In one paragraphArticle in Ecology letters, 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
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
24 authors.
Fengqi WuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-6512-6830 Constantin M ZohnerInstitute for Future Initiatives, University of Tokyo (UTokyo), Tokyo, Japan.
Nan YangState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Tingting DongState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0009-0006-2987-1645 Weiying XuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0009-0009-8921-3179 Zhihui WangGuangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China.
Xiaojuan LiuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-9292-4432 Guanhua DaiResearch Station of Changbai Mountain Forest Ecosystems, Chinese Academy of Sciences, Antu, China.
Jinlong DongYunnan Key Laboratory of Forest Ecosystem Stability and Global Change, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, China.ORCID https://orcid.org/0009-0006-2731-3551 Yuan ZengUniversity of Chinese Academy of Sciences, Beijing, China.
J Hans C CornelissenSystems Ecology, Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit, Amsterdam, the Netherlands.
Zhengbing YanState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-5028-8167 Funding
HKU Science Faculty RAE Improvement Fund and the Innovation and Technology Fund (Funding Support to State Key Laboratory of Agrobiotechnology)Hong Kong Research Grant Council Collaborative Research Fund #C5062-21GFKey Talent Project of the State Key Laboratory of Vegetation and Environmental Change LVEC-2023rc01National Natural Science Foundation of China 32401379National Natural Science Foundation of China 32471573National Natural Science Foundation of China 32588202National Natural Science Foundation of China 32622082National Science Foundation NSF-MSA 2406847Open Project of the State Key Laboratory for Vegetation Structure, Function and Construction VegLabOF2025001SNSF Ambizione grant PZ00P3_193646the Laboratory Directed Research and Development Program of Oak Ridge National Laboratorythe National Science Foundation ASCEND Biology Integration Institute NSF-DBI-2021898the Pioneer Center for Landscape Research in Sustainable Agricultural Futures (Land-CRAFT) DNRF P2
6 · The paper itselfAbstract
Global trait axes reveal overarching dimensions of plant functional variation. However, how these dimensions are spatially organized within and across forest types remains unclear. We combined drone-based full-range imaging spectroscopy with crown-level measurements of 16 physiological, morphological and biochemical traits across temperate, subtropical and tropical forests in China to enable spatially-explicit trait mapping. Through site-training scenario, leaf-to-canopy scaling and spectral-domain modelling tests, we find that reliable canopy trait retrieval depends not only on trait and spectral coverage, but also on preserving trait-spectral relationships across sites and scales. Spectral predictions recovered observed multivariate covariation, summarizing crown variation into a leaf-economics dimension and two additional biochemical dimensions related to hydro-thermal regulation and defence/metabolism. Mapping these dimensions revealed distinct community-level trait organization alongside substantial species- and crown-level variation within forests. These findings link remotely sensed trait retrieval to environmental filtering and plant functional differentiation, providing a scalable framework for monitoring forest functional diversity.
Indexed as
ForestsPlant LeavesRemote Sensing TechnologyTreesChinaSpectrum Analysiscommunity assemblyenvironmental adaptationforest ecosystemsfunctional biogeographyhyperspectral imageryindividual tree crownleaf economics spectrumplant functional traitsremote sensingspecies
Identifiers
PMID42695460
PMCPMC13543332
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