Abstract
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-based-model 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.
Highlights
[7] Many participatory modeling methods focus on the questions and needs of the community the model is meant to serve, and perhaps the most important criterion for a participatory simulation’s validity is its credibility to and/or usefulness for its users, often assessed through an interactive, relational process. [8,9,10] as communities themselves are becoming more sophisticated in their collection and use of data to address questions that concern them, [11] quantitative methods of external validation may become desirable in addition to more internal methods associated with usefulness
[17] Participatory modeling often engages with structural validation processes, but as quantitative data are increasingly available via processes like citizen science, [11] behavioral validation is becoming more feasible as well
We review the results of validating the model against independent community-based data, the sensitivity analysis indicating whether underlying parameters had comparable effects to the management interventions and rainfall scenarios, and the impact of spatial configurations, management interventions, and rainfall scenarios on model sustainability
Summary
Bringing together simulation modeling strategies with community collaboration has been referred to by many names, but can be broadly termed “participatory modeling.” [6] These processes can involve focus groups, role-playing games, workshops, and many other types of community engagement, and can involve community members in some or all parts of the modeling process (including goal setting, data collection, design, implementation, verification and calibration, validation, use, and outcome analysis). [7] Many participatory modeling methods focus on the questions and needs of the community the model is meant to serve, and perhaps the most important criterion for a participatory simulation’s validity is its credibility to and/or usefulness for its users, often assessed through an interactive, relational process. We engaged in a participatory modeling process with Zimbabwean non-governmental organization The Muonde Trust to address their concerns around land-use decisions and management practices in their agro-pastoral system. We describe the model and the results of this validation process: the model was successfully structurally validated by the community, and quantitative behavioral validation was more successful for some model targets than others
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