What makes populations, communities, and ecosystems fluctuate in time and space? Why are some communities more stable than others? Given the inherently variability of ecological systems, how can we best forecast future states at spatial scales relevant to land managers? These questions form the core of my research program, and I strive to answer them by bringing together dynamic statistical models and data. A major theme throughout my research is the concept that ecosystem functioning can ultimately be understood through the lens of population dynamics (e.g., Michel Loreau’s great book, ‘From Populations to Ecosystems’). So, I use dynamic population models and long term datasets to understand what makes communities and ecosystems stable, or not. The overarching goal of my research is to understand the causes and consequences of biodiversity.

The Drivers of Ecosystem Stability

Ecosystems are hierarchical: individuals within populations within communities within metacommunities within… You get the idea. The dynamics within each hierarchical level help to determine the stability of ecosystem functioning through time and over space. Our work seeks to understand the processes the determine stability at multiple spatial scales. At the local, community level, we use multi-species population models fit to long term demographic data to decipher how environmental stochasticity, demographic stochasticity, and interspecific interactions combine to determine the degree of synchrony.

Looking across spatial scales, I am collaborating with Kevin Wilcox, Sally Koerner, Emily Grman, and Lauren Hallet on an empirical test of theory on the drivers of ecosystem stability in space. We are using data from aound the globe to identify how asynchrony among species through time and communities in space determines aggregated, landscape level ecosystem stability.

We have also developed new theory to explicitly link modern coexistence theory and biodiversity-ecosystem functioning theory. Both bodies of work recognize the key role of environmental variability, but how coexistence mechanisms alter the relationship between diversity and stability remains unknown (until now).

Ecological Forecasting

A major challenge facing ecology in the 21st century is predicting the consequences of climate change. To meet this challenge, we have developed a new approach to make population forecasts at the landscape scale using remotely-sensed time series of plant abundance. We are also interested testing different approaches for making population forecasts at spatial scales beyond the traditional field study plot. We are particularly interested in understanding the limits to ecological forecasts in time and space, and discovering if those limits can be overcome. We do this by partitioning forecast uncertainty to identify the sources of uncertainty and how those increase (or decrease) over time.

Tree Harvest and Alternative Stable States in Africa

My PhD work focused on the sustainability and biome-level impacts of tree harvest for fuelwood in sub-Saharan Africa. Our work on the sustainability of tree harvest across Africa is still in the works, but we have used theory to show how tree harvest effects stable state dynamics between forest and savanna. My collaborators and I are also actively engaged in research on detecting and delimiting hypothesized alternate stable states in Africa.