We are interested in demography, ecology, and evolution, and how neutral and adaptive processes shape populations in stochastic environments. We aim at understanding the evolution and maintenance of individual heterogeneity, how it drives ecological and evolutionary population dynamics, and whether it is neutral or adaptive.
We address these questions by developing structured models and thereby link quantitative genetics, population genetics, life history theory, and population dynamics. These models are tested by with empirical data that span in level of control, from highly controlled bacteria microfluidic systems to data collected on natural populations.
We aim to bridge the gap between empirical and theoretical approaches within and across fields.
We work on age-stage structured population models to link individual level demographic data to population level dynamics. Much of this work is in collaboration with Shripad Tuljapurkar, Stanford. We ask how individual dynamics have evolved by investigating sensitivities to the rate of diversification of life histories, trade-offs at the individual level, and investigate how stochastic processes at different levels of biological organization buffer or enhance each other to drive population dynamics.
We investigate influences of density dependence on stage dynamics and the diversity of life histories. For this question we use longitudinal data on macaques from Cayo Santiago. This work is in collaboration with Raisa Hernandez-Pacheco, USULB.
We study aging and senescence in bacteria using a highly automated microfluidic system in order to bridge the gap between single cell transcription and protein expression dynamics, the demographic fates of individual cells and the evolutionary consequences at the population level. We detect classical senescence patterns of progeny born early in the life of a cell (early daughters), whereas late daughters do not show senescence and are born at an older biological age. Our results suggest stochastic patterns of damage accumulation within and stochastic transmission across generations. This work is in collaboration with the CRI and INSERM U1001 in Paris.
Biomarkers of aging in humans. In investigating the difference between the biological or perceived age (how old one looks) and chronological age (how old one is) we aim at addressing a series of questions related to the rate of aging and the quantification of biological age. The data is largely collected through a citizen science project (ageguess.org) for which we collaborate with Dusan Misevic at INSERM/Paris Descartes, France.
Our interest on the evolution of neutral and adaptive processes in variable environments also captures work on the evolution of phenotypic plasticity, mainly related to cryptic genetic variation and whether plasticity is adaptive. This work is in collaboartion withoup lead by Courtney Murren and Carl Schlichting.