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

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.

Authors

Institutions

Publication Details

Journal
Plants
Published
2025-12-27
DOI
https://doi.org/10.3390/plants15010093
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Ying Meng, Jianfeng Liu, Xiaoyu Li, Yubo Liu et al.
Plants
Remote Sensing in Agriculture
article

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

Ying Meng, Jianfeng Liu, Xiaoyu Li, Yubo Liu, Yuxin Du, Yanying Li, Junjuan Yan
article en

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.

PlantsVol. 15(1)
Northwest University (CN), Science and Technology on Surface Physics and Chemistry Laboratory (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 29%
Remote Sensing in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.