Citizen science plant observations encode global trait patterns

doi:10.1038/s41559-022-01904-x

Citizen science plant observations encode global trait patterns

2022-10-20

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Francesco María Sabatini

Álvaro Moreno‐Martínez

DOI：10.1038/s41559-022-01904-x

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Comparing global vegetation trait patterns derived from citizen science data versus those from scientific survey plots, the authors reveal high correlations between the two approaches and improvements over previously published trait maps. 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.

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Citizen science plant observations encode global trait patterns

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