Effects of drought and climate factors on vegetation dynamics in Central Asia from 1982 to 2020

Liu, Liang; Peng, Jian; Li, Gangyong; Guan, Jingyun; Han, Wanqiang; Ju, Xifeng; Zheng, Jianhua

doi:10.1016/j.jenvman.2022.116997

Cited by 42 publications

(11 citation statements)

References 61 publications

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“…The random error ε i , model parameters a and b are utilized in the time series interpolation. The variables are computed using the least squares method, obtaining the optimal regression equation through the following expression ( Liu et al., 2023a ):…”

Section: Methodsmentioning

confidence: 99%

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Ma,

Zheng,

Pen

et al. 2024

Front. Plant Sci.

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It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region.

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Section: Methodsmentioning

confidence: 99%

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Ma,

Zheng,

Pen

et al. 2024

Front. Plant Sci.

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“…Previous studies have noted that different vegetation types have different response characteristics to drought (Liu et al, 2023) and the characteristics regarding the response of different grassland types to drought remain to be explored. This study shows that the response of NPP to drought was also correlated with grassland type.…”

Section: Concurrent Effect Of Drought On Grassland Nppmentioning

confidence: 99%

“…This study showed a time lag of 1-3 months in the response of grassland NPP to drought, but the response was mainly dominated by the current month. Liu et al (2023) studied the response of vegetation to drought and its time lag in arid areas, showing that the time lag between woodland and shrubs and drought was mainly 1 month. This may be because grassland is shallow-rooted vegetation, and its growth condition is mainly governed by soil surface moisture.…”

Section: Lagged Effect Of Drought On Grassland Nppmentioning

confidence: 99%

Concurrent and lagged effects of drought on grassland net primary productivity: a case study in Xinjiang, China

et al. 2023

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Xinjiang grasslands play a crucial role in regulating the regional carbon cycle and maintaining ecosystem stability, and grassland net primary productivity (NPP) is highly vulnerable to drought. Drought events are frequent in Xinjiang due to the impact of global warming. However, there is a lack of more systematic research results on how Xinjiang grassland NPP responds to drought and how its heterogeneity is characterized. In this study, the CASA (Carnegie Ames Stanford Application) model was used to simulate the 1982–2020 grassland NPP in Xinjiang, and the standardized Precipitation Evapotranspiration Index (SPEI) was calculated using meteorological station data to characterize drought. The spatial and temporal variability of NPP and drought in Xinjiang grasslands from 1982 to 2020 were analyzed by the Sen trend method and the Mann-Kendall test, and the response characteristics of NPP to drought in Xinjiang grasslands were investigated by the correlation analysis method. The results showed that (1) the overall trend of NPP in Xinjiang grassland was increasing, and its value was growing season > summer > spring > autumn. Mild drought occurred most frequently in the growing season and autumn, and moderate drought occurred most frequently in spring. (2) A total of 64.63% of grassland NPP had a mainly concurrent effect on drought, and these grasslands were primarily located in the northern region of Xinjiang. The concurrent effect of drought on NPP was strongest in plain grassland and weakest in alpine subalpine grassland. (3) The lagged effect is mainly in the southern grasslands, the NPP of alpine subalpine meadows, meadows, and alpine subalpine grasslands showed mainly a 1-month time lag effect to drought, and desert grassland NPP showed mainly a 3-month time lag effect to drought. This research can contribute to a reliable theoretical basis for regional sustainable development.

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“…In arid regions, lake water resources (e.g., surface area, water level, and volume), vegetation (e.g., Normalized Difference Vegetation Index (NDVI), net primary productivity, and gross primary productivity), and hydroclimatic factors (e.g., temperature, precipitation, and runoff) have garnered global attention ( Jiapaer et al., 2011 ; Voss et al., 2013 ; Chen et al., 2020 ; Kooch et al., 2022 ; Liu et al., 2023 ). The relationships between lake surface area and hydroclimatic factors and between NDVI and hydroclimatic factors have been extensively scrutinized across various spatial scales ( Shen et al., 2017 ; Nourani et al., 2021 ; Ogou et al., 2022 ; Gbetkom et al., 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Responses of vegetation cover to hydro-climatic variations in Bosten Lake Watershed, NW China

Ge,

Ding,

Amantai

et al. 2024

Front. Plant Sci.

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Amidst the backdrop of global climate change, it is imperative to comprehend the intricate connections among surface water, vegetation, and climatic shifts within watersheds, especially in fragile, arid ecosystems. However, these relationships across various timescales remain unclear. We employed the Ensemble Empirical Mode Decomposition (EEMD) method to analyze the multifaceted dynamics of surface water and vegetation in the Bosten Lake Watershed across multiple temporal scales. This analysis has shed light on how these elements interact with climate change, revealing significant insights. From March to October, approximately 14.9–16.8% of the areas with permanent water were susceptible to receding and drying up. Both the annual and monthly values of Bosten Lake’s level and area exhibited a trend of initial decline followed by an increase, reaching their lowest point in 2013 (1,045.0 m and 906.6 km2, respectively). Approximately 7.7% of vegetated areas showed a significant increase in the Normalized Difference Vegetation Index (NDVI). NDVI volatility was observed in 23.4% of vegetated areas, primarily concentrated in the southern part of the study area and near Lake Bosten. Regarding the annual components (6 < T < 24 months), temperature, 3-month cumulative NDVI, and 3-month-leading precipitation exhibited the strongest correlation with changes in water level and surface area. For the interannual components (T≥ 24 months), NDVI, 3-month cumulative precipitation, and 3-month-leading temperature displayed the most robust correlation with alterations in water level and surface area. In both components, NDVI had a negative impact on Bosten Lake’s water level and surface area, while temperature and precipitation exerted positive effects. Through comparative analysis, this study reveals the importance of temporal periodicity in developing adaptive strategies for achieving Sustainable Development Goals in dryland watersheds. This study introduces a robust methodology for dissecting trends within scale components of lake level and surface area and links these trends to climate variations and NDVI changes across different temporal scales. The inherent correlations uncovered in this research can serve as valuable guidance for future investigations into surface water dynamics in arid regions.

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Effects of drought and climate factors on vegetation dynamics in Central Asia from 1982 to 2020

Cited by 42 publications

References 61 publications

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Concurrent and lagged effects of drought on grassland net primary productivity: a case study in Xinjiang, China

Responses of vegetation cover to hydro-climatic variations in Bosten Lake Watershed, NW China

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