Ecological Responses to Climate Change and Human Activities in the Arid and Semi-Arid Regions of Xinjiang in China

Zhou, Yihang; Li, Yaoming; Li, Wei; Li, Feng; Xin, Qinchuan

doi:10.3390/rs14163911

Cited by 14 publications

(4 citation statements)

References 67 publications

(153 reference statements)

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“…Xinjiang is situated in the northwestern part of China, covering approximately onesixth of the country's total land area. Due to its inland location and distance from oceans, the region experiences a typical temperate continental arid and semi-arid climate [31]. As the Chinese province with the largest expanse of desert, it is characterized by desert soils and inland saline soils [32].…”

Section: Study Areamentioning

confidence: 99%

Quantifying the Spatial Distribution Pattern of Soil Diversity in Southern Xinjiang and Its Influencing Factors

Luo,

Fan,

et al. 2024

Sustainability

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Soil diversity plays an important role in maintaining ecological balance and ensuring the sustainability of the land. Xinjiang is a typical arid and semi-arid region of China, and the study of Xinjiang soils is significant for understanding soil properties in all such environments. This study applied the moving window technique and the species–area curve model from ecology to establish optimal analysis windows, calculate landscape pattern indices, and reveal soil distribution characteristics in Southern Xinjiang. Additionally, we used geographic detectors to identify the primary influencing factors in different geomorphic regions. The results indicate a positive correlation between soil richness and area in the Southern Xinjiang region. The Tarim Basin, despite being the largest area, shows the lowest diversity and evenness indices. Overall, mountainous areas have higher soil evenness when compared to basins. In terms of natural factors, temperature, precipitation, and topography play a crucial role in the variation of soil diversity in mountainous areas, while parent material has a greater influence in the basin regions. The characteristics of soil diversity vary by region and are influenced by the interactive effects of various natural factors. However, the impact of human activities also requires consideration. The low evenness poses a greater challenge for soil restoration in the basin regions. Soil conservation efforts in arid regions are of paramount importance. The research findings can provide valuable insights for the development of sustainable agriculture, soil conservation, and for addressing climate change challenges in arid regions.

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Section: Study Areamentioning

confidence: 99%

Quantifying the Spatial Distribution Pattern of Soil Diversity in Southern Xinjiang and Its Influencing Factors

Luo,

Fan,

et al. 2024

Sustainability

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show abstract

“…Semi-arid and arid areas [34] refer to regions where the ratio of average annual precipitation to annual potential evaporation is between 0.2 and 0.5. The characteristics of semi-arid and arid areas are low rainfall, scarce water resources, and grassland vegetation as the main natural vegetation.…”

Section: Study Areamentioning

confidence: 99%

RLNformer: A Rainfall Levels Nowcasting Model Based on Conv1D_Transformer for the Northern Xinjiang Area of China

Liu,

Chen

2023

Water

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Accurate precipitation forecasting is of great significance to social life and economic activities. Due to the influence of various factors such as topography, climate, and altitude, the precipitation in semi-arid and arid areas shows the characteristics of large fluctuation, short duration, and low probability of occurrence. Therefore, it is highly challenging to accurately predict precipitation in the northern Xinjiang area of China, which is located in the semi-arid and arid climate region. In this study, six meteorological stations in the northern Xinjiang area were selected as the research area. Due to the high volatility of rainfall in this area, the rainfall was divided into four levels, namely, “no rain”, “light rain”, “moderate rain”, and “heavy rain and above”, for rainfall level prediction. In order to improve the prediction performance, this study proposed a rainfall levels nowcasting model based on Conv1D_Transformer (RLNformer). Firstly, the maximum information coefficient (MIC) method was used for feature selection and sliding the data, that is, the data of the first 24 h were used to predict the rainfall levels in the next 3 h. Then, the Conv1D layer was used to replace the word-embedding layer of the transformer, enabling it to extract the relationships between features of time series data and allowing multi-head attention to better capture contextual information in the input sequence. Additionally, a normalization layer was placed before the multi-head attention layer to ensure that the input data had an appropriate scale and normalization, thereby reducing the sensitivity of the model to the distribution of input data and helping to improve model performance. To verify the effectiveness and generalization of the proposed model, the same experiments were conducted on the Indian public dataset, and seven models were selected as benchmark models. Compared with the benchmark models, RLNformer achieved the highest accuracy on both datasets, which were 96.41% and 88.95%, respectively. It also had higher accuracy in the prediction of each category, especially the minority category, which has certain reference significance and practical value.

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“…Understanding the relationship between PM2.5 and LAI is important for understanding the sensitivity of vegetation to aerosol radiative forcing and developing strategies to mitigate the effects of climate change on vegetation (Zhang et al, 2020). Most of studies utilized land use change analysis to reflect the influence of human activities on LAI (Mao et al, 2013;Zeng et al, 2017;Zhu et al, 2017;Buitenwerf et al, 2018;Wong et al, 2018;Peng et al, 2021;Zhang et al, 2021;Zhou et al, 2022). Few studies quantifying impacts of human activities on changes of LAI with PM2.5.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal analysis of LAI using multisource remote sensing data for source region of Yellow River Basin

Zhang,

Hou,

Han

et al. 2024

Front. Environ. Sci.

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Introduction: The Leaf area index (LAI) of source region of yellow river basin is an important indicator for environmental sustainability. Most studies focus on the trend of LAI in Yellow River Source Region (YRSR) in accordance with both climate change and human actives. However, quantifying the effect of human activities on LAI is difficult but urgently needed. Specifically, Particle Matter 2.5 (PM2.5) can be an indirect indicator of human activities.Methods: In this study, we explored the potential dependence of LAI on temperature, precipitation, and PM2.5 in different land cover types in YRSR with linear regression and correlation analysis.Results: Over the period of 2001–2020, the climate in the region has been warming and becoming more humid, leading to overall improvements in vegetation. The mean LAI values varied between seasons, with summer having the highest and winter having the lowest LAI. The analysis of the LAI trends revealed that the mean LAI has been steadily increasing, particularly in the eastern region. The correlation analysis showed a significant positive correlation between annual average LAI and both annual precipitation and temperature, indicating that temperature has a greater impact on vegetation growth. The analysis of land cover types showed that most types exhibited a unimodal trend in LAI throughout the year, except for construction land which had two distinct peaks. Human-induced land cover change had a small impact on the overall increase in LAI. Furthermore, the interannual variation of PM2.5 showed a downward trend, with a strong correlation with the trend of LAI. Additionally, multiple linear regression analysis and residual trend analysis showed that climate factors had the strongest impact on LAI.Conclusion: The study highlights the spatiotemporal variations of LAI in the YRSR and its correlation with climatic and human factors. The findings suggest that climate change plays a crucial role in the vegetation growth and LAI in the region.

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Ecological Responses to Climate Change and Human Activities in the Arid and Semi-Arid Regions of Xinjiang in China

Cited by 14 publications

References 67 publications

Quantifying the Spatial Distribution Pattern of Soil Diversity in Southern Xinjiang and Its Influencing Factors

Quantifying the Spatial Distribution Pattern of Soil Diversity in Southern Xinjiang and Its Influencing Factors

RLNformer: A Rainfall Levels Nowcasting Model Based on Conv1D_Transformer for the Northern Xinjiang Area of China

Spatio-temporal analysis of LAI using multisource remote sensing data for source region of Yellow River Basin

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