Evidence map›Paper›PMID 40530287›Full record

ArticleFrontiers in plant science2025

Disentangling the relationship between environmental drivers and productivity in subalpine wet grasslands.

Shuqiao Zhang, Langlang Shu, Wendou Liu, Zizhi Wang, Wengui Wu, Shengxi Liao

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. 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
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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

6 authors.

Shuqiao ZhangInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.
Langlang ShuInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.
Wendou LiuInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.
Zizhi WangInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.
Wengui WuInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.
Shengxi LiaoInstitute of Highland Forest Science, Chinese Academy of Forestry, Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Grasslands exhibit significant variability in productivity across fine spatial scales, which is crucial for understanding terrestrial carbon cycling, particularly under global climate change. While alpine grasslands have been extensively studied, subalpine wet grasslands (2000-4000 m) remain underexplored. Investigating their productivity and responses to environmental factors is essential for a comprehensive understanding of ecosystem dynamics in these regions. Method: We applied destructive sampling techniques, optimized grassland investigation, and employed multivariate modeling to examine how different environmental variables influence grassland biomass. An 80-plot field-based dataset was established in a subalpine wet grassland. Results: Our findings reveal that plant biomass peaked at elevations between 3400 and 3500 m. Belowground biomass accounted for 85% of total productivity, with the majority contributed by dominant species. Vegetation-related variables, such as coverage and root/shoot ratio, were the primary determinants of aboveground biomass, whereas soil properties were key regulators of belowground biomass. Although direct and indirect effects of landform and climatic factors influenced total biomass, the patterns of total and belowground biomass were consistent. The results underscore the significant positive impact of vegetation cover, root-to-shoot ratio, and soil conditions on grassland productivity. Notably, soil organic carbon, water content, and the nitrogen-to-phosphorus ratio affected belowground biomass. Discussion: These insights enhance our understanding of the intricate interactions between climate, soil, landform, and plant communities in influencing grassland biomass and highlight the importance of preserving plant diversity and maintaining optimal soil conditions in subalpine wet grasslands. One grassland does not fit all; fine-scale classification is essential to capture the variability in productivity across different grassland types.

Indexed as

biodiversitybiomassmultivariate modelingplant ecologystructural equation modelingvegetation

Identifiers

PMID40530287
PMCPMC12170661

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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.