Abstract

Inner Mongolia in China is a typically arid and semi-arid region with vegetation prominently affected by global warming and human activities. Therefore, investigating the past and future vegetation change and its impact mechanism is important for assessing the stability of the ecosystem and the ecological policy formulation. Vegetation changes, sustainability characteristics, and the mechanism of natural and anthropogenic effects in Inner Mongolia during 2000–2019 were examined using moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) data. Theil–Sen trend analysis, Mann–Kendall method, and the coefficient of variation method were used to analyze the spatiotemporal variability characteristics and sustained stability of the NDVI. Furthermore, a trend estimation method based on a Seasonal Trend Model (STM), and the Hurst index was used to analyze breakpoints and change trends, and predict the likely future direction of vegetation, respectively. Additionally, the mechanisms of the compound influence of natural and anthropogenic activities on the vegetation dynamics in Inner Mongolia were explored using a Geodetector Model. The results show that the NDVI of Inner Mongolia shows an upward trend with a rate of 0.0028/year (p < 0.05) from 2000 to 2019. Spatially, the NDVI values showed a decreasing trend from the northeast to the southwest, and the interannual variation fluctuated widely, with coefficients of variation greater than 0.15, for which the high-value areas were in the territory of the Alxa League. The areas with increased, decreased, and stable vegetation patterns were approximately equal in size, in which the improved areas were mainly distributed in the northeastern part of Inner Mongolia, the stable and unchanged areas were mostly in the desert, and the degraded areas were mainly in the central-eastern part of Inner Mongolia, it shows a trend of progressive degradation from east to west. Breakpoints in the vegetation dynamics occurred mainly in the northwestern part of Inner Mongolia and the northeastern part of Hulunbuir, most of which occurred during 2011–2014. The future NDVI trend in Inner Mongolia shows an increasing trend in most areas, with only approximately 10% of the areas showing a decreasing trend. Considering the drivers of the NDVI, we observed annual precipitation, soil type, mean annual temperature, and land use type to be the main driving factors in Inner Mongolia. Annual precipitation was the first dominant factor, and when these four dominant factors interacted to influence vegetation change, they all showed interactive enhancement relationships. The results of this study will assist in understanding the influence of natural elements and human activities on vegetation changes and their driving mechanisms, while providing a scientific basis for the rational and effective protection of the ecological environment in Inner Mongolia.

Highlights

  • Vegetation is an important component of ecosystems and plays a key role in the carbon cycle [1,2,3]

  • To study the annual changes in the normalized difference vegetation index (NDVI) during 2000–2019 in Inner Mongolia, a time series analysis of the vegetation cover was conducted for each year (Figure 3)

  • The results showed that the annual NDVI values in Inner Mongolia fluctuated upward from 0.42 to 0.51 between 2000 and 2019, at a growth rate of 0.0028/year (p < 0.05) and a multi-year average of 0.46

Read more

Summary

Introduction

Vegetation is an important component of ecosystems and plays a key role in the carbon cycle [1,2,3]. Vegetation indices can provide substantial information on terrestrial vegetation; they are often used as an important parameter in characterizing surface vegetation for environmental quality assessments. Vegetation indices are important for studying the hydrology, ecology, and regional changes [6,7]. Numerous studies have shown that the normalized difference vegetation index (NDVI) correlates well with the biomass and leaf area indices, allowing a good representation of the surface vegetation coverage. This can be used to effectively characterize vegetation activity and productivity and is suitable for representing changes in surface vegetation cover [1,8,9,10]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call