Lianas in tropical dry seasonal forests have a high hydraulic efficiency but not always a higher embolism resistance than lianas in rainforests.

BACKGROUND AND AIMS: Lianas have higher relative abundance and biomass in drier seasonal forests than in rainforests, but whether this difference is associated with their hydraulic strategies is unclear. Here, we investigate whether lianas of seasonally dry forests are safer and more efficient in water transport than rainforest lianas, explaining patterns of liana abundance. METHODS: We measured hydraulic traits on five pairs of congeneric lianas of the tribe Bignonieae in two contrasting forest sites: the wet 'Dense Ombrophilous Forest' in Central Amazonia (~2 dry months) and the drier 'Semideciduous Seasonal Forest' in the inland Atlantic Forest (~6 dry months). We also gathered a broader database, including 197 trees and 58 liana species from different tropical forests, to compare hydraulic safety between habits and forest types. KEY RESULTS: Bignonieae lianas from both forests had high and similar hydraulic efficiency but exhibited variability in resistance to embolism across forest types when phylogenetic relationships were taken into account. Three genera had higher hydraulic safety in the seasonal forest than in the rainforest, but species across both forests had similar positive hydraulic safety margins despite lower predawn water potential values of seasonal forest lianas. We did not find the safety-efficiency trade-off. Merging our results with previously published data revealed a high variability of resistance to embolism in both trees and lianas, independent of forest types. CONCLUSIONS: The high hydraulic efficiency of lianas detected here probably favours their rapid growth across tropical forests, but differences in hydraulic safety highlight that some species are highly vulnerable and may rely on other mechanisms to cope with drought. Future research on the lethal dehydration threshold and the connection between hydraulic resistance strategies and liana abundance could offer further insights into tropical forest dynamics under climatic threats.

The other side of tropical forest drought: do shallow water table regions of Amazonia act as large-scale hydrological refugia from drought?

Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they represent c. 50% of the Amazon and are expected to respond differently to global-change-related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource-acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During 'normal' climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought-intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts.

O funcionamento da floresta tropical é de importância global para as respostas às mudanças climáticas e é criticamente determinado pelos padrões de disponibilidade de água. A água subterrânea está intimamente relacionada à água do solo através da profundidade do lençol freático, que tem sido historicamente negligenciado em estudos ecológicos. Florestas com lençol freático raso (< 5 m) estão sub-representadas nas redes de pesquisa florestal e ausentes nas medições de fluxo de gases, embora representem ~ 50% da Amazônia e devam responder de forma diferente às secas relacionadas às mudanças globais. Aqui revisamos os padrões de profundidade do lençol freático e suas consequências para plantas, resultados emergentes, e avançamos em um modelo conceitual que integra o ambiente e as distribuições de características funcionais para prever os efeitos das mudanças climáticas. As florestas com lençol freático raso têm uma composição de espécies distinta, com árvores mais aquisitivas na obtenção de recursos e hidrologicamente vulneráveis, dosséis mais baixos e menor biomassa do que as florestas com lençol freático profundo. Durante os anos climáticos 'normais', as florestas com lençol freático raso têm maior mortalidade e menor produtividade do que as florestas com lençol freático profundo, mas durante secas moderadas, a mortalidade é amortecida e a produtividade aumenta. No entanto, durante secas severas, as florestas com lençol freático raso podem ser mais sensíveis devido às raízes superficiais e características funcionais de intolerância à seca. Nossas evidências apoiam a hipótese de que as florestas com lençol freático raso, historicamente negligenciadas, sejam resilientes à seca moderada, desafiando a visão predominante dos efeitos negativos generalizados da mudança climática nas florestas amazônicas que ignora gradientes de profundidade do lençol freático, mas prevê que elas podem entrar em colapso sob secas muito fortes.

La función de los bosques tropicales es de importancia mundial para las respuestas al cambio climático y está críticamente determinada por los patrones de disponibilidad de agua. El agua subterránea está estrechamente relacionada con el agua del suelo a través de la profundidad del nivel freático (NF), pero históricamente se há negligenciado en los estudios ecológicos. Los bosques con NF poco profundos (NF < 5 m) están subrepresentados en las redes de investigación forestal y ausentes en las mediciones de flujo de gases, aunque representan ~ 50% de la Amazonía y se espera que respondan de manera diferente a las sequías relacionadas con el cambio climático global. Aquí revisamos los patrones de NF y las consecuencias para las plantas, los resultados emergentes y avanzamos en un modelo conceptual que integra distribuciones ambientales y de rasgos funcionales para predecir los efectos del cambio climático. Los bosques con NF poco profundos tienen una composición de especies distinta, con árboles más adquisitivos en la obtención de recursos e hidrológicamente más vulnerables, dosel más bajo y menor biomasa que los bosques de NF profundo. Durante los años climáticos 'normales', los bosques con NF poco profundos tienen una mayor mortalidad y menor productividad que los bosques con NF profundos, pero durante sequías moderadas la mortalidad se amortigua y la productividad aumenta. Sin embargo, durante una sequía severa, los bosques de NF poco profundos pueden ser más sensibles debido a raíces poco profundas y rasgos de intolerancia a la sequía. Nuestra evidencia apoya la hipótesis de que los bosques de NF poco profundos, mayoritariamente desconsiderados, son resistentes a sequías moderadas, desafiando la visión predominante de impactos negativos generalizados del cambio climático en los bosques amazónicos, que ignora los gradientes de NF, pero predice que podrían colapsar bajo sequías muy fuertes.

Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

For more than three decades, major efforts in sampling and analyzing tree diversity in South America have focused almost exclusively on trees with stems of at least 10 and 2.5 cm diameter, showing highest species diversity in the wetter western and northern Amazon forests. By contrast, little attention has been paid to patterns and drivers of diversity in the largest canopy and emergent trees, which is surprising given these have dominant ecological functions. Here, we use a machine learning approach to quantify the importance of environmental factors and apply it to generate spatial predictions of the species diversity of all trees (dbh ≥ 10 cm) and for very large trees (dbh ≥ 70 cm) using data from 243 forest plots (108,450 trees and 2832 species) distributed across different forest types and biogeographic regions of the Brazilian Amazon. The diversity of large trees and of all trees was significantly associated with three environmental factors, but in contrasting ways across regions and forest types. Environmental variables associated with disturbances, for example, the lightning flash rate and wind speed, as well as the fraction of photosynthetically active radiation, tend to govern the diversity of large trees. Upland rainforests in the Guiana Shield and Roraima regions had a high diversity of large trees. By contrast, variables associated with resources tend to govern tree diversity in general. Places such as the province of Imeri and the northern portion of the province of Madeira stand out for their high diversity of species in general. Climatic and topographic stability and functional adaptation mechanisms promote ideal conditions for species diversity. Finally, we mapped general patterns of tree species diversity in the Brazilian Amazon, which differ substantially depending on size class.

Local hydrological gradients structure high intraspecific variability in plant hydraulic traits in two dominant central Amazonian tree species.

Addressing the intraspecific variability of functional traits helps understand how climate change might influence the distribution of organismal traits across environments, but this is notably understudied in the Amazon, especially for plant hydraulic traits commonly used to project drought responses. We quantified the intraspecific trait variability of leaf mass per area, wood density, and xylem embolism resistance for two dominant central Amazonian tree species, along gradients of water and light availability, while accounting for tree age and height. Intraspecific variability in hydraulic traits was high, with within-species variability comparable to the whole-community variation. Hydraulic trait variation was modulated mostly by the hydrological environment, with higher embolism resistance of trees growing on deep-water-table plateaus compared with shallow-water-table valleys. Intraspecific variability of leaf mass per area and wood density was mostly modulated by intrinsic factors and light. The different environmental and intrinsic drivers of variation among and within individuals lead to an uncoupled coordination among carbon acquisition/conservation and water-use traits. Our findings suggest multivariate ecological strategies driving tropical tree distributions even within species, and reflect differential within-population sensitivities along environmental gradients. Therefore, intraspecific trait variability must be considered for accurate predictions of the responses of tropical forests to climate change.

The other side of droughts: wet extremes and topography as buffers of negative drought effects in an Amazonian forest.

There is a consensus about negative impacts of droughts in Amazonia. Yet, extreme wet episodes, which are becoming as severe and frequent as droughts, are overlooked and their impacts remain poorly understood. Moreover, drought reports are mostly based on forests over a deep water table (DWT), which may be particularly sensitive to dry conditions. Based on demographic responses of 30 abundant tree species over the past two decades, in this study we analyzed the impacts of severe droughts but also of concurrent extreme wet periods, and how topographic affiliation (to shallow - SWTs - or deep - DWTs - water tables), together with species functional traits, mediated climate effects on trees. Dry and wet extremes decreased growth and increased tree mortality, but interactions of these climatic anomalies had the highest and most positive impact, mitigating the simple negative effects. Despite being more drought-tolerant, species in DWT forests were more negatively affected than hydraulically vulnerable species in SWT forests. Interaction of wet-dry extremes and SWT depth modulated tree responses to climate, providing buffers to droughts in Amazonia. As extreme wet periods are projected to increase and at least 36% of the Amazon comprises SWT forests, our results highlight the importance of considering these factors in order to improve our knowledge about forest resilience to climate change.

Embolism resistance drives the distribution of Amazonian rainforest tree species along hydro-topographic gradients.

Species distribution is strongly driven by local and global gradients in water availability but the underlying mechanisms are not clear. Vulnerability to xylem embolism (P50 ) is a key trait that indicates how species cope with drought and might explain plant distribution patterns across environmental gradients. Here we address its role on species sorting along a hydro-topographical gradient in a central Amazonian rainforest and examine its variance at the community scale. We measured P50 for 28 tree species, soil properties and estimated the hydrological niche of each species using an indicator of distance to the water table (HAND). We found a large hydraulic diversity, covering as much as 44% of the global angiosperm variation in P50 . We show that P50 : contributes to species segregation across a hydro-topographic gradient in the Amazon, and thus to species coexistence; is the result of repeated evolutionary adaptation within closely related taxa; is associated with species tolerance to P-poor soils, suggesting the evolution of a stress-tolerance syndrome to nutrients and drought; and is higher for trees in the valleys than uplands. The large observed hydraulic diversity and its association with topography has important implications for modelling and predicting forest and species resilience to climate change.

Can traits predict individual growth performance? A test in a hyperdiverse tropical forest.

The functional trait approach has, as a central tenet, that plant traits are functional and shape individual performance, but this has rarely been tested in the field. Here, we tested the individual-based trait approach in a hyperdiverse Amazonian tropical rainforest and evaluated intraspecific variation in trait values, plant strategies at the individual level, and whether traits are functional and predict individual performance. We evaluated > 1300 tree saplings belonging to > 383 species, measured 25 traits related to growth and defense, and evaluated the effects of environmental conditions, plant size, and traits on stem growth. A total of 44% of the trait variation was observed within species, indicating a strong potential for acclimation. Individuals showed two strategy spectra, related to tissue toughness and organ size vs leaf display. In this nutrient- and light-limited forest, traits measured at the individual level were surprisingly poor predictors of individual growth performance because of convergence of traits and growth rates. Functional trait approaches based on individuals or species are conceptually fundamentally different: the species-based approach focuses on the potential and the individual-based approach on the realized traits and growth rates. Counterintuitively, the individual approach leads to a poor prediction of individual performance, although it provides a more realistic view on community dynamics.

Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches.

The linking of individual functional traits to ecosystem processes is the basis for making generalizations in ecology, but the measurement of individual values is laborious and time consuming, preventing large-scale trait mapping. Also, in hyper-diverse systems, errors occur because identification is difficult, and species level values ignore intra-specific variation. To allow extensive trait mapping at the individual level, we evaluated the potential of Fourrier-Transformed Near Infra-Red Spectrometry (FT-NIR) to adequately describe 14 traits that are key for plant carbon, water, and nutrient balance. FT-NIR absorption spectra (1,000-2,500 nm) were obtained from dry leaves and branches of 1,324 trees of 432 species from a hyper-diverse Amazonian forest. FT-NIR spectra were related to measured traits for the same plants using partial least squares regressions. A further 80 plants were collected from a different site to evaluate model applicability across sites. Relative prediction error (RMSErel ) was calculated as the percentage of the trait value range represented by the final model RMSE. The key traits used in most functional trait studies; specific leaf area, leaf dry matter content, wood density and wood dry matter content can be well predicted by the model (R2  = 0.69-0.78, RMSErel  = 9-11%), while leaf density, xylem proportion, bark density and bark dry matter content can be moderately well predicted (R2  = 0.53-0.61, RMSErel  = 14-17%). Community-weighted means of all traits were well estimated with NIR, as did the shape of the frequency distribution of the community values for the above key traits. The model developed at the core site provided good estimations of the key traits of a different site. An evaluation of the sampling effort indicated that 400 or less individuals may be sufficient for establishing a good local model. We conclude that FT-NIR is an easy, fast and cheap method for the large-scale estimation of individual plant traits that was previously impossible. The ability to use dry intact leaves and branches unlocks the potential for using herbarium material to estimate functional traits; thus advancing our knowledge of community and ecosystem functioning from local to global scales.

The importance of hydraulic architecture to the distribution patterns of trees in a central Amazonian forest.

Species distributions and assemblage composition may be the result of trait selection through environmental filters. Here, we ask whether filtering of species at the local scale could be attributed to their hydraulic architectural traits, revealing the basis of hydrological microhabitat partitioning in a Central Amazonian forest. We analyzed the hydraulic characteristics at tissue (anatomical traits, wood specific gravity (WSG)), organ (leaf area, specific leaf area (SLA), leaf area : sapwood area ratio) and whole-plant (height) levels for 28 pairs of congeneric species from 14 genera restricted to either valleys or plateaus of a terra-firme forest in Central Amazonia. On plateaus, species had higher WSG, but lower mean vessel area, mean vessel hydraulic diameter, sapwood area and SLA than in valleys; traits commonly associated with hydraulic safety. Mean vessel hydraulic diameter and mean vessel area increased with height for both habitats, but leaf area and leaf area : sapwood area ratio investments with tree height declined in valley vs plateau species. [Correction added after online publication 29 March 2017: the preceding sentence has been reworded.] Two strategies for either efficiency or safety were detected, based on vessel size or allocation to sapwood. In conclusion, contrasting hydrological conditions act as environmental filters, generating differences in species composition at the local scale. This has important implications for the prediction of species distributions under future climate change scenarios.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites.

AIM: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. LOCATION: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. METHODS: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. RESULTS: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. MAIN CONCLUSIONS: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

One sixth of Amazonian tree diversity is dependent on river floodplains.

Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function.

The biogeography of the Amazonian tree flora.

We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central-eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia.

Pervasive gaps in Amazonian ecological research.

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%-18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost.

More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia.

Indigenous societies are known to have occupied the Amazon basin for more than 12,000 years, but the scale of their influence on Amazonian forests remains uncertain. We report the discovery, using LIDAR (light detection and ranging) information from across the basin, of 24 previously undetected pre-Columbian earthworks beneath the forest canopy. Modeled distribution and abundance of large-scale archaeological sites across Amazonia suggest that between 10,272 and 23,648 sites remain to be discovered and that most will be found in the southwest. We also identified 53 domesticated tree species significantly associated with earthwork occurrence probability, likely suggesting past management practices. Closed-canopy forests across Amazonia are likely to contain thousands of undiscovered archaeological sites around which pre-Columbian societies actively modified forests, a discovery that opens opportunities for better understanding the magnitude of ancient human influence on Amazonia and its current state.

Mapping density, diversity and species-richness of the Amazon tree flora.

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.

Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment.

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) - remotely estimated from LiDAR - control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function.

Amazon tree dominance across forest strata.

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 'hyperdominant' species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations.

Biased-corrected richness estimates for the Amazonian tree flora.

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come.

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors.