Invading a mutualistic network: to be or not to be similar

Abstract

Biological invasion remains a major threat to biodiversity in general and a disruptor to mutualistic interactions in particular. While a number of empirical studies have directly explored the role of invasion in mutualistic pollination networks, a clear picture is yet to emerge and a theoretical model for comprehension still lacking. Here, using an eco‐evolutionary model of bipartite mutualistic networks with trait‐mediated interactions, we explore invader trait, propagule pressure, and network features of recipient community that contribute importantly to the success and impact of an invasion. High level of invasiveness is observed when invader trait differs from those of the community average, and level of interaction generalization equals to that of the community average. Moreover, multiple introductions of invaders with declining propagules enhance invasiveness. Surprisingly, the most successful invader is not always the one having the biggest impact on the recipient community. The network structure of recipient community, such as nestedness and modularity, is not a primary indicator of its invasibility; rather, the invasibility is best correlated with measurements of network stability such as robustness, resilience, and disruptiveness (a measure of evolutionary instability). Our model encompasses more general scenarios than previously studied in predicting invasion success and impact in mutualistic networks, and our results highlight the need for coupling eco‐evolutionary processes to resolve the invasion dilemma.

Using Network Theory to Understand and Predict Biological Invasions

“…Given that ecological interaction networks vary greatly among ecosystems, habitats, or communities [44,45], understanding how network structure is related to niche space available for invasion, and ultimately invasibility, may allow us to identify communities that are resistant or vulnerable. For antagonistic networks, the prediction that high connectance should simultaneously confer stronger biotic resistance to higher trophic levels and provide fewer available niches for invaders has mixed support from theoretical studies [29][30][31]46,47]. These varying results suggest that the relationship between network connectance and invasibility is complex and may vary with other factors, such as species richness (diversity-invasibility hypothesis, [19,31]), the trophic level being invaded [29,44,48], and the relative strength of interspecific interactions and intraspecific density dependence [49].…”

Coexistence theory as a tool to understand biological invasions in species interaction networks: Implications for the study of novel ecosystems

“…Contrary to competitive networks, such trophic structures have received much more attention in the literature, particularly in the last years (Bohan, Dumbrell, & Massol, ; Hui & Richardson, ). Examples range from mutualistic interactions in plant–pollinator networks (Aizen, Morales, & Morales, ; Minoarivelo & Hui, ; Traveset & Richardson, ) and plant–rhizobia networks (Le Roux, Hui, Keet, & Ellis, ) to antagonistic interactions mainly in food webs (David et al, ; Patterson et al, ; Smith, ). It is therefore not my intention to provide here a summary of how prior work has established connections between these trophic networks and invasion biology.…”

“…Contrary to competitive networks, such trophic structures have received much more attention in the literature, particularly in the last years (Bohan, Dumbrell, & Massol, 2017;Hui & Richardson, 2019). Examples range from mutualistic interactions in plant-pollinator networks (Aizen, Morales, & Morales, 2008;Minoarivelo & Hui, 2016;Traveset & Richardson, 2014) F I G U R E 2 A structural approach to understand species coexistence (Saavedra et al, 2017) is readily available to explore the invasibility question in full detail by studying the role of the network of species interactions in promoting or limiting invasion. Here is represented the case of a competitive network composed of three species for visualization purposes.…”

Modelling coevolution in ecological networks with adaptive dynamics

“…High tolerance as in many generalists often leads to bias between interacting traits. Strong cross‐trophic interactions often lead to convergence evolution towards an ESS, while species involving weak cross‐trophic interactions behave independently as resource competition within its own functional group . Mutualistic interactions can trigger diversification when the cross‐trophic interaction is moderate so that asymmetric fitness between the 2 groups often triggers the diversification in the less fit group .…”