Paraguay's Atlantic Forest cover loss - Satellite-based change detection and fragmentation analysis between 2003 and 2013

- This paper reveals deforestation rates and fragmentation level in the BAAPA forest.
- From 2003 to 2013 forest cover decreased 18% (6000 km2 of forest were loss).
- Protected areas shown to be effective to preserve the forest.
- An increment on the fragmentation level of the BAAPA forest was disclosed.
- Almost no connectivity among the remaining forest patches is revealed.

The subtropical Atlantic Forest is a highly diverse ecosystem in South America and one of the most endangered rain forests in the world. The present study focuses specifically on the Paraguayan part of the tri-national Atlantic Forest. Over the last decades, the Paraguayan Atlantic Forest presented one of the highest deforestation rates in the world, and today, only a small share remains. Hence, forest loss in Paraguay's Atlantic Forest was detected and analysed through remote sensing and GIS methodologies based on Landsat images obtained in 2003 and 2013. The objective of this study was to examine the spatial impact of forest loss in Paraguay's Atlantic Forest over the past decade with a special focus on biodiversity conservation. Classifications results obtained overall accuracies above 83% and revealed that over 6000 km2 of forest was cleared during the study period. The forest landscape and its fragmentation level were characterised through a set of landscape metrics, in particular the proximity analysis which support the identification of forest priority areas for nature conservation and potential biological corridors. In summary, the study revealed that deforestation and fragmentation of the Atlantic Forest area continued, but at a slower pace than that in the previous decade. Protected areas were conserved very effectively; however, forest core areas without any protection status require further attention. Intact forest patches and their connectivity are a crucial prerequisite to biodiversity conservation in a highly fragmented forest area. The combination of different remote sensing and GIS methods provides valuable information for sustainable forest management in the region.