Response to Comment on "The extent of forest in dryland biomes".

De la Cruz et al question the reliability of our results, claiming that we do not refer to the most appropriate spatial extent of drylands. In our response, we explain why we chose an existing and internationally recognized delineation of drylands among several options, and why our findings are due to a difference of remote sensing technique and not to the definition of drylands we have selected.

Response to Comment on "The extent of forest in dryland biomes".

Griffith et al do not question the quality of our analysis, but they question our results with respect to the definition of forest we employed. In our response, we explain why the differences we report result from a difference of technique and not of definition, and how anyone can adapt-as we did-our data set to any forest definition and tree cover threshold of interest.

Response to Comment on "The extent of forest in dryland biomes".

Schepaschenko et al question our findings, claiming that we did not refer to all existing maps and that we did not account for all sources of uncertainty. In our response, we detail our selection criteria for reference maps, which clarify why the work of Schepaschenko et al was not used, and we explain why our uncertainty assessment is complete and how it was misunderstood by Schepaschenko et al.

Seeing Central African forests through their largest trees.

Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.