Wave breaking on reefs, many of which have steep slopes, results in elevated mean water levels (or wave setup) across the reef, which can drive mean flows over the reef and inside adjacent lagoons (if present) (e.g., Lowe & Falter, 2015;Monismith, 2007). The mean flows and setup dynamics in such environments have been found to greatly depend on the reef properties at both large scales (reef geometry and bathymetry Abstract Two-dimensional mean wave-driven flow and setup dynamics were investigated at a reef-lagoon system at Ningaloo Reef, Western Australia, using the numerical wave-flow model, SWASH. Phase-resolved numerical simulations of the wave and flow fields, validated with highly detailed field observations (including >10 sensors through the energetic surf zone), were used to quantify the main mechanisms that govern the mean momentum balances and resulting mean current and setup patterns, with particular attention to the role of nonlinear wave shapes. Momentum balances from the phaseresolved model indicated that onshore flows near the reef crest were primarily driven by the wave force (dominated by radiation stress gradients) due to intense breaking, whereas the flow over the reef flat and inside the lagoon and channels was primarily driven by a pressure gradient. Wave setup inside the lagoon was primarily controlled by the wave force and bottom stress. The bottom stress reduced the setup on the reef flat and inside the lagoon. Excluding the bottom stress contribution in the setup balance resulted in an over prediction of the wave-setup inside the lagoon by up to 200-370%. The bottom stress was found to be caused by the combined presence of onshore directed wave-driven currents and (nonlinear) waves. Exclusion of the bottom stress contribution from nonlinear wave shapes led to an over prediction of the setup inside the lagoon by approximately 20-40%. The inclusion of the nonlinear wave shape contribution to the bottom stress term was found to be particularly relevant in reef regions that experience a net onshore mass flux over the reef crest.Plain Language Summary Coral reefs that are located in close proximity to a coastline are typically characterized by a steep slope and reef crest that is connected to the coast or front a shallow lagoon. At the reef crest, waves break and drive onshore-directed currents and elevate the mean (timeaveraged) water level in the lagoon. In this study, we combined measurements of waves, currents and water levels with simulations from an advanced computer model to understand the physical mechanisms that determine the current patterns and water level variations at a coral reef-lagoon system in Western Australia. Friction generated by the water moving over the rough reef structures was found to reduce the mean water levels inside the lagoon. This friction was explained by the combined presence of both waves and mean currents. Furthermore, near the reef crest, the waves peak and pitch forward before they break, and this nonlinear wave shape was found to enhance the friction from ...

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Microbial natural products, in particular secondary or specialized metabolites, are an important source and inspiration for many pharmaceutical and biotechnological products. However, bioactivity-guided methods widely employed in natural product discovery programs do not explore the full biosynthetic potential of microorganisms, and they usually miss metabolites that are produced at low titer. As a complementary method, the use of genome-based mining in natural products research has facilitated the charting of many novel natural products in the form of predicted biosynthetic gene clusters that encode for their production. Linking the biosynthetic potential inferred from genomics to the specialized metabolome measured by metabolomics would accelerate natural product discovery programs. Here, we applied a supervised machine learning approach, the K-Nearest Neighbor (KNN) classifier, for systematically connecting metabolite mass spectrometry data to their biosynthetic gene clusters. This pipeline offers a method for annotating the biosynthetic genes for known, analogous to known and cryptic metabolites that are detected via mass spectrometry. We demonstrate this approach by automated linking of six different natural product mass spectra, and their analogs, to their corresponding biosynthetic genes. Our approach can be applied to bacterial, fungal, algal and plant systems where genomes are paired with corresponding MS/MS spectra. Additionally, an approach that connects known metabolites to their biosynthetic genes potentially allows for bulk production via heterologous expression and it is especially useful for cases where the metabolites are produced at low amounts in the original producer.