Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

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Colonialism has devastated the lifeways, more-than-human relations, and collective stewardship practices of Indigenous people. Decolonial restoration may be assisted by collaborative methods like participatory modeling, but further careful evaluation is needed to ensure that these methods that have the potential to connect ways of knowing actually do secure long-term benefit for Indigenous life and land. In this study, we engage in a mixed-methods analysis to assess our participatory modeling of a Zimbabwean agropastoral system. The Muonde Trust, a community-based research organization, partnered with international researchers from outside the community to create an agent-based model (ABM) representing the dynamics of land use in Mazvihwa Communal Area, Zimbabwe. Using interviews and participant observation during modeling workshops, Muonde and their allies assessed the immediate increases in confidence and self-efficacy for members of the research team (during workshops), intermediate-term changes in local land-use policy and management discussions (months to years later), and long-term changes in on-the-ground land use (up to four years later). We find that the model successfully assisted the Muonde Trust in working with local leaders to create policies allowing recultivation of fallow fields rather than further deforesting woodland grazing areas. This success is due to the involvement of the community at key times in the modeling process, resulting in a model that felt accessible and that Muonde (as a key information broker) could use to bring the community together to discuss collective management. Though aspects of our process still relied on colonial tools and power structures, the community in Mazvihwa finds the model useful and feels ownership over it.

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