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.

No abstract

Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio-Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.Participatory approaches to resource management must involve those who are affected by the decisions that stem from environmental management decisions (Reed et al., 2009). Environmental resource management often requires a combination of descriptive and normative knowledges as well as local capacity for action (and inaction). Because resource users have such knowledge and capacity, local engagement is crucial in PM. However, there are imbricated layers of power between researchers and locals-often with researchers holding the balance of power due to their increased access to social goods such as money, formal education,

Abstract. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

Abstract:The negative impacts of climate change on agriculture could erode gains made toward gender equality in Ghana. Much of the literature on gender dimensions of climate change adaptation has focused on assessing differences in coping and adaptation practices of smallholder farmers. Mostly overlooked is whether gender influences influenced perception of effectiveness of adaptation practices and preferences for institutional support for future adaptation. Using key informant interviews, household surveys, and focus group discussions, we address these gaps by exploring coping and adaptation measures adopted by heads of farm households to counter climate change impacts on their livelihood activities and household well-being in the Guinea Savanna agroecological zone in Ghana. Additionally, we assessed the preferred institutional adaptation support of heads of farm households in adapting to future projected impacts. We find that female heads of farm households relied mainly on borrowed money from village savings and loans group as a coping measure; male heads of farm households depended primarily on sales of livestock. Varying planting and harvesting dates, crop diversification, and use of improved crop varieties were the major adaptation strategies adopted by farmers. We argue that provision of dams and/or dugouts, postharvest processing facilities, adaptation capacity-building resources, and improved access to markets and credit could enhance the adaptive capacity of male and female heads of farm households to mitigate projected climate change impacts on their livelihood activities and household well-being.

As lockdown and school closure policies were implemented in response to the coronavirus, the federal government provided funding and relaxed its rules to support emergency food provision, but not guidance on best practices for effectiveness. Accordingly, cities developed a diverse patchwork of emergency feeding programs. This article uses qualitative data to provide insight into emergency food provision developed in five cities to serve children and families. Based on our qualitative analysis, we find that the effectiveness of local approaches appears to depend on: (i) cross‐sector collaboration, (ii) supply chains, and (iii) addressing gaps in service to increased risk populations.

Participatory Modeling (PM) is becoming increasingly common in environmental planning and conservation, due in part to advances in cyberinfrastructure as well as to greater recognition of the importance of engaging a diverse array of stakeholders in decision making. We provide lessons learned, based on over 200 years of the authors’ cumulative and diverse experience, about PM processes. These include successful and, perhaps more importantly, not-so-successful trials. Our collective interdisciplinary background has supported the development, testing, and evaluation of a rich range of collaborative modeling approaches. We share here what we have learned as a community of participatory modelers, within three categories of reflection: a) lessons learned about participatory modelers; b) lessons learned about the context of collaboration; and c) lessons learned about the PM process. First, successful PM teams encompass a variety of skills beyond modeling expertise. Skills include: effective relationship-building, openness to learn from local experts, awareness of personal motivations and biases, and ability to translate discussions into models and to assess success. Second, the context for collaboration necessitates a culturally appropriate process for knowledge generation and use, for involvement of community co-leads, and for understanding group power dynamics that might influence how people from different backgrounds interact. Finally, knowing when to use PM and when not to, managing expectations, and effectively and equitably addressing conflicts is essential. Managing the participation process in PM is as important as managing the model building process. We recommend that PM teams consider what skills are present within a team, while ensuring inclusive creative space for collaborative exploration and learning supported by simple yet relevant models. With a realistic view of what it entails, PM can be a powerful approach that builds collective knowledge and social capital, thus helping communities to take charge of their future and address complex social and environmental problems.

No abstract