François Rousset

Brassica rapa pollen tube length after growing through recipient pistil tissue is donor-by-recipient specific, predicts siring success under competition, and matters more in longer-styled recipients.

The paper provides the first empirical test of cryptic female choice in an angiosperm, showing that pistil traits influence paternal fertilization success based on pollen donor traits.

The paper introduces an iterative framework for population genetic inference using simulation and machine learning, showing improved confidence interval coverage compared to existing methods.

This study quantifies sexual selection in Brassica rapa by integrating pollinator monitoring and genetic paternity analysis, showing pollinator abundance affects pre- and post-pollination selection.

This study evaluates adaptive introgression classification methods using simulated datasets from different evolutionary scenarios, finding that Q95-based methods are most efficient for exploratory analysis.

The paper develops likelihood methods for inferring migration rates and demographic changes using coalescent models and sequential importance sampling techniques.

This paper introduces mixed models for modeling isoscapes, showing higher predictive power than alternative methods for hydrogen isotope composition in European precipitation.