Welcome to the Weiss-Lehman Lab
Using innovative quantitative approaches to understand the interplay of ecology and evolution in spatially structured systems
Our Mission
Explore, quantify, and test the eco-evolutionary mechanisms driving complex ecological dynamics
Ecology is a science rooted in complexity and variation. This can cause differences among studies performed in different species, different locations, or even different years, complicating the search for generality.
While this can be daunting, we view it as a challenge to apply a mechanistic view of both ecological and evolutionary drivers to disentangle the complexity and explain the variation. To achieve this, we begin with theoretical models and microcosm experiments to rigorously explore and test mechanisms, subsequently linking them to real-world ecological data through sophisticated statistical approaches.
Discover Our Research Approach
We build models to generate testable predictions
Our research approach begins with theoretical explorations of ecological and evolutionary mechanisms. By exploring these eco-evolutionary dynamics in mathematical and computational models, we challenge our assumptions and create empirically testable predictions.
We use microcosms as a model of our natural world
Using controlled microcosms allows us to definitively test a variety of mechanisms (rapid evolution, ecological interactions, etc.) and quantify their contributions to complex dynamics and variation in even relatively simple systems.
Our statistical methods untangle complexity.
Developing novel statistical methods allows us to then do more with the variation present in field data and use that variation to identify the key mechanistic drivers of real-world systems.
Happenings in the lab
Using basic science to address global challenges
Global biodiversity is threatened by multiple forces causing population declines and community upheavals. Whether considering range expansions of invasive species, range shifts in response to climate change, or population persistence in fragmented landscapes, considering the complex interplay of ecological and evolutionary mechanisms in a spatial context can dramatically improve our ability to predict and manage responses of biodiversity to ongoing global changes.
