Increasing fragmentation of forest cover in Brazil’s Legal Amazon from 2001 to 2017

Abstract

cluster. Points with a high positive Z-score (≥1.645) and a significant P value (i.e., hot spots) represent clusters of large forest loss areas, whereas points with a low negative Z-score (≤-1.645) and a significant P value (i.e., cold spots) represent clusters of small forest loss areas. We performed the hotspot analysis separately for each year. Active fire data. To estimate the forest loss potentially caused by fire, we used the Fire Information for Resource Management System (FIRMS) active fire product 68 which is derived from the MODIS sensor aboard the NASA Aqua and Terra satellites. We used the MCD14ML (collection 6) product for active fire data from 2001 to 2017. This data is produced based on the daily MODIS middle-infrared and thermal infrared bands, which are compared with reference data in order to identify pixels with an active fire. We used the definition "potentially caused by fire" for two reasons. The first one relates to the difference in spatial resolution between the forest loss data (30 m) and the MODIS-based product (1 km), which is a limitation of our results because a fire could be located in any area within the 1-km MODIS pixel. The second relates to the fact that fire is used as a management tool for purposes such as burning the residual vegetation that remains or begins to grow after deforestation, which means that it was not directly responsible for the forest loss. We combined the annual (FIRMS) active fire points with the forest loss patches (polygons) during the same year in order to identify forest loss patches that contained one or more FIRMS active fire points within their borders. By summarizing the area of these forest loss patches, we obtained the total area of forest loss that had been potentially caused by fire.

Spatio-temporal patterns of extreme fires in Amazonian forests

“…The increase in extreme fire activity which we also found in 2019 (Fig. 3a) has been associated with increasing deforestation rates by several studies [59][60][61]. In agreement with that, we find 34% more deforested area in 2019 than in the previous year, and the highest deforestation rate since 2009 (Fig.…”

A new nurse frog (Anura: Allobates) from Brazilian Amazonia with a remarkably fast multi-noted advertisement call

“…Yet, the conservation of A. velocicantus , and of regional biodiversity in general, is not guaranteed. Deforestation in this part of Amazonia, including in conservation units, has increased with the expansion of illegal logging, cattle ranching, and agriculture ( Kröger, 2020 ; Montibeller et al, 2020 ). Moreover, deforestation and degradation rates in Amazonia are increasing substantially due to the anti-environmental agenda of the current Brazilian government ( Ferrante & Fearnside, 2019 ; Kröger, 2020 ).…”

Monthly Deforestation Monitoring with Sentinel-1 Multi-temporal Signatures and InSAR Coherences

“…The second issue refers to the reliability of the polygons provided by PRODES. Indeed, this ground inventory does not identify forest loss patches smaller than 6.25 ha even though the nominal resolution is 30 m (Kalamandeen et al, 2018;Montibeller et al, 2020). This criterion results in a lower error at the cost of limiting the detection of smaller patches.…”