Evidence map›Paper›PMID 42014391›Full record

ArticleNature communications2026

Leveraging remote sensing and crowd-sourced biodiversity data for enhanced plant functional trait mapping.

Álvaro Moreno-Martínez, Jordi Muñoz-Marí, Jose E Adsuara, Benjamin Dechant, Jens Kattge, Teja Kattenborn, Francesco Maria Sabatini, Fabian D Schneider, Gregory Duveiller, Peter M van Bodegom and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Álvaro Moreno-MartínezImage Processing Laboratory, Universitat de Valéncia, Valéncia, Spain. alvaro.moreno@uv.es.ORCID http://orcid.org/0000-0003-2990-7768
Jordi Muñoz-MaríImage Processing Laboratory, Universitat de Valéncia, Valéncia, Spain.ORCID http://orcid.org/0000-0002-3014-3921
Jose E AdsuaraImage Processing Laboratory, Universitat de Valéncia, Valéncia, Spain.
Benjamin DechantGerman Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.ORCID http://orcid.org/0000-0001-5171-2364
Jens KattgeGerman Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.ORCID http://orcid.org/0000-0002-1022-8469
Teja KattenbornDepartment for Sensor-based Geoinformatics, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany.ORCID http://orcid.org/0000-0001-7381-3828
Francesco Maria SabatiniBIOME Lab, Department of Biological, Geological and Environmental Sciences (BiGeA), Alma Mater Studiorum, University of Bologna, Bologna, Italy.ORCID http://orcid.org/0000-0002-7202-7697
Fabian D SchneiderJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.ORCID http://orcid.org/0000-0003-1791-2041
Gregory DuveillerMax Planck Institute for Biogeochemistry, Jena, Germany.ORCID http://orcid.org/0000-0002-6471-8404
Peter M van BodegomInstitute of Environmental Sciences, Leiden University, Leiden, the Netherlands.ORCID http://orcid.org/0000-0003-0771-4500
Ethan E ButlerDepartment of Forest Resources, University of Minnesota, St. Paul, MN, USA.ORCID http://orcid.org/0000-0003-3482-1950
Miguel D MahechaGerman Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.ORCID http://orcid.org/0000-0003-3031-613X
Emma Izquierdo-VerdiguierInstitute of Geomatics, BOKU, Vienna, Austria.ORCID http://orcid.org/0000-0003-2179-1262
Josep PeñuelasGlobal Ecology Unit, CREAF (CSIC), Barcelona, Spain.ORCID http://orcid.org/0000-0002-7215-0150
Gerhard BoenischMax Planck Institute for Biogeochemistry, Jena, Germany.
Ryan PavlickDepartment of Forest Resources, University of Minnesota, St. Paul, MN, USA.
Philip A TownsendDepartment of Forest Resources, University of Minnesota, St. Paul, MN, USA.ORCID http://orcid.org/0000-0001-7003-8774
Nuno CarvalhaisMax Planck Institute for Biogeochemistry, Jena, Germany.ORCID http://orcid.org/0000-0003-0465-1436
Daniel LuskDepartment for Sensor-based Geoinformatics, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany.ORCID http://orcid.org/0009-0002-9745-5011
Gustau Camps-VallsImage Processing Laboratory, Universitat de Valéncia, Valéncia, Spain.ORCID http://orcid.org/0000-0003-1683-2138

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 01137682
6 · The paper itself

Abstract

High-resolution maps of plant functional traits are crucial for understanding terrestrial ecosystem processes; however, their integration into ecosystem models has been hindered by uncertainties and a lack of spatially detailed data. Here we combine optical remote sensing, global crowd-sourced biodiversity records and plant trait databases to map community trait distributions worldwide at 1-km resolution, estimating community-weighted means (CWMs) and higher-order moments (standard deviation, skewness, and kurtosis) for specific leaf area (SLA), leaf nitrogen (LNC) and leaf phosphorus (LPC) concentrations. Benchmarking against sPlotOpen plot-level CWMs shows low explained variance (R

Indexed as

BiodiversityPlantsRemote Sensing TechnologyEcosystemNitrogenPhosphorusPlant LeavesNitrogenPhosphorus

Identifiers

PMID42014391
PMCPMC13284179

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.