Local perspectives provide different insights into disaster planning and response as compared to those of experts. Eliciting them, however, can be challenging, particularly for marginalised groups whose viewpoints have historically been excluded from planning processes. Fuzzy cognitive mapping (FCM) provides a semi-quantitative approach to representing the collective understanding or \'mental models\' of diverse individuals and communities. This study involved 23 FCM interviews across three neighbourhoods of Saint Martin to comprehend: (i) how individuals\' mental models of Hurricane Irma (2017) differ based on their context; (ii) how aligned mental models are with policy and planning documents; and (iii) the implications for the inclusiveness and representativeness of disaster response policies. It found that the residents of different neighbourhoods provided unique insights into the factors driving the social-ecological system, and that official policies aligned closely with priorities. The paper argues that the inclusion of the perspectives of different groups in disaster recovery is essential for an equitable process.

BACKGROUND: Fuzzy cognitive mapping (FCM) is a graphic technique to describe causal understanding in a wide range of applications. This practice review summarises the experience of a group of participatory research specialists and trainees who used FCM to include stakeholder views in addressing health challenges. From a meeting of the research group, this practice review reports 25 experiences with FCM in nine countries between 2016 and 2023.
RESULTS: The methods, challenges and adjustments focus on participatory research practice. FCM portrayed multiple sources of knowledge: stakeholder knowledge, systematic reviews of literature, and survey data. Methodological advances included techniques to contrast and combine maps from different sources using Bayesian procedures, protocols to enhance the quality of data collection, and tools to facilitate analysis. Summary graphs communicating FCM findings sacrificed detail but facilitated stakeholder discussion of the most important relationships. We used maps not as predictive models but to surface and share perspectives of how change could happen and to inform dialogue. Analysis included simple manual techniques and sophisticated computer-based solutions. A wide range of experience in initiating, drawing, analysing, and communicating the maps illustrates FCM flexibility for different contexts and skill bases.
CONCLUSIONS: A strong core procedure can contribute to more robust applications of the technique while adapting FCM for different research settings. Decision-making often involves choices between plausible interventions in a context of uncertainty and multiple possible answers to the same question. FCM offers systematic and traceable ways to document, contrast and sometimes to combine perspectives, incorporating stakeholder experience and causal models to inform decision-making. Different depths of FCM analysis open opportunities for applying the technique in skill-limited settings.

Decision-makers are increasingly asked to act differently in how they respond to complex urban challenges, recognising the value in bringing together and integrating cross-disciplinary, cross-sectoral knowledge to generate effective solutions. Participatory modelling allows to bring stakeholders together, enhance knowledge and understanding of a system, and identify the impacts of interventions to a given problem. This paper uses an interdisciplinary and systems approach to investigate a complex urban problem, using a participatory System Dynamics modelling process as an approach to facilitate learning and co-produce knowledge on the factors influencing the use of urban natural space. Stakeholders used a Systems Dynamics model and interface, as a tool to collectively identify pathways for improving the use of space and simulating their impacts. Under the lens of knowledge co-production, the paper reflects how such mechanisms can lead to the co-production of knowledge and social learning. The findings also contribute to identify ways of increasing the value of urban natural space focusing on urban areas undergoing physical and social transformation, such as the Thamesmead case study, London, UK.

As we face complex and dynamically changing public health and environmental challenges, simulation modelling has come to occupy an increasingly central role in public engagements with policy. Shifts are occurring not only in terms of wider public understandings of modelling, but also in how the value of modelling is conceptualised within scientific modelling communities. We undertook a critical literature review to synthesise the underlying epistemic, theoretical and methodological assumptions about the role and value of simulation modelling within the literature across a range of fields (e.g., health, social science and environmental management) that engage with participatory modelling approaches. We identified four cross-cutting narrative conceptualisations of the value of modelling across different research traditions: (1) models simulate and help solve complex problems; (2) models as tools for community engagement; (3) models as tools for consensus building; (4) models as volatile technologies that generate social effects. Exploring how these ideas of \'value\' overlap and what they offer one another has implications for how participatory simulation modelling approaches are designed, evaluated and communicated to diverse audiences. Deeper appreciation of the conditions under which simulation modelling can catalyse multiple social effects is recommended.

The youth mental health sector is persistently challenged by issues such as service fragmentation and inefficient resource allocation. Systems modelling and simulation, particularly utilizing participatory approaches, is offering promise in supporting evidence-informed decision making with limited resources by testing alternative strategies in safe virtual environments before implementing them in the real world. However, improved evaluation efforts are needed to understand the critical elements involved in and to improve methods for implementing participatory modelling for youth mental health system and service delivery. An evaluation protocol is described to evaluate the feasibility, value, impact, and sustainability of participatory systems modelling in delivering advanced decision support capabilities for youth mental health. This study applies a comprehensive multi-scale evaluation framework, drawing on participatory action research principles as well as formative, summative, process, and outcome evaluation techniques. Novel data collection procedures are presented, including online surveys that incorporate gamification to enable social network analysis and patient journey mapping. The evaluation approach also explores the experiences of diverse stakeholders, including young people with lived (or living) experience of mental illness. Social and technical opportunities will be uncovered, as well as challenges implementing these interdisciplinary methods in complex settings to improve youth mental health policy, planning, and outcomes. This study protocol can also be adapted for broader international applications, disciplines, and contexts.

Participatory modelling seeks to foster stakeholder engagement to better attune models to their decision-making and policy contexts. Such approaches are increasingly advocated for use in the field of health. We review the instrumental and epistemological claims made in support of participatory modelling approaches. These accentuate participatory models as offering a better evidence-base for health policy decisions. By drawing attention to recent modelling experiments in a sector outside of health, that of water management, we outline a different way of thinking about participation and modelling. Here, the participatory model is configured in relation to matters of \'knowledge controversy\', with modelling constituted as an \'evidence-making intervention\' in relation to the making of science and expertise. Rather than presenting participatory models as an improved technical solution to addressing given policy problems within an evidence-based intervention approach, models are alternatively potentiated as sites for the redistribution of expertise among actor networks as they seek to engage politically in a matter of concern. This leads us to consider possible new directions for participatory modelling in the field of health.

Several barriers still hamper the effective implementation of Nature-Based Solutions (NBS). Among the others, this work focuses on collaboration barriers. NBS implementation claims for effective collaboration among different decision-agents. However, ambiguity in problem framings, which is ineradicable in multi-agents\' decision environments, could create collaboration barriers. This work aims to demonstrate that collaboration barriers to NBS implementation can be overcome by enhancing the network of interactions among the decision-agents. An innovative method based on the integration between Social Network Analysis and hybrid Agent-Based Model/System Dynamic Model was adopted to this aim. The analysis results were used for designing networking interventions, i.e. efforts using social network characteristics that could enhance interactions mechanisms among decision-agents. The developed method was implemented in the Medina del Campo (Spain) case study. This area is characterised by one of the most critical groundwater bodies of the Duero River Basin. This work aims at supporting the implementation of suitable NBS to stop the degradation of the groundwater status and associated ecosystem services. The activities carried out within the framework of the NAIAD project showed that, by enhancing the interaction mechanisms, ambiguity in problem frames can still yield collective actions for NBS implementation.

Nature-Based Solutions (NBS) have been gaining importance in many European cities to reduce floods\' impacts. However, evidence of their effectiveness in reducing the impacts of droughts in rural areas are scarce. Besides, ignoring future climate conditions or the specific socio-economic context in which NBS is applied could decrease their long-term effectiveness. This study aims to stress the importance of developing scientifically-based and customised information on climate change impacts as a precondition for designing and implementing NBS. For that, a System Dynamic model was developed to analyse and understand the dynamic behaviour of NBS responding to different scenarios of climate change and socio-economic contexts. This article recognises the proactive involvement at all societal levels as an essential component to enhance and maintain ecosystem resilience and, therefore, NBS1effectiveness. Thus, participatory modelling activities were carried out to engage stakeholders in the model development process to obtain relevant bottom-up information and organise stakeholders\' collective knowledge in a graphical structure that captures the system\'s main dynamics. The Medina del Campo Groundwater Body was used as a frame for the analysis. The study results highlight the need for developing scientifically-based and customised information on the impacts of climate change on NBS as an essential precondition to maintain their long-term effectiveness.

The complex relationship that exists between water resources and agricultural production has been increasing constantly globally. Several factors are interacting to influence the management of water resources making the system complex and dynamic. To increase the understanding of these complex and dynamic systems, relevant tools are needed to identify the causal relationships that exist between the drivers and their influences on the system. Participatory modelling based on the system dynamics approach provides a simplistic and visualisation tool that can improve the understanding of the functioning of a complex and dynamic system. A multi-stage participatory approach was used in this study involving relevant stakeholders in the development of an integrated conceptual system dynamic model using causal loop diagrams. This approach was used because it captures the thought process and mental model of relevant stakeholders in the development of the model, making it a valuable tool for policy and decision making at government and individual levels. The integrated model built in this study used causal loop diagrams to address problems of water management and agricultural sustainability in the Breede River Catchment. The model shows major causal-relationships and feedback loops that determine the functioning of the overall system. The model demonstrates the usefulness of the participatory approach in solving problems related to water management and agricultural development in the catchment.

The contribution of Nature Based Solutions (NBSs) for supporting climate change adaptation and water-related risks reduction is becoming increasingly relevant for policy and decision-makers, compared to \'grey infrastructures\', thanks to their capability to jointly deal with a multiplicity of societal and environmental challenges, producing several co-benefits besides limiting the impacts of water-related risks. Nevertheless, their mainstreaming is still limited by several barriers, which are often related to socio-institutional (e.g. limited cooperation and stakeholders\' involvement, limited awareness about NBSs impacts) rather than to technical aspects. In this context, innovative tools for NBSs planning, design, implementation and assessment are required, along with effective processes capable of supporting stakeholders\' participation. The present research aims to propose a shift in the approach to NBSs design, based on the early stakeholders\' involvement in the identification, modelling and performance assessment in terms of benefits and, particularly, co-benefits production. A multi-step methodology was implemented for the purpose, combining both individual and participatory activities. Reference is made to one of the case studies of the NAIAD project, namely the Balta Potelu Pond Area (Lower Danube, Romania). Causal Loop Diagrams (CLDs) were used to describe the system in terms of causal connections and mutual influences, incorporating stakeholders\' views and ideas. Inputs from both institutional (e.g. ministries and municipalities) and non-institutional stakeholders (e.g. NGOs and members of the local communities) were integrated. This allowed a comparative assessment of multiple NBSs, based on the analysis of benefits and co-benefits produced, as well as the identification of trade-offs among different stakeholders (e.g. the increase of agricultural production versus biodiversity conservation) and potential side effects. CLDs were then coupled with a Performance Matrix (a basic feature of Multi-Criteria Decision Analysis) and fuzzy logic to help decision-makers identify the most suitable NBSs for the area. The whole process was aimed at facilitating the process of NBSs selection and analysis, while considering the multiple impacts associated with their implementation.