Using social-network analysis to map institutional actors’ links with vulnerable municipalities under climate change in Honduras’ dry corridor. Pathways towards improved cooperation and territorial interventions

The Honduras dry corridor, located in Central America’s Pacific region, has high natural climate variability. Nearly half of the Honduran population depends on socio-economic activities linked to agriculture, making climate-change adaptation crucial for the agricultural sector to ensure food and nutrition security. This research analyzes how institutional structures function and interact as a network to investigate the spatial coherence and relevance of public- and private-sector interventions related to agriculture, climate change, and food security in 153 municipalities of Honduras’ dry corridor. We employed a Social Network Analysis (SNA) approach to examine these interactions over the territories, revealing two network patterns: the first favors a single municipality, observed only in the Central District where Honduras’ capital is located; the second is an egocentric network, favoring a single institution, observed in four cases, particularly in municipalities bordering with El Salvador and Guatemala. The SNA results reveal a spatial misalignment, where only 9% of interventions linked to climate-change adaptation are conducted in the highly vulnerable, outlying zones located farthest from the capital. The study highlights the need for improved coordination and strategic prioritization of interventions in the most vulnerable municipalities within the Honduras dry corridor, specifically improvement in collaborative actions, use of resources, and setting strategic priorities in regions where future demand will require progressively mobilizing institutional capabilities. By identifying the current gaps and misalignments in institutional actions, this research provides valuable insights for policymakers and stakeholders to enhance collaborative efforts to ensure that climate-change adaptation measures effectively target the most vulnerable areas.