Combined Effects of Meteorological Factors, Terrain, and Greenhouse Gases on Vegetation Phenology in Arid Areas of Central Asia from 1982 to 2021 DOI Creative Commons

Ruikang Tian,

Liang Liu,

Jianghua Zheng

et al.

Land, Journal Year: 2024, Volume and Issue: 13(2), P. 180 - 180

Published: Feb. 3, 2024

Spatiotemporal variations in Central Asian vegetation phenology provide insights into arid ecosystem behavior and its response to environmental cues. Nevertheless, comprehensive research on the integrated impact of meteorological factors (temperature, precipitation, soil moisture, saturation vapor pressure deficit), topography (slope, aspect, elevation), greenhouse gases (carbon dioxide, methane, nitrous oxide) remains insufficient. Utilizing methods such as partial correlation structural equation modeling, this study delves direct indirect influences climate, topography, vegetation. The results reveal that start season decreased by 0.239 days annually, length increased 0.044 end 0.125 annually from 1982 2021 regions Asia. Compared with gases, are dominant affecting interannual phenological changes. Temperature deficits (VPD) have become principal elements influencing dynamic changes phenology. Elevation slope primarily regulate variation VPD whereas aspect mainly affects spatiotemporal patterns precipitation temperature. findings contribute a deeper understanding how various collectively influence vegetation, thereby fostering more profound exploration intricate relationships terrestrial ecosystems

Language: Английский

Application of geographical detector and geographically weighted regression for assessing landscape ecological risk in the Irtysh River Basin, Central Asia DOI Creative Commons
Mingrui Li,

Jilili Abuduwaili,

Wenzhao Liu

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 158, P. 111540 - 111540

Published: Jan. 1, 2024

The exponential growth of human activities has resulted in a substantial increase land use practices that not only modify the characteristics landscape patterns but also pose significant ecological risk (LER), with latter being pivotal for ecosystem conservation and sustainable social development. However, research on LER driving factors Irtysh River Basin (IRB) are limited. Objectively assessing high latitudes within Central Asia (Irtysh Basin) quantitatively identifying environmental its changes holds value ensuring security habitation amidst global change. In this study, spatial autocorrelation analysis method geographically weighted regression (GWR) geographical detector (Geo-Detector) models were utilized to reveal spatiotemporal based use/land cover (LULC) IRB from 1992 2020. findings indicate (1) temporal scale reveals slight increasing trend IRB. (2) distribution is characterized by dominance lower- medium-risk regions, evident positive autocorrelation. (3) pattern influenced various factors, impact temperature geo-detector model. addition, heterogeneity effects major was further obtained using GWR presented herein can serve as scientific references development sustainability safety management arid zones high-latitude cold thus promoting protection countries, enhancing consensus facilitating international cooperation conservation.

Language: Английский

Citations

33
Grassland cover dynamics and their relationship with climatic factors in China from 1982 to 2021 DOI
Liang Liu,

Jianghua Zheng,

Jingyun Guan

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 905, P. 167067 - 167067

Published: Sept. 17, 2023

Language: Английский

Citations

31
Cumulative effects of drought have an impact on net primary productivity stability in Central Asian grasslands DOI
Liang Liu, Jingyun Guan,

Jianghua Zheng

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 344, P. 118734 - 118734

Published: Aug. 10, 2023

Language: Английский

Citations

26
Assessing the impacts of rural depopulation and urbanization on vegetation cover: Based on land use and nighttime light data in China, 2000–2020 DOI Creative Commons

Shengdong Yang,

Xu Yang, Jingxiao Zhang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 159, P. 111639 - 111639

Published: Jan. 27, 2024

Since the 21st century, China has shown dramatic rural depopulation and rapid urbanization, surface vegetation been affected by this urban–rural development pattern. Using remote sensing population data from 2000 to 2020, we investigated spatial temporal evolution of terrestrial under coexistence “rural loss urbanization”. We also analyzed relationship between loss, urbanization area covered four types (forest, grassland, shrubs cropland). found that forests is increasing, shrubs, grasslands, cropland decreasing. Spatially, results Moran index prove characterized autocorrelation. Grasslands are predominantly located on western side Hu line, forests, croplands eastern line. Rural contributes growth forest grassland cover, but inhibits shrub cover. The advance reduces benefits As a result direct effect, reduction cropland, while promotes opposite true for spillover effect. This study helps us better understand direction ecological shifts in migration patterns.

Language: Английский

Citations

15
Changes in Vegetation NDVI and Its Response to Climate Change and Human Activities in the Ferghana Basin from 1982 to 2015 DOI Creative Commons
Heli Zhang, Lu Li, Xiaoen Zhao

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(7), P. 1296 - 1296

Published: April 6, 2024

Exploring the evolution of vegetation cover and its drivers in Ferghana Basin helps to understand current ecological status analyze changes drivers, with a view providing scientific basis for regional environmental management planning. Based on GIMMS NDVI3g meteorological data, spatial temporal characteristics NDVI were analyzed from multiple perspectives help linear trend Mann–Kendall (MK) test methods using arcgis R language analysis module, combined partial correlation coefficients residual impacts climate change human activities 1982 2015. driving forces. The results showed following: (1) growing season an increasing 34-year period, increase rate 0.0044/10a, distribution was significantly different, which high central part country low northern southern parts country. (2) Temperature precipitation simultaneously co-influenced growth season, most temperature contributing spring, summer being negatively phased positively correlated, fall inhibiting growth. (3) effect main reason overall rapid great variations China, namely change, contributed 44.6% season. contribution 62.32% 93.29%, respectively. study suggests that more attention should be paid role restoration inform ecosystem green development.

Language: Английский

Citations

15
Assessing vegetation resilience and vulnerability to drought events in Central Asia DOI
Liangliang Jiang,

Bing Liu,

Hao Guo

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 634, P. 131012 - 131012

Published: March 7, 2024

Language: Английский

Citations

14
The spatial–temporal evolution and influencing factors of the coupling coordination of new-type urbanization and ecosystem services value in the Yellow River Basin DOI Creative Commons
Shengwu Zhang, Chaoqun Huang, Xiaosheng Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112300 - 112300

Published: July 3, 2024

Language: Английский

Citations

14
Characteristics of spatial and temporal dynamics of vegetation and its response to climate extremes in ecologically fragile and climate change sensitive areas – A case study of Hexi region DOI
Jun Zhang, Qingyu Guan, Zepeng Zhang

et al.

CATENA, Journal Year: 2024, Volume and Issue: 239, P. 107910 - 107910

Published: Feb. 21, 2024

Language: Английский

Citations

10
Spatiotemporal changes of vegetation in the northern foothills of Qinling Mountains based on kNDVI considering climate time-lag effects and human activities DOI
Lili Chen,

Zhenhong Li,

Chenglong Zhang

et al.

Environmental Research, Journal Year: 2025, Volume and Issue: unknown, P. 120959 - 120959

Published: Jan. 1, 2025

Language: Английский

Citations

1
From meteorological to agricultural drought: Propagation time and influencing factors over diverse underlying surfaces based on CNN-LSTM model DOI Creative Commons

Junchen Long,

Changchun Xu, Yazhen Wang

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102681 - 102681

Published: June 17, 2024

As global warming intensifies and extreme weather events become more frequent, the severity of drought conditions in China's Xinjiang region has escalated. This exacerbates socio-economic pressures area presents increasingly formidable challenges for future. In response to these challenges, researching phenomena is imperative. study employs Bayesian methods copula functions estimate propagation time. It utilizes a hybrid deep learning model (CNN-LSTM) analyze process its influencing factors across four land cover types: crops, forest land, grassland, unused land. The findings indicate that Cropland experiences longest average time (5.27 months), while forests have shortest duration (4.2 months). Unused grassland exhibit similar durations (4.8 On an annual scale, each type manifests two phases: from January May June December. former phase shows ranging 6 9 months, latter ranges 1 5 months; both demonstrate increasing trend over Seasonally, all Land Cover Types pattern shorter times summer autumn compared with winter spring. Moreover, longer correlates greater disparity between meteorological resultant agricultural severity. analyzing influence on propagation, soil moisture content El Niño-Southern Oscillation(ENSO) were found significantly impact Types, progressively strengthening their years.

Language: Английский

Citations

8