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The soil freeze-thaw phenomenon is one of the most distinguishing peculiarities of the land surface processes over the Qinghai-Tibetan Plateau. By utilizing soil temperature/moisture and air temperature data from the GLDAS-NOAH product, 4 observing networks and 10 meteorological stations over the Qinghai-Tibetan Plateau, the spatio-temporal distribution of the start/end date and the duration of soil freezing and their relationships with air temperature and altitude were investigated with the analytical methods of linear regression model, correlation analysis, sliding t -test and Mann-Kendall test. As a result, the spatial distribution of top-layer soil freeze-thaw processes was characterized by a trend of delaying freezing and advancing thawing from the northwest to the southeast throughout the Qinghai-Tibetan Plateau. Moreover, in the period 1948–2019, the begin date of soil freezing was delayed at a rate of 1.2 d/10a (p-lev <0.0001, R2 = 0.40), and the end date of the soil freezing was advanced at a rate of 0.5 d/10a (p-lev = 0.105, R2 = 0.04). The duration of the soil freeze was shortened with a rate of 2.1 d/10a (p-lev <0.0001, R2 = 0.23) in the southern Changtang but 0.4 d/10a (p-lev <0.0001, R2 = 0.47) in Qinghai and the southern Tibet Plateau. Additionally, the start date of the soil freeze is to be delayed by 2.8 days (p-lev <0.0001, R2 = 0.53), and the end date of the soil freeze is to be advanced by 3.6 (p-lev <0.0001, R2 = 0.61) days as the air temperature rises by 1.0 °C. In the high cold climatological zone on the Qinghai-Tibetan Plateau, there is a trend toward earlier start date of soil freezing by 9.9 days (p-lev <0.0001, R2 = 0.36), and later end date of soil freezing by 14.4 days (p-lev <0.0001, R2 = 0.56) as the altitude increases by 1000.0 m. Furthermore, the seasonal variations of soil temperature and moisture were significantly different from typical strong and weak freezing years, which were defined according to the duration of soil freezing period. These results are of great significance for understanding the soil freeze-thaw process and its variation over the Qinghai-Tibetan Plateau. • The soil freeze-thaw process over the Qinghai-Tibetan Plateau is analyzed by utilizing observing and reanalysis data. • Notable variability of the soil freeze-thaw process was observed at spatio-temporal scales. • The soil freeze-thaw process over the Qinghai-Tibetan Plateau is closely related to the air temperature and altitude. • Soil water and heat vary with intensity of freezing over the Qinghai-Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Changes in the habitats of species can provide insights into the impact of climate change on their habitats. Species in the genus Morina (Morinoideae) are perennial herbaceous plants that are mainly distributed in the South Asian Mountains and Eastern Mediterranean. In China, there are four species and two varieties of this genus distributed across the Yunnan, Sichuan, Qinghai, and Gansu provinces. This study used the optimal MaxEnt model to simulate past, current, and future potentially suitable habitats of Morina kokonorica and Morina chinensis. Seventy data of M. kokonorica occurrences and 3 of M. chinensis were used in the model to predict potentially suitable habitats. The model prediction results indicated that both M. kokonorica and M. chinensis exhibited trends of northward migration to higher latitudes and westward migration along the Himalayas to higher elevations, suggesting that the northern valleys of Hengduan Mountains and northern and eastern parts of the Himalayas were potential refugia for M. kokonorica, and the potential refugia for M. chinensis was located in the eastern part of Qinghai‐Tibet Plateau. The results of this niche analysis showed that the two species had higher levels of interspecific competition and that the environmental adaptability of M. chinensis was stronger. This research could help further understand the response pattern of Morina to environmental change, to understand the adaptability of species to the environment, and promote the protection of species. [ABSTRACT FROM AUTHOR]

Potassium is the active element of potash fertilizer, its concentration determines the quality of the product. Self-absorption occurs in laser-induced breakdown spectroscopy (LIBS) analysis of potash, since potassium is the major element with a concentration that can reach the level of 95 wt.%. The present work simulated an online analysis of potassium in potash with a laboratory setup, LIBS spectra were recorded on 27 potash samples collected from a factory in Qinghai province in China with different potassium concentrations in the range from 90 to 97 wt.%. The self-absorption correction was applied to the spectra for K I 404.4 nm and K I 693.9 nm lines. Multivariate regression based on machine learning were processed with the self-absorption corrected spectra in order to get a better potassium determination performance compared to that with uncorrected spectra. The results show the effectiveness of self-absorption correction in the improvement of the analytical performance. The obtained multivariate regression model presents a satisfactory performance to fill the requirements of the aimed application of online and real-time analysis of potash on a product transportation belt in a production site with respect to the specific requirements of the related current national standards. [ABSTRACT FROM AUTHOR]