Evidence map›Paper›PMID 41170132›Full record

ArticleBiodiversity data journal2025

Dendrometric traits for developing biomass equations of tree and shrub species in carbon sequestration projects.

Chun-Jing Wang, Xue Wang, Mei-Quan Wang, De-Chao Chen, Wu-Xian Yan, Dong-Zhou Deng

Abstract read
In one paragraph

Article in Biodiversity data journal, 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
–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

6 authors.

Chun-Jing WangEcological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry, Chengdu, China Ecological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry Chengdu China.
Xue WangSichuan Provincial Forestry and Grassland Key Laboratory of Combating Desertification, Chengdu, China Sichuan Provincial Forestry and Grassland Key Laboratory of Combating Desertification Chengdu China.
Mei-Quan WangSichuan Provincial Forestry and Grassland Key Laboratory of Combating Desertification, Chengdu, China Sichuan Provincial Forestry and Grassland Key Laboratory of Combating Desertification Chengdu China.
De-Chao ChenEcological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry, Chengdu, China Ecological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry Chengdu China.
Wu-Xian YanEcological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry, Chengdu, China Ecological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry Chengdu China.
Dong-Zhou DengEcological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry, Chengdu, China Ecological Conservation, Restoration and Resource Utilization on Forest and Wetland Key Laboratory of Sichuan Province, Sichuan Academy of Forestry Chengdu China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The advancement of carbon sequestration projects holds significant potential to deliver mutually beneficial outcomes for both the environment and the economy. In this context, biomass models have been extensively developed to estimate the aboveground biomass of woody plants - such as trees and shrubs - using dendrometric characteristics, like diameter and height. The datasets presented in this study compile dendrometric traits from multiple tree and shrub species, supporting the construction of robust biomass models. As a result, tree and shrub biomass can serve as integral indicators for evaluating the effectiveness of carbon sequestration projects, incorporating key factors such as diameter, height and plantation density. By establishing reliable biomass estimation models, it becomes possible to enhance the monitoring and verification of carbon storage, thereby providing a scientific basis for the planning, management and policy-making of carbon sink initiatives. This approach contributes significantly to ecological restoration and climate change mitigation efforts. New information: This study presents two dendrometric datasets of individual trees and shrub bushes from carbon sequestration projects in north-western China, covering sites in Xining and Haidong (Qinghai Province), Tianshui (Gansu Province) and Aba (Sichuan Province). Specifically, the tree dataset comprises measurements of canopy breadth (in two perpendicular directions), height, diameter at breast height (DBH) and base perimeter for 2084 individuals across 25 species. The shrub dataset includes crown diameter (in two perpendicular directions), height and basal perimeter for 998 bushes across 36 species. These dendrometric traits serve as key parameters in biomass estimation equations. Furthermore, as the diameter and height of trees and shrubs significantly influence understorey plant diversity - primarily through their effects on stand density, species interactions and community composition - these datasets are valuable for advancing biomass modelling and assessing plant diversity outcomes under conservation management.

Indexed as

base perimeterbiodiversitycanopy breadthChinaforest managementheightwoody species

Identifiers

PMID41170132
PMCPMC12569629

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.