Impact of human activities and climate change on the grassland dynamics under different regime policies in the Mongolian Plateau

Zhang, Yanzhen; Wang, Qian; Wang, Zhaoqi; Yang, Young-Hoon; Li, Jianlong

doi:10.1016/j.scitotenv.2019.134304

Cited by 108 publications

(48 citation statements)

References 36 publications

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“…The slope is the trend of variables. We used the ordinary least squares method [39][40][41][42] to determine the trends in climate, VI, and VGEG in time series:…”

Section: Trend Analysismentioning

confidence: 99%

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

et al. 2021

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The vegetation of the Qinghai–Tibet Plateau (QTP) is vital to the global climate change and ecological security of China. However, the impact of climate variation on the spatial pattern and zonal distribution of vegetation in the QTP remains unclear. Accordingly, we used multisource remote-sensing vegetation indices (GIMMS-LAI, GIMMS NDVI, GLOBMAP LAI, MODIS EVI, MODIS NDVI, and MODIS NIRv), climate data, a digital elevation model, and the moving window method to investigate the changes in vegetation greenness and its response to climate variations in the QTP from 2001 to 2016. Results showed that the vegetation was greening in the QTP, which might be attributed to the increases in temperature and radiation. By contrast, the browning of vegetation may be caused by drought. Notably, the spatial patterns of vegetation greenness and its variations were linearly correlated with climate at low altitudes, and vegetation greenness was non-linearly correlated with climate at high altitudes. The Northwestern QTP needs to be focused on in regard to positive and decreased VGEG (vegetation greenness along the elevation gradient). The significantly positive VGEG was up to (34.37 ± 2.21) % of the QTP, which indicated a homogenization of vegetation greenness on elevation. This study will help us to understand the spatial distribution of vegetation greenness and VGEG in the QTP under global warming, and it will benefit ecological environment management, policymaking, and future climate and carbon sink (source) prediction.

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“…The slope is the trend of variables. We used the ordinary least squares method [39][40][41][42] to determine the trends in climate, VI, and VGEG in time series:…”

Section: Trend Analysismentioning

confidence: 99%

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

et al. 2021

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“…However, the region is located in arid and semi-arid climate areas, and its grassland ecosystems are particularly vulnerable to climate change. In recent decades, climate change in combination with frequent human activity, has caused increasing land degradation and desert expansion in the Mongolian Plateau [21]. Therefore, investigations into the long-term vegetation dynamics and its driving forces have become urgent issues in the region.…”

Section: Introductionmentioning

confidence: 99%

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

Guo

Wang

et al. 2021

Remote Sensing

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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.

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“…Net primary productivity (NPP), defined as the amount of organic matter photosynthetically fixed by vegetation per unit area and time (Field, Behrenfeld, Randerson, & Falkowski, 1998; Gang et al, 2015; Imhoff et al, 2004), is the material basis of numerous ecosystem functions (Song, Dannenberg, & Hwang, 2013; Zhang, Wang, Wang, Yang, & Li, 2020b; Zhao, Liu, Zhang, Cui, & Zhao, 2019). As an effective indicator of environment changes, the variation of NPP over a range of time intervals can well reflect ecological status (Guo et al, 2020; Jenkins, Fleenor, & Dietz, 2019; Zhao et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

et al. 2021

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Monitoring the nonlinear trend of net primary productivity (NPP) is essential for assessing the changes of ecosystems quality. Land use change caused by human activities is considered to be a key factor leading to vegetation changes. However, how land use change impacts the nonlinear trend of NPP has not yet been determined. This article analyzed the nonlinear trend of NPP in arid and semiarid areas of China during in the period 1982-2015 based on the ensemble empirical mode decomposition (EEMD) method and elucidated the effects of land use changes on the nonlinear trends of NPP. The results revealed that: (a) With the EEMD method, although monotonic increase was the main type of the trend of NPP (28.40 %), trend reversals from increase to decrease and from decrease to increase accounted for 13.52 and 20.90 % of the study area, respectively. (b) Although vegetation in most types of land use has been improved a lot, it has not been improved significantly in forest areas and changed from improvement to degradation in some forest and urban land areas. (c) Urbanization limited vegetation recovery but other land use changes generally favoured vegetation improvement. Although afforestation improved vegetation, there was a considerable area of the forest converted from nonforest threatened by the changes from improvement to degradation due to water limitation.Overall, nonlinear trend analysis can reveal the hidden trend reversals to prevent the overestimation or underestimation of the risk of vegetation degradation and is conducive to accurate assessment of the effects of land use changes on vegetation trends. K E Y W O R D Sarid and semiarid areas, ensemble empirical mode decomposition (EEMD) method, land use change, net primary productivity, nonlinear trend analysis

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Impact of human activities and climate change on the grassland dynamics under different regime policies in the Mongolian Plateau

Cited by 108 publications

References 36 publications

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

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