Lancaster University

About: Lancaster University is a education organization based out in Lancaster, Lancashire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 13080 authors who have published 44563 publications receiving 1692277 citations. The organization is also known as: The University of Lancaster & Lancaster University.

Vadose Zone Flow Model Parameterisation Using Cross-Borehole Radar and Resistivity Imaging

Abstract: Cross-borehole geoelectrical imaging, in particular electrical resistivity tomography (ERT) and transmission radar tomography, can provide high-resolution images of hydrogeological structures and, in some cases, detailed assessment of dynamic processes in the subsurface environment. Through appropriate petrophysical relationships, these tools offer data suitable for parameterising and constraining models of groundwater flow. This is demonstrated using cross-borehole radar and resistivity measurements collected during a controlled vadose zone tracer test, performed at a field site in the UK Sherwood Sandstone. Both methods show clearly the vertical migration of the tracer over a 200 h monitoring period. By comparing first and second spatial moments of changes in moisture content predicted from a numerical simulation of vadose zone flow with equivalent statistics from two- and three-dimensional ERT and cross-borehole radar profiles the effective hydraulic conductivity is estimated to be approximately 0.4 m/d. Such a value is comparable to field estimates from borehole hydraulic tests carried out in the saturated zone at the field site and provides valuable information that may be utilised to parameterise pollutant transport models of the site.

Robust estimation of microbial diversity in theory and in practice

Abstract: Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ('Hill diversities'), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.

Design and Construction of the MicroBooNE Detector

Abstract: This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported.