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Citizen science plant observations encode global trait patterns.
Wolf, Sophie; Mahecha, Miguel D; Sabatini, Francesco Maria; Wirth, Christian; Bruelheide, Helge; Kattge, Jens; Moreno Martínez, Álvaro; Mora, Karin; Kattenborn, Teja.
Afiliación
  • Wolf S; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany. sophie.wolf@uni-leipzig.de.
  • Mahecha MD; Remote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany.
  • Sabatini FM; Remote Sensing Centre for Earth System Research, Helmholtz Centre for Environmental Research, UFZ, Leipzig, Germany.
  • Wirth C; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
  • Bruelheide H; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
  • Kattge J; BIOME Lab, Department of Biological, Geological and Environmental Sciences (BiGeA), Alma Mater Studiorum University of Bologna, Bologna, Italy.
  • Moreno Martínez Á; Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany.
  • Mora K; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
  • Kattenborn T; Institute of Systematic Botany and Functional Biodiversity, Leipzig University, Leipzig, Germany.
Nat Ecol Evol ; 6(12): 1850-1859, 2022 12.
Article en En | MEDLINE | ID: mdl-36266458
ABSTRACT
Global maps of plant functional traits are essential for studying the dynamics of the terrestrial biosphere, yet the spatial distribution of trait measurements remains sparse. With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. The question emerges whether such opportunistic citizen science data can help map plant functional traits globally. Here we show that we can map global trait patterns by complementing vascular plant observations from the global citizen science project iNaturalist with measurements from the plant trait database TRY. We evaluate these maps using sPlotOpen, a global collection of vegetation plot data. Our results show high correlations between the iNaturalist- and sPlotOpen-based maps of up to 0.69 (r) and higher correlations than to previously published trait maps. As citizen science data collections continue to grow, we can expect them to play a significant role in further improving maps of plant functional traits.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ciencia Ciudadana Idioma: En Revista: Nat Ecol Evol Año: 2022 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ciencia Ciudadana Idioma: En Revista: Nat Ecol Evol Año: 2022 Tipo del documento: Article País de afiliación: Alemania