Why network analysis is often disconnected from community ecology: A critique and an ecologist's guide

Network analyses of mutualistic or antagonistic interactions between species are very popular, but their biological interpretations are often unclear and incautious. Here I propose to distinguish two possible implications of network patterns in conjunction with solutions to avoid misinterpretations. Interpretations can be either (1) niche-based, describing specialisation, trait (mis-)matching between species, niche breadth and niche overlap and their relationship to interspecific competition and species coexistence, or (2) impact-based, focusing on frequencies of interactions between species such as predation or infection rates and mutualistic services, aiming to quantify each species' relative contribution to an ecological effect. For niche-based implications, it is crucial to acknowledge the sampling limitations of a network and thus control for the number of observations of each species. This is particularly important for those kinds of networks that summarise observed interactions in communities (e.g. bipartite host-parasitoid or plant-animal networks), rather than compile information from different sources or experiments (as in many food webs). Variation in total observation frequencies may alone explain network patterns that have often been interpreted as 'specialisation asymmetries' (nestedness, dependence asymmetries). I show analytically that 'dependence asymmetries' between two species (or two guilds) only reflect variation in their total observation frequencies. To depict true asymmetries in niche breadth, independent data are required for both species. Moreover, simulated co-extinction scenarios assume that each species 'depends' on its associated partners in the network (again niche-based), but species that appear most endangered are simply those with one or very few observations and are not necessarily specialised. Distinguishing niche-based and impact-based interpretations may help to bridge terminological and conceptual gaps between network pattern analyses and traditional community ecology. (C) 2010 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.