Effects of rapid evolution on alternative community states

Species interactions can often allow for multiple different discrete states, or alternative community states, into which a given community can assemble. Which state is realized depends on initial conditions, and this role of history makes predicting community outcomes notoriously difficult. Feedbacks across spatial scales coupled with coevolution within communities further complicates matters. I will use the well-described study system of microbes in Diplacus aurantiacus nectar to study how rapid evolution alters alternative community states at both single-community and metacommunity scales.

Maintenance of variation for ongoing eco-evo dynamics

source: alexanderwild.com

Feedbacks between evolutionary and ecological processes that occur because they operate on similar timescales is called eco-evo dynamics. For eco-evo dynamics to persist, the variation underlying both processes must be maintained, yet this fundamental component of eco-evo dynamics has received little attention. Pea aphids can evolve resistance to parasitoid wasps rapidly enough to affect the host–parasitoid dynamics. Through long-term lab experiments and simulations, we show that aphids dispersing among patches that vary in parasitoid abundance can produce both the ecological stability and balancing selection necessary for ongoing eco-evo dynamics.

Effects of population fluctuations on genome evolution in the wild

Long-duration bottlenecks are known to reduce genetic diversity, but what happens when populations experience frequent, short-duration bottlenecks? How does this vary across the genome? I’m exploring these questions with a population of midges in Lake Mývatn, Iceland, where they have irregular population fluctuations of about 5 orders of magnitude. The Lake Mývatn long-term monitoring project (led by Dr. Árni Einarsson) has gathered midge densities, environmental data, and abundances for many other species at Mývatn since 1977. They have also collected and stored midge samples across this same period, which we used to generate whole-genome sequencing that spans 24 years and 3 major population crashes. I am leveraging this time series of whole-genome and ecological data to assess how genomic structure is affected by extreme population dynamics, and how these effects interact with biotic and abiotic factors.

Trait coevolution among competitors and coexistence

Coevolution among competitors can result in traits that promote niche partitioning and coexistence or traits that promote greater conflict and competitive exclusion. We used an eco-evolutionary model where competitors “invest” in coexistence- and exclusion-promoting traits to assess when trait coevolution should promote coexistence or exclusion. We found that communities should often contain both types of traits, but exclusion-promoting traits should more strongly influence trait coevolution community-wide. We also found that, despite being more influential, species invested relatively more in exclusion-promoting traits should be most vulnerable to exclusion by a new invader. This may make communities containing multiple species with exclusion-promoting traits evolutionary transitory.