Evidence map›Paper›PMID 41550759›Full record

ArticleiScience2026

Developing mixed-effects height-diameter model using stand and environmental factors for mixed forests in northern China.

Yaxiong Zheng, Yongjie Yue, Runhong Gao, Ram P Sharma

Abstract read
In one paragraph

Article in iScience, 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
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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

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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

4 authors.

Yaxiong ZhengCollege of Forestry, Inner Mongolia Agricultural University, Hohhot, China.
Yongjie YueCollege of Forestry, Inner Mongolia Agricultural University, Hohhot, China.
Runhong GaoCollege of Forestry, Inner Mongolia Agricultural University, Hohhot, China.
Ram P SharmaInstitute of Forestry, Tribhuvan University, Kathmandu, Nepal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding tree height (H)-diameter at breast height (D) allometric relationship is crucial for estimating biomass, carbon storage, and productivity. Environmental factors and species diversity strongly influence this relationship, yet remain understudied. Using data from 99 plots in Hulunbuir mixed forests, inner Mongolia, we developed an environment-sensitive nonlinear mixed-effects model for five tree species. The model incorporates variables representing stand-level attributes, soil properties, climate factors, and species diversity. Variations at the sample plot and species levels were accounted for by introducing random components into the H-D model. Quadratic mean diameter, total basal area greater than the target D (BAL), Simpson's diversity index (SIM), mean annual precipitation (MAP), and soil organic carbon significantly affected the H-D relationship. Height growth increased with BAL and MAP but declined with higher SIM. Species traits and environmental factors jointly shaped H-D scaling. The proposed model supports adaptive forest management under changing environments.

Indexed as

applied sciencesenvironmental monitoringenvironmental science

Identifiers

PMID41550759
PMCPMC12809735

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Registered trials

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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.