Evidence map›Paper›PMID 41698897›Full record

ArticleNature communications2026

Biophysical factors and management practices are key to shaping forest resilience.

Yu Yan, Xingyu Feng, Zhiyong Liu, Zizhao Wang, Zeqin Huang, Yajun Wang, Xin Lan, Juan Chen, Kairong Lin, Xiaohong Chen and 3 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Yu Yan *Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0002-7045-0459
Xingyu Feng *Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0009-0001-8668-4356
Zhiyong LiuCenter for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China. liuzhiy25@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-6930-5879
Zizhao WangSchool of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0009-0005-8833-4914
Zeqin HuangCenter for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0001-5682-3477
Yajun WangInstitute of Estuarine and Coastal Research, School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0009-0004-7221-5366
Xin LanCollege of Agricultural Science and Engineering, Hohai University, Nanjing, China.
Juan ChenKey Laboratory of Eco-environments in Three Gorges Reservoir Region of Ministry of Education, School of Life Sciences, Southwest University, Chongqing, China.
Kairong LinCenter for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0001-6533-3357
Xiaohong ChenCenter for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0002-2043-8638
Chunyu DongCenter for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China.ORCID http://orcid.org/0000-0001-5721-9247
Xiaogang HeDepartment of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0001-7428-0269
Giovanni ForzieriDepartment of Civil and Environmental Engineering, University of Florence, Florence, Italy.ORCID http://orcid.org/0000-0002-5240-1303

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52179031Natural Science Foundation of Guangdong Province (Guangdong Natural Science Foundation) 2023B1515020116
6 · The paper itself

Abstract

Forest management influences key ecosystem services essential for societal well-being. However, how these human management activities affect forest resilience under different environmental conditions remains poorly understood. This study investigates how different forest management practices interact with biophysical factors and explores their joint effect on forest resilience globally during 2001-2015. To address this gap, we develop a framework that integrates Critical Slowing Down theory, satellite-based vegetation indices, and machine learning. Results show that natural forests without management exhibit the highest resilience among all forest management types, followed by natural forests with management and planted forests. Overall, forest management practices weaken resilience prominently under intensive anthropogenic pressures. However, specific biophysical conditions can reverse this pattern. Planted forests show higher resilience than natural forests when the ratio of precipitation to potential evapotranspiration exceeds 1.5 in wet climates, whereas natural forests remain more resilient in drier climates below this threshold. This threshold reflects the point where water availability becomes sufficient to compensate for the detrimental effects originating from human pressures. Cold temperatures, dense vegetation, and high soil fertility may further enhance the resilience of managed forests to levels typical of natural forests.

Indexed as

Biophysical PhenomenaConservation of Natural ResourcesForestryForestsClimateEcosystemHumansSoilTreesSoil

Identifiers

PMID41698897
PMCPMC13022478

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.