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My research spans many facets of ecology and evolution but centers on the idea that broad-scale patterns in the structure, function, and diversity of communities and ecosystems ultimately emerge from the performance of individual organisms interacting with their environment through traits. I'm specifically interested in understanding how biological systems are reorganized when environmental conditions change. I combine ecological and evolutionary theory with microbial experiments and analysis of large datasets and my study systems include a variety of organisms ranging from viruses and microbial communities in the laboratory to forest communities and food webs throughout the world.


Scaling up from traits to predict environmental impacts on ecosystems


Microbes play an important role in global carbon cycling. They ingest carbon by eating dead organic matter and other microbes and send it back into the atmosphere in the form of carbon dioxide through respiration. We have shown that certain traits—cell size, shape, and contents—are related to population-level temperature responses (TPCs), allowing us to predict ecosystem-level consequences of warming. Complex patterns emerge across levels of organization that ultimately produce a nonlinear relationship between total-system respiration rate and temperature that is predictable based on species' traits. This work shows that traits are key to understanding the impacts of climate across levels of organization.


Climate, functional biogeography, and productivity


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.

For more info, check out the PNAS Science Sessions podcast about this work.


Environmental fluctuations 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, biological invasions during climate warming, and the evolution of tolerance to withstand environmental stress.

Eco-evolutionary processes

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.

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