Are we all equal? What happens to reproduction and survival among individuals if we take away variability in genotypes and environments?
Welcome to the Evolutionary demography group on stage-and-age-structured biodemography.
Our focus is on advancing demographic methods and theories in stage- and age-structured populations rooted in Markov chain theories. We aim at scaling individual level stage dynamics to population level processes. In particular we are interested in how we can interpret variability in individual fitness components with respect to the evolution of life histories, and ecological and evolutionary demographic dynamics, what role stochastic processes play for aging and senescence, and how they enforce and buffer each other at different levels of organization.
The demographic tools we develop are confronted with data collected using a simple model system, a microfluidic device that collects demographic data of individual bacteria. We explore the evolution and maintenance of phenotypic variability in constant and stochastic environments.
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Generation Time, Net Reproductive Rate, and Growth in Stage-Age-Structured Populations
Steiner U, Tuljapurkar S, Coulson T.
American Naturalist. 2014 Jun;183(6),771-83.
Neutral theory for life histories and individual variability in fitness components.
Steiner U, Tuljapurkar S.
National Academy of Sciences. Proceedings. 2012; 109(12):4684-9.
Trading stages : life expectancies in structured populations.
Steiner U, Tuljapurkar S, Coulson T, Horvitz C.
Experimental Gerontology. 2012; 47(10):773-81.
Structured population models : Introduction.
Tuljapurkar S, Coulson T, Steiner U.
Theoretical Population Biology. 2012; 82(4):241-3.
Dynamic heterogeneity and life history variability in the kittiwake.
Steiner U, Tuljapurkar S, Orzack SH.
The Journal of Animal Ecology. 2010; 79(2): 436-44.
Dynamic heterogeneity and life histories.
Tuljapurkar S, Steiner U.
New York Academy of Sciences. Annals. 2010; 1204: p. 65-72.