Using Participatory Modeling Processes to Identify Sources of Climate Risk in West Africa
October 4, 2017 - Author: Schmitt Olabisi, L. K., Liverpool-Tasie, L.S.O., Rivers, L., Ligmann-Zielinska, A., Du, J. Denny, R., Li, J. Marquart-Pyatt, S. & Sidibe, A.
Using Participatory Modeling Processes to Identify Sources of Climate Risk in West Africa. Environment Systems and Decisions. Schmitt Olabisi, L. K., Liverpool-Tasie, L.S.O., Rivers, L., Ligmann-Zielinska, A., Du, J. Denny, R., Li, J. Marquart-Pyatt, S. & Sidibe, A. (2017). https://link.springer.com/article/10.1007/s10669-017-9653-6
Participatory modeling has been widely recognized in recent years as a powerful tool for dealing with risk and uncertainty. By incorporating multiple perspectives into the structure of a model, we hypothesize that sources of risk can be identified and analyzed more comprehensively compared to traditional ‘expert-driven’ models. However, one of the weaknesses of a participatory modeling process is that it is typically not feasible to involve more than a few dozen people in model creation, and valuable perspectives on sources of risk may therefore be absent. We sought to address this weakness by conducting parallel participatory modeling processes in three countries in West Africa with similar climates and smallholder agricultural systems, but widely differing political and cultural contexts. Stakeholders involved in the agricultural sector in Ghana, Mali, and Nigeria participated in either a scenario planning process or a causal loop diagramming process, in which they were asked about drivers of agricultural productivity and food security, and sources of risk, including climate risk, between the present and mid-century (2035–2050). Participants in all three workshops identified both direct and indirect sources of climate risk, as they interact with other critical drivers of agricultural systems change, such as water availability, political investment in agriculture, and land availability. We conclude that participatory systems methods are a valuable addition to the suite of methodologies for analyzing climate risk and that scientists and policy-makers would do well to consider dynamic interactions between drivers of risk when assessing the resilience of agricultural systems to climate change.
Keywords: Participatory modeling, Food security, West Africa, System dynamics, Scenarios