Competition for food affects the strength of reproductive interference and its consequences for species coexistence

Abstract

Competition for food and reproductive interference (negative interspecific sexual interactions) have been identified as major drivers of species exclusion. Still, how these biotic interactions jointly determine competitive dominance remains largely unknown. We tackle this by coupling population models and laboratory experiments with two sibling species of spider mites. Using experiments specifically designed to measure the single and combined effects of food competition and reproductive interference, we first show that the strength and symmetry of reproductive interference between species changes in the presence of food competition. Next, we show that population models incorporating each type of interaction alone lead to markedly different predictions, from systematic exclusion of one of the two species under food competition to priority effects instead favouring this same species (the inferior competitor for food) under the sole effect of reproductive interference. Moreover, accounting for the observed reduction in the strength of reproductive interference in the presence of food competition changes the threshold frequency determining the dominant competitor when both interactions are at play, from equal chances for the two species to exclude the other depending on their initial frequency to favouring the superior competitor for food except when it is extremely rare. Finally, we showed that the model generates accurate predictions for population dynamics in an independent population cage experiment, indicating that our approach captures the most relevant processes governing the outcomes of interactions between competing spider mite species. Altogether, our results suggest that trophic interactions can modulate sexual interactions, significantly impacting population dynamics and competitive outcomes. Hence, the joint consideration of food competition and reproductive interference is critical to accurately predict and understand species coexistence.