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Climate change and anthropogenic activities pose a formidable challenge to regional ecological systems, necessitating robust research frameworks to assess ecological environment quality. The dynamic, quantitative evaluation of such quality serves as a cornerstone for strategizing ecological protection measures and fostering ecological civilization. Leveraging MODIS data spanning from 2001 to 2020, this study harnesses the power of the Google Earth Engine (GEE) platform and the remote sensing ecological index (RSEI) as a pivotal evaluation tool to conduct a comprehensive appraisal of the ecological health of the southern slope of the Qilian Mountains. Employing Sen's trend analysis and the Mann-Kendall (M-K) test, we delineate the spatial evolution patterns of the RSEI, offering insights into its temporal dynamics. Furthermore, by integrating geological information mapping with Pearson correlation analysis, we delve into the intricate interplay between natural environmental factors and human activities that shape RSEI variations. Our findings revealed several salient points: Firstly, the ecological quality of the southern slope of the Qilian Mountains exhibited pronounced spatial heterogeneity, with the vicinities of the Datong, Heihe, Beida, and Babao River basins boasting exceptional ecological quality, in contrast to the relatively degraded conditions in higher-elevation areas. Temporally, from 2001 to 2020, the RSEI index fluctuated within a range of 0.62 to 0.70, signifying an overall enhancement in ecological environment quality, a testament to the vigorous implementation of ecological restoration projects in recent years. The average annual RSEI value stood at 0.66, indicative of stability amidst modest fluctuations, though peripheral regions experienced notable RSEI volatility due to climatic shifts. Encouragingly, over 80% of the southern slope experienced ecological improvement, with a mere 11% experiencing slight degradation, suggesting a promising trajectory for future ecological enhancement. However, caution must be exercised against the risk of unsustainable improvement. Temperature, precipitation, and human interventions all contributed to RSEI variations, with temperature exerting a more pronounced influence than precipitation. Notably, human activities correlated positively with RSEI, underscoring the significance of human stewardship in ecological improvement. This research fills a critical gap in the long-term, dynamic monitoring of the ecological environment on the southern slope of the Qilian Mountains, providing a robust foundation for targeted ecological governance and fostering green development initiatives in this vital region.
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http://dx.doi.org/10.13227/j.hjkx.202406195 | DOI Listing |
Nat Ment Health
August 2025
Department of Psychiatry, Washington University School of Medicine.
Psychotic-like experiences (PLEs) may arise from genetic and environmental risk leading to worsening cognitive and morphometry metrics over time, which in turn lead to worsening PLEs. Analyses used three waves of unique longitudinal Adolescent Brain Cognitive Development Study data (ages 9-13) to test whether changes in cognition and global morphometry metrics attenuate associations between genetic and environmental risk with persistent distressing PLEs. Multigroup univariate latent growth models examined three waves of cognitive metrics and global morphometry separately for three PLE groups: persistent distressing PLEs (n=356), transient distressing PLEs (n=408), and low-level PLEs (n=7901).
View Article and Find Full Text PDFBiology (Basel)
July 2025
College of Geographical Sciences, Qinghai Normal University, Xining 810008, China.
Understanding the distribution patterns of soil bacterial community structure and diversity across different forest types is essential for elucidating the mechanisms underlying microbial community assembly and its ecological drivers, particularly under the pressures of climate change. In this study, we examined six forest types-including four monocultures and two mixed-species stands-to systematically evaluate the structural composition, diversity metrics, and functional potential of soil bacterial communities. Significant differences in microbial structure and functional composition were observed among forest types.
View Article and Find Full Text PDFInt J Public Health
September 2025
National Institute of Public Health, Faculty of Health Sciences, University of Southern Denmark, Copenhagen, Denmark.
Objectives: This study aimed to examine trends in relative and absolute social inequality in overweight/obesity among Danish infants born between 2002 and 2022.
Methods: The study applied yearly cross-sectional data on infants' weight and length at age 6-10 months, n = 63,100. Data was linked with parental education from population registers.
J Behav Addict
September 2025
1Department of Psychology and Research Center of Adolescent Psychology and Behavior, School of Education, Guangzhou University, Guangzhou, China.
Background And Aims: Problematic social media use (PSMU) is a concerning public health issue among adolescents. Existing literature has paid attention to the role of singular family risk on PSMU, but how cumulative family risks affect the trajectory of PSMU needs to be further explored.
Methods: The current study employed a five-wave longitudinal design that lasted for three years (each time interval: 6, 6, 12, and 12 months) to reveal the longitudinal mechanism between cumulative family risks and the trajectory of PSMU, examining the mediating roles of escape and relationship motivations.
Ying Yong Sheng Tai Xue Bao
July 2025
Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation (Ministry of Education), Qinghai Normal University, Xining 810008, China.
The southern slope of the Qilian Mountains is a typical mountain ecosystem. To understand the vegetation phenological response mechanisms under the interaction between complex terrain and climate change is of significance in revealing ecological adaptability laws. Based on MODIS NDVI data from 2002 to 2020, combined with topographic and meteorological datasets, we used correlation analysis and structural equation modeling to quantitatively assess the role of topography in mediating vegetation phenological responses to climate change.
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