Simulations of Life History Variation for Demographic Inference From Population Genomic Data

Ecological differences among species, particularly dispersal capacity and life history strategies, influence population response to environmental changes. Genetic simulations now allow us to directly incorporate this variation into models of past demographic changes. However, the impact of life history strategies in demographic inference has been far less explored relative to that of dispersal capacity. Here, we utilise individual-based simulations of a non-Wright-Fisher population to ask whether differences in life history traits (the average age of first reproduction of individuals, the average adult mortality and the average number of mates per reproductive season) lead to consistent and predictable differences in the summary statistics of genetic diversity commonly used for simulation-based parameter estimation and demographic inference. Using a Random Forest model, we also estimate three population parameters (variance in reproductive success, generation time and effective population size) from genome-wide SNP variation for two bird species known to have distinct life history strategies. The results demonstrate that life history variation leads to predictable differences in patterns of genetic diversity: higher values of life history traits, representing extreme polygamy, long adult longevity and later onset of reproduction, are associated with higher variance in reproductive success, longer generation times, smaller effective population sizes and overall lower genetic diversity. Parameter estimates from empirical datasets also agree with the general expectation that polygamic species with later onset of reproduction and long adult longevity exhibit higher variance in reproductive success, longer generation times and smaller effective population sizes. Since the signal of life history differences is observed in the genetic summary statistics, we argue that simulation- and model-based multi-species demographic inference will gain from the incorporation of life history information.