Discovery Early Career Researcher Award - Grant ID: DE180101520
Funder
Australian Research Council
Funding Amount
$365,058.00
Summary
Diet, variance and individual variability in life-history. This project aims to provide biologists with novel statistical tools that will shift analytical paradigms. In many species, dietary restrictions increase average lifespan, and affect average rates of growth and reproduction, also known as ‘life history’. The use of recently developed tools has shown that individual variability in life history also appears to increase under dietary restrictions. This project will explore the effects of di ....Diet, variance and individual variability in life-history. This project aims to provide biologists with novel statistical tools that will shift analytical paradigms. In many species, dietary restrictions increase average lifespan, and affect average rates of growth and reproduction, also known as ‘life history’. The use of recently developed tools has shown that individual variability in life history also appears to increase under dietary restrictions. This project will explore the effects of diet composition on variability in life-history traits, and the factors driving this variation. This is expected to improve the prediction of the effects of changing nutritional environments.Read moreRead less
Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provi ....Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provide a new way of fitting a wide class of statistical models to evolutionary data, in a very general setting. Further, this project will unite current methodology in a broader framework so that the proposed new methods are a generalisation of currently accepted theory. The outcomes will include a freely-available software package that implements the methods in a user-friendly form.Read moreRead less