Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1038/s41559-022-01904-x |
| Document | Shareable Link |
| Title (Primary) | Citizen science plant observations encode global trait patterns |
| Author | Wolf, S.; Mahecha, M.D.; Sabatini, F.M.; Wirth, C.; Bruelheide, H.; Kattge, J.; MartÃnez, A.M.; Mora, K.; Kattenborn, T. |
| Source Titel | Nature Ecology & Evolution |
| Year | 2022 |
| Department | iDiv; RS |
| Volume | 6 |
| Issue | 12 |
| Page From | 1850 |
| Page To | 1859 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Data and Software links | https://doi.org/10.5281/zenodo.6671891 |
| Supplements | https://static-content.springer.com/esm/art%3A10.1038%2Fs41559-022-01904-x/MediaObjects/41559_2022_1904_MOESM1_ESM.pdf |
| 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. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=26751 |
| Wolf, S., Mahecha, M.D., Sabatini, F.M., Wirth, C., Bruelheide, H., Kattge, J., MartÃnez, A.M., Mora, K., Kattenborn, T. (2022): Citizen science plant observations encode global trait patterns Nat. Ecol. Evol. 6 (12), 1850 - 1859 10.1038/s41559-022-01904-x |
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