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.

The atmospheric boundary layer height ($zi$) is a key parameter in the vertical transport of mass, energy, moisture, and chemical species between the surface and the free atmosphere. There is a lack of long-term and continuous observations of $zi$, however, particularly for remote regions, such as the Amazon forest. Reanalysis products, such as ERA5, can fill this gap by providing temporally and spatially resolved information on $zi$. In this work, we evaluate the ERA5 estimates of $zi$ ($zi$-ERA5) for two locations in the Amazon and corrected them by means of ceilometer, radiosondes, and SODAR measurements ($zi$-experimental). The experimental data were obtained at the remote Amazon Tall Tower Observatory (ATTO) with its pristine tropical forest cover and the T3 site downwind of the city of Manaus with a mixture of forest ($63\%$), pasture ($17\%$), and rivers ($20\%$). We focus on the rather typical year 2014 and the El Niño year 2015. The comparison of the experimental vs. ERA5 $zi$ data yielded the following results: (i) $zi$-ERA5 underestimates $zi$-experimental daytime at the T3 site for both years 2014 (30%, underestimate) and 2015 (15%, underestimate); (ii) $zi$-ERA5 overestimates $zi$-experimental daytime at ATTO site (12%, overestimate); (iii) during nighttime, no significant correlation between the $zi$-experimental and $zi$-ERA5 was observed. Based on these findings, we propose a correction for the daytime $zi$-ERA5, for both sites and for both years, which yields a better agreement between experimental and ERA5 data. These results and corrections are relevant for studies at ATTO and the T3 site and can likely also be applied at further locations in the Amazon.

The Amazon biome contains more than half of the remaining tropical forests of the planet and has a strong impact on aspects of meteorology such as the planetary boundary layer (PBL). In this context, the objective of this study was to conduct observational evaluations of the daily cycle of the height of the PBL during its stable (night) and convective (day) phases from data that were measured and/or estimated using instruments such as a radiosonde, sodar, ceilometer, wind profiler, lidar and microwave radiometer installed in the central Amazon during 2014 (considered a typical year) and 2015 during which an intense El Niño–Southern Oscillation (ENSO) event predominated during the GoAmazon experiment. The results from the four intense observation periods (IOPs) show that during the day and night periods, independent of dry or rainy seasons, the ceilometer is the instrument that best describes the depth of the PBL when compared with in situ radiosonde measurements. Additionally, during the dry season in 2015, the ENSO substantially influenced the growth phase of the PBL, with a 15 % increase in the rate compared to the same period in 2014.

Planetary Boundary Layer (PBL) parameterization schemes are employed to handle subgrid-scale processes on atmospheric models, playing a key role in accurately representing the atmosphere. Recent studies have shown that PBL schemes are particularly fundamental to the depiction of PBL height (PBLH), especially over the Amazon. In the present study, we investigated the performance of PBL schemes on the representation of meteorological variables, turbulent fluxes, PBL vertical structures, and PBLH over the central Amazon basin under dry conditions, taking advantage of observations from the Observations and Modeling of the Green Ocean Amazon campaign (GoAmazon2014/5) for validation and evaluation. Numerical experiments were carried out within the WRF model using eight PBL schemes for two dry periods from 2014 (typical year) and 2015 (El-Niño year), and results from the 1-km resolution domain were directly compared to hourly in situ observations. In general, all PBL schemes present good performance to reproduce meteorological variables, with nonlocal (local) PBL schemes producing better performance in the 2014 (2015) study period. All PBL schemes in general overestimate (>100%) daytime turbulent fluxes. Thermodynamic (daytime) vertical structures are better predicted than mechanical (nocturnal) ones. The local MYNN2.5 scheme showed the overall best performance for PBLH prediction, mainly at night.

This study investigated the erosion of the nocturnal boundary layer (NBL) over the central Amazon using a high-resolution model of large-eddy simulation (LES) named PArallel Les Model (PALM) and observational data from Green Ocean Amazon (GoAmazon) project 2014/5. This data set was collected during four intense observation periods (IOPs) in the dry and rainy seasons in the years 2014 (considered a typical year) and 2015, during which an El Niño–Southern Oscillation (ENSO) event predominated and provoked an intense dry season. The outputs from the PALM simulations represented reasonably well the NBL erosion, and the results showed that it has different characteristics between the seasons. During the rainy season, the IOPs exhibited slow surface heating and less intense convection, which resulted in a longer erosion period, typically about 3 h after sunrise (that occurs at 06:00 local time). In contrast, dry IOPs showed more intensive surface warming with stronger convection, resulting in faster NBL erosion, about 2 h after sunrise. A conceptual model was derived to investigate the complete erosion during sunrise hours when there is a very shallow mixed layer formed close to the surface and a stable layer above. The kinematic heat flux for heating this layer during the erosion period showed that for the rainy season, the energy emitted from the surface and the entrainment was not enough to fully heat the NBL layer and erode it. Approximately 30% of additional energy was used in the system, which could come from the release of energy from biomass. The dry period of 2014 showed stronger heating, but it was also not enough, requiring approximately 6% of additional energy. However, for the 2015 dry period, which was under the influence of the ENSO event, it was shown that the released surface fluxes were sufficient to fully heat the layer. The erosion time of the NBL probably influenced the development of the convective boundary layer (CBL), wherein greater vertical development was observed in the dry season IOPs (~1500 m), while the rainy season IOPs had a shallower layer (~1200 m).

The use of stable isotopes of hydrogen and oxygen is a tool widely used to trace water paths along the hydrological cycle, providing support for understanding climatic conditions in different spatial scales. One of the main synoptic scale events acting in southeastern Brazil is the South Atlantic Convergence Zone (SACZ), which causes a large amount of precipitation from southern Amazonia to southeastern Brazil during the southern summer. In order to determine the isotopic composition of precipitation during the action of SACZ in São Francisco Xavier in southeastern Brazil, information from the Weather Forecasting and Climate Studies Center of the National Institute for Space Research (CPTEC) was used regarding SACZ performance days, the retrograde trajectories of the HYSPLIT model, and images from the GOES-16 satellite, in addition to the non-parametric statistical tests by Spearman and Kruskal–Wallis. A high frequency of air mass trajectories from the Amazon to southeastern Brazil was observed when the SACZ was operating. During the SACZ events, the average isotopic composition of precipitation was more depleted, with a δ¹⁸O of −9.9‰ (±2.1‰), a δ²H of −69.3‰ (±17.9‰), and d-excess of 10.1‰ (±4.0‰). When disregarding the SACZ performance, the annual isotopic composition can present an enrichment of 1.0‰ for δ¹⁸O and 8.8‰ for the δ²H. The long-term monitoring of trends in the isotopic composition of precipitation during the SACZ events can assist in indicating the evapotranspiration contribution of the Amazon rainforest to the water supply of southeastern Brazil.