Citizen science observations encode global trait patterns

With the increasing popularity of species identification smartphone apps, citizen scientists contribute to large and rapidly growing vegetation data collections. The question emerges whether such data can be utilized to monitor essential biodiversity variables across the globe.

Here, we use the freely available field observations of vascular plants provided by iNaturalist, a citizen science project that has encouraged users across the globe to identify, share and jointly validate species they encounter via photo and geolocation. We test whether iNaturalist observations complemented with trait measurements from the TRY database (Kattge et al, 2020) are able to represent global trait patterns.

As a reference for evaluating the iNaturalist observations, we use trait community-weighted means from the database sPlotOpen (Bruelheide et al, 2019; Sabatini et al, 2021). sPlotOpen is a curated database of globally distributed plots with vegetation abundance measurements, balanced over global climate and soil conditions. It provides community-weighted means for each vegetation plot for 18 traits. These community-weighted means are also derived from TRY measurements. We thus compare spatially and taxonomically biased occurrence samples provided by iNaturalist citizen scientists to professionally sampled environmentally balanced plot-based abundance data.

Author: Sophie Wolf