Effects of climate changes on vegetation cover in the northern Tianshan mountains using multiple time scales

Sun, Qin; Liu, Tong; Han, Zhi Quan; Liu, Hua Feng

doi:10.5958/j.2348-7542.15.1.038

Cited by 4 publications

(3 citation statements)

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“…Although numerous studies have monitored the changes in the vegetation NPP [20,21], most of them focused on the linear and monotonic trend with linear regression or the Manner-Kendall trend detecting method [22,23], and its nonlinear characteristics remain unclear. Vegetation changes are nonlinear and non-stationary [23,24]. Therefore, the changes in the vegetation NPP are also nonlinear, characterized by variations of multiple time scales and nonlinear trend.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

et al. 2021

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Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

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Section: Introductionmentioning

confidence: 99%

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

et al. 2021

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“…The land use data were derived from the 30-meter raster dataset furnished by the Resource and Environment Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn). The Chinese Academy of Sciences has classified the LUCC data into categories such as cropland, woodland, grassland, water body, construction land, and unused land, with a comprehensive evaluation accuracy exceeding 94.3% (Sun et al 2014. Digital elevation model (DEM) data was obtained with a spatial resolution of 30 meters from the geospatial data cloud (https://www.gscloud.cn).…”

Section: Data Sourcesmentioning

confidence: 99%

Analysis of spatial and temporal evolution and drivers of cropland in the economic zone of the northern slope of Tianshan mountain

Qiao,

Liu,

Liu

et al. 2023

Environ. Res. Commun.

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The rapid population growth has intensified the need for increased food production, making cropland resources crucial for ensuring food security. Comprehending the evolutionary trends of cropland resources can aid in making well-informed decisions concerning their judicious utilization and contribute to the enhancement of ecological stability. In this investigation, the focus was directed towards the economic zone of the northern slope of Tianshan Mountain, situated in the arid expanse of northwest China. By analyzing land use data from 2000 to 2020, a range of methodologies, including Lorenz curves, local spatial autocorrelation, and Geodetector were employed to investigate the spatial and temporal distribution patterns, evolution, driving forces, heterogeneity, and driving mechanisms of cropland in this region. The findings revealed that the cropland in research area underwent three distinct stages: steady expansion, rapid expansion, and relative stability. The overall annual increase rate was 11.993%, primarily driven by the conversion of grassland and unused land. The spatial distribution of cropland resources was uneven, with concentrations in the central oasis plains in the form of strips and patches. The center of gravity of cropland exhibited a circular movement pattern of ‘northwest-southeast-northwest’. The migration speed followed a sequence of ‘slow-fast-slow’, and the spatial distribution appeared scattered. The main driving forces influencing cropland change included mean annual temperature, elevation, total grain output and agricultural output value. Among these, socioeconomic factors (0.403, 0.430) exerted a greater influence on the spatial distribution of cropland compared to natural factors (0.167). Most interactions between the factors demonstrated non-linear enhancement and two-factor enhancement. The discoveries of this study can assist decision-makers in formulating conservation strategies for cropland based on the current status of cropland resources and drivers in different regions. Furthermore, these findings can stimulate the coordinated development of cropland, water resources, population, and industries, facilitating informed decision-making across various domains.

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“…The terrain is high in the southeast and low in the northwest, and the landscape types from south to north are the medium-alpine mountain belt, foreland mountain belt, oasis, oasis-desert transitional zone and the desert (Luo et al, 2003). There are obvious interactive responses between vegetation cover types and climate change (Sun et al, 2014). Due to the central alluvial plain being suitable for agricultural development, especially since the 21st century, the cultivated land area has been continuously increasing and the urbanization degree has been continuously enhanced, the north slope of Tianshan Mountains has become one of the most conspicuous areas affected by human activities in Xinjiang (Yin et al, 2020).…”

Section: Study Areamentioning

confidence: 99%

Spatio-temporal correlation between human activity intensity and land surface temperature on the north slope of Tianshan Mountains

Chen

Liu²,

Zhang³

et al. 2022

J. Geogr. Sci.

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Research on the spatio-temporal correlation between the intensity of human activities and the temperature of earth surfaces is of great significance in many aspects, including fully understanding the causes and mechanisms of climate change, actively adapting to climate change, pursuing rational development, and protecting the ecological environment. Taking the north slope of Tianshan Mountains, located in the arid area of northwestern China and extremely sensitive to climate change, as the research area, this study retrieves the surface temperature of the mountain based on MODIS data, while characterizing the intensity of human activities thereby data on the night light, population distribution and land use. The evolution characteristics of human activity intensity and surface temperature in the study area from 2000 to 2018 were analyzed, and the spatio-temporal correlation between them was further explored. It is found that: (1) The average human activity intensity (0.11) in the research area has kept relatively low since this century, and the overall trend has been slowly rising in a stepwise manner (0.0024•a -1 ); in addition, the increase in human activity intensity has lagged behind that in construction land and population by 1-2 years. (2) The annual average surface temperature in the area is 7.18 ℃ with a pronounced growth. The rate of change (0.02 ℃•a -1 ) is about 2.33 times that of the world. The striking boost in spring (0.068 ℃•a -1 ) contributes the most to the overall warming trend. Spatially, the surface temperature is low in the south and high in the north, due to the prominent influence of the underlying surface characteristics, such as elevation and vegetation coverage. (3) The intensity of human activity and the surface temperature are remarkably positively correlated in the human activity areas there, showing a strong distribution in the east section and a weak one in the west section. The expression of its spatial differentiation and correlation is comprehensively affected by such factors as scopes of human activities, manifestations, and

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Effects of climate changes on vegetation cover in the northern Tianshan mountains using multiple time scales

Cited by 4 publications

References 0 publications

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Analysis of spatial and temporal evolution and drivers of cropland in the economic zone of the northern slope of Tianshan mountain

Spatio-temporal correlation between human activity intensity and land surface temperature on the north slope of Tianshan Mountains

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