Evidence map›Paper›PMID 36266458›Full record

ArticleNature ecology & evolution2022

Citizen science plant observations encode global trait patterns.

Sophie Wolf, Miguel D Mahecha, Francesco Maria Sabatini, Christian Wirth, Helge Bruelheide, Jens Kattge, Álvaro Moreno Martínez, Karin Mora, Teja Kattenborn

Abstract read
PubMed Publisher
In one paragraph

Article in Nature ecology & evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Global grassland productivity and carbon storage benefit from functional diversity under climate change.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Statistical power from the people.Nature ecology & evolution · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Sophie WolfRemote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany. sophie.wolf@uni-leipzig.de.ORCID http://orcid.org/0000-0001-7848-3725
Miguel D MahechaRemote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0003-3031-613X
Francesco Maria SabatiniGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0002-7202-7697
Christian WirthGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0003-2604-8056
Helge BruelheideGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0003-3135-0356
Jens KattgeGerman Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.ORCID http://orcid.org/0000-0002-1022-8469
Álvaro Moreno MartínezImage Processing Laboratory, Universitat de Valéncia, Valéncia, Spain.ORCID http://orcid.org/0000-0003-2990-7768
Karin MoraRemote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0002-3323-4490
Teja KattenbornRemote Sensing Centre for Earth System Research, Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0001-7381-3828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Citizen SciencePlants

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.