1. The development of pattern-based models to predict how communities will respond to environmental changes. Instead of trying to make predictions about community composition by building a mechanistic, dynamical model from the ground up, my work focuses on building probabilistic models that best recovers the emergent patterns of the system (e.g., which species can coexist with each other). For this work, I use both global forest inventory datasets as well as experimental data generated by a network of colleagues. By avoiding the need to mechanistically model the dynamics of the community, this approach bypasses many of the challenges that plague traditional efforts to predict species' and community responses to disturbances, giving us the potential to make real-time projections of how coexistence and community structure will respond to environmental change. 

2. Disentangling how biotic and abiotic processes structure broad-scale biodiversity patterns. The resilience of ecosystems is tightly coupled to the underlying community assembly processes, which govern the functional diversity of the community. In places where habitat filtering is the overriding filter on community composition, slight changes in environmental conditions can lead to drastic changes in species occurrences. In locations where biotic processes dominate, changes in environmental conditions should alter the strength of interactions, thereby shuffling the relative abundance of species. In this work, I identify unifying trends that allow us to infer underlying assembly processes from patterns in functional and phylogenetic diversity, with an emphasis on how these patterns shift across scales, habitats, and traits. 

3. The maintenance of biodiversity through the lens of functional ecology. Instead of using the traditional taxonomic approach, much of my work adopts a functional approach to understanding the drivers of biodiversity. Doing so has provided key insight into trait trade-offs governing biogeographical patterns, the demarcation of species' niches and the drivers of coexistence and diversity in spatially structured, sessile microbial communities. By focusing on traits rather than taxonomic identities, my work seeks to provide a scalable and mechanistically-informed approach to understanding ecological patterns and processes in hyper-diverse natural ecosystems. 

By addressing these questions at various scales and systems -- most notably using global forest inventory data and experimental microbial systems -- we look to find overarching principles that extend across study systems. In doing so, we aim to develop new tools and approaches that can help address the biodiversity and climate crises in real time.