Application of stand biomass in the evaluation of site quality for broadleaf forests in China

A scientific evaluation of site quality is essential for the sustainable management of forest ecosystems. However, the absence of a standardized evaluation framework has resulted in site quality assessments that are not comparable across different broadleaf forest types on large spatial scales, impacting forest management decisions related to afforestation, thinning, and carbon sink management. Therefore, establishing a methodological framework for evaluating the site quality of various broadleaf stands could provide practical implications for forestry. Using the data from four cycles of the National Forest Inventory (NFIs) of China, the Richards, Logistic, and Korf models were applied to simulating the growth of 18 major groups of broadleaf trees. We fitted guide curves using the models and constructed site productivity index models for each group. A generalized site productivity index model for broadleaf stands was developed using conversion coefficients between species, with subsequent applicability testing and spatial analysis to assess dynamic changes in site productivity. Results indicate that the Richards model, with an average coefficient of determination ( R 2 ) of 0.91, performed better than the Logistic and Korf models. Statistical tests show that the site productivity index models of major broadleaf stands achieve accuracy rates exceeding 90%. The Spearman correlation coefficient is greater than 0.99 between the productivity index classes based on generalized and specific models, demonstrating both the reliability and applicability of the generalized model. Proportional and spatial analyses indicate a continuous trend of improvement in the site productivity of broadleaf stands from 2003 to 2018. The generalized productivity index model based on the relationship between age and biomass was validated by feasibility tests, making it suitable for application in forestry management and prediction. A continuous improvement trend in the site productivity of broadleaf forest was demonstrated, despite fluctuations during short intervals related to uncertainties in our models, which provided a robust, large-scale tool for evaluating forest productivity, offering critical support for sustainable forest management, policy-making, and carbon sequestration strategies in China.

Authors

Institutions

Publication Details

Journal
Frontiers in Forests and Global Change
Published
2025-09-29
DOI
https://doi.org/10.3389/ffgc.2025.1650547
Primary Topic
Forest ecology and management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of stand biomass in the evaluation of site quality for broadleaf forests in China

Chunling Luo, Annikki Mäkelä, Xianglin Tian, Francesco Minunno et al.
Frontiers in Forests and Global Change
Forest ecology and management
article

Application of stand biomass in the evaluation of site quality for broadleaf forests in China

Chunling Luo, Annikki Mäkelä, Xianglin Tian, Francesco Minunno, Heng Wu, Che Liu, Xianpeng Xu, Changping Sun
article en

Abstract

A scientific evaluation of site quality is essential for the sustainable management of forest ecosystems. However, the absence of a standardized evaluation framework has resulted in site quality assessments that are not comparable across different broadleaf forest types on large spatial scales, impacting forest management decisions related to afforestation, thinning, and carbon sink management. Therefore, establishing a methodological framework for evaluating the site quality of various broadleaf stands could provide practical implications for forestry. Using the data from four cycles of the National Forest Inventory (NFIs) of China, the Richards, Logistic, and Korf models were applied to simulating the growth of 18 major groups of broadleaf trees. We fitted guide curves using the models and constructed site productivity index models for each group. A generalized site productivity index model for broadleaf stands was developed using conversion coefficients between species, with subsequent applicability testing and spatial analysis to assess dynamic changes in site productivity. Results indicate that the Richards model, with an average coefficient of determination ( R 2 ) of 0.91, performed better than the Logistic and Korf models. Statistical tests show that the site productivity index models of major broadleaf stands achieve accuracy rates exceeding 90%. The Spearman correlation coefficient is greater than 0.99 between the productivity index classes based on generalized and specific models, demonstrating both the reliability and applicability of the generalized model. Proportional and spatial analyses indicate a continuous trend of improvement in the site productivity of broadleaf stands from 2003 to 2018. The generalized productivity index model based on the relationship between age and biomass was validated by feasibility tests, making it suitable for application in forestry management and prediction. A continuous improvement trend in the site productivity of broadleaf forest was demonstrated, despite fluctuations during short intervals related to uncertainties in our models, which provided a robust, large-scale tool for evaluating forest productivity, offering critical support for sustainable forest management, policy-making, and carbon sequestration strategies in China.

Frontiers in Forests and Global ChangeVol. 8
University of Helsinki (FI), Southwest Forestry University (CN), State Forestry and Grassland Administration (CN), Forest Research (GB), Jiangxi Province Forestry Survey Planning Institute (CN), Northwest A&F University (CN)
National Forestry and Grassland Administration
Openalex Percentile: Top 73%
Forest ecology and management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.