Accurate characterization of the role of the dry tropics in the global carbon cycle requires precise estimation of woody biomass changes due to ecological and anthropogenic change, including deforestation, forest degradation, regrowth, mortality and enhanced tree growth due to climate change. L-band Synthetic Aperture Radar (SAR) backscatter observations offer a reliable option to consistently map these processes as they are (i) available globally since 2007 (JAXA ALOS-1, ALOS-2 and ALOS-4), and (ii) sensitive to woody structure, such as aboveground biomass density (AGBD) up to similar to 100 t ha(-1). However, we lack multi-site empirical understanding of the scattering processes that determine the relationship between L-band SAR and woody vegetation structure in the dry tropics, and how this is mediated by soil properties. This study used observations from ground plots in Africa (n = 171), Australia (n = 6), and South America (n = 44) to understand the impact of vegetation structure and soil properties on spatially and temporally coincident fully-polarimetric L-band SAR data. Fully-polarimetric L-band SAR single-look complex data were converted to scattering mechanisms/parameters using van Zyl, Cloude-Pottier, and Freeman-Durden polarimetric decompositions to elucidate the physical mechanisms involved. Multivariate SAR-vegetation-soil relationships were analysed using a theory-informed structural equation modelling approach. The strongest positive effects on volume scattering come from stem density (stems ha(-1)) and mean stem biomass of trees, and soil water and sand content (standardized regression coefficients of 0.3, 0.1, 0.2 and 0.1, respectively). The only significant effect on surface scattering is from stem density (0.1). Significant effects on double bounce scattering are from stem density (0.3) and soil sand content (-0.2). Since AGBD is the product of stem density and mean stem biomass, this modelling framework points to a stronger effect from the number of trees rather than their size/biomass. Therefore, AGBD maps relying solely on radar intensity may not reflect significant changes when AGBD is increasing due to the growth of existing stems. Additionally, such maps might overestimate changes in AGBD when driven by the recruitment of new stems or loss of existing stems. Full-polarimetric observations allow the decomposition of the radar signal into volume scattering, surface scattering, and double bounce, enabling the inversion of structural equation models to retrieve both stem density and mean stem biomass. This provides a more comprehensive description of forest structure compared to retrieving only AGBD. As this approach depends on full-polarimetric data, its effectiveness is closely tied to the availability of such observations. Our findings underscore the value of recent and upcoming missions such as ALOS-4 PALSAR-3, BIOMASS and ROSE-L, and highlight the need to prioritise the acquisition of quad-pol SAR data to support future large-scale retrieval of vegetation structure attributes.

Hydraulic traits mediate trade-offs between growth and mortality in plants yet characterizing these traits at the community level remains challenging, particularly in the Amazon, where they vary widely across species and environments. While previous studies have used reflectance-based estimates, hydraulic traits, which arise from wood and/or whole-plant anatomy and physiology, have not been comprehensively explored. For the first time, we comprehensively investigated the use of leaf reflectance to predict hydraulic traits alongside leaf functional traits in tropical evergreen and deciduous trees. For 196 Amazonian trees, we measured water potential, leaf mass per area (LMA), leaf reflectance, hydraulic conductivity curves (e.g., P50), and wood density (WD). We examined the relationships between leaf reflectance and traits using partial least square regression (PLSR). Our findings indicate that leaf reflectance accurately predicts variation in LMA (R2 = 0.8), and reasonably estimates xylem water potential (R2 = 0.51) and WD (R2 = 0.52). However, P50 predictions were much less reliable (R2 = 0.27), with water absorption bands greatly influencing the PLSR model. Leaf phenological strategy had little impact on the results. These findings suggest that reflectance-based remote sensing could monitor water status and forest carbon dynamics through water potential and wood density, respectively. However, our case study applying the PLSR approach to hyperspectral canopy spectra to predict wood density revealed challenges to upscaling. Despite these limitations, remote sensing of forest hydraulic traits at scale could enhance our understanding of drought vulnerability and carbon dynamics in Amazonian forests, with significant implications for conservation.

Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.

Global warming poses a significant impact on plant species in the Cerrado, the largest savanna in the world. However, there is still a gap in understanding how species distribution patterns are associated with their thermal sensitivity. One approach to address this is quantifying species´ specific responses through leaf traits related to heat stress. Therefore, we determined the temperature that caused a 50

Tropical forest canopies are the biosphere's most concentrated atmospheric interface for carbon, water and energy1,2. However, in most Earth System Models, the diverse and heterogeneous tropical forest biome is represented as a largely uniform ecosystem with either a singular or a small number of fixed canopy ecophysiological properties3. This situation arises, in part, from a lack of understanding about how and why the functional properties of tropical forest canopies vary geographically4. Here, by combining field-collected data from more than 1,800 vegetation plots and tree traits with satellite remote-sensing, terrain, climate and soil data, we predict variation across 13 morphological, structural and chemical functional traits of trees, and use this to compute and map the functional diversity of tropical forests. Our findings reveal that the tropical Americas, Africa and Asia tend to occupy different portions of the total functional trait space available across tropical forests. Tropical American forests are predicted to have 40% greater functional richness than tropical African and Asian forests. Meanwhile, African forests have the highest functional divergence-32% and 7% higher than that of tropical American and Asian forests, respectively. An uncertainty analysis highlights priority regions for further data collection, which would refine and improve these maps. Our predictions represent a ground-based and remotely enabled global analysis of how and why the functional traits of tropical forest canopies vary across space.

From heightened canopy dieback to tree die-off, many forest ecosystems are showing signs of poorly coping with more severe, more frequent, or hotter droughts. Understanding forest resilience to drought has become paramount, and eco‐physiological optimisation approaches that test behavioural hypotheses have been proposed as a means to build this understanding in global terrestrial models. Here, we used a land-surface model that considers competing optimality principles to simulate canopy gas exchange and leaf nitrogen investments into the photosynthetic apparatus, whilst also accounting for sustained hydraulic impairment (Sabot et al., 2022). We applied this model to a pristine observational site of the Caatinga, Brazil’s drought-hardy, seasonally deciduous, and exceptionally diverse dry tropical forest. Six woody species dominate 80% of the study area whilst displaying contrasting functional strategies – for example, their respective P50s (the water potential at which 50% of a plant’s hydraulic conductivity is lost) range between -1 MPa and -5 MPa. Model predictions were assessed against species-specific leaf-level observations of stomatal conductance and photosynthetic uptake, as well as eddy covariance measurements of ecosystem carbon and water fluxes spanning a period with high interannual rainfall variability (and including a severe multi-year regional drought). We found that none of the six species could, in isolation, explain the magnitude and dynamics of the observed surface fluxes. However, taken together and accounting for their relative contribution to total ecosystem fluxes, they did. Further, our analysis emphasises the vital role of phenology in mitigating seasonal and inter-annual hydraulic risks, with foliage reductions triggered by a 10 to 20% loss of hydraulic conductivity in the canopy. On the whole, accounting for diverging species-level responses and their relative influence at the ecosystem-scale appears key to improving model predictions in functional diverse forests. Reference: Sabot, M.E.B., De Kauwe, M.G., Pitman, A.J., Ellsworth, D.S., Medlyn, B.E., Caldararu, S. et al. (2022) Predicting resilience through the lens of competing adjustments to vegetation function. Plant, Cell & Environment, 45, 2744–2761.

Nutrient resorption efficiency (RE) occurs before leaf abscission, with nutrients being actively transported via phloem through abscission zones from senescent leaves to be used in other parts of the plant. It is an essential nutrient conservation strategy for tropical plants growing on soils depleted of P (phosphorus) and other rock-derived elements (K; potassium, Ca; calcium, and Mg; magnesium), influencing nutrient cycling in these ecosystems. The environment heavily influences resorption; therefore, a better understanding of nutrient resorption processes in tropical trees, which act as a carbon sink, is important when facing the rapid climatic changes. Thus, our objective was to investigate the resorption of five macro elements (C; carbon, N; nitrogen, P, K, Ca, and Mg) and three micronutrients (Fe; iron, Zn; zinc, and Mn; manganese), and the effects of leaf longevity, foliar nutrient concentration, and canopy position in RE in a lowland forest tree community in Central Amazon. The study was conducted in two experimental plots at the AmazonFACE Program (Free-Air CO2 Enrichment) in Manaus, Amazonas, Brazil. Two 40 m scaffolding towers in the center of the plot granting access to the canopy of the twelve tree species studied. Young, mature, and senesced leaves were collected, totaling 188 leaves, from 2018 to 2019 for nutrient laboratory analysis. We found that K, P, and N were the most resorbed nutrients (42%, 33%, and 7%, respectively), while Zn, Fe, and Ca were the most accumulated (-65%, -27%, and -21%, respectively). Additionally, we found that C, N, P, Fe, and Zn resorption positively correlated with their concentration in leaves. Likewise, P, N, Mg, K, and C resorption positively correlated with leaf longevity. On the other hand, canopy position influenced the resorption of three elements: C, K, and Zn resorption. Our results suggest that P was the scarcest nutrient stored in leaves; the higher resorption efficiencies for K and P than for N suggest higher plant internal nutrient recycling of K and P, likely due to their scarcity in the soil during leaf senescence, species with longer leaf life span are often assumed to have higher nutrient resorption efficiency than species with short leaf life span to reduce nutrient loss, species in the community studied can optimize leaf anatomy and physiology to make the best use of the variable light encountered regarding of its position on the forest vertical profile. These trends suggest that nutrient resorption from senescent leaves may be a general adaptive strategy for conserving nutrients by plants in tropical forests growing on nutrient-poor soils, which should be considered when predicting future scenarios.

Global warming significantly threatens species in the Cerrado, the world's largest savannah. Therefore, understanding how plants respond to temperature change, particularly in relation to leaf-level photosynthetic capacity, is crucial to understanding the future of Cerrado vegetation. Here, we determined the optimum temperature of the maximum rate of RuBP-carboxylation and maximum electron transport rate (TOptV and TOptJ, respectively) of 12 tree species in two opposite borders (northeastern and southeastern) of the Cerrado with distinct temperature regimes. We focused on four widespread species found in both sites, four restricted to the northeast, and four to the southeast. We compared TOptV and TOptJ between regions and between widespread species (co-occurring in both sites) and species restricted to each ecoregion. Additionally, we also explored the relationship between TOptV and TOptJ with leaf nitrogen (N), phosphorus (P) and potassium (K). As a result, we found that TOptV and TOptJ values were similar across species, regardless of the study region or species distribution range. The similarity of TOpt values among species suggests that photosynthetic performance is optimized to current temperatures. Additionally, we also observed that the TOptV and TOptJ were similar to the local maximum ambient temperatures. Therefore, if these species do not have enough plasticity, the increasing temperature predicted for this region may reduce their photosynthetic performance. Finally, the studied species exhibited general relationships between the TOptV and TOptJ and foliar key nutrients, particularly with P, suggesting the nutrient availability has an important role in the thermal acclimation of leaves. These findings offer valuable insights into physiological and ecological mechanisms in photosynthesis performance present in the Cerrado species.

The Amazon Rainforest vegetation responses to climate change are still far from being fully understood, especially when the focus is not on the forest canopy stratum. Concerning the changes in water use related to rising atmospheric CO2 levels, the distinct responses between forest strata of the Amazon are still uncertain. The project presented here consists in exploring data from an experimental study coupled with a mathematical modeling approach, with the goal to elucidate, in relation to rising CO2 levels, the transpiration responses of Central Amazon understorey plants, which may influence the entire region due to forest-atmosphere water flux disturbances. More specifically, we artificially increase the CO2 atmospheric concentration inside open-top chambers installed in the understory, providing a way to evaluate the response of the plants inside the chamber to the increased CO2 levels. With the estimation of carbon assimilation and stomatal conductance processes parameters defined by mathematical models, it is possible to characterize physiologically the response of the individuals in the experiment and compare the differences between control and treatment groups. Then, the impact of these changes in the understory transpiration is estimated by measuring the leaf area index of the understory and combining the obtained stomatal conductance parameters with another mathematical model, which makes it possible to compare the impact of the experimental treatment in the amount of water that travels from the understorey plants to the atmosphere through stomata. The results and methodology from this study, in addition to the importance to accomplishing the main goal mentioned above, are also relevant for the use of Dynamic Global Vegetation Models (DGVM), as the mathematical equations employed are also frequently used in DGVM studies. Finally, the experimental site being studied is also where the first Free-Air CO2 Enrichment experiment in the Amazon, known as AmazonFACE, will be conducted, so the open-top chambers data can be considered a source of basal knowledge for the large scale project that is being implemented at the same location.

The Atlantic Forest is critically threatened by habitat fragmentation, requiring various restoration efforts to restore essential ecosystem functions. However, with the projected rise in extreme weather events such as heatwaves and droughts, the success of ecological restoration will depend on species’ ability to perform at higher temperatures. To better understand the thermal response of tree species in restored Atlantic Forest areas, we measured carbon assimilation under saturating light (Asat), the maximum rate of RuBP carboxylation (VCmax), the rate of electron transport (Jmax), and stomatal conductance (gs) in six species from contrasting successional groups in a restored area, across a range of leaf temperatures to determine their thermal optima for each parameter (TOptA, TOptV, TOptJ, and TOpgs, respectively). We tested the difference in thermal optima between early- and late-successional species and examined stomatal and biochemical control over TOptA. As a result, no significant differences were found in the photosynthetic thermal optimum between successional groups. Additionally, TOptgs was most strongly correlated with TOptA. However, TOptA in early successional species exhibited a stronger relationship with TOptJ, which contradicts findings in the literature for tropical biomes. These contrasting results raise important questions about the ecological and physiological mechanisms that may differ between reforested and natural ecosystems. Consequently, further research is needed to better understand species acclimation and adaptation in restored areas.

The response of plants to increasing atmospheric CO2 concentration depends on several factors such as life history of specific species, availability of water, nutrients and light, and the ecological context that the plants are found. Although several experiments with elevated CO2 (eCO2) have been done worldwide, none was performed in the Amazon forest understory focusing in a community growing naturally. The understory of the central Amazon is limited by both light and phosphorus. Understanding how such ecosystem responds to eCO2 is important to foresee how the forest will function in the future. Also, quantifying the response of this forest compartment helps to constrain Ecosystem Models that compute carbon and water fluxes. For this study, we used the open-top chamber (OTC) approach, with a CO2 enrichment of +250 ppm above the ambient concentration. Eight OTC were installed (4 with ambient CO2 and another 4 with eCO2) in the understory of a natural forest in the Central Amazon, approximately 70 km from Manaus city. The eCO2 experiment started in November 2019 and, after 120 days, we quantified the average community response of the following photosynthetic parameters: light saturated carbon assimilation rate (Asat), stomatal conductance (gs), transpiration rate (E), intrinsic water use efficiency (iWUE), apparent quantum yield (Φ), light compensation point (LCP), maximum carboxylation capacity (Vcmax), maximum electron transport rate (Jmax). After 240 days of treatment, we quantified mean individual leaf production and accumulated leaf production, leaf area (Lfarea). After 300 days, we quantified the increment in base diameter (BD), height (Ht) and relative growth rate (RGR). Under eCO2, we observed increases in Asat (67%), Jmax (19%), Φ (56%), and iWUE (78%), in agreement with the hypothesis that plants near the light compensation point respond strongly to eCO2. We also detected an increase in Lfarea (51%) and BD (65%), indicating that the extra primary productivity was not allocated to growth in height, but to supporting more light intercepting organs (leaf and conducting tissues). No detectable changes were observed for the other variables. Apart from the expected increase in assimilation rates, understory plants in Central Amazon responded positively to eCO2 by increasing their ability to capture and use light (leaf size, Φ, and Jmax). The increment in leaf area while maintaining E rates signifies that this forest compartment will increase its contribution to the whole forest water fluxes to the atmosphere. That might be related to the prevailing acquisitive strategy necessary for competing for phosphorus brought by water flow through plants. As a possible consequence, this forest might be less resistant to extreme drought associated with El Niño years. Funding: Coordination for the Improvement of Higher Education Personnel - CAPES (grants 312589/2022-0) and São Paulo Research Foundation-FAPESP processes numbers (2022/07735-5) and (2015/02537-7).

ABSTRACTTraditional leaf gas exchange experiments have focused on net CO2 exchange (Anet). Here, using California poplar (Populus trichocarpa), we coupled measurements of net oxygen production (NOP), isoprene emissions and δ18O in O2 to traditional CO2/H2O gas exchange with chlorophyll fluorescence, and measured light, CO2 and temperature response curves. This allowed us to obtain a comprehensive picture of the photosynthetic redox budget including electron transport rate (ETR) and estimates of the mean assimilatory quotient (AQ = Anet/NOP). We found that Anet and NOP were linearly correlated across environmental gradients with similar observed AQ values during light (1.25 ± 0.05) and CO2 responses (1.23 ± 0.07). In contrast, AQ was suppressed during leaf temperature responses in the light (0.87 ± 0.28), potentially due to the acceleration of alternative ETR sinks like lipid synthesis. Anet and NOP had an optimum temperature (Topt) of 31°C, while ETR and δ18O in O2 (35°C) and isoprene emissions (39°C) had distinctly higher Topt. The results confirm a tight connection between water oxidation and ETR and support a view of light‐dependent lipid synthesis primarily driven by photosynthetic ATP/NADPH not consumed by the Calvin–Benson cycle, as an important thermotolerance mechanism linked with high rates of (photo)respiration and CO2/O2 recycling.

This dataset is for paper "Leaf nitrogen from the perspective of optimal plant function"

The response of plants to increasing atmospheric CO2 depends on the ecological context where the plants are found. Several experiments with elevated CO2 (eCO2) have been done worldwide, but the Amazonian forest understory has been neglected. As the central Amazon is limited by light and phosphorus, understanding how understory responds to eCO2 is important for foreseeing how the forest will function in the future. In the understory of a natural forest in the Central Amazon, we installed four open-top chambers as control replicates and another four under eCO2 (+250 ppm above ambient levels). Under eCO2, we observed increases in carbon assimilation rate (67%), maximum electron transport rate (19%), quantum yield (56%), and water use efficiency (78%). We also detected an increase in leaf area (51%) and stem diameter increment (65%). Central Amazon understory responded positively to eCO2 by increasing their ability to capture and use light and the extra primary productivity was allocated to supporting more leaf and conducting tissues. The increment in leaf area while maintaining transpiration rates suggests that the understory will increase its contribution to evapotranspiration. Therefore, this forest might be less resistant in the future to extreme drought, as no reduction in transpiration rates were detected.

Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an 'isohydric-anisohydric' spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (Psi L) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum Psi L. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in Psi L. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems.

The leaf phenology of seasonally dry tropical forests (SDTFs) is highly seasonal, marked by synchronized flushing of new leaves triggered by the first rains of the wet season. Such phenological transitions may not be accurately detected by remote sensing vegetation indices and derived transition dates (TDs) due to the coarse spatial and temporal resolutions of satellite data. The aim of this study was to compared TDs from PhenoCams and satellite remote sensing (RS) and used the TDs calculated from PhenoCams to select the best thresholds for RS time series and calculate TDs. For this purpose, we assembled cameras in seven sites along an aridity gradient in the Brazilian Caatinga, a region dominated by SDTFs. The leafing patterns were registered during one to three growing seasons from 2017 to 2020. We drew a region of interest (ROI) in the images to calculate the normalized green chromatic coordinate index. We compared the camera data with the NDVI time series (2000–2019) derived from near-infrared (NIR) and red bands from MODIS product data. Using calibrated PhenoCam thresholds reduced the mean absolute error by 5 days for SOS and 34 days for EOS, compared to common thresholds in land surface phenology studies. On average, growing season length (LOS) did not differ significantly among vegetation types, but the driest sites showed the highest interannual variation. This pattern was applied to leaf flushing (SOS) and leaf fall (EOS) as well. We found a positive relationship between the accumulated precipitation and the LOS and between the accumulated precipitation and maximum and minimum temperatures and the vegetation productivity (peak and accumulated NDVI). Our results demonstrated that (A) the fine temporal resolution of phenocamera phenology time series improved the definitions of TDs and thresholds for RS landscape phenology; (b) long-term RS greening responded to the variability in rainfall, adjusting their timing of green-up and green-down, and (C) the amount of rainfall, although not determinant for the length of the growing season, is related to the estimates of vegetation productivity.

We propose a temperature-dependent scaling factor for the ‘one-point method’ to mitigate the overestimation of the maximum carboxylation capacity of photosynthesis at high temperatures.

Soil nitrogen isotopic composition (δ15Nsoil) is an invaluable tool as it integrates nitrogen (N) transformations in soils. In addition to serving as a baseline to understand the N cycle, spatial representations of δ15Nsoil across landscapes (or isoscapes) is a multi-purpose tool useful to investigate, for example, plant-microbe interactions, animal migration and forensics. We investigate the climatic and edaphic controls of δ15Nsoil utilising data from 29 geographical locations sampled across the semiarid Brazilian Caatinga biome. The sampling covered a mean annual precipitation (PA) gradient ranging from 0.51 to 1.36 m a-1 and eight soil types originating from three different geological origins. Our data show that the combination of higher aridity and lower seasonality (ψ) leads to higher values of δ15Nsoil. Moreover, soil total carbon had a positive relationship with δ15Nsoil, appearing within the best-supported models according to the information-theoretic approach undertaken here. The contribution to the plant communities by the Fabaceae trees expressed as their basal area was not related to δ15Nsoil values, suggesting that the magnitude of biological N fixation in the Caatinga is not large enough to be reflected in the soil. In addition, considering PA in a categorical fashion, i.e., 'high' (> 0.8 m a-1) and 'low' PA (< 0.8 m a-1), we found that, within the wetter category, δ15Nsoil was positively related to several soil properties (i.e., clay content, effective cation exchange capacity, exchangeable calcium, silt content, pHH2O, total phosphorus and sum of bases) and negatively related to sand content. Our study provides new insights into the functioning of semiarid ecosystems from a pedo-isotopic perspective and contributes to the overall understanding of the N cycle in the Caatinga region, with the potential to support the development of new conceptualisation of biogeochemical process and testing of global models that simulate N and C cycles.

AimUnderstanding tree mortality under climate change-induced droughts requires knowledge of hydraulic trait distribution across environmental gradients. The spatial distribution of embolism resistance (i.e., P50), a key trait linked to hydraulic failure, is currently unknown across the Amazon. Here, we tested how precipitation, water table depth (WTD) and soil fertility interact as filters modulating the geographic hydraulic trait distribution.LocationFour sites in three key regions across the Amazon basin: Central, Western peripheral area and Brazilian Shield.Time PeriodPresent.Major Taxa StudiedTree species.MethodWe measured hydraulic vulnerability curves of 64 tree species (165 individuals) using an orthogonal design contrasting seasonal precipitation gradients, soil fertility and WTD. To estimate the geographical distribution of hydraulic traits for the basin scale, we use the coefficients of the best generalized linear model, projected on a 1 km grid in each environmental layer.ResultsWe show that WTD and soil fertility are the main drivers of embolism resistance, while precipitation has a secondary effect. Trees in shallow WTD and fertile soils had riskier hydraulic strategies. Our spatial projection identified the Amazonian southern band and valleys across the basin as the most vulnerable areas. High soil fertility in these regions increases the variability of hydraulic traits and thus uncertainty in predictions of drought responses.Main ConclusionAt the scale of the Amazon basin, we show that dominant tree species traits converge toward hydraulic resistance when resource (water and nutrients) levels are low and towards hydraulic vulnerability (but with higher trait variability) when resources increase. These results highlight the importance of WTD and soil fertility in structuring hydraulic traits and their effects on tree mortality under climate change-induced droughts. Further empirical tests covering a wider spatial range and more tree species will help validate our biogeographical distribution model.