Social Perception of Climate Change and Ecosystem Based Risk Reduction in Teresópolis, Brazil

In January 2011 once again the population in the mountain region of Rio de Janeiro state, Brazil, suffered from an environmental disaster: excessive rainfall in a short time provoked landslides, mudslides, floods and rock debris which caused more than 900 fatalities, left more than 35.000 people homeless and led to an estimated material damage of 1.2 billion USD. Generally, those events are natural because of the rugged topography and the vulnerable geology and soils, but anthropogenic land degradation due to inadequate land use by agriculture and informal housing contribute to an elevated disaster risk. To worsen the situation, predictions of climate change for south-eastern Brazil forecast an increase of torrential rainfall and, therefore, enforcing the need for adaptation to environmental risks in the region.

Up to the present, the disaster risk reduction strategy followed by the authorities in the mountain region includes manly “grey” infrastructural measures such as contention of slopes or channelization of rivers as well as the partial relocation of population in risk. However,  rather than relying solely on grey infrastructure, “green” measures based on the ecosystem services approach are important for a feasible and cost-effective adaption strategy and an increase of resilience. The preservation and recuperation of dense forests on steep mountain slopes, gallery forests on river banks or flood parks play an important yet underestimated role for efficient risk reduction.

The paper presents a case study in the municipality of Teresópolis where quantitative and qualitative data collection has been conducted in order to assess the perception of the local population of environmental risks, climate change and the potential of adaptation through the valorization of ecosystem services. This analysis is an essential basis for developing a sensitization strategy for ecosystem based measures for disaster risk reduction in times of climate change on community level.