Abstract

In recent years, global warming and intense human activity have been responsible for significantly altering vegetation dynamics on the Mongolian Plateau. Understanding the long-term vegetation dynamics in this region is important to assess the impact of these changes on the local ecosystem. Long-term (1982–2015), satellite-derived normalized difference vegetation index (NDVI) datasets were used to analyse the spatio-temporal patterns of vegetation activities using linear regression and the breaks for additive season and trend methods. The links between these patterns and changes in temperature, precipitation (PRE), soil moisture (SM), and anthropogenic activity were determined using partial correlation analysis, the residual trends method, and a stepwise multiple regression model. The most significant results indicated that air temperature and potential evapotranspiration increased significantly, while the SM and PRE had markedly decreased over the past 34 years. The NDVI dataset included 71.16% of pixels showing an increase in temperature and evaporation during the growing season, particularly in eastern Mongolia and the southern border of the Inner Mongolia Autonomous region, China. The proportion indicating the breakpoint of vegetation dynamics was 71.34% of pixels, and the trend breakpoints mainly occurred in 1993, 2003, and 2010. The cumulative effects of PRE and SM in the middle period, coupled with the short-term effects of temperature and potential evapotranspiration, have had positive effects on vegetation greening. Anthropogenic factors appear to have positively impacted vegetation dynamics, as shown in 81.21% of pixels. We consider rapid economic growth, PRE, and SM to be the main driving factors in Inner Mongolia. PRE was the main climatic factor, and combined human and livestock populations were the primary anthropogenic factors influencing vegetation dynamics in Mongolia. This study is important in promoting the continued use of green projects to address environmental change in the Mongolian Plateau.

Highlights

  • The trends and slopes in the temporal variation of different climatic factors during the growing season of 1982–2015 in the Mongolian Plateau were detected via the linear regression method (Figure 2)

  • We focused on the detection and characterisation of such changes within the trend component of the monthly normalized difference vegetation index (NDVI)

  • After exploring the climatic and vegetation change characteristics, this study offers an improved understanding of the effect of climatic and anthropogenic factors on NDVI on the Mongolian Plateau for the 1982–2015 period

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Summary

Introduction

Vegetation is an important component of terrestrial ecosystems; it is a natural link between the soil and atmosphere, and an indicator of regional and global ecosystem. The normalized difference vegetation index (NDVI) is relatively easy to obtain and use in calculations, and reflects surface vegetation conditions to a certain extent [2]. The global inventory modelling and mapping studies (GIMMS) NDVI has been demonstrated to have the highest temporal consistency, including in trend analyses. Based on the latest generation of GIMMS NDVI (NDVI3g V1.0), long-term (>30 years) seasonal or annual trends in vegetation have been reported at the continental and global scales [6,7,8], including piecewise linear regression [9], polynomial fitting [10], and ensemble empirical mode decomposition (EEMD) method [11]

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