Evidence map›Paper›PMID 41515038›Full record

ArticlePlants (Basel, Switzerland)2025

Alpine Grassland Growth and Its Ecological Responses to Environmental Impacts: Insights from a Comprehensive Growth Index and SHAP-Based Analysis.

Yanying Li, Yongmei Liu, Xiaoyu Li, Junjuan Yan, Yuxin Du, Ying Meng, Jianhong Liu

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yanying LiCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Yongmei LiuCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Xiaoyu LiCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Junjuan YanCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Yuxin DuCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Ying MengCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Jianhong LiuCollege of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.ORCID 0000-0002-8050-4780

Funding

National Natural Science Foundation of China No. 41871335
6 · The paper itself

Abstract

The alpine grassland is one of the most representative ecosystems on the Qinghai-Tibet Plateau, Growth monitoring is fundamental for the alpine grassland maintenance and husbandry sustainability. In this study, by the integration of regression model, principal component analysis, and SHAP-enhanced machine learning, a comprehensive growth index (CGI) was proposed for the accurate and quick assessment of alpine grassland growth in Qinghai Province, located in the eastern Qinghai-Tibet Plateau. The temporal and spatial growth behaviors of the main grassland types over 2001-2023 were then determined and the differences in key driving factors and their responses explored. The results indicated that the CGI composed of KNDVI, EVI, MSAVI, GNDVI and CVI characterized the typical ecological and physical parameters related to grassland growth, proved to be optimal and efficient in long-term growth monitoring. Alpine grassland growth fluctuated but gradually increased from 2001 to 2023, but individual types exhibited different trends. In particular, the two main types of alpine meadow and alpine steppe displayed the weakest increasing trend in growth, with the good-growth and continuous-increasing area proportions of 26.01% and 18.03%, 70.45% and 74.72%, respectively. Soil total nitrogen was the most critical common factor and significantly increased the growth across all five grassland types, then followed by grazing intensity and precipitation, which exhibits diverse effects on the individual types. The result implies the significant heterogeneity in the key driviers which affect the alpine grassland growth over large scale.

Indexed as

alpine grasslandcomprehensive growth indexQinghai ProvinceSHAP-enhanced machine learningvegetation index

Identifiers

PMID41515038
PMCPMC12788055

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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.