COS 5-1 - Niche conservatism and phylogenetic signal in North American beetles

Monday, August 12, 2019: 1:30 PM
M111, Kentucky International Convention Center
Jacob D. Stachewicz, Austin Koontz, William D. Pearse, Hillary Woolf and Amanda S. Gallinat, Department of Biology & Ecology Center, Utah State University, Logan, UT
Background/Question/Methods

Niche conservatism is an important aspect of evolutionary biology that can reveal how species traits have evolved, and why closely related species tend to resemble one-another. Yet, identifying precise macroevolutionary models of niche conservatism within taxa has proven difficult due to a lack of species-rich comparative datasets. By utilizing NEON images of beetles (Coleoptera) collected across multiple North American sites we have created a database from >1300 beetle images of observed functional traits of 283 species that is sufficient for a comparative phylogenetic analysis. We also generated a corresponding phylogeny of 188 beetle species from NEON genetic data. We applied a phylogenetic comparative approach to test whether the evolution of beetle body size and shape traits is consistent with the Brownian motion model of trait evolution. Brownian Motion is consistent with the theory of drift, which states that individuals inherit their niches from their ancestors, and then slowly diverge over time.

Results/Conclusions

Of the seven functional traits we measured, the trait with the most variation among species was maximum body length (mean = 11.89 mm, SD = 4.72). Principal Components Analysis reveals strong correlation among measured traits. Our preliminary phylogenetic analysis reveals that beetle body size and shape traits exhibit little to no phylogenetic signal consistent with high trait lability (Pagel’s lambda < 0.1; p > 0.05). This suggests that closely related North American beetles do not resemble one another, and implies that their ecological niches evolve in response to environmental drivers. This work will allow us to digitize and release a novel beetle data product, and our findings allow us to further theorize on beetle community structure and predict future responses to environmental change.