by the Slovak Research and Development Agency (grant no. APVV-15-0270). R.H, M.C. and O.V. were supported by the grant agency of the Czech Republic (grant no. 17-09283S) and Czech Academy of Sciences (grant no. RVO 67985939). T.N. was supported by the Slovenian Research Agency (grant no. J4-1765). I.B. was supported by grant no. EFOP-3.6.1-16-2016-00018. R.P. was supported by a grant from the National Science Centre, Poland (no. 2016/20/S/NZ800428). B.T. was financed by the Higher Education Institutional Excellence Program of the Ministry for Innovation and Technology in Hungary, within the framework of the third thematic programme of the University of Pécs.

Author information

Authors and Affiliations

  1. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany

    Ingmar R. Staude, Ute Jandt & Henrique M. Pereira

  2. Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany

    Ingmar R. Staude, Ute Jandt & Henrique M. Pereira

  3. Department of Botany, University of Wisconsin, Madison, WI, USA

    Donald M. Waller

  4. Institute of Ecology and Evolution, Friedrich Schiller University Jena, Jena, Germany

    Markus Bernhardt-Römermann

  5. Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden

    Anne D. Bjorkman

  6. Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, Sweden

    Jörg Brunet

  7. Forest & Nature Lab, Ghent University, Gontrode, Belgium

    Pieter De Frenne, Kris Verheyen, Pieter Vangansbeke & Lander Baeten

  8. Institute of Botany, Czech Academy of Sciences, Brno, Czech Republic

    Radim Hédl, Markéta Chudomelová & Ondřej Vild

  9. Department of Botany, Faculty of Science, Palacký University in Olomouc, Olomouc, Czech Republic

    Radim Hédl

  10. UMR 7058 CNRS, EDYSAN—Ecologie et Dynamique des Systèmes Anthropisés, Jules Verne University of Picardie, Amiens, France

    Jonathan Lenoir & Guillaume Decocq

  11. Faculty of Forestry, Technical University in Zvolen, Zvolen, Slovakia

    František Máliš

  12. National Forest Centre, Zvolen, Slovakia

    František Máliš

  13. Leibniz Centre Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany

    Monika Wulf & Tobias Naaf

  14. Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany

    Monika Wulf & Thilo Heinken

  15. Department of Hidrobiology, University of Pécs, Szekszárd, Hungary

    Adrienne Ortmann-Ajkai

  16. Department of Forest Biodiversity, Faculty of Forestry, University of Agriculture in Kraków, Kraków, Poland

    Remigiusz Pielech

  17. Faculty of Forestry, Institute of Environmental and Earth Sciences, University of Sopron, Sopron, Hungary

    Imre Berki

  18. Environment Agency Austria, Vienna, Austria

    Thomas Dirnböck

  19. Department of Plant Physiology and Ecology, University of Rzeszów, Rzeszów, Poland

    Tomasz Durak

  20. Białowieża Geobotanical Station, Faculty of Biology, University of Warsaw, Warszawa, Poland

    Bogdan Jaroszewicz

  21. Institute of Botany of the Czech Academy of Sciences, Průhonice, Czech Republic

    Martin Kopecký, Martin Macek & Petr Petřík

  22. Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká, Czech Republic

    Martin Kopecký

  23. Department of Botany, Faculty of Biological Sciences, University of Wrocław, Wrocław, Poland

    Marek Malicki & Kamila Reczyńska

  24. Department of Forestry and Renewable Forest Resources, University of Ljubljana, Ljubljana, Slovenia

    Thomas A. Nagel

  25. Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, Bergen, Norway

    Fride Høistad Schei

  26. Department of Silviculture and Forest Ecology of the Temperate Zones, University of Göttingen, Göttingen, Germany

    Wolfgang Schmidt

  27. Department of Plant Systematics, Ecology and Theoretical Biology, Institute of Biology, L. Eötvös University, Budapest, Hungary

    Tibor Standovár

  28. Museum of Natural History, University of Wrocław, Wrocław, Poland

    Krzysztof Świerkosz

  29. Institute for Regional Development, University of Pécs, Szekszárd, Hungary

    Balázs Teleki

  30. MTA-DE Lendület Functional and Restoration Ecology Research Group, University of Debrecen, Debrecen, Hungary

    Balázs Teleki

  31. Research Institute for Nature and Forest, Brussels, Belgium

    Hans Van Calster

Authors
  1. Ingmar R. Staude
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  2. Donald M. Waller
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  3. Markus Bernhardt-Römermann
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  4. Anne D. Bjorkman
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  5. Jörg Brunet
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  6. Pieter De Frenne
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  7. Radim Hédl
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  8. Ute Jandt
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  9. Jonathan Lenoir
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  10. František Máliš
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  11. Kris Verheyen
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  12. Monika Wulf
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  13. Henrique M. Pereira
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  14. Pieter Vangansbeke
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  15. Adrienne Ortmann-Ajkai
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  16. Remigiusz Pielech
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  17. Imre Berki
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  18. Markéta Chudomelová
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  19. Guillaume Decocq
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  20. Thomas Dirnböck
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  21. Tomasz Durak
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  22. Thilo Heinken
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  23. Bogdan Jaroszewicz
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  24. Martin Kopecký
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  25. Martin Macek
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  26. Marek Malicki
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  27. Tobias Naaf
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  28. Thomas A. Nagel
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  29. Petr Petřík
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  30. Kamila Reczyńska
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  31. Fride Høistad Schei
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  32. Wolfgang Schmidt
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  33. Tibor Standovár
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  34. Krzysztof Świerkosz
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  35. Balázs Teleki
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  36. Hans Van Calster
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  37. Ondřej Vild
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  38. Lander Baeten
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Contributions

I.R.S., D.M.W. and L.B. conceived the study, with input from the sREplot working group (M.B.-R., A.D.B., J.B., P.D.F., R.H., U.J., J.L., F.M., K.V. and M.W.). I.R.S. performed the analyses, with input from D.M.W. and L.B. I.R.S., D.M.W. and L.B. wrote the manuscript, with input and contributions from M.B.-R., A.D.B., J.B., P.D.F., R.H., U.J., J.L., F.M., K.V., M.W., H.M.P., P.V., A.O.-A., R.P., I.B., M.C., G.D., T. Dirnböck, T. Durak, W.S., T.H., F.H.S., B.J., M.K., M. Macek, M. Malicki, T.N., T.A.N., P.P., K.R., T.S., K.Ś., B.T., H.V.C. and O.V. The authorship order was determined as follows: (1) core authors, (2) sREplot participants (alphabetical) and other major contributors and (3) authors contributing community composition data and to an advanced version of the manuscript (alphabetical).

Corresponding author

Correspondence to Ingmar R. Staude.

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Competing interests

The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Change in species numbers.

Frequency distribution of the difference in species numbers between the resurvey and baseline survey.

Extended Data Fig. 2 Change in nitrophilous species.

a, Frequency distribution of Ellenberg indicator values for nitrogen (eivN) across species. b, Frequency distribution of the mean eivN of extinct (dark green) and colonizing (light green) species.

Extended Data Fig. 3 Range sizes.

a, Frequency distribution of range sizes measured as area of occupancy (AOO) from GBIF point occurrence records. b, Spearman correlation plot of AOO and extent of occurrence (EOO) range sizes from digitized range maps. Points colored in magenta identify continental species. Correlation coefficient with and without continental species is: ρ = .71 and ρ = .74, respectively.

Extended Data Fig. 4 Correlations between predictor variables.

the year of the baseline survey (t1), time between surveys (∆t), cumulative N deposition between 1900 and the year of the baseline survey (Nt1) and intercensus cumulative nitrogen deposition (∆N).

Extended Data Fig. 5 Directed acyclic graph.

Directed acyclic graph of hypothesized causal links between predictor and response variables. Cumulative N deposition at the year of the baseline (Nt1), intercensus cumulative N-deposition (∆N) and time between surveys (∆t) directly influence the outcome (extinction probability, E). Year of the baseline survey (t1) directly influences ∆t and Nt1: the earlier the baseline survey, the longer the time between surveys; the earlier the baseline survey, the lower the cumulative N deposition at the year of the baseline survey. To estimate the direct effect of ∆N, it is sufficient to include ∆t as a covariate. This closes the backdoor81 through t1 (t1 →Nt1 → E) and as a result differences in baseline year do not confound the effect of ∆N.

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Supplementary Figs. 1–3 and Tables 1–7.

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Staude, I.R., Waller, D.M., Bernhardt-Römermann, M. et al. Replacements of small- by large-ranged species scale up to diversity loss in Europe’s temperate forest biome. Nat Ecol Evol 4, 802–808 (2020). https://doi.org/10.1038/s41559-020-1176-8

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