TY - JOUR
T1 - Six Decades of Losses and Gains in Alpha Diversity of European Plant Communities
AU - Midolo, Gabriele
AU - Clark, Adam Thomas
AU - Chytrý, Milan
AU - Essl, Franz
AU - Dullinger, Stefan
AU - Jandt, Ute
AU - Bruelheide, Helge
AU - Argagnon, Olivier
AU - Biurrun, Idoia
AU - Chiarucci, Alessandro
AU - Ćušterevska, Renata
AU - De Frenne, Pieter
AU - De Sanctis, Michele
AU - Dengler, Jürgen
AU - Divíšek, Jan
AU - Dziuba, Tetiana
AU - Ejrnæs, Rasmus
AU - Garbolino, Emmanuel
AU - Illa, Estela
AU - Jentsch, Anke
AU - Jiménez-Alfaro, Borja
AU - Lenoir, Jonathan
AU - Moeslund, Jesper Erenskjold
AU - Napoleone, Francesca
AU - Pielech, Remigiusz
AU - Rumpf, Sabine B.
AU - Sanz-Zubizarreta, Irati
AU - Silva, Vasco
AU - Svenning, Jens Christian
AU - Swacha, Grzegorz
AU - Večeřa, Martin
AU - Vynokurov, Denys
AU - Keil, Petr
N1 - Publisher Copyright:
© 2025 The Author(s). Ecology Letters published by John Wiley & Sons Ltd.
PY - 2025/11
Y1 - 2025/11
N2 - Biodiversity change forecasts rely on long-term time series, but such data are often scarce in space and time. Here, we interpolated spatiotemporal changes in species richness using a new method based on machine learning that does not require temporal replication at sites. Using 698,692 one-time sampled vegetation plots, we estimated trends in vascular plant alpha diversity across Europe and validated our approach against 22,852 independent time series. We found an overall near-zero net change in species richness between 1960 and 2020. However, species richness generally declined from 1960 to 1980 and increased from 2000 to 2020 across habitats. Declines were most pronounced in forests, but trends varied across habitats and regions, with overall increases at higher latitudes and elevations, and declines or stable trends elsewhere. Our findings demonstrate how data without temporal replication can be used to reveal context-dependent biodiversity dynamics, underscoring their importance for conservation and management.
AB - Biodiversity change forecasts rely on long-term time series, but such data are often scarce in space and time. Here, we interpolated spatiotemporal changes in species richness using a new method based on machine learning that does not require temporal replication at sites. Using 698,692 one-time sampled vegetation plots, we estimated trends in vascular plant alpha diversity across Europe and validated our approach against 22,852 independent time series. We found an overall near-zero net change in species richness between 1960 and 2020. However, species richness generally declined from 1960 to 1980 and increased from 2000 to 2020 across habitats. Declines were most pronounced in forests, but trends varied across habitats and regions, with overall increases at higher latitudes and elevations, and declines or stable trends elsewhere. Our findings demonstrate how data without temporal replication can be used to reveal context-dependent biodiversity dynamics, underscoring their importance for conservation and management.
KW - alpha diversity
KW - autocorrelation
KW - biogeographic regions
KW - habitat specificity
KW - latitudinal gradient
KW - machine learning
KW - nature conservation
KW - random forests
KW - statistical interpolation
KW - vegetation resurvey
UR - https://www.scopus.com/pages/publications/105020770651
U2 - 10.1111/ele.70248
DO - 10.1111/ele.70248
M3 - Article
C2 - 41176772
AN - SCOPUS:105020770651
SN - 1461-023X
VL - 28
SP - 1
EP - 12
JO - Ecology Letters
JF - Ecology Letters
IS - 11
M1 - e70248
ER -