Evidence map›Paper›PMID 40353238›Full record

ArticleFrontiers in plant science2025

Suitability mapping of native tree species in dry-hot valleys of Yunnan based on InVEST-MaxEnt coupled modeling: model validation framework with native tree species actual distribution and seed germination.

Meng Xie, Xiaobo Song, Xuexing Zhang, Yongpeng Ma, Zhilin Song, Fengjuan Li, Wei Li, Linyuan Fan, Hong Ma

Abstract read
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Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

9 authors.

Meng XieInstitute of Highland Forest Science, Chinese Academy of Forestry, State Key Laboratory of Efficient Production of Forest Resources, Yunnan, Kunming, China.
Xiaobo SongRushan Inspection and Testing Center, Rushan, China.
Xuexing ZhangYunnan Academy of Forestry and Grassland, Kunming, China.
Yongpeng MaKey Laboratory of Comprehensive Conservation for Extremely Small Populations of Wild Plants in Yunnan Province, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
Zhilin SongRushan Forestry Development Center, Rushan, China.
Fengjuan LiInstitute of Highland Forest Science, Chinese Academy of Forestry, State Key Laboratory of Efficient Production of Forest Resources, Yunnan, Kunming, China.
Wei LiYunnan Jicheng Landscape Technology Co., Ltd., Mile, China.
Linyuan FanYunnan General Administration of Forestry Seeds and Seedlings, Kunming, China.
Hong MaInstitute of Highland Forest Science, Chinese Academy of Forestry, State Key Laboratory of Efficient Production of Forest Resources, Yunnan, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The target valleys along the Jinsha, Nujiang, Lancang, and Yuanjiang Rivers exhibit acute human-land conflicts and ecosystem vulnerability. Predicting the distribution of potential suitable habitats for native tree species in Yunnan Province provides basin-scale insights for the management of ecosystems in dry and hot valleys, thereby advancing restoration planning in dry-hot valleys. Methods: This study investigates native tree species suitability in Yunnan's dry-hot valleys using an integrated MaxEnt-InVEST modeling framework. Results: Temperature and precipitation emerged as dominant bioclimatic controls, with optimal species occurrence (1 000-2 500 m) showing negative elevation correlation. Four native tree species ( Discussion: This methodology provides a cost-effective solution for vegetation restoration planning in ecologically fragile dry-hot ecosystems. The research results can provide scientific support for the restoration of degraded ecosystems in dry-hot valleys of Yunnan Province, the national Afforestation program and soil and water conservation projects.

Indexed as

dry-hot valleysInVEST-MaxEnt coupled modelingmodel validation frameworknative tree speciessuitability mapping

Identifiers

PMID40353238
PMCPMC12062750

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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.