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Shallow-water coral reefs hold large quantities of acrylate and its precursor dimethylsulfoniopropionate (DMSP), but production and removal processes for these compounds are poorly characterized. Here we determined the concentrations and cycling of acrylate and DMSP in a transect from a coral reef ecosystem to the open ocean, 2 km beyond the reef in Mo’orea, French Polynesia, during April 2018. Concentrations of dissolved acrylate and DMSP were low throughout the reef-ocean transect, ranging from 0.8–3.9 nM and 0.2–3.0 nM, respectively, with no difference observed between the coral reef and open ocean when comparing mean concentrations (± std dev) of dissolved acrylate (1.7 ± 0.7 vs 2.3 ± 0.8 nM) or DMSP (0.9 ± 0.7 vs 1.3 ± 0.6 nM). In the coral reef, dissolved acrylate was rapidly taken up by the heterotrophic community with a fast turnover time averaging ~ 6 h, six times faster than in the open ocean, and nearly as fast as the average turnover time of dissolved DMSP (~ 3 h). A clear diel trend was observed for the heterotrophic consumption of dissolved acrylate and DMSP in the coral reef, with higher uptake rate constants during daylight hours, synchronized with the larger daytime release of acrylate and DMSP from the coral compared to the nighttime release of these compounds. We also measured photochemical production rates of acrylate in Mo’orean waters, but rates were one to two orders of magnitude slower compared to its rates of biological consumption. Coral and macroalgae were the main sources of dissolved acrylate and DMSP to the reef ecosystem. Our results indicate there is rapid turnover of acrylate and DMSP in the coral reef with a tight coupling between production and removal pathways that maintain dissolved concentrations of these two compounds at very low levels. These algal and coral-derived substrates serve as important chemical links between the coral and heterotrophic communities, two fundamental components in the ecological network in coral reefs. 

Volatile organic compounds (VOCs) are constituents of marine ecosystems including coral reefs, where they are sources of atmospheric reactivity, indicators of ecosystem state, components of defense strategies, and infochemicals. Most VOCs result from sunlight-related processes; however, their light-driven dynamics are still poorly understood. We studied the spatial variability of a suite of VOCs, including dimethylsulfide (DMS), and the other dimethylsulfoniopropionate-derived compounds (DMSPCs), namely, DMSP, acrylate, and dimethylsulfoxide (DMSO), in waters around colonies of two scleractinian corals ( Acropora pulchra and Pocillopora  sp.) and the brown seaweed  Turbinaria ornata  in Mo’orean reefs, French Polynesia. Concentration gradients indicated that the corals were sources of DMSPCs, but less or null sources of VOCs other than DMS, while the seaweed was a source of DMSPCs, carbonyl sulfide (COS), and poly-halomethanes. A focused study was conducted around an A. pulchra  colony where VOC and DMSPC concentrations and free-living microorganism abundances were monitored every 6 h over 30 h. DMSPC concentrations near the polyps paralleled sunlight intensity, with large diurnal increases and nocturnal decrease. rDNA metabarcoding and metagenomics allowed the determination of microbial diversity and the relative abundance of target functional genes. Seawater near coral polyps was enriched in DMS as the only VOC, plus DMSP, acrylate, and DMSO, with a large increase during the day, coinciding with high abundances of symbiodiniacean sequences. Only 10 cm below, near the coral skeleton colonized by a turf alga, DMSPC concentrations were much lower and the microbial community was significantly different. Two meters down current from the coral, DMSPCs decreased further and the microbial community was more similar to that near the polyps than that near the turf alga. Several DMSP cycling genes were enriched in near-polyp with respect to down-current waters, namely, the eukaryotic DMS production and DMS oxidation encoding genes, attributed to the coral and the algal symbiont, and the prokaryotic DMS production gene dddD , harbored by coral-associated Gammaproteobacteria . Our results suggest that solar radiation-induced oxidative stress caused the release of DMSPCs by the coral holobiont, either directly or through symbiont expulsion. Strong chemical and biological gradients occurred in the water between the coral branches, which we attribute to layered hydrodynamics. 

Abstract Graphing is an important practice for scientists and in K-16 science curricula. Graphs can be constructed using an array of software packages as well as by hand, with pen-and-paper. However, we have an incomplete understanding of how students’ graphing practice vary by graphing environment; differences could affect how best to teach and assess graphing. Here we explore the role of two graphing environments in students’ graphing practice. We studied 43 undergraduate biology students’ graphing practice using either pen-and-paper (PP) ( n  = 21 students) or a digital graphing tool GraphSmarts (GS) ( n  = 22 students). Participants’ graphs and verbal justifications were analyzed to identify features such as the variables plotted, number of graphs created, raw data versus summarized data plotted, and graph types (e.g., scatter plot, line graph, or bar graph) as well as participants’ reasoning for their graphing choices. Several aspects of participant graphs were similar regardless of graphing environment, including plotting raw vs. summarized data, graph type, and overall graph quality, while GS participants were more likely to plot the most relevant variables. In GS, participants could easily make more graphs than in PP and this may have helped some participants show latent features of their graphing practice. Those students using PP tended to focus more on ease of constructing the graph than GS. This study illuminates how the different characteristics of the graphing environment have implications for instruction and interpretation of assessments of student graphing practices. 

Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise when students are given opportunities to work with authentic data from scientific research. First, we explore the overlap between the fields of quantitative reasoning, data science, and data literacy, specifically focusing on how data literacy results from practicing quantitative reasoning and data science in the context of authentic data. Next, we identify and describe features that influence the complexity of authentic data sets (selection, curation, scope, size, and messiness) and implications for data-literacy instruction. Finally, we discuss areas for future research with the aim of identifying the impact that authentic data may have on student learning. These include defining desired learning outcomes surrounding data use in the classroom and identification of teaching best practices when using data in the classroom to develop students’ data-literacy abilities. 

Navigating scientific challenges, persevering through difficulties, and coping with failure are considered hallmarks of a successful scientist. However, relatively few studies investigate how undergraduate science, technology, engineering, and mathematics (STEM) students develop these skills and dispositions or how instructors can facilitate this development in undergraduate STEM learning contexts. This is a critical gap, because the unique cultures and practices found in STEM classrooms are likely to influence how students approach challenges and deal with failures, both during their STEM education and in the years that follow. To guide research aimed at understanding how STEM students develop a challenge-engaging disposition and the ability to adaptively cope with failure, we generate a model representing hypotheses of how students might approach challenges and respond to failures in undergraduate STEM learning contexts. We draw from theory and studies investigating mindset, goal orientations, attributions, fear of failure, and coping to inform our model. We offer this model as a tool for the community to test, revise, elaborate, or refute. Finally, we urge researchers and educators to consider the development, implementation, and rigorous testing of interventions aimed at helping students develop a persevering and challenge-engaging disposition within STEM contexts.