Mapping Atlantic rainforest degradation and regeneration history with indicator species using convolutional network

The Atlantic rainforest of Brazil is one of the global terrestrial hotspots of biodiversity. Despite having undergone large scale deforestation, forest cover has shown signs of increases in the last decades. Here, to understand the degradation and regeneration history of Atlantic rainforest remnants near São Paulo, we combine a unique dataset of very high resolution images from Worldview-2 and Worldview-3 (0.5 and 0.3m spatial resolution, respectively), georeferenced aerial photographs from 1962 and use a deep learning method called U-net to map (i) the forest cover and changes and (ii) two pioneer tree species, Cecropia hololeuca and Tibouchina pulchra. For Tibouchina pulchra, all the individuals were mapped in February, when the trees undergo mass-flowering with purple and pink blossoms. Additionally, elevation data at 30m spatial resolution from NASA Shuttle Radar Topography Mission (SRTM) and annual mean climate variables (Terraclimate datasets at ∼ 4km of spatial resolution) were used to analyse the forest and species distributions. We found that natural forests are currently more frequently found on south-facing slopes, likely because of geomorphology and past land use, and that Tibouchina is restricted to the wetter part of the region (southern part), which annually receives at least 1600 mm of precipitation. Tibouchina pulchra was found to clearly indicate forest regeneration as almost all individuals were found within or adjacent to forests regrown after 1962. By contrast, Cecropia hololeuca was found to indicate older disturbed forests, with all individuals almost exclusively found in forest fragments already present in 1962. At the regional scale, using the dominance maps of both species, we show that at least 4.3% of the current region’s natural forests have regrown after 1962 (Tibouchina dominated, ∼ 4757 ha) and that ∼ 9% of the old natural forests have experienced significant disturbance (Cecropia dominated)

Tree community variation in a tropical continental island according to slope aspect and human interference

ABSTRACT Associating description of unrecorded tropical tree community structure to sampling approaches that can help determine mechanisms behind floristic variation is important to further the comprehension of how plant species coexist at tropical forests. Thus, this study had the goals of (i) evaluating tree community structure on the continental island of Marambaia (23°4’37.09”S; 43°59’2.15”W) and (ii) testing the prediction that there are local scale changes in a tropical tree community structure between slopes facing different geographic orientation and with distinct human interference history. We established 60 (0.6 ha) sampling units in three different slope sites with distinct predominant geographic orientation and human interference. We sampled all woody trees with diameter at breast height (dbh) ≥ 5 cm. We found a total of 1.170 individuals representing 220 species, 120 genera and 50 families. The overall tree community structure and structural descriptors (abundance of individuals, basal area, species richness and diversity) varied extensively between the sites. The evidence presented here supports that local scale topography variations and human interference history can be important factors contributing to the known floristic heterogeneity of the Atlantic Rainforest. Future work on the study area should focus on disentangling effects from distinct causal factors over tree community variation and species occurrence

Brazilian Atlantic Forest lato sensu: the most ancient Brazilian forest, and a biodiversity hotspot, is highly threatened by climate change

After 500 years of exploitation and destruction, the Brazilian Atlantic Forest has been reduced to less the 8% of its original cover, and climate change may pose a new threat to the remnants of this biodiversity hotspot. In this study we used modelling techniques to determine present and future geographical distribution of 38 species of trees that are typical of the Brazilian Atlantic Forest (Mata Atlântica), considering two global warming scenarios. The optimistic scenario, based in a 0.5% increase in the concentration of CO2 in the atmosphere, predicts an increase of up to 2 °C in the Earth's average temperature; in the pessimistic scenario, based on a 1% increase in the concentration of CO2 in the atmosphere, temperature increase may reach 4 °C. Using these parameters, the occurrence points of the studied species registered in literature, the Genetic Algorithm for Rule-set Predictions/GARP and Maximum entropy modeling of species geographic distributions/MaxEnt we developed models of present and future possible occurrence of each species, considering Earth's mean temperature by 2050 with the optimistic and the pessimistic scenarios of CO2 emission. The results obtained show an alarming reduction in the area of possible occurrence of the species studied, as well as a shift towards southern areas of Brazil. Using GARP, on average, in the optimistic scenario this reduction is of 25% while in the pessimistic scenario it reaches 50%, and the species that will suffer the worst reduction in their possible area of occurrence are: Euterpe edulis, Mollinedia schottiana, Virola bicuhyba, Inga sessilis and Vochysia magnifica. Using MaxEnt, on average, in the optimistic scenario the reduction will be of 20% while in the pessimistic scenario it reaches 30%, and the species that will suffer the worst reduction are: Hyeronima alchorneoides, Schefflera angustissima, Andira fraxinifolia and the species of Myrtaceae studied