Holistic and systems thinking modelling for strategic agriculture production planning in sub-Saharan Africa

Publication Type

Journal Article

Journal Name

Agricultural Systems

Publication Date

6-1-2026

Abstract

CONTEXT: Agriculture in sub-Saharan Africa (SSA) underpins food security, livelihoods, and economic growth, yet it faces mounting pressures from climate change, food insecurity, socioeconomic instability, and environmental degradation. While National Adaptation Plans (NAPs) and bioeconomic models are increasingly used to guide policy, most existing tools remain fragmented and fail to capture the complex interdependencies across agricultural, economic, social, technological, and environmental domains. OBJECTIVE: This study develops and applies a holistic bioeconomic systems model for strategic agricultural planning in SSA, aimed at identifying leverage points that enhance resilience, sustainability, and productivity. It specifically examines how climate-resilient crop variety (CRV) adoption and market infrastructure development influence agricultural performance in Kenya and Nigeria. METHODS: Using a systems thinking approach, causal loop diagrams (CLDs) were developed across agricultural, economic, social, technological, and environmental subsystems and synthesized into an integrated model in Vensim DSS. The model was preliminarily calibrated and validated using FAOSTAT and World Bank datasets (2000−2022), followed by scenario and counterfactual testing to evaluate the system-wide impacts of CRV adoption and market infrastructure improvements. A network analysis (closeness, degree, PageRank, and betweenness centrality) identified key variables shaping system resilience. RESULTS AND CONCLUSIONS: The CLD analysis revealed reinforcing loops that promote circular bioeconomy practices, technological innovation, and poverty reduction, as well as balancing loops that highlight risks from soil degradation, migration, and weak governance. Empirical structural assessment and sensitivity analyses confirmed strong correlations between CRV adoption, agricultural GDP, and market connectivity, validating the structural logic of the model. Scenario testing showed that increasing CRV adoption by 25% and improving market infrastructure by 15% enhanced agricultural GDP by up to 12% and weakened food insecurity loops by 15–18%. Network analysis identified climate-resilient crop varieties, agricultural production, markets, and strategic crops as central drivers of system resilience and sustainability. The integrated model underscores the critical role of feedback loops, governance, and cross-sectoral interactions in shaping long-term agricultural outcomes. SIGNIFICANCE: The model advances agricultural modelling beyond reductionist paradigms by integrating empirical structural assessment, scenario analysis, and network centrality. It provides policymakers, donors, and researchers with a diagnostic and informed conceptual framework for aligning NAP priorities, scaling strategic crops, and guiding climate-resilient agricultural investments in SSA. While currently conceptual, the model provides a flexible foundation for future quantitative simulations and participatory applications, making it highly relevant for climate-resilient agricultural development in Africa.

Keywords

Adaptation planning, Climate-resilient agriculture, Holistic bioeconomic modelling, Strategic crop scaling, Sustainable food systems, Systems thinking

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