Abstract

Human activities are critical factors influencing ecosystem sustainability. However, knowledge on regarding the mechanisms underlying the response of vegetation dynamics to human activities remains limited. To detect the driving factors and their individual contribution to the grassland vegetation dynamics in China’s Loess Plateau, a structural equation model (SEM) and a principal component regression model were built. The SEM showed that population change and urbanization, temperature and humidity, and agriculture and economy accounted for 62.5%, 31.2%, and 7.7%, respectively, of the overall impact directly affecting grassland vegetation dynamics. Furthermore, the principal component regression model demonstrated that the effects of the urbanization rate on the grassland above-ground biomass exceeded those of the other factors. The agriculture population had the maximum negative effect on grassland area. The higher the urbanization rate means the higher the number of residents migrates from rural to urban areas. Following this argument, the disturbances of human activities to grassland vegetation were expected to gradually decrease in rural areas, where the vast majority of the Loess Plateau is located. The migration of rural residents to urban areas promoted the increase in biomass and areas of grassland vegetation. Our findings suggest that the effect of urbanization should be considered when assessing vegetation change.

Highlights

  • Human activities and climate change are two of the most important factors driving the dynamics of terrestrial ecosystems [1,2,3]

  • We identified the increase in urbanization rate as the dominant driving factor, the influences of temperature and humidity on the dynamics of grassland vegetation gradually increased with time (Figure 4)

  • We investigated the specific factors driving the increase of grassland vegetation and assessed their impacts on grassland above-ground biomass (AGB) and area in the Loess Plateau of China

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Summary

Introduction

Human activities and climate change are two of the most important factors driving the dynamics of terrestrial ecosystems [1,2,3]. The spatiotemporal patterns of vegetation growth dynamics have been altered due to the ongoing climate change and intensifying human disturbances [4,5,6,7]. As human activities and global climate change further intensify, the responses of vegetation dynamics become increasingly complex [14,15]. Detecting key driving factors (e.g., climate change and human activities) and separating their individual influence on terrestrial ecosystems are important in ecosystem management and adaptation [2,16,17]

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