Probabilistic assessment of vegetation vulnerability to drought stress in Central Asia

Yuan, Y.; Bao, Anming; Jiang, Ping; Hamdi, Rafiq; Termonia, Piet; Maeyer, Philippe De; Guo, Hao; Zheng, Guoxiong; Yu, Tao; Prishchepov, Alexander V.

doi:10.1016/j.jenvman.2022.114504

Cited by 32 publications

(9 citation statements)

References 93 publications

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“…When considering a grassland NDVI below the 30th, 20th, and 10th percentiles in April, August, and September, respectively, it was further confirmed that August and September showed a positive response in the probability of deterioration of grassland NDVI with increasing drought, while the response was not significant in April. This result also shows the higher probability of a grassland NDVI decline during the growing season in areas with more severe water deficits when the grassland vegetation is at a lower percentage, consistent with the results of other regional studies ( Liu et al., 2016 ; Won et al., 2021 ; Yuan et al., 2022 ). Furthermore, region-wide, the probabilities of moderate, severe, and extreme drought scenarios below the 40th percentile were 28.7%, 27.5%, and 27.0% in April; 47.6%, 48.7%, and 49.2% in August; and 47.6%, 48.6%, and 49.1% in September, respectively ( Figures 6 - 8 ).…”

Section: Resultssupporting

confidence: 91%

“…season in areas with more severe water deficits when the grassland vegetation is at a lower percentage, consistent with the results of other regional studies (Liu et al, 2016;Won et al, 2021;Yuan et al, 2022). Furthermore, region-wide, the probabilities of moderate, severe, and extreme drought scenarios below the 40th percentile were 28.7%, 27.5%, and 27.0% in April; 47.6%, 48.7%, and 49.2% in August; and 47.6%, 48.6%, and 49.1% in September, respectively (Figures 6-8).…”

Section: A B Csupporting

confidence: 91%

Section: Discussionsupporting

confidence: 79%

“…Drought in semiarid regions is most likely to cause grassland losses in August and September of summer and autumn, and the results were consistent with those of Yuan et al. (2022) in Central Asia ( Yuan et al., 2022 ). This result is possibly due to the persistent high temperatures in Xinjiang at this time of year and the fact that semiarid regions are more dependent on precipitation than are semi-humid regions and appear to have a greater demand for soil moisture from iceberg meltwater ( Zheng et al., 2021 ).…”

Section: Discussionsupporting

confidence: 79%

“…The reason for the highest probability of grassland NDVI declining in April in spring when the arid region is subjected to drought is that the natural factor that has a greater impact on grass in April in spring is the gradual increase in temperature, since precipitation in the dry area is consistently low throughout the growing season (Zhang et al, 2020). Drought in semiarid regions is most likely to cause grassland losses in August and September of summer and autumn, and the results were consistent with those of Yuan et al (2022) in Central Asia (Yuan et al, 2022). This result is possibly due to the persistent high temperatures in Xinjiang at this time of year and the fact that semiarid regions are more dependent on precipitation than are semi-humid regions and appear to have a greater demand for soil moisture from iceberg meltwater (Zheng et al, 2021).…”

Section: Heterogeneity Of Climate Zones and Grassland Types In Respon...supporting

confidence: 75%

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Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

et al. 2023

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In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

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Section: Resultssupporting

confidence: 91%

Section: A B Csupporting

confidence: 91%