Road expansion risk predicts future hotspots of tropical deforestation
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underestimate the true extent of road networks and future predictions of road-related impacts rely on incomplete and outdated data, undermining development planning and conservation decision-making.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.
Authors
- Fritz Kleinschroth (ORCID: https://orcid.org/0000-0002-7614-2123)
- Jonas Botelho
- Junior Carlos Souza
- Jayden E. Engert (ORCID: https://orcid.org/0000-0002-5558-2058)
- W. F. Laurance
- Stefany P. Costa
- F. Yoko Ishida
Institutions
- Leibniz Centre for Agricultural Landscape Research (DE)
- Max Planck Institute of Animal Behavior (DE)
- Imazon (BR)
- Ecosystem Sciences (AU)
- James Cook University (AU)
Publication Details
- Journal
- Proceedings of the National Academy of Sciences
- Published
- 2025-12-22
- DOI
- https://doi.org/10.1073/pnas.2502426122
- Primary Topic
- Wildlife-Road Interactions and Conservation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Australian Government
- Max-Planck-Gesellschaft