Data-driven assessment of soil total nitrogen on the Qinghai-Tibet Plateau.

The investigation of soil total nitrogen (STN) holds significant importance in the preservation and sustainability of Earth's ecosystems. The Qinghai-Tibet Plateau (QTP), renowned as the world's most expansive plateau and characterized by its exceptionally delicate ecosystem, demands an in-depth exploration of its STN content. In this study, we use a machine learning approach to extrapolate point-scale measured STN stocks to the entire QTP and calculated STN storage from 0 to 2 m. Our results show that the XGB algorithm performs well in modeling STN despite variations in simulation accuracy for specific depth ranges. The spatial distribution of STN across the QTP exhibits pronounced heterogeneity, especially for the 0-50 cm soil layer, with relatively higher STN stocks in the southeast and lower stocks in the northwest of QTP. The vertical distribution reveals a gradual decrease in STN storage with increasing depth. The 0-50 cm soil layer holds the highest STN stocks, averaging around 0.78 kg/m2, which is almost the sum of STN stocks in the 50-100 cm and 100-200 cm soil layers. Meanwhile, the STN stocks are smaller in permafrost zone than that in non-permafrost zone. We also investigate the impact factors that control the spatiotemporal distribution of STN. It indicates that vegetation, precipitation, temperature, and elevation are the major factors for STN distribution, while physical properties of the soil have a relatively smaller impact. These findings are crucial for understanding the distribution and evolution of STN on the QTP.

Simulation and prediction of changes in maximum freeze depth in the source region of the Yellow River under climate change.

The source region of the Yellow River (SRYR) is located at the edge of the Qinghai-Tibet Plateau (QTP), which is completely covered by frozen ground. Due to relatively higher temperatures, the frozen ground in the SRYR is particularly fragile and susceptible to the impacts of global climate change. This study discusses the maximum freeze depth (MFD) of frozen ground in the SRYR, including analysis of measured data at the stations, comparison of simulation models, and projection of future changes. The MFD of frozen ground recorded at nine meteorological stations within the SRYR ranged from a few tens of centimeters to more than two meters. The decreasing trend of MFD was recorded except for a few stations from 1997 to 2017, with a maximum rate of -22.8 cm/10a. The decreasing rate of MFD for the whole SRYR from 1997 to 2017 is -10.8 cm/10a. Furthermore, we assessed the performance of three simulation methods: Stefan equation, multiple linear regression, and BP neural network predicting the MFD using the measured data. The Stefan equation exhibited limited accuracy in simulating the MFD, while the BP neural network demonstrated remarkable performance, with a correlation coefficient R of 0.949. In addition, we evaluated the applicability of different global climate models (GCMs) in the SRYR, identified the optimal model, and combined it with the BP neural network model to predict future MFD change. Among the five climate models, the BCC-CSM2-MR model and ensemble model fit the measured precipitation and air temperature well. The projected results based on the BCC-CSM2-MR model and ensemble model indicate that the MFD of different stations in the SRYR and the whole region will still tend to decrease in the future. Our results contribute to understanding the response of cold region frozen ground to climate change and provide available data.

Changes in permafrost spatial distribution and active layer thickness from 1980 to 2020 on the Tibet Plateau.

The Tibetan Plateau (TP) is experiencing extensive permafrost degradation due to climate change, which seriously threatens sustainable water and ecosystem management in the TP and its downstream areas. Understanding the evolution of permafrost is critical for studying changes in the water cycle, carbon flux, and ecology of the TP. In this study, we mapped the spatial distribution of permafrost and active layer thickness (ALT) at 1 km resolution for each decade using empirical models and machine learning methods validated with borehole data. A comprehensive comparison of model results and validation accuracy shows that the machine learning method is more advantageous in simulating the permafrost distribution, while the ALT simulated by the empirical model (i.e., Stefan model) better reflects the actual ALT distribution. We further evaluated the dynamics of permafrost distribution and ALT from 1980 to 2020 based on the results of the better-performing models, and analyzed the patterns and influencing factors of the changes in permafrost distribution and ALT. The results show that the permafrost area on the TP has decreased by 15.5 %, and the regionally average ALT has increased by 18.94 cm in the 2010s compared to the 1980s. The average decreasing rate of permafrost area is 6.33 × 104 km2 decade-1, and the average increasing rate of ALT is 6.31 cm decade-1. Permafrost degradation includes the decreasing permafrost area and the thickening active layer mainly related to the warming of the TP. Spatially, permafrost area decrease is more susceptible to occur at lower latitudes and lower altitudes, while ALT increases more dramatically at lower latitudes and higher altitudes. In addition, permafrost is more likely to degrade to seasonally frozen ground in areas with deeper ALT.

[Clinical study on treatment of HIV infected persons based on viral load detection and CD4+ T lymphocyte counting].

OBJECTIVE: To study the usage of viral load and CD4+ cell count methods in evaluating the effects of clinical treatment in HIV infected people. METHODS: Totally 73 cases of HIV infected persons were studied with clinical observation and laboratory examinations, six cases were treated with cocktail therapy, 36 cases with chinese herbs and the other 31 cases were untreated. RESULTS: The results indicated that the viral load levels in cocktail therapy group were significantly lower than the other two groups within 3 months and then kept at very low level. The CD4+ T lymphocyte levels showed a significant increase after 3 months and kept rising up. The chinese herb group, however, had no significant difference in viral load level and CD4+ T lymphocyte level as compared with untreated group. But in clinical observation chinese herbs showed the effect of improving clinical status in some cases. CONCLUSIONS: The authors conclude that the viral load and CD4+ count are efficient methods in clinical evaluation of HIV treatment, especially in routine anti-HIV therapy. As for the chinese herbs treatment, these two monitors did not reflect changes in clinical status.