Climate change and energy use : The role for anthropological research

The expression 'global climate change' no longer designates merely a discourse on possible future risks; today it us used as a shorthand for specific ongoing events that are having a serious impact on the lives of people around the world. In the light of this change and consequent efforts to limit carbon dioxide emissions, contributions from social scientists are increasingly in demand within the study of energy use. My concern here is not whether intervention is a proper role for anthropologists, but rather how we may position ourselves within energy- and climate-related research.

The Talking Neanderthals : What do Fossils, Genetics and Archeology Say?

Did Neanderthals have language? This issue has been debated back and forth for decades, without resolution. But in recent years new evidence has become available. New fossils and archeological finds cast light on relevant Neanderthal anatomy and behavior. New DNA evidence, both fossil and modern, provides clues both to the relationship between Neanderthals and Homo sapiens, and to the genetics of language. In this paper, I review and evaluate the available evidence. My conclusion is that the preponderance of the evidence supports the presence of some form of language in Neanderthals.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).