Evidence map›Paper›PMID 42528839›Full record

ArticleFrontiers in plant science2026

Scale-dependent biodiversity-biomass relationships vary among subtropical forest community types.

Theint Theint Soe, Boliang Wei, Wenjie Zhou, Zhongjie Yang, Zhibin Mao, Zhonghan Wang, Lei Zhong, Donghao Wu, Jinliang Liu, Mingjian Yu

Abstract read
In one paragraph

Article in Frontiers in plant science, 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

10 authors.

Theint Theint Soe *State Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Boliang Wei *State Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Wenjie ZhouState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Zhongjie YangState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Zhibin MaoState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Zhonghan WangState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Lei ZhongState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Donghao WuState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.
Jinliang LiuCollege of Life and Environmental Science, Wenzhou University, Wenzhou, China.
Mingjian YuState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exploring how biodiversity influences forest biomass is critical to biodiversity-ecosystem functioning (BEF) research. However, the combined effects of species diversity and compositional heterogeneity among communities and spatial scale on aboveground biomass (AGB) remain insufficiently resolved. We quantified species alpha diversity, beta diversity, and AGB in 15 one-hectare permanent forest plots representing five forest community types across three spatial scales (10 m, 20 m, 50 m) in eastern China, then analyzed the relationships between diversity and AGB. The results showed that positive relationships between alpha diversity and aboveground biomass were consistently observed in evergreen broad-leaved forests and low-elevation evergreen and deciduous broad-leaved mixed forests, and these relationships generally became stronger with increasing spatial scale in these forest types. In contrast, high-elevation mixed forests exhibited weak or negative associations between alpha diversity and biomass. For beta diversity, significant positive associations with biomass differences were detected at the 10 m scale across all forest communities. At 20 m scale, these relationships remained predominantly positive but were less uniform among community types, with some variation in direction and strength. At 50 m scale, the relationships weakened and became more variable among communities, showing a mixture of positive, negative, and non-significant patterns depending on forest type. Collectively, our findings highlight that incorporating spatial scale and forest type is essential for interpreting biodiversity-biomass relationships, and conserving both local species diversity and compositional heterogeneity is very important for sustaining forest productivity, carbon storage, and ecosystem stability.

Indexed as

aboveground biomassalpha diversitybeta diversitybiodiversity–biomass relationshipsscale–dependent effectssubtropical broad–leaved forests

Identifiers

PMID42528839
PMCPMC13415502

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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.