ABSTRACTRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics of network centrality. These centrality measures often rely on the calculation of the shortest path connecting any two nodes, and while the interpretation of a shortest paths is straightforward in binary,

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... weighted networks, whenever weights are accounted for, inconsistency between weight definition and shortest path interpretation could yield unexpected results. Here we review 129 studies of ecological networks published in the last decade and making use of shortest paths. We evidenced a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures) in ecological studies, particularly in interaction networks. Specifically, we found numerous studies in which the edge weights were not transformed prior to calculating shortest paths when the edge weights were proportional to the information flow between the nodes of the network at study. 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point check-list to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies.