Life History and Coexistence in a Dynamic World

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

One of the first things you might notice while taking a walk in the woods is that different plant species make fundamentally different investments---in wood, in speed of growth, and in seeds. The biggest trees have been around for decades or even centuries, growing slowly, and only producing seeds later in their lifespan. Smaller, weedier plants tend to produce a lot of seeds, but perhaps at the expense of lower survival rates and shorter lifespans. Yet here they all are, together in the same location. These different strategies are collectively known as the “life history” of each species. Some of the defining characteristics of a plant---its lifespan, growth rate, and seed production---fall under the umbrella of life history. But we lack a definitive picture of how, when and why these very different strategies will coexist. This research project will integrate cutting edge mathematical theory with empirical life history data to shed light on the question of which plant life history strategies will be found together, and why. New environmental conditions can substantially change species’ life history strategies, with potential knock-on effects on biodiversity. This research will begin to quantify the role of life history differences in determining these outcomes. The broader impacts of the project include the integration of new, quantitative approaches for life history analysis into university curricula, as well providing a window into ecological dynamics in an exhibit designed for a public audience. The project activities will engage with both forest ecologists and mathematicians, building new bridges between existing intellectual communities. Finally, multiple trainees will collaborate on the project, contributing to their training and career development at the interface of plant ecology and mathematical biology. The project will develop a range of theoretical models analyzing the dynamics of communities of species, where each can have its own, idiosyncratic life history strategy, characterized by growth, mortality, and fecundity rates that vary with life stage. These models will integrate life history differences with competition for resources, across a range of scenarios for different levels of species diversity and resource partitioning, and will generate predictions for patterns of biodiversity and species abundances across space and through time. In parallel, the project will use publicly-available plant community censuses to infer life history strategies for multiple species in the same community, providing a way to test and guide the development of new theory. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.