Evolution and Climate Drivers of NDVI of Natural Vegetation during the Growing Season in the Arid Region of Northwest China

Li, Zhi; Niu, Yun; Li, Xinchuan; Cao, Linglong; Feng, Ru; He, Qian; Pan, Yingping

doi:10.3390/f13071082

Cited by 6 publications

(8 citation statements)

References 71 publications

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“…The GIMMS NDVI3g data products comprised a global data set with a spatial resolution of 1/12° (8 km at the equator) and a temporal resolution of 15‐day intervals, with the longest time series available from July 1981 to December 2015. This data set has been verified to have the best temporal consistency (Marshall et al., 2016) and has been extensively used in China (Liang & Yang, 2016; Tao et al., 2017; H. Wang et al., 2022; H. J. Xu et al., 2018). Data from 1982 to 2015 were extracted in this study, and to further reduce the impact of clouds and haze, monthly values were integrated using the Maximum Value Composite (MVC) technique (Holben, 1986).…”

Section: Methodsmentioning

confidence: 99%

“…However, in the study conducted by Y. Zhang et al. (2021), radiation was not considered as the major influencing factor that plays an important role in the growth of vegetation in drylands (H. Wang et al., 2022), and there is a lack of studies on the structural overshoot in water‐limited drylands, which occupy over 40% area of the global land (L. Wang et al., 2022). Given the significant regional discrepancies in spatiotemporal characteristics, the response and feedback mechanisms of vegetation to climate vary considerably at different timescales across regions.…”

Section: Introductionmentioning

confidence: 99%

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Intensified Structural Overshoot Aggravates Drought Impacts on Dryland Ecosystems

Zhang,

Liu,

Cheng

et al. 2024

Earth's Future

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A favorable environment can induce vegetation overgrowth to exceed the ecosystem carrying capacity, exacerbating water resource depletion and increasing the risk of lagged effects on vegetation degradation. This phenomenon is defined as structural overshoot, which can lead to large‐scale forest mortality and grassland deterioration. However, the current understanding of structural overshoot remains incomplete due to the complex time‐varying interactions between vegetation and climate. Here, we used a dynamic learning algorithm to decompose the contributions of vegetation and climate to drought occurrence, trace the connection between antecedent and concurrent vegetation dynamics, thus effectively capturing structural overshoot. This study focused on the climate‐sensitive hotspot in Northwest China drylands, where significant vegetation greening induced by a warming and wetting climate was detected during 1982–2015, leading to soil moisture deficit and aggravating vegetation degradation risks during droughts. We found that during this period, structural overshoot induced approximately 34.6% of the drought events, and lagged effects accounted for 16.7% of the vegetation degradation for these overshoot drought events. The occurrence of overshoot droughts exhibited an increasing trend over time, which was primarily driven by vegetation overgrowth followed by precipitation variation. Although the severity of overshoot and non‐overshoot droughts were generally comparable in spatial distribution, the impact of overshoot droughts is still becoming increasingly obvious. Our results indicate that the expected intensified overshoot droughts cannot be ignored and emphasize the necessity of sustainable agroecosystem management strategies.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intensified Structural Overshoot Aggravates Drought Impacts on Dryland Ecosystems

Zhang,

Liu,

Cheng

et al. 2024

Earth's Future

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“…The growth in the FVC around the Tarim Basin's oasis was linked to increased alpine snow and ice melt. Additionally, the regional government's active involvement in initiatives such as the farmland protection forest project and ecological water conveyance in the Tarim Basin [56] has not only fostered oasis agriculture but also enhanced the oasis's vegetation cover and significantly improved the environmental ecology.…”

Section: Relative Contribution Of Climate Change and Human Activities...mentioning

confidence: 99%

Characteristics and Drivers of Vegetation Change in Xinjiang, 2000–2020

Li,

Liang,

Wang

et al. 2024

Forests

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Examining the features of vegetation change and analyzing its driving forces across an extensive time series in Xinjiang are pivotal for the ecological environment. This research can offer a crucial point of reference for regional ecological conservation endeavors. We calculated the fractional vegetation cover (FVC) using MOD13Q1 data accessed through the Google Earth Engine (GEE) platform. To discern the characteristics of vegetation changes and forecast future trends, we employed time series analysis, coefficient of variation, and the Hurst exponent. The correlation between climate factors and FVC was investigated through correlation analysis. Simultaneously, to determine the relative impact of meteorological change and anthropogenic actions on FVC, we utilized multiple regression residual analysis. Furthermore, adhering to China’s ecological functional zone classification, Xinjiang was segmented into five ecological zones: R1 Altai Mountains-Junggar West Mountain Forest and Grassland Ecoregion, R2 Junggar Basin Desert Ecoregion, R3 Tianshan Mountains Mountain Forest and Grassland Ecoregion, R4 Tarim Basin-Eastern Frontier Desert Ecoregion, and R5 Pamir-Kunlun Mountains-Altan Mountains Alpine Desert and Grassland Ecoregion. A comparative analysis of these five regions was subsequently conducted. The results showed the following: (1) During the first two decades of the 21st century, the overall FVC in Xinjiang primarily exhibited a trend of growth, exhibiting a rate of increase of 4 × 10−4 y−1. The multi-year average FVC was 0.223. The mean value of the multi-year FVC was 0.223, and the mean values of different ecological zones showed the following order: R1 > R3 > R2 > R5 > R4. (2) The predominant spatial pattern of FVC across Xinjiang’s landscape is characterized by higher coverage in the northwest and lower in the southeast. In this region, 66.63% of the terrain exhibits deteriorating vegetation, while 11% of the region exhibits a notable rise in plant growth. Future changes in FVC will be dominated by a decreasing trend. Regarding the coefficient of variation outcomes, a minor variation, representing 42.12% of the total, is noticeable; the mean coefficient of variation stands at 0.2786. The stability across varied ecological zones follows the order: R1 > R3 > R2 > R4 > R5. (3) Factors that have a facilitating effect on vegetation FVC included relative humidity, daylight hours, and precipitation, with relative humidity having a greater influence, while factors that have a hindering effect on vegetation FVC included air temperature and wind speed, with wind speed having a greater influence. (4) Vegetation alterations are primarily influenced by climate change, while human activities play a secondary role, contributing 56.93% and 43.07%, respectively. This research underscores the necessity for continued surveillance of vegetation dynamics and the enhancement of policies focused on habitat renewal and the safeguarding of vegetation in Xinjiang.

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“…And climatic factors in the NWAC contributed as much as 73.3% to the change of NDVI (Jiang et al2018). While regional variations of NDVI in the NWAC are mainly driven by temperature and precipitation (Wang et al 2022). In addition to this, human activities have seriously affected the forested areas of the NWAC and the transitional exploitation of the water table, which in turn affects the vegetation cover index in the NWAC (Aizen et al 2000).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal distribution and response relationship of NDVI based on GeoDetector in the arid regions in Northwest China

ke,

LIANG,

TIAN

et al. 2024

Preprint

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Vegetation is an essential component of the earth's ecosystem. Exploring the dynamic changes of vegetation and its influencing factors in the arid regions in Northwest China (NWAC) is of great significance to the restoration and management of the regional ecological environment. In this paper, based on the long time series Normalized Difference Vegetation Index (NDVI) data (2000–2020), we analyzed the ecological changes in the NWAC at different spatial and temporal scales by using Theil-Sen Median and Mann-Kendall (Sen-MK), hurst index and others, and discussed the driving factors affecting NDVI changes using GeoDetector. The results indicate that the NDVI in the NWAC shows a significant upward trend (growth rate of 1.5×103 per year). Approximately 10% of the NWAC was ecologically improved, while 3% was degraded. In addition, the future changes of NDVI in the NWAC are characterized by anti-persistence. Precipitation (q = 0.502) is the main factor affecting NDVI in the NWAC, and the interaction with other factors has the strongest effect on the spatial differentiation of NDVI in the whole region. The results of this study can help to better understand the intricate mechanism of vegetation change, and provide a scientific foundation for future vegetation restoration and rational implementation of ecological projects in the NWAC.

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Evolution and Climate Drivers of NDVI of Natural Vegetation during the Growing Season in the Arid Region of Northwest China

Cited by 6 publications

References 71 publications

Intensified Structural Overshoot Aggravates Drought Impacts on Dryland Ecosystems

Intensified Structural Overshoot Aggravates Drought Impacts on Dryland Ecosystems

Characteristics and Drivers of Vegetation Change in Xinjiang, 2000–2020

Spatio-temporal distribution and response relationship of NDVI based on GeoDetector in the arid regions in Northwest China

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