Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Summary • Tropical forest degradation is widely recognised as a driver of biodiversity loss and a major source of carbon emissions. However, in contrast to deforestation, the more gradual changes from degradation are challenging to detect, quantify, and monitor. Here we present a field protocol for rapid, area-standardised quantifications of forest condition, which can also be done by non-specialists. Using the example of threatened high-biodiversity forests in Tanzania, we analyse and predict degradation based on this method. We also compare the field data to optical and radar remote sensing datasets, thereby conducting a large-scale, independent test of the ability of these products to map degradation in East Africa from space. • Our field data consist of 551 ‘degradation’ transects collected between 1996 and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and coastal forests. • Degradation was widespread, with over one third of the study forests – mostly protected areas – having more than 10% of their trees cut. Commonly-used optical remote-sensing maps of complete tree cover loss only detected severe impacts (≥25% of trees cut), i.e. a focus on remotely sensed deforestation would have significantly underestimated carbon emissions and declines in forest quality. Radar-based maps detected even low impacts (