Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping

• Autoři: LUSK Daniel; WOLF Sophie; SVIDZINSKA Daria; DORMANN Carsten F.; KATTGE Jens; BRUELHEIDE Helge; SABATINI Francesco Maria; DAMASCENO Gabriella; MORENO MARTINEZ Alvaro; VIOLLE Cyrille; HENDING Daniel; HAHN Georg J. A.; TABENI Solana; PHARTYAL Shyam; GONCALVES Fernando; KREFT Holger; SCHMIDT Marco; CHEN Han; GULER Behlul; DOLEZAL Jiri; PIELECH Remigiusz; GUIDO Anaclara; DWYER Ciara; NAPOLEONE Francesca; WILLIE Jacob; GASPER Andre Luis; MACIA Manuel J.; CHYTRÝ Milan; LENOIR Jonathan; THAKUR Dinesh; DENGLER Jurgen; SWIERSZCZ Sebastian; ALTMAN Jan; MUCINA Ladislav; NERLEKAR Ashish N.; KAKINUMA Kaoru; RAWAT Pravin; STANCIC Zvjezdana; TESTOLIN Riccardo; HATIM Mohamed Z.; RODRIGUES Flavio; HOMEIER Jurgen; MARQUES Marcia C. M.; MCCARTHY James K.; EL-SHEIKH M. A.; KORZNIKOV Kirill; GERBERDING Kilian; KATTENBORN Teja
• Rok publikování: 2026
• Druh: Recenzovaný odborný článek
• Časopis / Zdroj: NATURE COMMUNICATIONS
• Fakulta / Pracoviště MU: Přírodovědecká fakulta

www

• https://doi.org/10.1038/s41467-026-68996-y
• https://doi.org/10.5281/zenodo.18108765
• https://doi.org/10.5281/zenodo.18269445

• Doi: https://doi.org/10.1038/s41467-026-68996-y
• Klíčová slova: Biodiversity; Crowdsourcing; Ecosystem; Plants

Přiložené soubory

• s41467-026-68996-y.pdf

• Popis: 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.