Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Foto på Ciara Dwyer

Ciara Dwyer

Affilierad

Foto på Ciara Dwyer

Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping

Författare

  • Daniel Lusk
  • Sophie Wolf
  • Daria Svidzinska
  • Carsten F. Dormann
  • Jens Kattge
  • Helge Bruelheide
  • Francesco Maria Sabatini
  • Gabriella Damasceno
  • Álvaro Moreno Martínez
  • Cyrille Violle
  • Daniel Hending
  • Georg J.A. Hähn
  • Solana Tabeni
  • Shyam Phartyal
  • Fernando Gonçalves
  • Holger Kreft
  • Marco Schmidt
  • Han Chen
  • Behlül Güler
  • Jiri Dolezal
  • Remigiusz Pielech
  • Anaclara Guido
  • Ciara Dwyer
  • Francesca Napoleone
  • Jacob Willie
  • André Luís Gasper
  • Manuel J. Macía
  • Milan Chytry
  • Jonathan Lenoir
  • Dinesh Thakur
  • Jürgen Dengler
  • Sebastian Świerszcz
  • Jan Altman
  • Ladislav Mucina
  • Ashish N. Nerlekar
  • Kaoru Kakinuma
  • Pravin Rawat
  • Zvjezdana Stančić
  • Riccardo Testolin
  • Mohamed Z. Hatim
  • Flávio Rodrigues
  • Jürgen Homeier
  • Marcia C.M. Marques
  • James K. McCarthy
  • M. A. El-Sheikh
  • Kirill Korznikov
  • Kilian Gerberding
  • Teja Kattenborn
Visa allt

Summary, in English

Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by available field surveys and trait measurements. Recent expansions in biodiversity data aggregation—including vegetation surveys, citizen science observations, and trait measurements—offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km2 resolution. Our approach achieves correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance understanding of plant community properties and ecosystem functioning, while serving as tools for modeling global biogeochemical processes and informing conservation efforts. Our framework highlights the power of crowdsourced biodiversity data in addressing longstanding extrapolation challenges in global plant trait modeling, with continued advancements in data collection and remote sensing poised to further refine trait-based understanding of the biosphere.

Avdelning/ar

  • Miljö- och geovetenskapliga institutionen (MGeo)
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • Centre for Environmental and Climate Science (CEC)

Publiceringsår

2026

Språk

Engelska

Publikation/Tidskrift/Serie

Nature Communications

Volym

17

Avvikelse

1

Dokumenttyp

Artikel i vetenskaplig tidskrift

Förlag

Nature Publishing Group

Ämne

  • Ecology (including Biodiversity Conservation)

Aktiv

Published

ISBN/ISSN/Övrigt

  • ISSN: 2041-1723