Information theoretic approaches and model averaging are increasing in popularity, but this approach can be difficult to apply to the realistic, complex models that typify many ecological and evolutionary analyses. This is especially true for those researchers without a formal background in information theory. Here, we highlight a number of practical obstacles to model averaging complex models. Although not meant to be an exhaustive review, we identify several important issues with tentative solutions where they exist (e.g. dealing with collinearity amongst predictors; how to compute model‐averaged parameters) and highlight areas for future research where solutions are not clear (e.g. when to use random intercepts or slopes; which information criteria to use when random factors are involved). We also provide a worked example of a mixed model analysis of inbreeding depression in a wild population. By providing an overview of these issues, we hope that this approach will become more accessible to those investigating any process where multiple variables impact an evolutionary or ecological response.

Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity1–4. Sparse taxon sampling has previously been proposed to confound phylogenetic inference5, and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families—including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confidently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specific variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will offer new perspectives on evolutionary processes in cross-species comparative analyses and assist in efforts to conserve species.

The major histocompatibility complex (MHC) forms an integral component of the vertebrate immune response and, due to strong selection pressures, is one of the most polymorphic regions of the entire genome. Despite over 15 years of research, empirical studies offer highly contradictory explanations of the relative roles of different evolutionary forces, selection and genetic drift, acting on MHC genes during population bottlenecks. Here, we take a meta-analytical approach to quantify the results of studies into the effects of bottlenecks on MHC polymorphism. We show that the consequences of selection acting on MHC loci prior to a bottleneck event, combined with drift during the bottleneck, will result in overall loss of MHC polymorphism that is ∼15% greater than loss of neutral genetic diversity. These results are counter to general expectations that selection should maintain MHC polymorphism, but do agree with the results of recent simulation models and at least two empirical studies. Notably, our results suggest that negative frequency-dependent selection could be more important than overdominance for maintaining high MHC polymorphism in pre-bottlenecked populations.

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