Stakeholder participation is increasingly seen as beneficial for short and long term responses to climate change risks. Past research highlights the role social networks play as both a key outcome of participation, as well as an important step towards other environmental governance goals. This paper focuses on the social relation of mutual understanding, which is often discussed in the environmental governance literature, but has yet to be studied as an empirical social network in its own right. Our paper builds and tests a conceptual framework linking participation to mutual understanding and social learning. We analyze three waves of network and perceptions data gathered on stakeholders participating in the Integrated Coastal Resiliency Assessment (ICRA) project, a 2.5 year-long project aimed at developing a collaborative research assessment on the vulnerabilities to climate change experienced by an island community located in the Chesapeake Bay, USA. Our findings suggest that participation (measured as co-attendance in project events) leads to the formation of mutual understanding ties among stakeholders, but these ties do not necessarily lead to more similarity in stakeholders’ perceptions on climate change. We reflect on these findings, and the project more broadly, noting that our study lends support to scholars arguing that feelings of mutual understanding are potentially more important for certain forms of collective action, as opposed to whether or not stakeholders increase their shared beliefs or perceptions about the environmental problem in question.@en

Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.@en