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The Atlantic forest is one of the world's major tropical biomes due to its rich biodiversity. Its vast diversity of plant species poses challenges in floristic surveys. Fourier transform infrared spectroscopy (FTIR) enables rapid and residue-free data collection, providing diverse applications in organic sample analysis. FTIR spectra quality depends on the sample preparation methodology. However, no research on FTIR spectroscopy methodology for taxonomy has been conducted with tropical tree species. Hence, this study addresses the sample preparation influence on FTIR spectra for the taxonomic classification of 12 tree species collected in the Serra do Mar State Park (PESM) - Cunha Nucleus – São Paulo State, Brazil. Spectra were obtained from intact fresh (FL), intact dried (DL), and heat-dried ground (GL) leaves. The spectra were evaluated through chemometrics using Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Linear Discriminant Analysis (LDA) with validation by LDA-PCA. The results demonstrate that sample preparation directly influences tropical species FTIR spectra categorization capability. The best taxonomic classification result for all techniques, validated by LDA-PCA, was obtained from GL. FTIR spectra evaluation through PCA, HCA, and LDA allow for the observation of phylogenetic relationships among the species. FTIR spectroscopy proves to be a viable technique for taxonomic evaluation of tree species in floristic exploration of tropical biomes which can complement traditional tools used for taxonomic studies.

ABSTRACT Knowledge about water resources is critical for climate adaptation in face of long-term changes and more frequent extreme events occurrence. During the major droughts of 2005 and 2010, a large epicenter was located in the southwestern Amazon over the Purus River Basin. In this sense, we conducted a hydrological simulation in this basin to assess the climate change impacts on its water resources throughout the 21st century. The water balance was simulated using the Distributed Hydrological Model (MHD-INPE). The future climate projections were simulated by the regional ETA-INPE model driven by a 4-member HadCM3 global model regarding the A1B-AR4/IPCC scenario of greenhouse gases emissions. As simulated by the ETA-INPE/HadCM3, the 4-members mean response for the A1B scenario represents a rainfall reduction of up to 11.1%, a temperature increase of up to 4.4 °C, and a wind speed increase of up to 8.4% in the Purus Basin by the end of 21st century. Under these conditions, the discharge projections represent an overall 27% decrease in the Purus Basin with different patterns between dry and wet season, as well as changes in seasonality trends. The consequences of projected climate change are severe and will probably have a great impact upon natural ecosystem maintenance and human subsistence. In a climate change adaptation process, the preservation of the natural forest cover of the Purus Basin may have great importance in water retention.