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Recent studies identifying underlying and proximate drivers of tropical deforestation and forest degradation have applied a multitude of methodologies, with varying and sometimes conflicting results. Divergent results can have implications for evidence-informed programs, policy action, and land use planning since these differences can lead to controversy as to which drivers should be addressed by deforestation and emissions-reduction or conservation programs, in addition to mismatch between the scale of study results and the scale of policy and program implementation. To identify and reconcile divergences between results among different scales and methodological approaches, we systematically reviewed 231 articles in the drivers of deforestation literature and found inconsistency in scale applied within studies (e.g., differences between the stated scale of analysis and scale of article recommendations), and variation in the number and type of drivers identified between studies by methodology. Additionally, global and regional studies tended to feature recommendations that would be difficult to implement, or that targeted large-scale problems lacking specificity. This study clarifies common themes in driver identification and what is needed for drawing contextualized, scale-appropriate conclusions relevant to forest conservation policy and sustainable land use planning. We suggest improvements to recommendations drawn from drivers of deforestation studies and avenues to reconcile divergences in approaches and results, which will support efforts to advance forest conservation and sustainable forest management outcomes. 

The forests of Central Africa constitute the continent’s largest continuous tract of forest, maintained in part by over 200 protected areas across six countries with varying levels of restriction and enforcement. Despite protection, these Central African forests are subject to a multitude of overlapping proximate and underlying drivers of deforestation and degradation, such as conversion to small-scale agriculture. This pilot study explored whether transboundary protected area complexes featuring mixed resource-use restriction categories are effective in reducing the predicted disturbance risk to intact forests attributed to small-scale agriculture. At two transboundary protected area complex sites in Central Africa, we used Google Earth Engine and a suite of earth observation (EO) data, including a dataset derived using a replicable, open-source methodology stemming from a regional collaboration, to predict the increased risk of deforestation and degradation of intact forests caused by small-scale agriculture. For each complex, we then statistically compared the predicted increased risk between protected and unprotected forests for a stratified random sample of 2 km sites (n = 4000). We found varied effectiveness of protected areas for reducing the predicted risk of deforestation and degradation to intact forests attributed to agriculture by both the site and category of protected areas within the complex. Our early results have implications for sustainable agriculture development, forest conservation, and protected areas management and provide a direction for future research into spatial planning. Spatial planning could optimize the configuration of protected area types within transboundary complexes to achieve both forest conservation and sustainable agricultural production outcomes.