Estimating Carbon Sequestration Potential of Forest and Its Influencing Factors at Fine Spatial-Scales: A Case Study of Lushan City in Southern China.

Geng He, Zhiduo Zhang, Qing Zhu, Wei Wang, Wanting Peng, Yongli Cai

Abstract read

In one paragraph

Article in International journal of environmental research and public health, 2022. 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.

Linking woody plant species richness with selected ecosystem services and dendrometric features in Okalma natural forest reserve.Scientific reports · 2025
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

6 authors.

Geng HeSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.

Zhiduo ZhangSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-4283-3460

Qing ZhuSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.

Wei WangSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.

Wanting PengSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-5119-4461

Yongli CaiSchool of Design & China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-9461-1157

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate prediction of forest carbon sequestration potential requires a comprehensive understanding of tree growth relationships. However, the studies for estimating carbon sequestration potential concerning tree growth relationships at fine spatial-scales have been limited. In this paper, we assessed the current carbon stock and predicted sequestration potential of Lushan City, where a region has rich vegetation types in southern China, by introducing parameters of diameter at breast height (DBH) and tree height in the method of coupling biomass expansion factor (BEF) and tree growth equation. The partial least squares regression (PLSR) was used to explore the role of combined condition factors (e.g., site, stand, climate) on carbon sequestration potential. The results showed that (1) in 2019, the total carbon stock of trees in Lushan City was 9.22 × 10

Indexed as

Carbon SequestrationForestsBiomassCarbonChinaTreesCarbonbiomass expansion factorcarbon sequestration potentialfine-scalesite characteristicstree growth equation

Identifiers

PMID35954542

DOI10.3390/ijerph19159184

PMCPMC9368071

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.