Predicting species invasiveness with genomic data: is Genomic Offset related to establishment probability?

Abstract

Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species, but have still rarely been used in this context. Here, we evaluated the relationship between GO and the estab-lishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which the-oretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public real data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the estab-lishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g. propagule pressure or admixture) will need further investigation.