COS 270-3 - Shortcomings of reusing species interaction networks created by different sets of researchers

Abstract: Given the requisite cost associated with observing species interactions, ecologists often reuse species interaction networks created by different sets of researchers to test their hypotheses regarding how ecological processes drive network topology. Yet, topological properties identified across these networks may not be sufficiently attributable to ecological processes alone as often assumed. Instead, much of the totality of topological differences between networks---topological heterogeneity---could be due to variations in research designs and approaches that different researchers use to create each species interaction network. To evaluate the degree to which this topological heterogeneity is present in available ecological networks, we first compared the amount of topological heterogeneity across 723 bipartite species interaction networks created by different sets of researchers with the amount quantified from non-ecological bipartite networks known to be constructed following more consistent approaches. Then, to further test whether the topological heterogeneity was due to differences in study designs, and not only to inherent variation within bipartite ecological networks, we compared the amount of topological heterogeneity between bipartite species interaction networks created by the same sets of researchers (i.e., networks from the same publication) with the amount quantified between bipartite networks that were each from a unique publication source. We found that bipartite species interaction networks are highly topologically heterogeneous: while species interaction networks from the same publication are much more topologically similar to each other than interaction networks that are from a unique publication, they still show at least twice as much heterogeneity as any category of non-ecological bipartite networks that we tested. Altogether, our findings suggest that extra care is necessary to effectively analyze species interaction networks created by different researchers, perhaps by controlling for the publication source of each network.