Evidence map›Paper›PMID 41530138›Full record

ArticleNature communications2026

Climate and traits drive bark decomposition patterns at global scale.

Chenhui Chang, Jiayuan Liu, Biao Zhu, Gbadamassi G O Dossa, Wanqin Yang, Xiaodan Wang, Johannes H C Cornelissen

Abstract read
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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Chenhui Chang *Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, China.ORCID http://orcid.org/0000-0002-4107-2065
Jiayuan Liu *State Key Laboratory of Vegetation Structure, Function and Construction (VegLab), Ministry of Education Key Laboratory of Earth Surface Processes, and College of Urban and Environmental Sciences, Peking University, Beijing, China.
Biao ZhuState Key Laboratory of Vegetation Structure, Function and Construction (VegLab), Ministry of Education Key Laboratory of Earth Surface Processes, and College of Urban and Environmental Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-9858-7943
Gbadamassi G O DossaYunnan Key Laboratory of Forest Ecosystem Stability and Global Change Response, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, China.ORCID http://orcid.org/0000-0001-9767-7306
Wanqin YangZhejiang Key Laboratory for Restoration of Damaged Coastal Ecosystems, School of Life Sciences, Taizhou University, Taizhou, Zhejiang, China.
Xiaodan WangInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan, China. wxd@imde.ac.cn.ORCID http://orcid.org/0000-0002-0545-1041
Johannes H C CornelissenDepartment of Ecological Science, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32425038
6 · The paper itself

Abstract

Tree bark represents a large global carbon stock, comprising 2-20 % of woody biomass, and plays a distinct role in carbon and nutrient cycling. It is poorly understood how different abiotic and biotic drivers contribute to bark decomposition globally, or how these relationships play out in a changing climate. Here, we compile a global dataset to estimate the spatial variability of current bark decomposition rates (k values) and employ three machine learning approaches to project the response of k in future climate scenarios. We find that, globally, bark decomposes 2.9 times faster than the rate previously estimated for tree trunks (including bark). Mean k values increase latitudinally from 0.093 year

Indexed as

ClimatePlant BarkTreesBiomassCarbonCarbon CycleClimate ChangeCycadopsidaMachine LearningMagnoliopsidaTemperatureCarbon

Identifiers

PMID41530138
PMCPMC12800307

What OpenQuestion holds

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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 OpenQuestion graph.