What is it about?

We have developed a method to represent systems consisting of human, technical, environmental, institutional, and knowledge components as networks. The network representation, constructed with historical qualitative data, enables quantitative metrics to study system structure. We used the approach to study evolution of food production in the Punjab province of Pakistan. Reported data shows total crop production on aggregate has increased in the region despite repeated political instability, institutional change, and devastating floods. We studied the food production system by constructing five networks (each representing a period of a decade or more). The five networks, that collectively described the system over seventy-five years (1947-2022), were then compared to systematically examine structural evolution and association with sustainability of food production. We found that key structural components remained stable and new pathways associated with food production emerged over time.

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Why is it important?

Models for informing sustainability interventions in complex adaptive systems involving nature-society interactions are challenging to construct due to lack of detailed, quantitative data on the changing structure of system interactions. The approach we have developed combines qualitative descriptions of system components and interactions with network representation for quantitative characterization of system structure. The network models allow not just for historical but also prospective analyses in which addition or removal of components and their interactions can be readily simulated. In this work, we demonstrated such a prospective analysis for our region of study and found that there is food production vulnerability due to on-going urbanization of arable land with implications on livelihoods for farm laborers and small-business owners (engaged in the agricultural economy). The simulations highlighted the importance of coordinating rural and urban land-use and water policies.


The approach developed in this work enables systems analysis for which qualitative data is available. It opens possibilities for studying documented cases that may offer important insights for sustainability-related interventions. The Human-Technical-Environmental (HTE) systems framework used here, to develop the networks, includes three categories of material components: H (human), T (technical), and E (environmental). Two nonmaterial categories, institutions (I) defined as sets of rules, norms, and policies, and knowledge (K) defined as data and research, provide the mediating context within which the material components interact. These five types of components enable a rich description of systems and can allow for insights that may otherwise not be possible with simpler models wherein only a few of these components are included in system representation and analysis.

Afreen Siddiqi
Massachusetts Institute of Technology

This article involved extended collaboration between network analysis, HTE modeling, and historical geographic analysis of the sustainability of water and food production in Punjab province of the Indus River basin in Pakistan. Readers are thus encouraged to tap into the detailed body of Supplementary Materials and qualitative research that support the article.

Massachusetts Institute of Technology

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This page is a summary of: Evolution of system connectivity to support food production in the Indus Basin in Pakistan, Proceedings of the National Academy of Sciences, April 2024, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2215682121.
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