The role of self-organized spatial patterns in the persistence of weak invasive species: A case study of the invasive ant W. auropunctata
Using a spatially explicit multispecies competition framework, we examine how self-organized spatial patterns impact the invasive dynamics of the ant W. auropunctata. Based on the classical dominance-discovery trade-off, with some species being good resource dominators and others being good resource discovers, we modeled the competitive interactions between native and invasive ant species. We constructed a stochastic cellular automata model with connected lattices. The bottom lattice represents the terrestrial ant community and the top lattice represents the arboreal ant community, in accordance with the natural history of W. auropunctata. We establish the species covariance of the potential invader as the covariance of the row competition coefficients versus the column competition coefficients. We determine the community covariance of the native ant community as the covariance of the row and column sums of the competition matrix. Given this theoretical framework, we investigate how the species covariance of the invader interacts, through migration between the lattices, with the overall community covariance of the native species to determine under which conditions the invasive species is able to spread in the community.
Our results show that when native species form a positive covariance and thus generate spatial mosaic patterns, the invader is not able to enter the community. However, when the overall structure of the community is a negative covariance, resulting in spiral spatial patterns, then invasion is possible even when the invader is a weak competitor. This study highlights the important role of spatial pattern formation on the invasion dynamics of W. auropunctata.