Quantifying the nonlinear response of vegetation greening to driving factors in Longnan of China based on machine learning algorithm

Xiao, Xiong; Wang, Qingzheng; Guan, Qingyu; Zhang, Zepeng; Yan, Yonghong; Mi, Jimin; Yang, Enqi

doi:10.1016/j.ecolind.2023.110277

Cited by 9 publications

(2 citation statements)

References 90 publications

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“…In recent years, global warming has lengthened the growing seasons of vegetation and increased vegetation productivity (Piao et al, 2006; Suzuki et al, 2007). However, when temperatures exceed a certain threshold, vegetation growth is inhibited, leading to reduced productivity (Xiao et al, 2023). Solar radiation also makes a certain contribution to vegetation variability (Wang et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

Fu,

Liu,

Qin

et al. 2024

Ecosphere

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Vegetation plays a crucial role in nature, with intricate interactions between it and the geographical environment. The Yangtze River Basin (YRB) refers to the third largest river basin globally and an essential ecological security barrier in China. Monitoring vegetation dynamics in the basin is of profound significance for addressing climate change, soil erosion, and biodiversity loss in the basin's ecosystems. Here, we investigate the spatiotemporal variations of vegetation at both the basin and land cover scales in the YRB from 2000 to 2020. We elucidate the determinants driving the changes and explore future normalized difference vegetation index (NDVI) trends. The results indicate that NDVI in the YRB increased at a rate of 0.0032 year−1 (p < 0.01) over the past 21 years, and it is anticipated to maintain an upward trend in the future. Regions in the upper and middle reaches of the YRB demonstrated higher NDVI, whereas regions in the headwater area and the lower reaches showed lower NDVI. Significant vegetation improvement was primarily concentrated in the central part of the basin, while noticeable vegetation degradation was observed in the eastern region. Temperature and wind speed were identified as the primary controlling factors affecting vegetation greenness. Global‐scale climate oscillations played a significant role in driving periodic variations in NDVI, with La Niña events tending to increase NDVI, while El Niño events hindered its rise. Land cover types were influenced by long‐term interactions between natural factors and human activities, although short‐term vegetation variations might be more affected by the latter. Our findings provide valuable insights into the mechanisms behind vegetation variability driven by multiple variables, and the strong vegetation carbon sink capacity advances the conservation and development of ecosystems.

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Section: Introductionmentioning

confidence: 99%

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

Fu,

Liu,

Qin

et al. 2024

Ecosphere

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“…However, most studies did not consider the nonlinearity of vegetation changes (J. He et al, 2018;Sun & Du, 2017;, which is reported by some studies (Xiao et al, 2023;L. Yang et al, 2021).…”

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confidence: 99%

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

Kong,

Zhang,

Gong

et al. 2023

JGR Biogeosciences

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Net ecosystem productivity (NEP) is important in the carbon cycle. However, the divergent responses of NEP to climate change along topographical gradient, particularly slope, and aspect, is not yet well understood. This study investigates divergent response of NEP to climate change during 1981–2018 along topographical gradient by Ensemble Empirical Mode Decomposition and multiple regression. The results indicate that: (a) NEP increases at low elevations, but first decreases and then increases at mid‐high elevations, and decreases at high elevations. NEP increases with slope. NEP is higher in the east and west but lower in the north and south. (b) With elevation increasing, negative correlation of temperature (TEM) and vapor pressure deficit (VPD), along with the positive correlation of precipitation (PRE) and Solar radiation (SR) strengthens first and then weaken, but PRE's positive correlation strengthens again after 4,000 m, and TEM's negative correlation changes to positive at high elevations. Moreover, soil moisture (SM's) positive correlation strengthens overall. NEP changes are dominated by PRE and VPD below 2,000 m, by TEM and PRE at 2,000–4,000 m, and by PRE and SM above 4,000 m. (c) With slope increasing, the negative correlation of TEM and the positive correlation of SM and SR and their importance strengthen. While PRE's positive correlation and VPD's negative correlation, and their importance weaken. (d) NEP changes are controlled by PRE and VPD in all respect, but the positive relationship of PRE and its importance weakens from north to west, opposite to VPD. Our results highlight the importance of topography for deeply understanding NEP's response to climate changes.

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A study on the monitoring of landslide deformation disasters in Wenxian County, Longnan City based on different time-series InSAR techniques

Zhang,

Yang,

et al. 2024

Nat Hazards

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Quantifying the nonlinear response of vegetation greening to driving factors in Longnan of China based on machine learning algorithm

Cited by 9 publications

References 90 publications

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

Divergent Response of Carbon Sink to Climate Change Along Topographical Gradient in China Based on EEMD Detrending

A study on the monitoring of landslide deformation disasters in Wenxian County, Longnan City based on different time-series InSAR techniques

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