Stormwater runoff has been known to cause increases in bacterial loadings in urban streams. However, little is known about its impacts on antibiotic resistance genes (ARGs) in urban watersheds. This study was performed to characterize the ARG composition of various environmental compartments of an urban watershed and to quantify their contributions of microbes and ARGs to an urban stream under wet weather conditions. Shotgun metagenomic results showed that the ARG abundance in wet weather flow was significantly higher than in base flow. Multidrug resistance genes were the most common ARG type across environmental samples. Vancomycin resistance genes were abundant in embankment soil and street sweeping samples. Analyses using SourceTracker estimated storm drain outfall water to be the biggest contributor of microbes (54-57%) and ARGs (82-88%) in the urban stream during wet weather flows. Furthermore, results on street sweepings showed that wash-off from streets was the biggest known contributor of microbes (41-45%) and ARGs (92-96%) in storm drain outfall water. Pantoea and Pseudomonas were associated with the highest numbers of ARGs and were most abundant in stormwater-related samples. Results from this study can advance our knowledge about ARGs in urban streams, an important medium linking environmental ARGs to the general public.

Psychology researchers have long attempted to identify educational practices that improve student learning. However, experimental research on these practices is often conducted in laboratory contexts or in a single course, which threatens the external validity of the results. In this article, we establish an experimental paradigm for evaluating the benefits of recommended practices across a variety of authentic educational contexts—a model we call ManyClasses. The core feature is that researchers examine the same research question and measure the same experimental effect across many classes spanning a range of topics, institutions, teacher implementations, and student populations. We report the first ManyClasses study, in which we examined how the timing of feedback on class assignments, either immediate or delayed by a few days, affected subsequent performance on class assessments. Across 38 classes, the overall estimate for the effect of feedback timing was 0.002 (95% highest density interval = [−0.05, 0.05]), which indicates that there was no effect of immediate feedback compared with delayed feedback on student learning that generalizes across classes. Furthermore, there were no credibly nonzero effects for 40 preregistered moderators related to class-level and student-level characteristics. Yet our results provide hints that in certain kinds of classes, which were undersampled in the current study, there may be modest advantages for delayed feedback. More broadly, these findings provide insights regarding the feasibility of conducting within-class randomized experiments across a range of naturally occurring learning environments.

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Investigating sources of microbial contamination in urban streams, especially when there are no contributions from combined sewer overflows or sewage effluent discharges, can be challenging. The objectives of this study were to identify the sources of microbes in an urban stream and quantify their relative contributions to the microbial community in the stream under dry and wet weather conditions. A microbial source tracking method relying on the 16S rRNA gene was used to investigate the microbial communities in water samples of an urban stream (i.e., from 11 dry and 6 wet weather events), as well as in streambed sediment, soils, street sweepings, sanitary sewage, an upstream lake, and feces of animals and birds collected between 2013 and 2015. The results showed that the levels in the stream were significantly higher in wet weather flow than in dry weather flow. The upstream lake contributed approximately 93% of the microbes in dry weather flows. Water discharged from storm drain outfalls was the biggest source of microbes in wet weather flows, with a median contribution of approximately 90% in the rising limb and peak flow and about 75% in the declining limb of storms. Furthermore, about 70 to 75% of the microbes in the storm drain outfall water came from materials washed off from the street surfaces in the watershed. Fecal samples did not appear to contribute substantially to the microbes in environmental samples. The results highlight the significance of street surfaces in contributing microbial loads to urban streams under wet weather conditions. Identifying the sources of microbial contamination is important for developing best management practices to protect the water quality of urban streams for recreational uses. This study collected a large number of water samples from an urban stream under both dry and wet weather conditions and provided quantitative information on the relative contributions of various environmental compartments to the overall microbial contamination in the stream under the two weather conditions. The watershed in this study represents urban watersheds where no dominant fecal sources are consistently present. The findings highlight the importance of reducing the direct contribution of microbes from street surfaces in the watershed to urban streams under wet weather conditions. The methods and findings from this study are expected to be useful to stormwater managers and regulatory agencies.