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Genetics and linguistic diversity

Evolution of learned behaviors in genetic and geographic contexts

Director:                 Nicole Creanza, Arts & Sciences

Collaborator:          TS Harvey, Arts & Sciences


Dr. Creanza’s lab focuses on the evolution of learned behaviors, integrating analysis of genomic and behavioral data to understand geographic patterns in genetic and cultural evolution. In both empirical systems that we study—the learned vocalizations of songbirds and the languages of human populations—we have found that learned behaviors can retain evolutionary information across great distances and over long timescales.  In this line of research, we analyze linguistic data to bring new perspectives to geographic questions in population genetics.

Anthropogenic linguistic patterns

Research Goal: Speculation remains about the demographic history of Native Americans, which is complicated by multiple waves of migration across the Bering Strait, admixture between groups, and numerous potential migration routes.

Methods: We are merging genotyped populations to assemble the largest Native American genome dataset and then test whether signals of population history in combined genomic and linguistic data can shed light on hypotheses for multiple independent migrations into the Americas.

Ornithological linguistic patterns

Research Goal: As modern cities continue to grow and sprawl, there is increasing concern about how wildlife communities are affected.  We continue our focus on the relationship between genes and language by focusing on the effect urbanization has on birdsong characteristics.

Methods: We will analyze many species across the U.S., merging citizen-science bird recordings with OpenStreetMap data and land use (a proxy for urbanization). GIS analysis will be conducting using ModelBuilder to run extensive proximity analyses. To analyze thousands of songs with consistency, we developed song analysis software. Our software enables the involvement of Vanderbilt biology students in this large-scale study (BSCI 1512L). Combining these techniques for song analysis and proximity analysis to urban-area indicators, we will explore whether urbanization affects birdsong characteristics.