Citizen Science Plant Observations Encode Global Trait Patterns

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.

Publication
Nature Ecology & Evolution
Sophie Wolf
Sophie Wolf
PhD candidate / Earth System Data Science

Researcher

Miguel D. Mahecha
Miguel D. Mahecha
Professor for Earth System Data Science

Professor

Karin Mora
Karin Mora
Postdoctoral fellow / Earth System Data Science

Wissenschaftlicher Mitarbeiter