Previous research showed that anaerobic respiration using iron (Fe) oxides as terminal electron acceptor contributed substantially to ecosystem respiration (ER) in a drained thaw lake basin (DTLB) on the Arctic coastal plain. As DTLBs age, the surface organic layer thickens, progressively burying the Fe‐rich mineral layers. We therefore hypothesized that Fe(III) availability and Fe reduction would decline with basin age. We studied four DTLBs across an age gradient, comparing seasonal changes in the oxidation state of dissolved and extractable Fe pools and the estimated contribution of Fe reduction to ER. The organic layer thickness did not strictly increase with age for these four sites, though soil Fe levels decreased with increasing organic layer thickness. However, there were surprisingly high levels of Fe minerals in organic layers, especially in the ancient basin where cryoturbation may have transported Fe upward through the profile. Net reduction of Fe oxides occurred in the latter half of the summer and contributed an estimated 40–45% to ecosystem respiration in the sites with the thickest organic layers and 61–63% in the sites with the thinnest organic layers. All sites had high concentrations of soluble Fe(II) and Fe(III), explained by the presence of siderophores, and this pool became progressively more reduced during the first half of the summer. Redox titrations with humic acid (HA) extracts and chelated Fe support our view that this pattern indicates the reduction of HA during this interval. We conclude that Fe(III) and HA reductions contribute broadly to ER in the Arctic coastal plain.

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The challenge of spreading antibiotic resistance calls for systematic efforts to develop more “irresistible” drugs based on a deeper understanding of dynamics and mechanisms of antibiotic resistance acquisition. To address this challenge, we have established a comparative resistomics approach which combines experimental evolution in a continuous-culturing device, the morbidostat, with ultradeep sequencing of evolving microbial populations to identify evolutionary trajectories (mutations and genome rearrangements) leading to antibiotic resistance over a range of target pathogens.