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Qinghai-Tibet Plateau and Gansu Corridor of China with distinct geographic and climatic conditions are remote and less disturbed by humans, in which are likely to find some new strains of fungal entomopathogens against B-biotype whiteflies that is a very important invading pest worldwide. In this research, nineteen strains among six species of entomogenous fungi were isolated from the soil samples collected from 32 locations in Qinghai-Tibet Plateau and Gansu Corridor. From the data of isolation rates, it was indicated that the good biodiversity of entomogenous fungi was found in the soil covered good vegetations. On the contrary, no strains were isolated from the desert areas. In addition, the dominant species, Isaria fumosorosea and Metarhizium anisopliae var. anisopliae in the Qinghai-Tibet Plateau are different from the strains of other places based on ITS genetic homology analysis. It was verified that the Qinghai-Tibet Plateau area was less disturbed by human, and the fungi in this place exchanged less compared with other regional species. All of these strains showed the pathogenicity against the B-biotype whitefly with the mortality of more than 30%. However, a few strains of Paecilomyces lilacinus, Lecanicillium psalliotae, Aspergillus ustus, I. fumosorosea and M. anisopliae var. anisopliae had better virulence with LC50s of 0.36–26.44×106 spores/mL on post-treatment day 6–7. Especially, the L. psalliotae strain LpTS01 was the greatest virulence with LC50 of 0.36×106spores/mL and LT50 of 4.23d. Our research thus presents some new insights to discover new entomopathogenic fungal strains used for B-biotype whitefly biocontrol. [ABSTRACT FROM AUTHOR]

PM2.5 is closely linked to both air quality and public health. Many studies have used models combined with remote sensing and auxiliary data to inverse a large range of PM2.5 concentrations. However, the data's spatial resolution is limited. and better results might have been obtained if higher resolution data had been used. Therefore, this paper establishes a geographical and temporal weighted regression model (GTWR) and estimates the PM2.5 concentration in Xinjiang from 2015 to 2020 using 1 km resolution MCD19A2 (MODIS/Terra+Aqua Land Aerosol Optical Thickness Daily L2G Global 1km SIN Grid V006) data and 9 auxiliary variables. The findings indicate that the GTWR model performs better than the simple linear regression (SLR) and geographically weighted regression (GWR) models in terms of accuracy and feasibility in retrieving PM2.5 concentrations in Xinjiang. Simultaneously, by combining the GTWR model with MCD19A2 data, a spatial distribution map of PM2.5 with better spatial resolution can be obtained. Next, the regional distribution of annual PM2.5 concentrations in Xinjiang is consistent with the terrain from 2015 to 2020. The low value area is primarily found in the mountainous area with higher terrain, while the high value area is primarily in the basin with lower terrain. Overall, the southwest is high and the northeast is low. In terms of time change, the six-year PM2.5 shows a single peak distribution with 2016 as the inflection point. Lastly, from 2015 to 2020, the seasonal average PM2.5 concentration in Xinjiang has a significant difference, thereby showing winter (66.15μg/m3)>spring (52.28μg/m3)>autumn (40.51μg/m3)>summer (38.63μg/m3). The research shows that the combination of MCD19A2 data and GTWR model has good applicability in retrieving PM2.5 concentration., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Quan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)