Response of vegetation to drought in the Tibetan Plateau: Elevation differentiation and the dominant factors

Wang, Yijia; Fu, Bojie; Liu, Yanxu; Li, Yan; Feng, Xiaoming; Wang, Shuai

doi:10.1016/j.agrformet.2021.108468

Cited by 58 publications

(40 citation statements)

References 82 publications

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“…The growth trends identified in different reaches in the basin were basically the same. The results of other studies also suggest that GPP exhibited an upward trend in recent years (Geoghegan et al, 2018; Wang, Fu, et al, 2021), and other results indicate that the interannual changes in China's land net primary productivity (NPP) generally showed an upward trend from 1982 to 2010, especially from 1989 to 1999 (Liang, Yang, et al, 2015). Since the implementation of the GFGP in China, China's GPP has shown a significant growth trend (Jia et al, 2014).…”

Section: Discussionmentioning

confidence: 87%

“…We mainly studied the impact of abiotic factors (mainly including climate factors and social factors) on WUE. However, whether the dominant factor affecting WUE is human activities or climate change has always been controversial (Wang, Fu, et al, 2021). Due to the socioeconomic importance of the YRB, the water supply problem in the basin has received great attention (Guo et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…Under increasing global carbon emissions and relative water resource shortages (Chen et al, 2020; Du et al, 2010; Wang & Ge, 2020; Zhong et al, 2020), there exist great scientific and practical needs to understand the relationships among climate change, human activities and the carbon‐water coupling responses of terrestrial ecosystems (Wang, Fu, et al, 2021; Wang, Li, Wang, et al, 2020; Zhao, Wu, et al, 2020), especially in sensitive dryland ecosystems with deficient water resources and low‐carbon densities (Wang, Li, et al, 2021; Xu et al, 2021). Water use efficiency (WUE) is an important indicator for water resource management (Wang, Chen, et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Contributions of climatic and social factors to two water use efficiency indicators in the Yellow River

Fan

Wen

Cai

et al. 2022

Hydrological Processes

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Tracing the spatiotemporal tendency and driving forces of water use efficiency (WUE) is of great significance for understanding the carbon‐water balance, especially in large river basins. The lack of differential comparisons regarding the tendencies and driving forces of WUE indicators between the upper and lower reaches of rivers often affects the collaborative allocation and utilization of water resources at the basin scale, especially social factors such as population and economy distributions. Using remote sensing data and hierarchical decomposition methods, we identified the spatiotemporal distribution of the WUE of ecosystems (WUEe) and the WUE of canopies (WUEc) in the Yellow River Basin from 2003 to 2017 as well as the contribution rates of climatic and social factors to WUEe and WUEc. Our results show that WUEe had a different distribution pattern than WUEc. An increase in WUEe was accompanied by a decrease in WUEc, and these changes varied among the upper, middle and lower reaches. WUEc was most negatively correlated with pressure (| r | = 0.65), while WUEe was most positively correlated with the precipitation rate (| r | = 0.68). The contribution rates of climatic factors to both WUEc and WUEe in the upper reaches were higher than 95%. The middle reaches were mainly driven by climatic factors, with contribution rates higher than 90%. In the lower reaches, the contribution rates of social factors to WUEe were higher than 30%. These differentiated contributions indicated the importance of considering social factors in the lower reaches than in the upper reaches when managing WUEe under the dominance of climatic factors on WUEc.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Contributions of climatic and social factors to two water use efficiency indicators in the Yellow River

Fan

Wen

Cai

et al. 2022

Hydrological Processes

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“…Pearson correlation (PC) is an index to measure the degree of correlation between two variables [ 42 ]. In this study, the annual correlation coefficient of SPEI and NDVI in image pixels at different time scales was calculated, and the spatial distribution characteristics of the correlation coefficient between vegetation and drought were analyzed.…”

Section: Methodsmentioning

confidence: 99%

Assessing Vegetation Ecosystem Resistance to Drought in the Middle Reaches of the Yellow River Basin, China

Shi

Chen

Ding

et al. 2022

IJERPH

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The frequency and intensity of droughts are increasing in many parts of the world as a result of global climate change and human activity, posing a serious threat to regional ecological security. The climate in the middle reaches of the Yellow River Basin (MRYRB) has been warm and dry in recent years, with frequent droughts. In order to investigate the temporal trend of drought, and reveal the resistance of vegetation to drought in the MRYRB, this study used remotely-sensed vegetation index products (MODIS-NDVI and SPOT-NDVI) and the standardized precipitation evapotranspiration index (SPEI). The results indicated that: (1) drought intensity showed a weak upward trend in the study area from 2000 to 2018, with linear growth rates of SPEI at temporal scales of 1, 3, 6, 9 and 12 months of −0.002, 0.0034, 0.0198, 0.0234, and 0.0249, respectively; (2) drought was positively correlated with vegetation in most areas (97.6%), and vegetation was most affected by drought on long-term time scales (9 and 12 months); (3) with the extension of drought, vegetation resistance index decreased, then gradually recovered after the end of the drought. Forest had the longest resistance duration of 260 days, while grassland and cultivated land had resistance durations of only 170 days. This study adds to the understanding of vegetation’s ability to withstand drought, and these findings provide evidence to support drought response in the MRYRB.

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“…China has also implemented different land management measures in different regions, resulting in different ecological effects (Chen et al, 2019;Liu et al, 2020). In addition, elevation and climate are the determinants of the ecological effects from land cover changes (Dewan & Yamaguchi, 2009;Findell et al, 2017), and there is growing evidence that the rate of temperature change is amplified with increasing elevations Mountain Research Initiative EDW Working Group, 2015;Wang, Fu, et al, 2021). Therefore, temperature deviations due to elevation can have an impact on LST, which in turn affects the growth and physiological functions of vegetation (Zhang et al, 2004;Zou et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Regional differentiation in the ecological effects of land cover change in China

et al. 2021

Self Cite

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Land cover changes driven by either land degradation or land development have caused distinct alterations of the global environment. China has experienced a large area of land degradation and development, while the environmental responses to the national land cover changes are still vague. Based on remote-sensed datasets, we analyzed the multiple ecological effects (temperature, biomass formation, and observed greenness) of land cover changes in China and their regional differences through neighbourhood analysis and Geogdetector, aiming to provide a theoretical basis for mitigating land degradation and sustainable land development. The results showed that the conversion of cultivated land to grassland and shrubland led to reductions in the greenness effect (À0.017) and biomass formation effect (À0.015 kg C m -2 ), while the conversion of forest to grassland and shrubland led to a reduction in greenness (À0.01) and an increase in temperature (0.079 C). As the amplitude of the change in the land cover fraction increased, these trends became more obvious and irreversible. The same land cover change could have either positive or negative

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Response of vegetation to drought in the Tibetan Plateau: Elevation differentiation and the dominant factors

Cited by 58 publications

References 82 publications

Contributions of climatic and social factors to two water use efficiency indicators in the Yellow River

Contributions of climatic and social factors to two water use efficiency indicators in the Yellow River

Assessing Vegetation Ecosystem Resistance to Drought in the Middle Reaches of the Yellow River Basin, China

Regional differentiation in the ecological effects of land cover change in China

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