Evidence map›Paper›PMID 41312405›Full record

ReviewForestry research2025

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

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

Abstract readReview
In one paragraph

Review in Forestry research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Qiming LiaoCollege of Forestry, Northwest A & F University, Yangling 712100, China.
Quan QiuGuangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
Jie GaoKey Laboratory for the Conservation and Regulation Biology of Species in Special Environments, College of life science, Xinjiang Normal University, Urumqi 830054, China.
Qiang LiuCollege of Forestry, Hebei Agricultural University, Baoding 071000, China.
Qin SuCollege of Forestry, Northwest A & F University, Yangling 712100, China.
Yue YangCollege of Forestry, Northwest A & F University, Yangling 712100, China.
Peilin XieCollege of Forestry, Northwest A & F University, Yangling 712100, China.
Yutian XinCollege of Forestry, Northwest A & F University, Yangling 712100, China.
Xiaolong ZhaoCollege of Ecology, Lanzhou University, Lanzhou 730000, China.
Pan WanCollege of Forestry, Northwest A & F University, Yangling 712100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Forest ecosystemSoil-plant interactionStand productivityStand qualityStand structureStructure-based forest managementSustainable forestry

Identifiers

PMID41312405
PMCPMC12648026

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.