My research focuses on population models, usually based on matrices, for plants, animals, and humans. I am interested in stochastic processes in demography, including individual stochasticity (random outcomes of individual lives, affecting indices such as longevity), demographic stochasticity (random growth of populations generated by the stochastic outcomes of survival and reproduction), and environmental stochasticity (fluctuations in the vital rates that affect all members of the population). I study both basic theory and the application of that theory, especially to evolutionary questions and to environmental questions related to climate change.
Beyond individuals, it is notable that family dynamics are important for the life histories of humans and of some kinds of animals: primates, whales, some birds, and social insects in particular. Matrix population models may provide an important analytical tool to explore the patterns of kinship and family structures implied by particular sets of demographic processes.
Some of the projects I am currently involved in:
You can download a CV with a complete list of publications here.
I have been fortunate enough to receive two Advanced Grants from the European Research Commission. The new one, beginning in June 2018, is The Formal Demography of Kinship and Family. Its goal is to develop a complete formal demographic structure for studying kinship at the individual, cohort, and population levels. Kinship structures arise from the relation betwen parents and offspring and spread out in directions both earlier (ancestors) and later (descendents) in time. This project is funded through the social science panel at ERC, and is focused on human kinship dynamics. However, it has not escaped my notice that kinship is also an important issue for some non-human species. I intend to investigate these interactions as well; the complexity of life cycles in the plant and animal kingdoms provides plenty of challenges for analysis.
My previous ERC Advanced Grant, Individual stochasticity and population heterogeneity in plant and animal demography (2013-2018) has developed new approaches to partitioning variance in demographic outcomes into contributions from heterogeneity (genuine differences among individuals) and stochasticity (random differences from probabilistic demographic events). A series of publications from the research team has produced new methods for matrix population models, Markov chains, sensitivity analysis, and statistical analyses. We have applied the results to populations of humans, laboratory studies of insects, and field studies of birds. Results will continue to accumulate for quite some time! My list of publications available on another tab here will give an idea of where we are at this point.