Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks

Abstract

Understanding the response of ecological networks to perturbations and disruptive events is needed to anticipate the biodiversity loss and extinction cascades. Here, we study how network plasticity reshapes the topology of mutualistic networks in response to species loss. We analyze more than one hundred empirical mutualistic networks and considered random and targeted removal as mechanisms of species extinction. Network plasticity is modeled as either random rewiring, as the most parsimonious approach, or resource affinity-driven rewiring, as a proxy for encoding the phylogenetic similarity and functional redundancy among species. This redundancy should be positively correlated with the robustness of an ecosystem, as functions can be taken by other species once one of them is extinct. We show that effective modularity, i.e. the ability of an ecosystem to adapt or restructure, increases with increasing numbers of extinctions, and with decreasing the replacement probability. Importantly, modularity is mostly affected by the extinction rather than by rewiring mechanisms. These changes in community structure are reflected in the robustness and stability due to their positive correlation with modularity. Resource affinity-driven rewiring offers an increase of modularity, robustness, and stability which could be an evolutionary favored mechanism to prevent a cascade of co-extinctions.

High-order interactions maintain or enhance structural robustness of a coffee agroecosystem network

“…In our study, the structural robustness of the network was evaluated with the change in size of the biggest connected component as the nodes were gradually removed, at random or by targeting nodes of higher degree first. This way of conceptualizing robustness assumes that the connection between network components is related to the function and integrity of the system, implying that a fully connected network can maintain its elements and overall functions better than a disaggregated or partially disconnected network (Albert et al 2000; Dekker & Colbert 2004; Piraveenan et al 2013; Sheykhali et al 2020). Indeed, previous work on the coffee agroecosystem for which the network under study has been uncovered suggests that some agroecosystemic functions, such as pest control, rely on the dynamics of the whole system and on the documented interactions taking place (Vandermeer et al 2010).…”

Impacts of plant invasions in native plant–pollinator networks

“…This high network resilience could be at least in part attributed to high interaction rewiring within communities, wherein a redundancy of interactions leads to a rapid replacement of native interactions that are lost due to the introduction of invasive species (e.g. Fonseca & Ganade, 2001; Ramos‐Jiliberto et al ., 2012; Sheykhali et al ., 2020; Vizentin‐Bugoni et al ., 2020) (Fig. 3a).…”

Characterising the response of plant-mycorrhizal networks to a changing alpine environment

“…Network analysis can also be used to illuminate other important functional characteristics within the community. In particular, Sheykhali et al, (2020) highlights how the computation of network "modularity" can reveal how significant properties such as interaction plasticity, generality and specialism are to a community's structure (Sheykhali et al, 2020). The primary limitation in the network approach is a result of the inherent restrictions of sampling ecological communities.…”

“…Determining these properties of network architecture further reveal key attributes that define a network's structure and robustness (Sheykhali et al, 2020). In particular, species that share common interaction partners, affect a redundancy that provides the network function a robustness to species loss (Biggs et al, 2020).…”