Thermomechanical erosion modelling of Baydaratskaya Bay, Russia with COSMOS

Rapid coastal erosion threatens Arctic coastal infrastructure, including communities and industrial installations. Erosion of permafrost depends on numerous processes, including thermal and mechanical behaviour of frozen and unfrozen soil, nearshore hydrodynamics, atmospheric forcing, and the presence of sea ice. The quantification and numerical modelling of these processes is essential to predicting Arctic coastal erosion. This paper presents a case study of Baydaratskaya Bay, Russia, using the COSMOS numerical model to predict thermal-mechanical erosion. In particular, this study focuses on thermoabrasional rather than thermodenudational processes. A field dataset of onshore thermal and mechanical soil characteristics was supplemented by sources from the literature to serve as input for the model. A detailed sensitivity analysis has been conducted to determine the influence of key parameters on coastal erosion rates at the study site. This case study highlights the need for expanded data collection on Arctic coastlines and provides direction for future investigations

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries