F-type plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum β-lactamases, particularly in Enterobacterales. Organising this plasmid diversity is challenging, and current knowledge is largely based on plasmids from clinical settings. Here, we present a network community analysis of a large survey of F-type plasmids from environmental (influent, effluent and upstream/downstream waterways surrounding wastewater treatment works) and livestock settings. We use a tractable and scalable methodology to examine the relationship between plasmid metadata and network communities. This reveals how niche (sampling compartment and host genera) partition and shape plasmid diversity. We also perform pangenome-style analyses on network communities. We show that such communities define unique combinations of core genes, with limited overlap. Building plasmid phylogenies based on alignments of these core genes, we demonstrate that plasmid accessory function is closely linked to core gene content. Taken together, our results suggest that stable F-type plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The association of F-type plasmids with AMR may reflect their suitability for rapid niche adaptation.

Escherichia coli and other Enterobacteriaceae are highly diverse species with ‘open’ pangenomes1,2, where genes move intra- and inter-species via horizontal gene transfer3. These species can cause clinical infections4,5 as well as persist environmentally6,7. Environmental populations have been suggested as important reservoirs of antimicrobial resistance (AMR) genes. However, as most analyses focus on clinical isolates8,9, the pangenome dynamics of natural populations remain understudied, particularly the role of plasmids. Here, we reconstructed near-complete genomes for 828 Enterobacteriaceae, including 553 Escherichia spp. and 275 non-Escherichia species with 2,293 circularised plasmids in total, collected from nineteen locations (livestock farms and wastewater treatment works in the United Kingdom) within a 30km radius at three timepoints over the course of a year. We find different dynamics for the chromosomal and plasmid-borne components of the pangenome, showing that plasmids have a higher burden of both AMR genes and insertion sequences, and AMR plasmids show evidence of being under stronger selective pressure. Focusing on E. coli, we observe that plasmid dynamics are more strongly dominated by niche and local geography, rather than phylogeny or season. Our results highlight the diversity of the AMR reservoir in these species and niches, and the importance of local strategies for controlling the emergence and spread of AMR.

The dissolved organic carbon (DOC) export from land to ocean via rivers is a significant term in the global C cycle, and has been modified in many areas by human activity. DOC exports from large global rivers are fairly well quantified, but those from smaller river systems, including those draining oceanic regions, are generally under-represented in global syntheses. Given that these regions typically have high runoff and high peat cover, they may exert a disproportionate influence on the global land–ocean DOC export. Here we describe a comprehensive new assessment of the annual riverine DOC export to estuaries across the island of Great Britain (GB), which spans the latitude range 50–60° N with strong spatial gradients of topography, soils, rainfall, land use and population density. DOC yields (export per unit area) were positively related to and best predicted by rainfall, peat extent and forest cover, but relatively insensitive to population density or agricultural development. Based on an empirical relationship with land use and rainfall we estimate that the DOC export from the GB land area to the freshwater-seawater interface was 1.15 Tg C year−1 in 2017. The average yield for GB rivers is 5.04 g C m−2 year−1, higher than most of the world’s major rivers, including those of the humid tropics and Arctic, supporting the conclusion that under-representation of smaller river systems draining peat-rich areas could lead to under-estimation of the global land–ocean DOC export. The main anthropogenic factor influencing the spatial distribution of GB DOC exports appears to be upland conifer plantation forestry, which is estimated to have raised the overall DOC export by 0.168 Tg C year−1. This is equivalent to 15% of the estimated current rate of net CO2 uptake by British forests. With the UK and many other countries seeking to expand plantation forest cover for climate change mitigation, this ‘leak in the ecosystem’ should be incorporated in future assessments of the CO2 sequestration potential of forest planting strategies.

High‐resolution monitoring of water quality and ecosystem functioning over large spatial scales in expansive lowland river catchments is challenging. Therefore, we need modeling tools to predict these processes at locations where observations are absent. Here, we present a new approach to estimate ecosystem metabolism underpinned by a high‐resolution, process‐based model of in‐stream flows and water quality. The model overcomes the current challenges in metabolism modeling by accounting for oxygen transport under varying flows and oxygen transformations due to biogeochemical processes. We implement the model in a 62‐km‐long stretch of the River Thames, England, using observations spanning 2 yr. Model outputs suggest that the river is primarily autotrophic from mid‐spring to mid‐summer due to high biomass during low‐flow periods, and is heterotrophic during the rest of the year. Ecosystem respiration in upstream reaches is driven mainly by biochemical oxygen demand, autotrophic respiration, and nitrification processes, whereas downstream sites also show a control of benthic oxygen demand in addition to the aforementioned processes. Using empirical modeling, we analyze the sensitivity of our estimated metabolism rates to multiple environmental stressors. Results demonstrate that empirical models could be useful for rapid river health assessments, but need improvements to reproduce peak metabolism rates. The process‐based model, although more complex than existing in situ approaches to metabolism quantification, allows inference when gaps in continuous observations are present. The model offers additional benefits for predicting metabolism rates under future scenarios of environmental change incorporating multiple stressor effects.

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