Colorado mountain landscape

Marc A. Beer

Postdoctoral Researcher · Population Genomics

School of Biological Sciences, Washington State University

My research focuses on understanding evolution in its geographic and environmental context. This includes studying how environmental variation results in spatially varying selection and heterogeneous gene flow across landscapes. My research largely falls under the fields of landscape genetics and landscape genomics, although I have a broader interest in evolutionary ecology. I also maintain an interest in evaluating the performance of emerging tools and reseearch practices by simulating spatial population genomic data.

Population Genomics Landscape Genetics & Genomics Molecular Ecology Evolutionary Ecology
Marc A. Beer

Research

🌍Global Change

Investigating how environmental change — including climate change and emerging infectious disease — shapes population genomic variation.

🧬Population Genomics

Using whole-genome data to understand patterns of genetic diversity, differentiation, and selection across natural populations.

🗺️Landscape Genetics & Genomics

Coupling genomic and environmental data to characterize environmental predictors of spatially varying selection and gene flow.

💻Simulations

Using simulations to test the performance of landscape genomics methodology.

Spatial repeatability of host evolution in response to infectious disease

An important question in evolutionary biology is the extent to which adaptive evolution is repeated across different populations or species experiencing similar selective pressures. Indeed, evolutionary repeatability is a continuum affected by numerous factors such as population history, genetic constraints, and the degree of environmental similarity. Tasmanian devils are an ideal system for studying the repeatability of evolution because multiple, genetically differentiated devil populations have experienced strong selection imposed by a lethal transmissible cancer, devil facial tumor disease (DFTD). I am testing whether the genomic basis of adaptation to DFTD is repeated among devil populations using time-series whole genome and transcriptome data collected at six long-term study sites.

Landscape community genomics of Tasmanian marsupials

Although the cascading community ecological changes resulting from top predator declines are relatively well-understood, concomitant evolutionary cascades are unclear. The Tasmanian devil, Tasmania's top predator, has experienced dramatic population declines due to devil facial tumor disease (DFTD), which have resulted in behavioral and numerical changes in other community members, including the spotted tailed quoll, a mesopredator species. I recently demonstrated that spatiotemporal variation in devil densities and DFTD occurrence have significant effects on spatial population genomic differentiation among quolls, including signatures of spatially varying selection. The publication associated with this research can be found here. I am currently collaborating with researchers exploring evolutionary effects of devil densities and DFTD on additional Tasmanian species. This research represents the framework of 'landscape community genomics', which involves testing for associations between population genomic variation and both abiotic and biotic environmental factors.

Landscape genomics of range-expanding and invasive species

Range expansions are evolutionarily complex phenomena that pose challenges for studying the genomic basis of local adaptation. I recently applied novel spatial statistical methodology to identify spatial variation in genomic signatures of local adaptation among invasive cane toad populations across Australia. Although environmental gradients are repeated across different portions of the cane toad's invasive range, toads at the invasion front have significantly higher dispersal capacity than toads in longer-established populations, which could swamp spatially varying selection. Using geographically weighted regression (GWR) - a form of regression modeling that permits spatial variation in the magnitude and direction of beta coefficients - we found that the slopes of genotype-environment associations (GEAs) are significantly shallower at the expanding invasion front than in longer-established geographic regions. This may reflect increased gene flow at the invasion front swamping local adaptation or a temporal lag between the establishment of populations and the evolution of GEAs. GWR may be broadly applicable for detecting spatial variation in genomic signatures of local adaptation in many species. The publication associated with this research can be found here.


Publications

See also Google Scholar.

2025

2024

2022

2021

2018


Curriculum Vitae

View CV

Contact

I am always happy to connect with other researchers interested in evolutionary biology and genomics.