Urbanization drives adaptive evolution in a Neotropical bird.

Urbanization has dramatic impacts on natural habitats and such changes may potentially drive local adaptation of urban populations. Behavioral change has been specifically shown to facilitate the fast adaptation of birds to changing environments, but few studies have investigated the genetic mechanisms of this process. Such investigations could provide insights into questions about both evolutionary theory and management of urban populations. In this study, we investigated whether local adaptation has occurred in urban populations of a Neotropical bird species, Coereba flaveola, specifically addressing whether observed behavioral adaptations are correlated to genetic signatures of natural selection. To answer this question, we sampled 24 individuals in urban and rural environments, and searched for selected loci through a genome-scan approach based on RADseq genomic data, generated and assembled using a reference genome for the species. We recovered 46 loci as putative selection outliers, and 30 of them were identified as associated with biological processes possibly related to urban adaptation, such as the regulation of energetic metabolism, regulation of genetic expression, and changes in the immunological system. Moreover, genes involved in the development of the nervous system showed signatures of selection, suggesting a link between behavioral and genetic adaptations. Our findings, in conjunction with similar results in previous studies, support the idea that cities provide a similar selective pressure on urban populations and that behavioral plasticity may be enhanced through genetic changes in urban populations.

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.