Assessing the social context of wildfire-affected areas: the case of mainland Portugal

• Autor(a) principal: Oliveira, Sandra
• Data de Publicação: 2017
• Outros Autores: Zêzere, José, Queirós, Margarida, Pereira, José Miguel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/30248
• topic: Social context; Wildfire impacts; Coping capacity; Random forest; Cluster analysis; Portugal

Wildfires cause different impacts, depending on the conditions and resilience level of the exposed communities. Wildfire occurrence in mainland Portugal was assessed with regard to socioeconomic and demographic parameters, to identify the most distinctive conditions of fire-affected areas, without implying the existence of causal relationships. The latest population and agriculture census data were used to retrieve conditions at the civil parish level, regarding demographic patterns, social and labor conditions, physical structures and agricultural activities. To identify differences between parishes, two groups were created with the communities that showed the highest and lowest 20% of wildfire incidence between 2007 and 2014, separately for density of fire events and for burned area. A stepwise approach based on classification trees and random Forest methods was applied to identify the best discriminant variables between the groups. First, irrelevant variables were removed by an interactive process based on misclassification rates. The second step used random Forest analysis to the remaining variables to evaluate their importance in distinguishing the groups. In the final step, cluster analysis was applied to test the correspondence between the clusters created with the selected variables and the initial groups. Results showed that parishes with higher fire density have higher population density, higher proportion of young and educated people, larger families and more overcrowded buildings. On the contrary, parishes with larger burned area are less populated, less attractive to foreigners, have a higher proportion of elderly people, more degraded housing conditions and agricultural activities, visible in the density of sheep and goat and pastures, are still relevant. The cluster analysis demonstrated a better performance of the model for wildfire density, revealing a strong association with socioeconomic dynamics with an agreement above 0.85, much higher than for burned areas which is 0.29. Overall, the spatial distribution of wildfire impacts is framed by societal settings and particular conditions must be further understood to improve the coping capacity of affected communities.