[Effect of seasonal distribution in precipitation on soil nitrogen mineralization in a subtropical forest]

Soil N mineralization is a key process of nutrient cycling in ecosystems. The mechanism of the seasonal distribution of precipitation on soil N mineralization remains unclear. We conducted a precipitation manipulation experiment in a subtropical forest in the middle and lower reaches of the Yangtze River in China from 2020 to 2022, with three treatments, including control (CK), decreased precipitation in the dry season with extremely increased precipitation in the wet season (T1), and decreased precipitation in the dry season with proportionally increased precipitation in the wet season (T2). With in situ resin core method, we explored the effect of seasonal distribution of precipitation on soil N mineralization. The results showed that T1 and T2 significantly decreased dry season net nitrification rate by 57.9% and 72.5% and the net N mineralization rate by 82.5% and 89.6%, respectively, and significantly increased wet season net nitrification rate by 64.3% and 79.5% and net N mineralization rate by 64.2% and 81.1%, respectively. Proportionally increased precipitation in the wet season was more conducive to soil N mine-ralization process than extremely increased precipitation in the wet season. Results of the structural equation model showed that change in seasonal distribution of precipitation could significantly affect soil N mineralization processes in the subtropical forest by changing soil water content, ammonium nitrogen, microbial biomass nitrogen, and soil C:N. Our results had important reference for understanding soil nitrogen cycling and other ecological processes, and were conducive to more accurate assessment on the impacts of future changes in seasonal precipitation pattern on subtropical forest ecosystems.

Synergistic Application of Molecular Markers and Community-Based Microbial Source Tracking Methods for Identification of Fecal Pollution in River Water During Dry and Wet Seasons

It is important to track fecal sources from humans and animals that negatively influence the water quality of rural rivers and human health. In this study, microbial source tracking (MST) methods using molecular markers and the community-based FEAST (fast expectation–maximization microbial source tracking) program were synergistically applied to distinguish the fecal contributions of multiple sources in a rural river located in Beijing, China. The performance of eight markers were evaluated using 133 fecal samples based on real-time quantitative (qPCR) technique. Among them, six markers, including universal (BacUni), human-associated (HF183-1 and BacH), swine-associated (Pig-2-Bac), ruminant-associated (Rum-2-Bac), and avian-associated (AV4143) markers, performed well in the study. A total of 96 water samples from the river and outfalls showed a coordinated composition of fecal pollution, which revealed that outfall water might be a potential input of the Fsq River. In the FEAST program, bacterial 16S rRNA genes of 58 fecal and 12 water samples were sequenced to build the “source” library and “sink,” respectively. The relative contribution (<4.01% of sequence reads) of each source (i.e., human, swine, bovine, or sheep) was calculated based on simultaneous screening of the operational taxonomic units (OTUs) of sources and sinks, which indicated that community-based MST methods could be promising tools for identifying fecal sources from a more comprehensive perspective. Results of the qPCR assays indicated that fecal contamination from human was dominant during dry weather and that fecal sources from swine and ruminant were more prevalent in samples during the wet season than in those during the dry season, which were consistent with the findings predicted by the FEAST program using a very small sample size. Information from the study could be valuable for the development of improved regulation policies to reduce the levels of fecal contamination in rural rivers.