Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSC_T) concentrations in both organs were remarkably similar across communities. However, NSC_T and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSC_T in the form of SS (SS:NSC_T) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.

Tropical forests are recognized for their role in providing diverse ecosystem services (ESs), with carbon uptake the best recognized. The capacity of tropical forests to provide ESs is strongly linked to their enormous biodiversity. However, causal relationships between biodiversity and ESs are poorly understood. This may be because biodiversity is often translated into species richness. Here, we argue that focusing on multiple attributes of biodiversity—structure, composition, and function—will make relationships between biodiversity and ESs clearer. In this review, we discuss the ecological processes behind ESs from tropical humid and subhumid forests of South America. Our main goal is to understand the links between the ESs and those three biodiversity attributes. While supporting and regulating services relate more closely to forest structure and function, provisioning services relate more closely to forest composition and function, and cultural services are more related to structure and composition attributes. In this sense, ESs from subhumid forests (savannas) differ from those provided by the Amazon Forest, although both ecosystems are recognized as harboring tremendous biodiversity. Given this, if anthropogenic drivers of change promote a shift in the Amazon Forest toward savanna—the savannization hypothesis—the types of services provided will change, especially climate regulating services. This review emphasizes the importance of deeply understanding ecosystem structure, composition, and function to better understand the services ecosystems provide. Understanding that anthropogenic impacts on biodiversity occur through these three main attributes, it becomes easier to anticipate how humans will impact ESs.

We investigated the water use of Caatinga vegetation, the largest seasonally dry forest in South America. We identified and analysed the environmental phenological drivers in woody species and their relationship with transpiration. To monitor the phenological evolution, we used remote sensing indices at different spatial and temporal scales: normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and green chromatic coordinate (GCC). To represent the phenology, we used the GCC extracted from in-situ automated digital camera images; indices calculated based on sensors included NDVI, SAVI and GCC from Sentinel-2A and B satellites images, and NDVI products MYD13Q1 and MOD13Q1 from a moderate-resolution imaging spectroradiometer (MODIS). Environmental drivers included continuously monitored rainfall, air temperature, soil moisture, net radiation, and vapour pressure deficit. To monitor soil water status and vegetation water use, we installed soil moisture sensors along three soil profiles and sap flow sensors for five plant species. Our study demonstrated that the near-surface GCC data played an important role in permitting individual monitoring of species, whereas the species’ sap flow data correlated better with NDVI, SAVI, and GCC than with species’ near-surface GCC. The wood density appeared to affect the transpiration cessation times in the dry season, given that species with the lowest wood density reach negligible values of transpiration earlier in the season than those with high woody density. Our results show that soil water availability was the main limiting factor for transpiration during more than 80% of the year, and that both the phenological response and water use are directly related to water availability when relative saturation of the soil profile fell below 0.25.

Several studies have explored the linkages between phenology and ecosystem productivity across the Amazon basin. However, few studies have focused on flooded forests, which correspond to c.a. 14% of the basin. In this study, we assessed the seasonality of ecosystem productivity (gross primary productivity, GPP) from eddy covariance measurements, environmental drivers and phenological patterns obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)) in an Amazonian floodplain forest. We found that ecosystem productivity is limited by soil moisture in two different ways. During the flooded period, the excess of water limits GPP (Spearman’s correlation; rho = −0.22), while during non-flooded months, GPP is positively associated with soil moisture (rho = 0.34). However, GPP is maximized when cumulative water deficit (CWD) increases (rho = 0.81), indicating that GPP is dependent on the amount of water available. EVI was positively associated with leaf litter mass (Pearson’s correlation; r = 0.55) and with GPP (r = 0.50), suggesting a coupling between new leaf production and the phenology of photosynthetic capacity, decreasing both at the peak of the flooded period and at the end of the dry season. EVI was able to describe the inter-annual variations on forest responses to environmental drivers, which have changed during an observed El Niño-Southern Oscillation (ENSO) year (2015/2016).

Long-term meteorological analyzes suggest an increase in air temperature and a decrease in rainfall over the Amazon biome. The effect of these climate changes on the forest remains unresolved, because field observations on functional traits are sparse in time and space, and the results from remote sensing analyses are divergent. Then, we analyzed the drought response in a ‘terra firme’ forest fragment in the southwestern Amazonia, during an extreme drought event influenced by ENSO episode (2015/2017), focusing on stem growth, litter production, functional traits and forest canopy dynamics. We use the Moderate Resolution Imaging Spectroradiometer (MODIS), corrected by Multi-Angle Implementation of Atmospheric Correction (MAIAC) to generate the enhanced vegetation index (EVI) and green chromatic coordinate (Gcc) vegetation indices. We monitor stem growth and measure the functional traits of trees in situ, such as the potential at which the plant loses 50% of hydraulic conductivity (P₅₀), turgor loss point (πTLP), hydraulic safety margin (HSM) and isohydricity. Our results suggest that: (a) during the dry season, there is a smooth reduction in EVI values (browning) and an increase in the wet season (greening); (b) in the dry season, leaf flush occurs, when the water table still has a quota at the limit of the root zone; (c) the forest showed moderate resistance to drought, with water as the primary limiting factor, and the thickest trees were the most resistant; and (d) a decline in stem growth post-El-Niño 2015/2016 was observed, suggesting that the persistence of negative rainfall anomalies may be as critical to the forest as the drought episode itself.

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.