Dynamic Effects of Close-to-Nature Forest Management on the Growth Investment Strategies of Future Crop Trees

Close-to-nature forest management is a sustainable forest management approach aimed at achieving a balance between ecological and economic benefits. The cultivation of future crop trees in the later successional stages following the removal of competitive trees is crucial for promoting positive development trajectories of succession. Understanding the dynamic process of growth investment strategies in future crop trees facilitates the rational planning of management cycles and scopes, ultimately enhancing the quality of tree cultivation. This study was conducted in a Pinus massoniana secondary forest with close-to-nature forest management in Ningbo City, Zhejiang Province, using handheld mobile laser scanning technology to precisely reconstruct the structure of future crop trees. Over a period of 2–5 years following the initial implementation of close-to-nature forest management, 3D point cloud data were collected annually from both managed and reference (non-managed) plots. Using these multi-temporal data, we analyzed the dynamics of the investment strategies, structural growth components, and crown competition of future crop trees. A linear mixed-effect model was applied to compare the temporal variations in these indices between the managed and control plots. Our results revealed that the height-to-diameter ratio of the future crop trees gradually declined over time, while the crown-to-diameter ratio initially increased and then decreased in the managed plots. These trends were significantly different from those observed in the control plots. Additionally, the height growth rates of the future crop trees in the managed plots were consistently lower than those in the control plots, whereas the crown and diameter at breast height (DBH) growth rates were higher. Furthermore, the crown gap area between the future crop trees and their neighboring trees gradually diminished, and the crown overlap progressively increased. These results suggest that the investment in height growth, initially driven by crown competition, shifted toward crown and DBH growth following close-to-nature forest management. In the initial stage after the removal of competitive trees, future crop trees benefited from ample crown radial space and minimal crown competition. However, as the crown radial space became increasingly limited, the future crop trees shifted their growth investment toward DBH to enhance mechanical stability and achieve a balanced tree structure. Understanding these dynamic processes and the underlying mechanisms of growth investment strategies contributes to predicting future forest community development, improving forest productivity, maintaining structural diversity, and ensuring sustainable forest management.

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Publication Details

Journal
Forests
Published
2025-03-16
DOI
https://doi.org/10.3390/f16030523
Citations
2
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.60
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article

Dynamic Effects of Close-to-Nature Forest Management on the Growth Investment Strategies of Future Crop Trees

Qingsong Yang, Qiushi Yu, R B Chen, Zhengkang Zhou et al.
2 citations
Forests
Remote Sensing and LiDAR Applications
1.60
article

Dynamic Effects of Close-to-Nature Forest Management on the Growth Investment Strategies of Future Crop Trees

Qingsong Yang, Qiushi Yu, R B Chen, Zhengkang Zhou, Shan Jiang, Xihua Wang, Heming Liu, Huimin Yin, Yangyi Qin
article en
2 citations

Abstract

Close-to-nature forest management is a sustainable forest management approach aimed at achieving a balance between ecological and economic benefits. The cultivation of future crop trees in the later successional stages following the removal of competitive trees is crucial for promoting positive development trajectories of succession. Understanding the dynamic process of growth investment strategies in future crop trees facilitates the rational planning of management cycles and scopes, ultimately enhancing the quality of tree cultivation. This study was conducted in a Pinus massoniana secondary forest with close-to-nature forest management in Ningbo City, Zhejiang Province, using handheld mobile laser scanning technology to precisely reconstruct the structure of future crop trees. Over a period of 2–5 years following the initial implementation of close-to-nature forest management, 3D point cloud data were collected annually from both managed and reference (non-managed) plots. Using these multi-temporal data, we analyzed the dynamics of the investment strategies, structural growth components, and crown competition of future crop trees. A linear mixed-effect model was applied to compare the temporal variations in these indices between the managed and control plots. Our results revealed that the height-to-diameter ratio of the future crop trees gradually declined over time, while the crown-to-diameter ratio initially increased and then decreased in the managed plots. These trends were significantly different from those observed in the control plots. Additionally, the height growth rates of the future crop trees in the managed plots were consistently lower than those in the control plots, whereas the crown and diameter at breast height (DBH) growth rates were higher. Furthermore, the crown gap area between the future crop trees and their neighboring trees gradually diminished, and the crown overlap progressively increased. These results suggest that the investment in height growth, initially driven by crown competition, shifted toward crown and DBH growth following close-to-nature forest management. In the initial stage after the removal of competitive trees, future crop trees benefited from ample crown radial space and minimal crown competition. However, as the crown radial space became increasingly limited, the future crop trees shifted their growth investment toward DBH to enhance mechanical stability and achieve a balanced tree structure. Understanding these dynamic processes and the underlying mechanisms of growth investment strategies contributes to predicting future forest community development, improving forest productivity, maintaining structural diversity, and ensuring sustainable forest management.

ForestsVol. 16(3)
University of Nottingham Ningbo China (CN), Shanghai Chenshan Plant Science Research Center (CN), East China Normal University (CN)
Openalex Percentile: Top 20%
Remote Sensing and LiDAR Applications
1.60
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