Correction: Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models.

[This corrects the article DOI: 10.1371/journal.pone.

Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models.

Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems.

Evidence of incipient forest transition in Southern Mexico.

Case studies of land use change have suggested that deforestation across Southern Mexico is accelerating. However, forest transition theory predicts that trajectories of change can be modified by economic factors, leading to spatial and temporal heterogeneity in rates of change that may take the form of the Environmental Kuznets Curve (EKC). This study aimed to assess the evidence regarding potential forest transition in Southern Mexico by classifying regional forest cover change using Landsat imagery from 1990 through to 2006.