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Barriers to food security and climate adaptation operate in complex and dynamic ways but are often perceived as static impediments to be overcome. In this study, we apply systems thinking for the assessment of barriers in agricultural decision-making for food security and climate adaptation. Using a mixed method approach of participatory simulation game design and causal loop diagrams, we explore the dynamic pathways through which barriers inhibit farmers from achieving food security and climate adaptation in Southern Mali. Results show that the key barriers in the region are financial, land, and climate-related barriers including unavailability of formal credit sources, high input prices, inadequate land access and ownership rights, time and labor constraints in collective vs individual plots, and climate risks such as early and late season droughts, high temperature, excessive rainfall, water scarcity, and pest incidences. These barriers operate in complex, interdependent, and dynamic ways where factors that act as enablers in one context can also function as barriers in another context. We see such interdependencies in three cases: i) access to interlocked credit and loans for cotton cultivation acts as enablers of income generation for male farmers but become barriers to female farmers who do not cultivate cotton ii) land ownership and land use rights for male farmers act as enablers for cultivation of income generating cash and food crops but acts as a barrier for female farmers by way of intra-household labor dynamics within collective plots iii) increase in land allocation to cotton and maize cultivation acts as enablers for increased household income but becomes a barrier to food security due to higher vulnerability to climate risks. Assessment of causal loop diagrams identified deep and shallow leverage points. Policies and interventions that focused on input subsidies and credit facilities are shallow leverage points where incremental changes will only lea

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 cap

Non-PR, IFPRI2; DCA; Feed the Future Initiative; Feed the Future Innovation Laboratory for Food Security Policy (FSP), DSGD, West Africa is expected to suffer yield and production losses of staple crops under climate change, with more severe yield reductions occurring in the period between 2030 and 2050 (Ittersum et al., 2016). In addition, extreme events, including droughts and floods, are expected to become more frequent under climate change, also potentially affecting yields (Abiodun, Lawal, Salami, & Abatan, 2013). Internal displacement and natural resource conflicts are another expected climate impact, as are pest and disease outbreaks (Gregory, Johnson, Newton, & Ingram, 2009; Obioha, 2008). Given these potentially serious climate impacts, a team comprising researchers from Michigan State University and Nigerian partner universities conducted studies intended to inform Nigerian agricultural policy around climate adaptation. This brief presents a summary of findings from 4 of these studies conducted between 2016 and 2019.

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.