Biotic and abiotic drivers of community assembly

Global environmental change is likely to produce significant shifts in species distributions. Because species differ in their dispersal abilities and their fundamental niches, communities are unlikely to move as a unit, resulting in novel communities that will assemble gradually as the environment changes. The future communities that result will depend greatly on the mechanisms of community assembly. I am working with Wilfried Thuiller at the Laboratroire d’Écologie Alpine in Grenoble, France to build a new suite of metacommunity models to better understand the contemporary drivers of community assembly in alpine and subalpine grasslands in Europe. These models will employ a novel Bayesian framework that can characterize the uncertainty in community composition resulting from different drivers and project this uncertainty into the future. The result should be probabilistic predictions of future community composition conditioned on both the environment and species interactions.

Modeling range dynamics in response to climate change

A second axis of research has been improving the ability to model the distributions of individual species. Climate change is the most obvious forcing mechanism that may change ranges in the future, and current methods (including species distribution models, SDMs, and dynamic global vegetation models, DGVMs, among others) have a number of drawbacks. Using a long-term dataset of permanent forest plots from North America, we have developed a semi-mechanistic distribution model that uses metapopulation theory as the foundation to predict species distribution. A strength of this approach is that can predict both transient and equlibrium states (unlike typical SDMs, which assume equilibrium with climate), and transient predictions naturally incorporate limitations on the rate of spread.

Eco-evolutionary dynamics of serotiny in lodgepole pinepic-res4

For my dissertation work, modeled spatial variation in the strength of multiple selective agents to determine the effects on the evolution of serotiny in lodgepole pine. Serotiny is a heritable fire adaptation that dramatically affects how lodgepole pine forests recover from fire. Highly serotinous stands recover with several orders of magnitude greater seedling density than non-serotinous stands. Spatial variation in the frequency of serotiny is common, and is not completely explained by variance in fire regime. Amrican red squirrels are an important seed predator of lodgepole pine, and they preferentially take serotinous cones. Previous work has shown that red squirrels are associated with greatly reduced frequencies of serotiny, suggesting that they are an important selective agent in this system.

My own data have shown a strong negative association between serotiny and red squirrel density, and an interaction with fire regime that suggests that selection from fire and from squirrels combines to produce landscape-scale patterns in the frequency of serotiny. I also found a strong mechanistic link; survival of serotinous cones is lower than that of non-serotinous cones in the presence of red squirrels, implying selection against serotiny. I am also developing a spatially explicit simulation model that investigates how the scales at which seed predation and fire act on lodgepole pine combine to influence landscape structure. The model will also investigate whether feedbacks and interactions between these two drivers influences landscape structure, and how changes to these drivers (likely due to climate change) will affect the structure of this ecosystem in the future.