Socio-economic factors influencing household dependence on forests and its implication for forest-based climate change interventions
In most African countries, forest-based climate change intervention initiatives such as nationally appropriate mitigation actions (NAMAs) and national adaptation programmes of action (NAPAs) are widely accepted. This is mainly due to the fact that they are relevant in addressing multiple challenges associated with rural development, mitigation and adaptation to climate change, and sustainable forest management. However, there are concerns about the implications of strategic and practical steps taken in this context on forest-dependent communities. Thus, there is need to reconcile local socio-economic vulnerabilities and forest-based climate change intervention initiatives. In the current study, socio-economic factors influencing households’ dependence on forest resources and associated implications on climate change interventions were investigated. Proportionate stratified random sampling was used to select 366 households from forest-based rural communities in Vhembe District of South Africa. A structured questionnaire was administered to household heads in 21 villages. The Pearson’s chi-square test was used to analyse the factors that influence household dependence on forest. The effects of household socio-economic characteristics on households’ forest dependence influencing factor were determined using the binary logit model. Up to 97% of the respondents depended on the forest resources predominantly because of low costs associated with using them. It was observed that socio-economic characteristics of households such as farm husbandry skills, years of residence (53–65) in the community and age of respondents (≤38–65) significantly (P < 0.05) influenced use of the forest resources. Thus, effectiveness and sustainability of forest-based climate change intervention initiatives can be promoted if the socio-economic conditions prevailing within households in areas next to forests are improved.
Keywords: household, livelihood, rural community, vulnerability