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Everett, R.

Publications and source records attributed to Everett, R..

2 recordsLinked to original sources

Multi-proxy evidence for the impact of the Storegga Slide Tsunami on the early Holocene landscapes of the southern North Sea

Doggerland was a land mass occupying an area currently covered by the North Sea until marine inundation took place during the mid-Holocene, ultimately separating the British land mass from the rest of Europe. The Storegga Slide, which triggered a tsunami reflected in sediment deposits in the Northern North Sea, North East coastlines of the British Isles and across the North Atlantic, was a major event during this transgressive phase. The spatial extent of the Storegga tsunami however remains unconfirmed because to date no direct evidence for the event has been recovered from the southern North Sea. We present evidence that Storegga associated deposits occur in the southern North Sea. Palaeo-river systems have been identified using seismic survey in the southwestern North Sea and sedimentary cores extracted to track the Mid Holocene inundation. At the head of one palaeo-river system near the Outer Dowsing Deep, the Southern River, we observed an abrupt and catastrophic inundation stratum. Based on lithostratigraphic, macro and microfossils and sedimentary ancient DNA (sedaDNA) evidence, supported by optical stimulation luminescence (OSL) and radiocarbon dating, we conclude these deposits were a result of the Storegga event. Seismic identification of this stratum to adjacent cores indicated diminished traces of the tsunami, largely removed by subsequent erosional processes. Our results demonstrate the catastrophic impact of Storegga within this area of the Southern North Sea, but indicate that these effects were temporary and likely localized and mitigated by the dense woodland and topography of the area. We conclude clear physical remnants of the wave are likely to be restricted to inland basins and incised river valley systems.

paleontology↗

Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models

Quantitative systems pharmacology (QSP) models aim to describe mechanistically the pathophysiology of disease and predict the effects of therapies on that disease. For most drug development applications, it is important to predict not only the mean response to an intervention but also the distribution of responses, due to inter-patient variability. Given the necessary complexity of QSP models, and the sparsity of relevant human data, the parameters of QSP models are often not well determined. One approach to overcome these limitations is to develop alternative virtual patients (VPs) and virtual populations (Vpops), which allow for the exploration of parametric uncertainty and reproduce inter-patient variability in response to perturbation. Here we evaluated approaches to improve the efficiency of generating Vpops. We aimed to generate Vpops without sacrificing diversity of the VPs pathophysiologies and phenotypes. To do this, we built upon a previously published approach (Allen, Rieger et al. 2016) by (a) incorporating alternative optimization algorithms (genetic algorithm and Metropolis-Hastings) or alternatively (b) augmenting the optimized objective function. Each method improved the baseline algorithm by requiring significantly fewer plausible patients (precursors to VPs) to create a reasonable Vpop. #ddct #qsp

pharmacology and toxicology↗