Pathways for socio-economic system transitions expressed as a Markov chain.

Cross-impact balance (CIB) analysis provides a system-theoretical view of scenarios useful for investigating complex socio-economic systems. CIB can synthesize a variety of qualitative or quantitative inputs and return information suggestive of system evolution. Current software tools for CIB are limited to identifying system attractors as well as describing system evolution from only one scenario of initial conditions at a time. Through this study, we enhance CIB by developing and applying a method that considers all possible system evolutions as transitions in a Markov chain. We investigated a simple three-variable system (27 possible scenarios) of the demographic transition and were able to generally replicate the findings of traditional CIB. Through our experiments with four possible approaches to produce CIB Markov chains, we found that information about transition pathways is gained; however, information about system attractors may be lost. Through a comparison of model results to a recent literature review on human demography, we found that low-income countries are more likely to remain stuck in a demographic trap if economic development is not prioritized alongside educational gains. Future work could test our comparative methodological findings for systems comprised of more than three variables.

Exploring "big picture" scenarios for resilience in social-ecological systems: transdisciplinary cross-impact balances modeling in the Red River Basin.

Climate change is increasing the frequency and the severity of extreme events in river basins around the world. Efforts to build resilience to these impacts are complicated by the social-ecological interactions, cross-scale feedbacks, and diverse actor interests that influence the dynamics of change in social-ecological systems (SESs). In this study, we aimed to explore big-picture scenarios of a river basin under climate change by characterizing future change as emergent from interactions between diverse efforts to build resilience and a complex, cross-scale SES. To do so, we facilitated a transdisciplinary scenario modeling process structured by the cross-impact balances (CIB) method, a semi-quantitative method that applies systems theory to generate internally consistent narrative scenarios from a network of interacting drivers of change. Thus, we also aimed to explore the potential for the CIB method to surface diverse perspectives and drivers of change in SESs. We situated this process in the Red River Basin, a transboundary basin shared by the United States and Canada where significant natural climatic variability is worsened by climate change. The process generated 15 interacting drivers ranging from agricultural markets to ecological integrity, generating eight consistent scenarios that are robust to model uncertainty. The scenario analysis and the debrief workshop reveal important insights, including the transformative changes required to achieve desirable outcomes and the cornerstone role of Indigenous water rights. In sum, our analysis surfaced significant complexities surrounding efforts to build resilience and affirmed the potential for the CIB method to generate unique insights about the trajectory of SESs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-023-01308-1.

Scenario processes for socio-environmental systems analysis of futures: A review of recent efforts and a salient research agenda for supporting decision making.

This paper reviews the latest research on scenarios including the processes and products for socio-environmental systems (SES) analysis, modeling and decision making. A group of scenario researchers and practitioners participated in a workshop to discuss consolidation of existing research on the development and use of scenario analysis in exploring and understanding the interplay between human and environmental systems. This paper presents an extended overview of the workshop discussions and follow-up review work. It is structured around the essential challenges that are crucial to progress support of decision making and learning with respect to our highly uncertain socio-environmental futures. It identifies a practical research agenda where challenges are grouped according to the process stage at which they are most significant: before, during, and after the creation of the scenarios as products. These challenges for SES include: enhancing the role of stakeholder and public engagement in the co-development of scenarios, linking scenarios across multiple geographical, sectoral and temporal scales, improving the links between the qualitative and quantitative aspects of scenario analysis, addressing uncertainties especially surprise, addressing scenario diversity and their consistency together, communicating scenarios including visualization methods, and linking scenarios to decision making.

Integrated Climate-Change Assessment Scenarios and Carbon Dioxide Removal.

To halt climate change this century, we must reduce carbon dioxide (CO2) emissions from human activities to net zero. Any emission sources, such as in the energy or land-use sectors, must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. Projections of demand for large-scale CDR are based on an integrated scenario framework for emission scenarios composed of emission profiles as well as alternative socio-economic development trends and social values consistent with them. The framework, however, was developed years before systematic reviews of CDR entered the literature. This primer provides an overview of the purposes of scenarios in climate-change research and how they are used. It also introduces the integrated scenario framework and why it came about. CDR studies using the scenario framework, as well as its limitations, are discussed. Possible future developments for the scenario framework are highlighted, especially in relation to CDR.