Abstract
We study how the community structure of bipartite mutualistic networks changes in a dynamic context. First, we consider a real mutualistic network and introduce extinction events according to several scenarios. We model extinctions as node or interaction removals. For node removal, we consider random, directed and sequential extinctions; for interaction removal, we consider random extinctions. The bipartite network reorganizes showing an increase of the effective modularity and a fast decrease of the persistence of the species in the original communities with increasing number of extinction events. Second, we compare extinctions in a real mutualistic network with the growth of a bipartite network model. The modularity reaches a stationary value and nodes remain in the same community after joining the network. Our results show that perturbations and disruptive events affect the connectivity pattern of mutualistic networks at the mesoscale level. The increase of the effective modularity observed in some scenarios could provide some protection to the remaining ecosystem.
Highlights
Mutualistic interactions between species are often represented as bipartite networks, where the interactions occur between two groups of species, but not within the groups
We have studied the evolution of the community structure of an empirical ecological bipartite network in the context of extinction of consumer nodes
To do so we have introduced 5 different extinction scenarios to account for different extinction dynamics: 1) random node extinction, 2) directed extinctions, 3) generalist extinctions, 4) specialist extinctions and 5) random interaction extinctions
Summary
Mutualistic interactions between species are often represented as bipartite networks, where the interactions occur between two groups of species (generically resources and consumers), but not within the groups. The number of communities (Fig. 4b) is increased initially in all the scenarios, but remains constant around 10 communities for random node extinctions and specialist extinctions, decaying fast when the fraction of extinction events is almost 1 due to network decomposition. For versatility (Fig. 5) the results show that random node and interaction extinctions behave with a decreasingly less defined community structure up to 75-80% of extinction events (growing versatility), followed by a decrease in versatility, associated with a more solid community structure. Structures in growing bipartite Networks we generate bipartite networks using an evolutionary model of mutualistic webs, through speciation and divergence of weights (Valverde et al 2018) and perform numerical simulations to detect the community evolutions (Fig. 6) In this model, nodes are considered to be either present or absent, with no role to be played by population size. The modularity and the nestedness remain low and constant during the network evolution (Fig. 8), in contrast with their response when the nodes are removed in any of the scenarios presented above
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