Our goal is to advance a more predictive ecological science to better meet societal needs in coming decades. We focus on delineating the limits to predictability, and developing novel concepts to improve predictability, at scales ranging from communities to continents. Our focus is primarily on understanding plant biodiversity from the interplay of ecophysiological, historical, and anthropogenic processes.

We use a combination of fieldwork, informatics, and modeling approaches to address these focus areas. We carry out fieldwork and monitoring programs in forests in the Neotropics and southeast Asia, and in alpine environments in North America and Scandinavia. We also develop a range of software tools to support research efforts of others, and lead education and capacity-building efforts to work towards a more inclusive and relevant science.

Paleoecological and anthropogenic perspectives on community dynamics

Past climate change and past human uses of landscapes may have a strong legacy on contemporary biodiversity patterns. Understanding these effects will be key to making robust predictions about future biodiversity dynamics. We develop concepts for understanding disequilibrium in communities and regions based on these effects, and also carry out comparative empirical studies using large eco-informatics resources and various Holocene and Anthropocene data sources.

Ecological and evolutionary drivers of vascular networks

Plants have leaves characterized by an intricate network of veins. These venation networks may play a key role in mediating plant performance via tradeoffs inherent to the construction of resource supply and distribution networks, and are a key example for understanding the general properties of other transport networks, e.g. urban systems. We are interested in understanding how the geometry of these networks reflects their evolutionary history and ecological context, to better use network traits to predict species functioning and distribution. We are especially interested in variation in reticulation (looping) within these networks. We develop conceptual and software approaches for quantifying these networks as well as carry out broad-scale trait measurements across environments and clades.

Hypervolume concepts in functional diversity and environmental niche modeling

Hutchinson's n-dimensional hypervolume concept underlies many areas of modern ecology and evolutionary biology. We examine the potential and the limitations of this approach for modeling species' distributions, quantifying functional diversity, and understanding community dynamics.

Scaling up plant traits to demography and distributions

We work to scale up plant functional trait measurements to performance, demographic parameters, and geographic distributions. We use a combination of ecophysiological and energy budget modeling approaches coupled to modern coexistence theory. Fieldwork includes monitoring and trait measurement campaigns throughout the world.

Incorporating species interactions into community dynamics

Biotic interactions play a key ecological role in shaping the compositions and dynamics of communities. We investigate trait-based approaches for predicting these interactions, as well as observational approaches for detecting them. We also develop theory for controlling and manipulating interaction networks and ultimately community structure.

Macroecology of urban systems

Urban systems share some important similarities to ecological systems in terms of their composition and spatiotemporal dynamics. We apply ecological concepts and use informatics methods to better understand constraints on urban development and diversity, and to better predict how future urbanization processes can be shaped to support better outcomes for humans and nature.


Aarhus University Ecoinformatics and Biodiversity Group
Arizona State University Center for Biodiversity Outcomes
Botanical Information and Ecology Network (BIEN3)
University of Oxford Global Ecosystem Monitoring network