# Optimizing forest structure for sustainability: a review of structure-based management effects on stand quality

**Authors:** Qiming Liao, Quan Qiu, Jie Gao, Qiang Liu, Qin Su, Yue Yang, Peilin Xie, Yutian Xin, Xiaolong Zhao, Pan Wan

PMC · DOI: 10.48130/forres-0025-0024 · 2025-10-29

## TL;DR

This review explores how structuring forests like natural ones improves growth, soil health, and sustainability through optimized tree arrangements.

## Contribution

The study provides a comprehensive synthesis of structure-based forest management effects on stand quality and ecosystem resilience.

## Key findings

- SBFM improves tree growth by reducing competition and enhancing diameter distribution.
- SBFM increases soil carbon and nutrients via litter and microbial activity.
- Structural adjustments create feedback loops that boost productivity and resilience.

## Abstract

Structure-based forest management (SBFM) has emerged as an innovative silvicultural approach that optimizes the spatial arrangement of trees to emulate natural forest structures and promote sustainability. Despite increasing applications of SBFM, a comprehensive synthesis of its impacts on stand quality and the underlying mechanisms remains lacking. This review synthesizes 126 peer-reviewed studies (2007–2025) to evaluate the multidimensional effects of SBFM on forest stand growth, structure, soil properties, and stability. Evidence indicates that SBFM enhances tree growth by reducing competitive pressure, improves diameter distribution and species mingling, thereby approximating natural stand patterns, and enriches soil carbon and nutrient pools through increased litter input and microbial activity. These structural adjustments collectively foster a positive feedback loop that integrates aboveground productivity, belowground processes, and overall ecosystem resilience. Future research should prioritize cross-regional ecological monitoring, mechanistic experiments that link structural optimization to biodiversity and carbon sequestration, the integration of artificial intelligence (AI) and remote sensing for precision management, and improvements in forest stand quality evaluation systems. Overall, SBFM markedly improves stand quality and constitutes a promising strategy for sustainable forest management that enhances ecological resilience.

## Full-text entities

- **Chemicals:** carbon (MESH:D002244)

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12648026/full.md

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Source: https://tomesphere.com/paper/PMC12648026