Motifs in bipartite ecological networks: uncovering indirect interactions

Abstract

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant–pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network‐ and species‐level indices for characterising the structure of bipartite ecological networks.

Effects of species traits, motif profiles, and environment on spatial variation in multi‐trophic antagonistic networks

“…, Olito and Fox , Simmons et al. ). Studies testing mechanisms for interaction turnover rarely validate that their proposed mechanisms are correctly predicting observed interactions, and thus, the observed similarity between empirical and predictive models of interaction turnover may be arising for the wrong reasons (Olito and Fox ).…”

“…A recent study by Simmons et al. () used a motif approach and demonstrated that it was significantly more effective at describing network structure than traditional network metrics. Further, when Baker et al.…”

“…, Olito and Fox , Simmons et al. ) and how individual species roles are altered by interaction turnover Baker et al. ().…”

“…One of the more tangible consequences of global change is fluctuations in local trait distributions, potentially leading to the uncoupling of traits between species (e.g., Olesen et al 2011, Gonz alez-Varo andTraveset 2016), a de-coupling which could be causing the rewiring of interactions across spatial gradients, potentially altering network structure and function. It has been recently demonstrated, however, that many mechanistic explanations of species' interactions are successful at predicting the summary statistics of networks (e.g., connectance), but fail to predict species-specific interactions (e.g., Allesina et al 2008, V azquez et al 2009, Olito and Fox 2015, Simmons et al 2019. Studies testing mechanisms for interaction turnover rarely validate that their proposed mechanisms are correctly predicting observed interactions, and thus, the observed similarity between empirical and predictive models of interaction turnover may be arising for the wrong reasons (Olito and Fox 2015).…”

“…These three-species motifs consist of 13 possible recurring three-node subgraphs observed across a variety of networks from biomolecules to neural cells (see Milo et al 2002 for more discussion). A recent study by Simmons et al (2019) used a motif approach and demonstrated that it was significantly more effective at describing network structure than traditional network metrics. Further, when Baker et al (2015) used this approach to measure the spatial and temporal variation in individual species roles in 22 host-parasitoid communities, they observed that despite a 50% turnover in species and a 70% turnover in interactions between years, species' roles were highly conserved.…”