Canopy properties predominately explain above-ground biomass stock in temperate forests

Abstract Canopy properties (e.g. canopy structure and spectral variables) strongly influence forest above-ground biomass (AGB). However, the importance of these canopy properties in driving AGB in natural forests, especially relative to other drivers such as plant species diversity and environmental conditions, remains poorly understood. We assessed the relative importance of canopy properties (structure and spectral variables) and plant species diversity (multidimensional diversity metrics and trait composition) in regulating AGB along environmental gradients (topography and soil nutrients) in a temperate forest in Northeast China, using UAV-based LiDAR and hyperspectral data. We found that the explanatory power of environmental conditions, plant species diversity, canopy spectral properties and canopy structure on temperate old-growth forests AGB was 3.8%, 8.0%, 4.1% and 13.3%, respectively. AGB increased with increasing canopy height and structural complexity. Canopy spectral diversity was a better predictor of AGB than traditional diversity metrics in old-growth forests. Canopy spectral composition also played an important role in explaining AGB in the secondary forests. In addition, plant phylogeny, functional diversity and the community-weighted mean of acquisitive traits had significant direct positive effects on AGB. Finally, topography and soil nutrient content indirectly influenced AGB through canopy properties and plant species diversity. Our study highlights the key role of canopy properties in influencing AGB. For future monitoring, regular monitoring with spectral and LiDAR data should be emphasized to provide real-time insights for forest management.

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Publication Details

Journal
Journal of Plant Ecology
Published
2025-03-11
DOI
https://doi.org/10.1093/jpe/rtaf026
Citations
4
Primary Topic
Forest ecology and management
Type
article
Field-Weighted Citation Impact
9.25
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article

Canopy properties predominately explain above-ground biomass stock in temperate forests

Jin Yin, Pengzhi Jiang, Hongyi Jiang, Shuai Fang et al.
4 citations
Journal of Plant Ecology
Forest ecology and management
9.25
article

Canopy properties predominately explain above-ground biomass stock in temperate forests

Jin Yin, Pengzhi Jiang, Hongyi Jiang, Shuai Fang, Zikun Mao, Mengxu Zhang, Yanjun Su, Xugao Wang, He Han, Zhichao Xu, Meihui Zhu
article en
4 citations

Abstract

Abstract Canopy properties (e.g. canopy structure and spectral variables) strongly influence forest above-ground biomass (AGB). However, the importance of these canopy properties in driving AGB in natural forests, especially relative to other drivers such as plant species diversity and environmental conditions, remains poorly understood. We assessed the relative importance of canopy properties (structure and spectral variables) and plant species diversity (multidimensional diversity metrics and trait composition) in regulating AGB along environmental gradients (topography and soil nutrients) in a temperate forest in Northeast China, using UAV-based LiDAR and hyperspectral data. We found that the explanatory power of environmental conditions, plant species diversity, canopy spectral properties and canopy structure on temperate old-growth forests AGB was 3.8%, 8.0%, 4.1% and 13.3%, respectively. AGB increased with increasing canopy height and structural complexity. Canopy spectral diversity was a better predictor of AGB than traditional diversity metrics in old-growth forests. Canopy spectral composition also played an important role in explaining AGB in the secondary forests. In addition, plant phylogeny, functional diversity and the community-weighted mean of acquisitive traits had significant direct positive effects on AGB. Finally, topography and soil nutrient content indirectly influenced AGB through canopy properties and plant species diversity. Our study highlights the key role of canopy properties in influencing AGB. For future monitoring, regular monitoring with spectral and LiDAR data should be emphasized to provide real-time insights for forest management.

Journal of Plant EcologyVol. 18(2)
Chinese Academy of Sciences (CN), Institute of Applied Ecology (CN), Czech Academy of Sciences, Institute of Botany (CZ), Terrestrial Ecosystem Research Network (AU), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 2%
Forest ecology and management
9.25
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