Spatial distribution characteristics of soil heavy metals in Sabao Chaqu watershed of Tuotuo river, Qinghai-Tibet Plateau based on geographic detector.

The Qinghai-Tibet Plateau belongs to the area of extremely fragile environment and sensitive to human activities. In recent years, more and more human interference has been detected in this area. In this study, 128 surface soil samples were collected from the Sabao Chaqu watershed of the Tuotuo river at the source of the Yangtze River on the Qinghai-Tibet Plateau. The soil pollution status and spatial distribution characteristics of Cd, Hg, As, Cu, Pb, Cr, Zn and Ni were evaluated by soil accumulation index, enrichment factor, pollution index and geographical detector. The results showed that the average contents of As, Cd, Pb and Zn in the study area were 1.2-3.64 times higher than soil background values of Tibet, while the contents of Hg, Cr, Cu and Ni were lower than the background values, while the average content of As was higher than the soil pollution risk screening value (GB15618-2018), and the pollution index showed that As was in a low pollution state, while the other 7 heavy metals were in a safe state. There were significant differences in the spatial distribution of 8 heavy metals and there was a significant correlation with soil properties and distance factors. Factor detection showed that natural factors had the strongest explanatory power to the contents of As, Cd, Cr, Cu and Ni, distance from the lake and soil Sc content had the strongest explanatory power to Hg content, and anthropogenic factors had the strongest explanatory power to Pb content. Interaction detection revealed that the q values of the strongest interaction explanatory power for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 2.81, 4.30, 1.26, 2.47, 2.33, 1.59, 6.37, and 5.08 times higher than their strongest factor detection explanatory power, respectively. The interaction between anthropogenic factors and other factors has an important influence on the spatial differentiation of heavy metals in the study area. Risk detection showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were the highest in the subregions of MgO, TS, Sc, X6, X13, MgO, TN and X4, respectively. Comprehensive study shows that the spatial differentiation of As, Cd, Cr, Cu, Ni and Zn is mainly affected by natural factors, but there are also some anthropogenic factors, the spatial differentiation of Hg is affected by both natural factors and atmospheric deposition, and the spatial distribution characteristics of Pb are mainly affected by anthropogenic factors.

Spatial differentiation of soil nutrients and their ecological chemometrics based on geographic detector in National Agricultural Park of Tangchang, Southwest China.

In order to analyze the spatial variability of soil nutrients and their ecological chemometrics in Tangchang Town, National Agricultural Park, 20 influencing factors were selected: soil pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni, Se, elevation, slope, aspect, land use type, distance from industrial land, distance from commercial land, distance from railway, distance from residential area, distance from highway and distance from river. The effects of various influencing factors on the spatial variability of total organic carbon (TOC), total nitrogen (N), total phosphorus (P), total potassium (K) and ecological stoichiometry were analyzed by means of geographic detector. The results showed that average contents of soil TOC, N, P and K in the study area are 10.24 g kg-1, 1.33 g kg-1, 1.14 g kg-1 and 23.60 g kg-1, respectively, and there were significant differences in the spatial distribution of soil nutrients and their eco-stoichiometry in the study area, and TOC, N, P, K, C/N, C/P, C/K, N/P, N/K and P/K has a significant correlation with each other and most correlation coefficients are above 0.5 or below -0.5. Factor detection showed that soil properties, distance from railway and distance from residential area had the most significant explanatory power to the spatial heterogeneity of soil nutrients and eco-stoichiometry. Interaction detection showed that the interaction between soil properties with other factors was the most important factor affecting the spatial differentiation of soil nutrients and their ecological chemometrics, and elevation, distance from railway and distance from residential area were also important factors. Risk detection showed that the differences of soil nutrients and their ecological stoichiometry were most significant in the subregions of soil properties (pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni and Se).

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.