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


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 The species composition data are available from, 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


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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.

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Authors and Affiliations



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).

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Correspondence to Ingmar R. Staude.

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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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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).

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