Analysis of Vegetation Changes and Driving Factors on the Qinghai-Tibet Plateau from 2000 to 2022
Year: 2024
Type: article
Abstract: This study assesses the impact of climate change and human activities on vegetation dynamics (kNDVI) on the Qinghai-Tibet Plateau (QTP) between 2000 and 2022, considering both lag and cumulative effects. Given the QTP’s high sensitivity to climate change and human activities, it is imperative to understand their effects on vegetation for the sustainable development of regional and national terrestrial ecosystems. Using MOD13Q1 NDVI and climate and human activity data, we applied methods such as Sen-MK, lag and cumulative effect analysis, improved residual analysis, and geographical detector analysis. The outcomes were as follows. (1) The vegetation kNDVI on the QTP showed an overall fluctuating growth trend between 2000 and 2022; improved regions were more significant than degraded regions, with improved regions primarily distributed in humid and semi-humid areas with favorable climate conditions, and degraded regions primarily in arid and semi-arid areas; this implies that climate conditions have a significant impact on vegetation changes on the QTP. (2) The analysis of lag and cumulative effects revealed that temperature and precipitation have a substantial cumulative effect on vegetation kNDVI on the QTP. The vegetation kNDVI showed a lag effect of 0 months and a cumulative effect of 1 month for temperature, and a lag effect of 0 months and a cumulative effect of 2 months for precipitation, respectively. (3) Improved residual analysis based on lag and cumulative effects revealed that human activities positively contributed 66% to the changes in vegetation kNDVI on the QTP, suggesting a notable positive impact of human activities. Geographical detector analysis indicated that, among different human activity factors affecting vegetation kNDVI changes, the explanatory power in 2005 and 2015 ranked as X3 (livestock density) > X1 (population density) > X2 (per capita GDP) > X4 (artificial afforestation density) > X5 (land use type), and in 2020, as X3 > X4 > X1 > X5 > X2. The explanatory power of afforestation density and land use type has relatively increased, indicating that recent efforts in ecological protection and restoration on the QTP, including developing artificial forest areas and afforestation programs, have considerably contributed to vegetation greening.
Source: Forests
DOI: 10.3390/f15122188
Authors: Xiaoqi Ren, Peng Hou, Yutiao Ma, Rongfei Ma, Jiahao Wang, Le Xie
Institutions: Ministry of Ecology and Environment, Satellite Application Center for Ecology and Environment, Shandong University of Science and Technology, Chinese Research Academy of Environmental Sciences, China University of Mining and Technology - Beijing, Beijing University of Civil Engineering and Architecture
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: gold
Estimated APC paid: $2,955
OpenAlex ID: W4405325784
