Trait-based ecology & community assembly
Trait-based ecology directly links the traits expressed by individuals (phenotype) with environmental context to better explain broad patterns in ecological systems. We've been using a theoretical framework called Trait Driver Theory to investigate how the functional composition of whole forests varies along climatic gradients and how these functional changes translate into shifts in primary productivity. By compiling trait and environmental data for tree communities throughout the world, we are able to identify the primary climatic drivers of functional diversity in forests to better understand how functional composition changes across space and over time, specifically in response to climate change. Recently, we have been using this framework to analyze remote sensing hyperspectral trait data taken from the air (left) to evaluate shifts in community structure and productivity along an elevational gradient in Peru.
Photo credit: Carnegie Airborne Observatory
Environmental 'color' in ecology and evolution
Many of the selective forces that sculpt the diversity of forms observed in nature vary over time. For example, climatic variables like temperature or the abundance of a predator/competitor tend to exhibit noisy dynamics with varying degrees of temporal autocorrelation, also known as 'noise colors.' Through a series of trait-based models and microbial experiments we have shown that the color of environmental noise alone can influence phenotypic diversity within a population, range expansions during climate warming, synchrony in population dynamics, and the evolution of tolerance to withstand environmental stress.
Ecological and evolutionary processes are not isolated, but merely different aspects of the same complex process which Hutchinson called "The Ecological Theater and the Evolutionary Play." It has become clear that the interplay between ecology and evolution can have drastic effects on biological systems, even on very short timescales, but there is no common framework for identifying and comparing different types of eco-evolutionary phenomena. In collaboration with members of a working group at Yale University, we have developed such a framework (Okamoto et al., In revision) that formally distinguishes between eco-evolutionary "interactions," "dynamics," and "feedbacks," thus allowing us to generalize conclusions across diverse systems in which ecology and evolution are intertwined.