Effects of forest canopy structural complexity on productivity and its stability in the Qinling Mountains: Insights into environmental dependence
Forest canopy structural complexity is a key determinant of forest productivity and exerts a strong influence on its stability. Yet, the relationship between forest canopy structural complexity and productivity and its stability under changing environmental factors remains unresolved. Based on a LiDAR approach for quantification of forest canopy structural attributes, this study chose China’s Qinling Mountains as the study area to investigate the impact of forest canopy structural complexity on NPP and its stability across different terrain aspects and environmental conditions. The results showed that three canopy parameters (LAI, MCH, and CE), environmental factors, NPP and its stability all exhibited significant differences between the northern and southern aspects, as well as across Qinling Mountains. Canopy structural complexity and productivity stability were higher on the southern aspect. The forest canopy structural attributes and environmental factors in the Qinling Mountains jointly influenced the mean productivity, explaining 53% of the variation in the mean productivity. On the humid southern aspect, the complexity of canopy structure had a significant impact on forest productivity. Conversely, on the arid northern aspect, the relationship was not significant. The response of productivity stability to canopy structure attributes and environmental changes displayed a similar pattern. Our study revealed that the effect of forest canopy structure on productivity and its stability is heavily dependent on environmental factors. This study offers a theoretical foundation for formulating forest management strategies adapted to diverse environmental conditions from a forest canopy perspective.
Authors
- Chenlu Li (ORCID: https://orcid.org/0000-0001-5330-2764)
- F. Richard Yu (ORCID: https://orcid.org/0000-0003-1006-7594)
- Huiwen Li (ORCID: https://orcid.org/0000-0001-7829-9063)
- Xiaohua Feng
- Zuoqiang Yuan (ORCID: https://orcid.org/0000-0002-5448-3162)
- Arshad Ali
- Jiangbo Yan
- Tiezhu Jiao
- Liang Zhao
Institutions
- Xi'an University of Architecture and Technology (CN)
- Northwestern Polytechnical University (CN)
- State Forestry and Grassland Administration (CN)
- Jiangxi Province Forestry Survey Planning Institute (CN)
- Experimental Center of Forestry in North China (CN)
- Hebei University (CN)
Publication Details
- Journal
- Trees Forests and People
- Published
- 2026-02-19
- DOI
- https://doi.org/10.1016/j.tfp.2026.101197
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00