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Sulfatases are commonly divided into three classes: type I, type II, and type III sulfatases. The type III sulfatase, alkylsulfatase, could hydrolyze the primary alkyl sulfates, such as sodium dodecyl sulfate (SDS) and sodium octyl sulfate. Thus, it has the potential application of SDS biodegradation. However, the roles of alkylsulfatase in biological control fungus remain unclear. In this study, an alkylsulfatase gene MaAts was identified from Metarhizium acridum. The deletion strain (ΔMaAts) and the complemented strain (CP) were constructed to reveal their functions in M. acridum. The activity of alkylsulfatase in ΔMaAts was dramatically reduced compared to the wild-type (WT) strain. The loss of MaAts delayed conidial germination, conidiation, and significantly declined the fungal tolerances to UV-B irradiation and heat-shock, while the fungal conidial yield and virulence were unaffected in M. acridum. The transcription levels of stress resistance-related genes were significantly changed after MaAts inactivation. Furthermore, digital gene expression profiling showed that 512 differential expression genes (DEGs), including 177 up-regulated genes and 335 down-regulated genes in ΔMaAts, were identified. Of these DEGs, some genes were involved in melanin synthesis, cell wall integrity, and tolerances to various stresses. These results indicate that MaAts and the DEGs involved in fungal stress tolerances may be candidate genes to be adopted to improve the stress tolerances of mycopesticides. [ABSTRACT FROM AUTHOR]

Accurate estimation for vegetation net primary production (NPP) at high resolution is essential for ecosystem management and at local to global scales. However, no reliable methods are available to achieve fine-resolution estimation. In this study, a new NPP estimation system was developed by integrating high spatial resolution remote sensing images, tree ring measurements, and process-based model CASA. The system was illustrated by estimating the historical NPP of caragana shrublands from 2011 to 2021 in Dingbian County, China. The results showed that: (1) by employing the biomass model and tree ring measurements, an NPP-crown width model was established to enable a large number of samples for calibrating the CASA model on high spatial resolution images without continuous field measurements. The calibrated parameters, including maximum NDVI, minimum NDVI, and maximum light use efficiency, were determined to be 0.415, 0.022 and 0.025, respectively; (2) according to the estimation by the calibrated CASA model, the NPP in Dingbian County revealed an increasing trend from 2011 to 2021, and the NPP in southern hilly and gully regions was significantly higher than the other regions; (3) among the different indices, max temperature of warmest month had a significant negative effect on the NPP of cagarana shrublands, whereas annual precipitation had a positive effect. In the northern and central regions, air temperature predominantly influenced NPP, while in the southern regions, both temperature and precipitation played a joint role. The implementation in this study illustrated that the NPP estimation system could provide reliable NPP with high resolution and efficient to monitor and detect dominant factors affecting NPP for ecosystem management. [ABSTRACT FROM AUTHOR]