Early-warning signals of impending speciation

Species formation is a central topic in biology, and a large body of theoretical work has explored the conditions under which speciation occurs, including whether speciation dynamics are gradual or abrupt. In some cases of abrupt speciation, differentiation slowly builds up until it reaches a threshold, at which point linkage disequilibrium (LD) and divergent selection enter a positive feedback loop that triggers accelerated change. Notably, such abrupt transitions powered by a positive feedback have also been observed in a range of other systems. Efforts to anticipate abrupt transitions have led to the development of early warning signals (EWS), that is, specific statistical patterns preceding abrupt transitions. Examples of EWS are rising autocorrelation and variance in time-series data due to the reduction of the ability of the system to recover from disturbances. Here, we investigate whether speciation dynamics in theoretical models also exhibit EWS. Using a model of genetic divergence between two populations, we search for EWS before gradual and abrupt speciation events. We do so using six different metrics of differentiation: the effective migration rate, the number of selected loci, the mean fitness of our studied population, LD, F-ST, and D-abs, a metric analogous to D-XY. We find evidence for EWS, with a heterogeneity in their strength among differentiation metrics. We specifically identify F-ST and the effective migration rate as the most reliable EWS of upcoming abrupt speciation events. Our results provide initial insights into potential EWS of impending speciation and contribute to efforts to generalize the mechanisms underlying EWS.

Automated summary

Species formation is a fundamental topic in biology and theoretical studies have investigated the conditions and dynamics of speciation. Both gradual and abrupt speciation events have been observed, with the latter being driven by positive feedback loops. Early warning signals (EWS) have been developed to anticipate abrupt transitions, based on statistical patterns observed before such transitions. In this study, the authors investigate the presence of EWS in speciation dynamics using a theoretical model, finding evidence for EWS and identifying particular metrics as reliable indicators of upcoming abrupt speciation events. These findings contribute to our understanding of the mechanisms underlying EWS and their potential application in predicting speciation events.