We developed an indicator that defines priority municipalities in order to facilitate the deployment of preventive policies and strategies for ecosystem-based adaptation to climate change (EbA) in Brazilian municipalities. Based on the premises that poor people are the population most vulnerable to climate change and that conservation and sustainable use of biodiversity and ecosystems are adaptive to climate change, our indicator uses three parameters: (1) poverty, (2) proportion of natural-vegetation cover, and (3) exposure to climate change. Thus, we searched for Brazilian municipalities that simultaneously belonged to the quartile of municipalities with the highest percentage of poverty, the quartile with the highest percentage of natural-vegetation cover, and the quartile with the highest exposure indices in two global climate models (Eta-HadGEM, Eta-Miroc). We found 398 (7.1%) EbA hotspots among 5565 Brazilian municipalities, which comprise 36% of the total area of native remnants in the country and are home to 22% of the poor people in Brazil. In their majority, these municipalities cover significant portions of the Amazon, Cerrado, Caatinga, and Atlantic forest, and indeed, these regions are recognised as some of the most vulnerable to climate change in the world. Considering the relevance of these biomes for the global water and nutrient cycle (Amazon), global food security (Cerrado), vulnerability to desertification (Caatinga), and biodiversity (all) we discuss the adaptive strategies in place, the need to bring them to scale, and existing policy gaps. Finally, in an effort to guide international and national investment and policies, we discuss how the approach described here can be applied to societies inhabiting tropical forests, savannas, and semiarid zones in other parts of the world. In particular, we propose that the indicator developed here is a simple and fast way to achieve early detection of priority municipalities for deployment of EbA action and policies, particularly in tropical developing countries.