Socio-economic predictors of domestic wood use in an Atlantic forest area (north-east Brazil): a tool for directing conservation efforts.

摘要

Given the excessive use pressure on forests, characterisation of the major users of forest resources can help guide conservation efforts. This study examines whether socio-economic variables explain domestic wood use in an area of Atlantic forest in the community of Tres Ladeiras (Pernambuco, north-east Brazil). Socio-economic data were collected from 62 households, and geometric measurements of wood products in each household were taken to calculate the wood volume. An informant in each household indicated the average replacement time for each type of wood use. Data were analysed for static volume (wood volume found at the time of the visit) and dynamic volume (rate of wood consumption, calculated as the ratio between volume and replacement time). Multiple regression analyses were performed to determine the relationships between wood volume (static and dynamic) and the number of species used; independent variables including monthly family income, number of residents, average age of heads of the household, age of oldest household member, average residence time of heads of the household, average education level of heads of the household and education level of the most educated household member. Monthly income was inversely related to the static wood volume (adjusted R2=17.6%, p<0.001), rate of wood consumption (adjusted R2=23.0%, p<0.001) and number of species used (adjusted R2=22.3%, p<0.001) and was the most important predictive variable for these three outcomes. Other factors such as average education level and average age of heads of the household were also explanatory variables of the total rate of wood consumption, as these two variables, together with monthly family income, explain 31.3% of the total dynamic volume. Given the high importance of income in our study, we suggest that future conservation strategies give special attention to the poorest members of the community.Digital Object Identifier http://dx.doi.org/10.1080/13504509.2011.614288