Using causal loop diagrams to develop evaluative research propositions: opportunities and challenges in applications to nature‐based solutions

Abstract

Causal loop diagrams (CLDs) are often used to provide an overview of important systemic elements related to an issue, rather than to inform empirical evaluations (studies which assess changes following an intervention using observed data). We suggest that empirical evaluations may benefit from the development of systems‐informed research propositions (specific testable causal assumptions with an emphasis on feedback loops) used to guide subsequent data collection, hypothesis testing and interpretation. We describe a qualitative systems‐thinking informed approach building on preexisting CLDs, published evidence, and expert/stakeholder consultation and reflect on our experience applying this to the early stages of two nature‐based solution (NBS) evaluations. We reflect on our experience and suggest that CLDs can be usefully employed to develop systems‐informed research propositions to inform subsequent empirical evaluation. This may lead to novel policy‐relevant research propositions which differ substantially from effectiveness‐oriented (“did it work?”) research questions.