Views from two mountains: exploring climate change impacts on traditional farming communities of Eastern Africa highlands through participatory scenarios

African mountains are characterized by high levels of biodiversity and provide ecosystem services to millions of people. Due to steep environmental gradients, growing human populations and geographical isolation, these coupled socio-ecological systems are highly vulnerable to climate change impacts. The capacity of local stakeholders to anticipate future changes and to assess their potential impacts is paramount for enhancing adaptation and resilience. Here we apply a participatory scenario development framework in two parts of the Eastern Afromontane Biodiversity Hotspot: Taita Hills in Kenya and Jimma rural area in Ethiopia. In each area, we facilitated local stakeholders in envisioning adaptation scenarios under projected climate changes by mid-21st century, and assessed the potential impacts of these pathways on land use and land cover. In the Taita Hills, under a business-as-usual scenario, human population and activities concentrate at high elevation, triggering cascade effects on remnant forest cover, biodiversity and ecosystem services. Alternative adaptation scenarios envisage reforestation associated with either improved agricultural practices or ecosystem restoration. In the Jimma area, rising temperatures are expected to disrupt traditional coffee production under a business-as-usual scenario, resulting in the loss of coffee-forest canopies and reduction of forest-dependent biodiversity. Alternative adaptation scenarios envisage either expansion of commercial coffee plantations or expansion of agroforestry, including traditional coffee farming. In the both Taita and Jimma, adaptation pathways present trade-offs between provisioning, supporting and regulating services, and between livelihoods and biodiversity conservation. Our findings encourage the use of multidisciplinary, bottom-up approaches for developing locally tailored, climate-smart and sustainable adaptation pathways.