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PREDICTING POPULATION DYNAMICS FROM QUANTITATIVE TRAITS IN APODEMUS SYLVATICUS (APODYNA)
Start date: 01 Jul 2008, End date: 30 Jun 2010 PROJECT  FINISHED 

"Population biology is concerned with understanding how population size, phenotypic trait distributions and allele frequencies fluctuate in time. Identifying how and why variation in demographic rates generates changes in the three, and in turn, how variation in these factors feeds back on variation in demographic rates, is consequently central to population biology. There are multiple factors that influence demographic rates including life history, environmental variation, density-dependence, age structure and chance. One way to incorporate this complexity is to examine how trait distributions arise at a point in time, how these influence demographic rates, and how the realised demography alters the trait distributions at the next point in time. In this proposal we will use an approach that describes the consequences of feedback between trait distributions and demography to understand the association between trait dynamics and population dynamics, hence addressing questions in animal stochastic demography. Specifically we are interested in understanding the links between inter-individual variation in life-histories (expressed as distributions of phenotypic traits) and population dynamics. In order to do so we have identified a wild species of rodent as a model species, the Wood mouse (Apodemus sylvaticus), which will allow collecting data on phenotypic traits, their distribution and population size over time. In technical terms we will be statistically characterising the link between trait variation and population growth and asking how these associations vary with time. We will then combine these statistical associations into population models. Understanding population dynamics is important for predicting population behaviour and this has practical implications for the management of threatened or endangered species relevant for conservation and of pest species which affect agriculture and that poses a risk to human health as disease vectors."
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