Mapping Valley Bottom Confinement at the Network Scale

In this article, we demonstrate the application of a continuous confinement metric across entire river networks. Confinement is a useful metric for characterizing and discriminating valley setting. At the reach scale, valley bottom confinement is measured and quantified as the ratio of the length of channel confined on either bank by a confining margin divided by the reach length. The valley bottom is occupied by the contemporary floodplain and/or its channel(s); confining margins can be any landform or feature that makes up the valley bottom margin, such as bedrock hillslopes, terraces, fans, or anthropogenic features such as stopbanks or constructed levees. To test the reliability of calculating confinement across entire networks, we applied our geoprocessing scripts across four physiographically distinct watersheds of the Pacific Northwest, USA using freely available national datasets. Comparison of manually digitized and mapped with modeled calculations of confinement revealed that roughly one‐third of reaches were equivalent and about two‐thirds of the sites differ by less than ±15%. A sensitivity analysis found that a 500 m reach segmentation length produced reasonable agreement with manual, categorical, expert‐derived analysis of confinement. Confinement accuracy can be improved (c. 4% to 17% gains) using a more accurately mapped valley bottom and channel position (i.e. with higher‐resolution model inputs). This is particularly important when differentiating rivers in the partly confined valley setting. However, at the watershed scale, patterns derived from mapping confinement are not fundamentally different, making this a reasonably accurate and rapid technique for analysis and measurement of confinement across broad spatial extents

Discovery of the First Insect Nidovirus, a Missing Evolutionary Link in the Emergence of the Largest RNA Virus Genomes

Nidoviruses with large genomes (26.3–31.7 kb; ‘large nidoviruses’), including Coronaviridae and Roniviridae, are the most complex positive-sense single-stranded RNA (ssRNA+) viruses. Based on genome size, they are far separated from all other ssRNA+ viruses (below 19.6 kb), including the distantly related Arteriviridae (12.7–15.7 kb; ‘small nidoviruses’). Exceptionally for ssRNA+ viruses, large nidoviruses encode a 3′-5′exoribonuclease (ExoN) that was implicated in controlling RNA replication fidelity. Its acquisition may have given rise to the ancestor of large nidoviruses, a hypothesis for which we here provide evolutionary support using comparative genomics involving the newly discovered first insect-borne nidovirus. This Nam Dinh virus (NDiV), named after a Vietnamese province, was isolated from mosquitoes and is yet to be linked to any pathology. The genome of this enveloped 60–80 nm virus is 20,192 nt and has a nidovirus-like polycistronic organization including two large, partially overlapping open reading frames (ORF) 1a and 1b followed by several smaller 3′-proximal ORFs. Peptide sequencing assigned three virion proteins to ORFs 2a, 2b, and 3, which are expressed from two 3′-coterminal subgenomic RNAs. The NDiV ORF1a/ORF1b frameshifting signal and various replicative proteins were tentatively mapped to canonical positions in the nidovirus genome. They include six nidovirus-wide conserved replicase domains, as well as the ExoN and 2′-O-methyltransferase that are specific to large nidoviruses. NDiV ORF1b also encodes a putative N7-methyltransferase, identified in a subset of large nidoviruses, but not the uridylate-specific endonuclease that – in deviation from the current paradigm - is present exclusively in the currently known vertebrate nidoviruses. Rooted phylogenetic inference by Bayesian and Maximum Likelihood methods indicates that NDiV clusters with roniviruses and that its branch diverged from large nidoviruses early after they split from small nidoviruses. Together these characteristics identify NDiV as the prototype of a new nidovirus family and a missing link in the transition from small to large nidoviruses

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

A geomorphic assessment to inform strategic stream restoration planning in the Middle Fork John Day Watershed, Oregon, USA

A geomorphic assessment of the Middle Fork John Day Watershed, Oregon, USA, was used to generate a hierarchical, map-based understanding of watershed impairments and potential opportunities for improvements. Specifically, we (1) assessed river diversity (character and behavior) and patterns of reach types (and their controls); (2) evaluated the geomorphic condition of the streams; (3) interpreted their geomorphic recovery potential; and (4) synthesized the above into a hypothetical, strategic management plan. Collectively, these maps can set bounds and provide realistic guidance for river rehabilitation, design and implementation efforts. Fifteen distinct reach types were identified, two-thirds of which are found along perennial streams. On the basis of a variety of geo-indicators, approximately two-thirds of all perennial stream reaches were found to be in ‘good’ geomorphic condition, whereas one-third had departed to ‘moderate’ and ‘poor’ condition. Departures from ‘good’ condition were primarily related to riparian vegetation removal, conversion of floodplain to agricultural land uses (farming and grazing), logging, and channel bed dredge mining for gold. Encouragingly, the majority of reaches classified as being in moderate geomorphic condition were found to have high recovery potential. While our geomorphic assessment has practical utility for informing physically realistic expectation management for efforts like salmonid habitat restoration, the maps themselves are the key vehicle for communicating and visualizing among stakeholders

Multibeam echosounder observations reveal interactions between Antarctic krill and air-breathing predators

A multibeam echosounder (MBE) was deployed on an inflatable boat (length = 5.5 m) to observe swarms of Antarctic krill Euphausia superba in the nearshore environment off Livingston Island, South Shetland Islands, Antarctica. Visual observations of air-breathing predators, including penguins and fur seals, were made from the boat at the same time. MBEs extend the 2-dimensional acoustic observations that can be made with conventional vertical echosounders to 3 dimensions, enabling direct observation of the surface areas and volumes of entire krill swarms. Krill swarms exhibited a wide range of various size metrics (e.g. height, length and width) but only a narrow range of surf ace-area-to-volume ratios or 'roughnesses', suggesting that krill adopt a consistent group behavior to maintain swarm shape. The variation in R was investigated using generalized additive models (GAMs). GAMs indicated that the presence of air-breathing predators influenced swarm shape (R decreased as the range to predators decreased, and the swarms became more spherical), as did swarm nearest-neighbor distance (R decreased with increasing distance) and swarm position in the water column (R decreased in the upper 70% of the water column). Therefore, swarm shape appears to be influenced by a combination of behavioral responses to predator presence and environmental variables. MBEs have the potential to contribute much to studies of krill, and can provide data to improve our understanding of the behavior of krill in situ.</p