# Road expansion risk predicts future hotspots of tropical deforestation

## TL;DR

This paper introduces a new index to predict where roads are likely to expand in tropical forests, helping identify future deforestation hotspots.

## Contribution

A novel multivariate road expansion risk index is developed to predict future road building and deforestation hotspots in tropical regions.

## Key findings

- The road expansion risk index effectively identifies areas likely to experience road building or contain unmapped roads.
- The index predicts deforestation probabilities even in areas with incomplete road data.
- The approach integrates biophysical, socioeconomic, and administrative factors to forecast human incursions into tropical forests.

## Abstract

This study identifies consistent biophysical and socioeconomic predictors of road building across the world’s major tropical rainforest regions. With this information, we devise a multivariate road expansion risk index that effectively identifies areas likely to bear unmapped roads or that are susceptible to future road building. Beyond predicting the risk of roads, the index can also predict the probability of deforestation, even for locales without road data. By disentangling the various factors influencing the contemporary explosion of tropical roads and associated deforestation, we present an important tool for use in various conservation planning and assessment practices, including protected area design and management and threatened species risk assessments, and for forecasting hotspots of human incursion into tropical forest regions.

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underestimate the true extent of road networks and future predictions of road-related impacts rely on incomplete and outdated data, undermining development planning and conservation decision-making.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.