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Blow flies (Lucilia sericataandPhormia regina) are necrophagous insects that interact with dense microbial reservoirs and are opportunistic vectors of human and animal pathogens. Despite constant exposure to diverse environmental microbes, it is unclear whether their bacterial communities are primarily acquired stochastically or shaped by host factors that could influence pathogen carriage. We conducted a systematic comparison of wildL. sericataandP. reginacollected from seven cities across an urban-rural gradient to determine whether microbiome composition is structured by host species identity or environmental variables. Using 16S rRNA gene sequencing of individual flies, we profiled bacterial communities and applied alpha- and beta-diversity analyses, PERMANOVA, and Random Forest classification to quantify species-level microbiome differentiation. Species identity was the strongest predictor of microbiome composition (PERMANOVA,p = 0.001), while location, land cover type, sampling month, and sex had no significant effects. Random Forest modeling identified multiple bacterial taxa that consistently distinguished the two species, includingIgnatzschineriaandDysgonomonas, which were enriched inP. regina, andVagococcusandEscherichia-Shigella, which were enriched inL. sericata. These taxa are of clinical relevance, withIgnatzschineriain particular increasingly reported from human myiasis and soft-tissue infections, sometimes exhibiting antimicrobial resistance. Our findings demonstrate that wild blow flies maintain species-specific microbiomes despite shared environments, suggesting that host identity strongly filters microbial communities. The presence of opportunistic pathogens within these structured microbiomes underscores the need to understand how blow fly–microbe associations contribute to pathogen persistence and dissemination. By revealing predictable, species-dependent microbiome patterns, this study highlights potential targets for microbiome-based strategies aimed at mitigating blow fly–associated disease risks. 

Starting in 2012 zooplankton sampling at Green Lake 4 was included in the long term monitoring data set at Niwot Ridge. Immediately after the ice has completely melted from the lakes, zooplankton samples are taken once a week for six consecutive weeks at the deepest portion of the lake from an inflatable raft. Zooplankton were sampled at the deepest location of each lake by pulling a conical net (Wisconsin net) vertically through the water column (i.e., vertical tow sample). For each zooplankton sample obtained, adult organisms were identified to species, or lowest taxonomic level (Chydoridae sp. and Bosminidae sp.). Larvae of cladocerans were counted together as neonates; calanoid and cyclopoid copepodites were counted together as nauplii. Individual body lengths of the first 50 -100 (when possible) individuals of each taxon were recorded using a calibrated eyepiece micrometer and means reported. 

Understanding the indirect and interactive effects of environmental stressors is critical to planning conservation interventions, but such effects are poorly understood. For example, invasive species may modify fire effects by altering fire intensity or frequency, increasing or decreasing their abundance in response to fire, and/or changing the trajectory of post‐fire recovery. Without a clear understanding of the direct, indirect, and interactive effects of prescribed fire and invasive species on native plants, managers cannot design effective conservation measures and risk exacerbating invasion through fire or wasting resources on approaches that do not yield desired results. In this study, researchers worked directly with the manager of a wet meadow in southern Idaho to explore how prescribed fire would directly and indirectly impact an iconic native herb (Camassia quamash) in areas invaded by a perennial pasture grass (Alopecurus arundinaceus). We found that spring prescribed fire increased the abundance of invasiveA. arundinaceus, which indirectly strengthened its suppression ofC. quamashgrowth and reproduction. In contrast, fire reversed the negative influence ofA. arundinaceusonC. quamashsurvival. Survival rates ofC. quamashwere higher after fire in areas with greater invasive grass abundance. This study points to the importance of understanding the indirect and interactive effects of prescribed fire and invasives on native plants across their life cycle for restoration projects and suggests fire, at least in spring, is not an appropriate management strategy for reducingA. arundinaceusinvasion at this site. 

High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up. 

High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up. 

High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up. 

High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up. 

Undergraduates enrolled in large, active learning courses must self-regulate their learning (self-regulated learning [SRL]) by appraising tasks, making plans, setting goals, and enacting and monitoring strategies. SRL researchers have relied on self-report and learner-mediated methods during academic tasks studied in laboratories and now collect digital event data when learners engage with technology-based tools in classrooms. Inferring SRL processes from digital events and testing their validity is challenging. We aligned digital and verbal SRL event data to validate digital events as traces of SRL and used them to predict achievement in lab and course settings. In Study 1, we sampled a learning task from a biology course into a laboratory setting. Enrolled students (N = 48) completed the lesson using digital resources (e.g., online textbook, course site) while thinking aloud weeks before it was taught in class. Analyses confirmed that 10 digital events reliably co-occurred ≥70% of the time with verbalized task definition and strategy use macroprocesses. Some digital events co-occurred with multiple verbalized SRL macroprocesses. Variance in occurrence of validated digital events was limited in lab sessions, and they explained statistically nonsignificant variance in learners’ performance on lesson quizzes. In Study 2, lesson-specific digital event data from learners (N = 307) enrolled in the course (but not in Study 1) predicted performance on lesson-specific exam items, final exams, and course grades. Validated digital events also predicted final exam and course grades in the next semester (N = 432). Digital events can be validated to reflect SRL processes and scaled to explain achievement in naturalistic undergraduate education settings. Educational Impact and Implications Statement Instructors often have difficulty identifying and helping struggling students in courses with hundreds of students. Digital trace data can be used to efficiently and effectively identify struggling students in these large courses, but such data are often difficult to interpret with confidence. In our study, we found that using verbal trace data to augment and validate our inferences about the meaning of digital trace data resulted in a powerful set of predictors of students’ achievement. These validated digital trace data can be used to not only identify students in need of support in large classes, but also to understand how to target interventions to the aspects of learning that are causing students the most difficulty. 

Novel tetrafluoro-λ6-sulfanyl-containing oligomers prepared by visible light-promoted addition of 1,4-(bis-chlorotetrafluoro-λ6-sulfanyl) benzene or 1,3-(bis-chlorotetrafluoro-λ6-sulfanyl) benzene to either 1,4-diethynyl benzene or the 1,3-diethynyl isomers form hard, stress resistant thin films on spin casting. The isomeric oligomers were utilized to establish a structure-function relationship for the mechanical properties of films prepared from the oligomers. The Young’s moduli of 145-nm-thick cured films could reach 60 GPa. The measured hardnesses, between 1.57 and 2.77 GPa, were more than double those of polymethyl methacrylate (PMMA) films. Curing of the tetrafluoro-λ6-sulfanyl-containing polymer films by UV irradiation resulted in coatings that exhibited remarkable hardness and modulus with good surface adhesion to silicon.