Abstract
Roads act as conduits for human incursions and hence underlie many of humanity's impacts on nature, including deforestation, wildfires, and natural-resource overexploitation. Unfortunately, existing roadmaps often drastically underestimate the true extent of road networks and future predictions of road-related impacts rely on incomplete and outdated data, undermining development planning and conservation decision-making. Here, we develop a multivariate "road expansion risk" index to identify areas prone to road building and therefore vulnerable to road-related environmental impacts. Using a massive road dataset-137 million 1-ha raster cells drawn from three different sources arrayed across the Amazon and Congo basins and insular Asia-Pacific region-we predict road-prone locations via a statistical model that integrates a range of biophysical, socioeconomic, and administrative data. This highly integrative, large-scale approach allowed us to identify areas likely to experience future road building and regions that may contain unmapped roads. Importantly, our road expansion risk index is a strong predictor of forest loss and degradation and can hence identify future road building and deforestation hotspots, even for the many tropical forest locales with grossly deficient road data.