R Package wgaim: QTL Analysis in Bi-Parental Populations Using Linear Mixed Models

The wgaim (whole genome average interval mapping) package developed in the R system for statistical computing (R Development Core Team 2011) builds on linear mixed modelling techniques by incorporating a whole genome approach to detecting significant quantitative trait loci (QTL) in bi-parental populations. Much of the sophistication is inherited through the well established linear mixed modelling package ASReml-R (Butler et al. 2009). As wgaim uses an extension of interval mapping to incorporate the whole genome into the analysis, functions are provided which allow conversion of genetic data objects created with the qtl package of Broman and Wu (2010) available in R. Results of QTL analyses are available using summary and print methods as well as diagnostic summaries of the selection method. In addition, the package features a flexible linkage map plotting function that can be easily manipulated to provide an aesthetic viewable genetic map. As a visual summary, QTL obtained from one or more models can also be added to the linkage map.

Agricultural science policy

Technological advances developed through R&D have supplied the world with not only more food, but better food. This report looks at issues raised by this changing environment for agricultural productivity, agricultural R&D, and natural resource management.Agriculture and state ,

Exploring the role of ions and amino acids in directing the growth of minerals from solutions

The influence of both sulphate ions and aspartic acid on directing the growth of baryte has been explored using computer simulation. Both species are found to significantly reduce the activation freeenergy to growth under appropriate conditions, with the influence of sulphate being surface specific.This offers the potential for a new approach to morphology control without inhibition that may have implications for biomineralization

Dynamic benthic communities: assessing temporal variations in benthic community structure, megafaunal composition and diversity at the Arctic deep-sea observatory HAUSGARTEN between 2004 and 2015

Established in the Fram Strait in 1999, the LTER (Long-Term Ecological Research) observatory HAUSGARTEN enables us to study changes on the deep Arctic seafloor. Repeated deployments of a towed camera system (Ocean Floor Observation System) along the same tracks allowed us to build a time series longer than a decade (2004 - 2015). Here, we present the first time-series results from a northern and the southernmost station of the observatory (N3 and S3, ~2650m and 2350m depth respectively) obtained via the analysis of still imagery. We assess temporal variability in community structure, megafaunal densities and diversity, and use a range of biotic and abiotic factors to explain the patterns observed. There were significant temporal differences in megafaunal abundances, diversity and abiotic factors at both stations. A particularly high increase in megafaunal abundance was recorded at N3 from 12.08 (±0.39; 2004) individuals m-2 to 35.21 (±0.97; 2007) ind. m-2 alongside a ten-fold increase in (drop-)stones. At S3, megafaunal densities peaked in 2015 (22.74 ±0.61 ind. m-2) after an increasing trend since 2004 (12.44 ±0.32 ind. m-2). Holothurians showed particularly striking temporal differences: densities of the small sea cucumber Elpidia heckeri densities rose ten-fold from 0.31 ind. m-2 (±0.04; 2004) to 3.74 ind. m-2 (±0.14; 2015) at S3, coinciding with a sustained increase in phytodetritial matter (chloroplastic pigment equivalents) at the seafloor. Initially entirely absent from N3, densities of the larger holothurian Kolga hyalina peaked in 2007 (5.87 ±0.22 ind. m-2) and declined continuously since then. Overall diversity (γ) increased at both stations over the course of the study, however, with varying contributions of α and β diversities. Our results highlight the importance of time-series studies as megafaunal community composition is characterised by continuous changes. This indicates that epibenthic communities from the deep seafloor are reactive and dynamic, with no “null” community state. To continue to monitor them is therefore crucial in understanding natural and anthropogenic impacts in an area exposed to the effects of climate change