Examining the expansion of qualitative network models towards integrating multifaceted human dimensions

Abstract

Abstract Qualitative network models (QNMs) have become a popular tool to assess how ecosystems respond to a perturbation within ecosystem-based fisheries management strategies. Yet, the incorporation of humans into these models is often rudimentary, potentially limiting the accuracy and reliability of the model results. We developed QNMs focusing solely on the social components, derived from content analysis of the literature on the effects of the US Pacific halibut Individual Fishing Quota (IFQ) Program and evaluated how the QNMs performed with respect to simulating the programmatic effects on individual well-being components. The QNMs were effective at reproducing IFQ programmatic effects and demonstrating how well-being heterogeneity across user groups can be incorporated into network models. However, key mechanistic variables were omitted to maintain model stability, reducing our ability to fully replicate the IFQ system. We conclude that QNMs require improvement to incorporate human dimensions that reflect broader social realities. Yet, given the current structural limitations of these modelling frameworks coupled with the complexity of human decision making, there are likely to be continued issues with integrating humans accurately and representatively into these models.