Interaction Matrices as Unifying Tools for Navigating Ecological Complexity

Interaction matrices summarise pairwise species impacts within ecological communities into an analytically tractable format and have been central to advancing our understanding of ecosystem dynamics. However, despite their ubiquity, they have faced constant, recurring, criticism for oversimplifying ecological complexity. While suggested extensions address specific shortcomings, they often come with significant trade-offs, including increased data demands and analytical complexity. Despite their challenges, interaction matrices have been a nexus of fundamental ecology connecting many subdisciplines, representing both cause and consequence of ecological dynamics. Here we overview the fundamental definitional, dynamism and data challenges confronting the interaction matrix framework and critically examine the current state-of-the-art of approaches developed to tackle them. We contend that the centrality of interaction matrices within academic ecology is set to continue. Nonetheless, their role as a unifying and focus of synthesis could be markedly improved by refreshing how they are considered. We argue that by fully embracing, rather than fighting, their inherent nature as uncertain, transient abstractions, ecology can better maximise their potential as a unifying nexus of ecological research and incorporate advances in wider complexity sciences. As we enter the second century of their use within ecology, such a shift will reinforce interaction matrices as a valuable tool to unlock the complex dynamics of ecological communities.