Publications

The extent to which any policy, planning, or funding frameworks aimed at supporting climate change adaptation contribute to improved adaptive capacity of smallholder farmers is strongly affected by the power/influence dynamics between actors within those regimes. Power and influence studies have renewed relevance due to the current proliferation of adaptation initiatives. As these initiatives evolve, they bring up questions of equity, justice, and fairness surrounding the origins and distribution of adaptation resources. In doing so, they have shed light on persistent inequalities in status quo development regimes and asymmetrical power balances between stakeholders.
To avoid exacerbating inequalities that contribute to conflict, perpetuate cycles of poverty, and prevent much needed resources from reaching vulnerable communities, it is essential that practitioners seek to make power/influence relationships transparent within any given adaptation regime. Exposing and characterizing these relationships is complex, sensitive, and involves multiple perspectives. This paper introduces the Multilevel Stakeholder Influence Mapping (MSIM) tool, which aims to assist analysts in the study of power dynamics across levels within climate adaptation regimes.
The tool is adapted from the Stakeholder Influence-Mapping tool (2005) of the International Institute for Environment and Development (IIED). MSIM is a simple visual tool to examine and display the relative power/influence that different individuals and groups have over a focal issue—in this case, climate change adaptation of smallholder farmers. The tool can be applied individually or in groups, as often as desired, to capture multiple perspectives and also to act as an intermediary object facilitating expression of sensitive information. The multilevel adapted version of the tool was trialed with a cross-section of actors in Nepal’s agricultural climate change adaptation regime. The results of this pilot, the tool use guidelines, and triangulation with supporting methods, as well as forward-looking applications in climate adaptation are provided herein.