This paper develops and applies a spatial econometric model that links road upgrading to forest clearing and biodiversity loss in the moist tropical forests of Bolivia, Cameroon and Myanmar. Using 250 m cells, the model estimates the relationship between the rate of forest clearing in a cell and its distance to the closest point on the nearest road; the transport distance-minimizing route to the nearest urban market, with an explicit control for road quality; terrain elevation and slope; the agricultural opportunity value of the land; and its legal protection status. The model takes into account spatial autocorrelation and simultaneity in the relationship between forest clearing and road location.
The findings emphasize the road transport results; forest clearing is highly responsive to the distance to the nearest urban market which comprises of the distance of the cell to the closest point on the nearest road and the transport distance-minimizing route to the nearest urban market the distance from market. The responsiveness of forest clearing to distance from the nearest market is lower for primary road links, because their higher average vehicle speeds and lower maintenance costs reduce the effect of distance to market. Using the estimated forest clearing response elasticities and a composite biodiversity indicator, this research computes an index of expected biodiversity loss from upgrading secondary roads to primary status in each 250 m cell. The results identify areas in Bolivia, Cameroon and Myanmar where high expected biodiversity losses may warrant additional protection as road upgrading continues. In addition, they provide ecological risk ratings for individual road corridors that can inform environmentally-sensitive infrastructure investment programs.