The accurate estimation of phenological metrics from satellite data, especially the start of season (SOS), is of great significance to enhance our understanding of trends in vegetation phenology under climate change at regional or global scales. However, for regions with winter snow cover, such as the alpine grasslands on the Tibetan Plateau, the presence of snow inevitably contaminates satellite signals and introduces bias into the detection of the SOS. Despite recent progress in eliminating the effect of snow cover on SOS detection, the mechanism of how snow cover affects the satellite-derived vegetation index (VI) and the detected SOS remains unclear. This study investigated the effect of snow cover on both VI and SOS detection by combining simulation experiments and real satellite data. Five different VIs were used and compared in this study, including four structure-based (i.e., NDVI, EVI2, NDPI, NDGI) VIs and one physiological-based (i.e., NIRv) VI. Both simulation experiments and satellite data analysis revealed that the presence of snow can significantly reduce the VI values and increase the local gradient of the growth curve, allowing the SOS to be detected. The bias in the detected SOS caused by snow cover depends on the end of the snow season (ESS), snow duration parameters, and the snow-free SOS. An earlier ESS results in an earlier estimate of the SOS, a later ESS results in a later estimate of the SOS, and an ESS close to the snow-free SOS results in small bias in the detected SOS. The sensitivity of the five VIs to snow cover in SOS detection is NDPI/NDGI < NIRv < EVI2 < NDVI, which has been verified in both simulation experiments and satellite data analysis. These findings will significantly advance our research on the feedback mechanisms between vegetation, snow, and climate change for alpine ecosystems.

Biocarriers are a key factor in moving bed biofilm reactors (MBBR) for domestic wastewater treatment and studies targeting biocarriers can be explored in more depth. In this study, two different types of biocarriers, namely anaerobic microbial carriers (AMC) and porous biogels (PBG), were used to treat real domestic wastewater and acted on a lab-scale tertiary MBBR system. The effects of the start-up process, water quality degradation, secondary start-up, and organic loading rate (OLR) on MBBR performance at room temperature (19–24 °C) and the same filling ratio (40%) were investigated, as well as the calculation of sludge yield. The results showed that the AMC–PBG/MBBR biological treatment process could complete the start-up process quickly in a short time and the OLR was finally determined to be 1.5 kgCOD/(m³·d). In this case, the system was able to operate stably and complete the secondary start-up relatively quickly, with 80% and 95% removal of COD and NH₄⁺-N, respectively. The biofilm was characterized by scanning electron microscopy (SEM) and high-throughput sequencing which revealed the changes of microorganisms in the biofilm during operation, among which the dominant phyla were Euryarchaeota and Proteobacteria. Finally, the apparent production of process sludge was monitored and calculated to be 0.043 kgMLSS/kgCOD which is a significant reduction in sludge compared to the conventional activated sludge method. These conclusions provide valuable information for the full-scale treatment of domestic wastewater.

The spatial and temporal distribution of the archaeal community and its driving factors in the sediments of large-scale regulated rivers, especially in rivers with cascade hydropower development rivers, remain poorly understood. Quantitative PCR (qPCR) and Illumina MiSeq sequencing of the 16S rRNA archaeal gene were used to comprehensively investigate the spatiotemporal diversity and structure of archaeal community in the sediments of the Lancang River cascade reservoirs (LRCR). The archaeal abundance ranged from 5.11×10⁴to 1.03×10⁶16S rRNA gene copies per gram dry sediment and presented no temporal variation. The richness, diversity, and community structure of the archaeal community illustrated a drastic spatial change.ThaumarchaeotaandEuryyarchaeotawere the dominant archaeal phyla in the sediments of the cascade rivers, andBathyarchaeotawas also an advantage in the sediments. PICRUSt metabolic inference analysis revealed a growing number of genes associated with xenobiotic metabolism and carbon and nitrogen metabolism in downstream reservoirs, indicating that anthropogenic pollution discharges might act as the dominant selective force to alter the archaeal communities. Nitrate and C/N ratio were found to play important roles in the formation of the archaeal community composition. In addition, the sediment archaeal community structure was also closely related to the age of the cascade reservoir and hydraulic retention time (HRT). This finding indicates that the engineering factors of the reservoir might be the greatest contributor to the archaeal community structure in the LRCR.