A novel coextinction model considering compensation and new interactions in ecological networks

Abstract

The robustness of communities to species loss is a major topic in ecological research. Here, we introduce the Dependent random-search Coextinction Model (DCM), a new approach for modelling the consequences of primary extinctions in ecological networks. The DCM assumes that species may persist after a primary extinction through two non-exclusive mechanisms: compensation (i.e., by increasing the interaction strength with living partners) and new interactions. In the DCM, the strengths of the compensated interactions are proportional to the dependence on the lost partner, while the strengths of new interactions are proportional to the resemblance (e.g. phylogenetic, functional) between the extinct partners and the new ones. Using simulations with mutualistic webs as templates, we show that the probability of extinction cascades and the total number of extinctions decrease in highly connected networks, and the probability of extinction cascades increased in highly nested networks. The proposed model is simple and can be used in a variety of interaction networks (e.g. mutualistic, food webs, host-parasite), with any species-species resemblances representing ecological or evolutionary dissimilarities.