The socioeconomic impacts of large-scale tree plantations on local communities

Book excerpt: Background. To meet increasing demand for forest products and services, the global area of planted forests has increased dramatically over the past 25 years. Further increases in large-scale tree plantations are expected due to their high productivity, economic profitability and contribution to climate change mitigation targets. This raises questions about their long-term sustainability, as well as their impacts on forest ecosystem services and local livelihoods, particularly in countries characterized by rural poverty and insecure property rights. Previous studies have revealed mixed impacts, but there is a lack of research on the contexts and practices that can contribute to positive and/or negative socioeconomic impacts. This protocol provides guidelines for a systematic review that synthesizes the current literature on the direct and indirect impacts of large-scale plantations on local communities, and which will also identify trends, bias and gaps in the empirical evidence base. Methods. The primary research question of the systematic review asks "What are the direct and indirect socioeconomic impacts of large-scale tree plantations on local human populations?" We apply a Population-Exposure-Comparator-Outcome-Context (PECOC) framework to structure each stage of the systematic review, which comprises a comprehensive literature search, screening, quality assessment, data extraction and analysis.We define the exposure of interest to be the establishment or management of a large-scale tree plantation by external actors, population of interest as households and communities living in close proximity to plantation sites, comparators as other communities who have not experienced the same exposure as well as the same communities prior to plantation establishment, outcomes as the direct or indirect socioeconomic impacts felt by the population as a result of plantation establishment, and context as the social, political and environmental factors that may have led to differences in experienced impacts. We will search multiple bibliographic databases and organizational websites for relevant studies in both the published and grey literatures. These results will be screened by their titles and abstracts followed by their full texts based on predetermined eligibility criteria. To ensure that selected studies have controlled for potential biases, quality assessment will then take place alongside data extraction. Finally, the results of quantitative and qualitative analyses will be reported in a narrative synthesis.