Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Autor: Jon Solera, Abraham Mawere Ndlovu, Emmanuel Mhike Hove, Andre Veski, K. B. Wilson, Kleber Neves, Aaron Fisher, M. V. Eitzel, Oluwasola E. Omoju
Rok vydání: 2020
Předmět:
0106 biological sciences
Systems Analysis
Process management
010504 meteorology & atmospheric sciences
Computer science
Psychological intervention
Social Sciences
Systems Science
Infographics
01 natural sciences
Agent-Based Modeling
Psychology
Animal Management
Data Management
Agent-based model
Multidisciplinary
Animal Behavior
Simulation and Modeling
Agriculture
Agricultural Methods
010601 ecology
Grazing
Physical Sciences
Medicine
Construct (philosophy)
Graphs
Research Article
Conservation of Natural Resources
Computer and Information Sciences
Matching (statistics)
Livestock
Process (engineering)
Science
Climate Change
Crops
Context (language use)
Research and Analysis Methods
Participatory modeling
Sustainability Science
Humans
Management process
Ecosystem
0105 earth and related environmental sciences
Behavior
Data Visualization
Ecology and Environmental Sciences
Biology and Life Sciences
Citizen journalism
Models
Theoretical
Crop Management
Sustainable Agriculture
Sustainability
Zoology
Mathematics
Crop Science
Zdroj: PLoS ONE
PLoS ONE, Vol 15, Iss 8, p e0237638 (2020)
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0237638
Popis: 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.
Databáze: OpenAIRE
Externí odkaz: