Greening or browning? The macro variation and drivers of different vegetation types on the Qinghai-Tibetan Plateau from 2000 to 2021

Huihui Wang; Jinyan Zhan; Chao Wang; Wei Liu; Zheng Yang; Huizi Liu; Chunyue Bai

doi:10.3389/fpls.2022.1045290

Greening or browning? The macro variation and drivers of different vegetation types on the Qinghai-Tibetan Plateau from 2000 to 2021

Front Plant Sci. 2022 Oct 26:13:1045290. doi: 10.3389/fpls.2022.1045290. eCollection 2022.

Authors

Huihui Wang¹, Jinyan Zhan¹, Chao Wang², Wei Liu³, Zheng Yang¹, Huizi Liu¹, Chunyue Bai¹

Affiliations

¹ State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China.
² School of Labor Economics, Capital University of Economics and Business, Beijing, China.
³ College of Geography and Environment, Shandong Normal University, Jinan, China.

Abstract

Vegetation greenness is one of the main indicators to characterize changes in terrestrial ecosystems. China has implemented a few large-scale ecological restoration programs on the Qinghai-Tibetan Plateau (QTP) to reverse the trend of ecosystem degradation. Although the effectiveness of these programs is beginning to show, the mechanisms of vegetation degradation under climate change and human activities are still controversial. Existing studies have mostly focused on changes in overall vegetation change, with less attention on the drivers of change in different vegetation types. In this study, earth satellite observation records were used to robustly map changes in vegetation greenness on the QTP from 2000 to 2021. The random forest (RF) algorithm was further used to detect the drivers of greenness browning on the QTP as a whole and in seven different vegetation types. The results show that an overall trend of greening in all seven vegetation types on the QTP over a 21-year period. The area of greening was 46.54×10⁴ km², and browning was 5.32×10⁴ km², representing a quarter and 2.86% of the natural vegetation area, respectively. The results of the browning driver analysis show that areas with high altitude, reduced annual precipitation, high intensity of human activity, average annual maximum and average annual minimum precipitation of approximately 500 mm are most susceptible to browning on the QTP. For the seven different vegetation types, their top 6 most important browning drivers and the ranking of drivers differed. DEM and precipitation changes are important drivers of browning for seven vegetation types. These results reflect the latest spatial and temporal dynamics of vegetation on the QTP and highlight the common and characteristic browning drivers of vegetation ecosystems. They provide support for understanding the response of different vegetation to natural and human impacts and for further implementation of site-specific restoration measures.

Keywords: MODIS NDVI; Qinghai-Tibetan Plateau (QTP); browning; climate change; greening; restoration.