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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.

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The lack of synthesized information regarding biodiversity is a major problem among researchers, leading to a pervasive cycle where ecologists make field campaigns to collect information that already exists and yet has not been made available for a broader audience. This problem leads to long-lasting effects in public policies such as spending money multiple times to conduct similar studies in the same area. We aim to identify this knowledge gap by synthesizing information available regarding two Brazilian long-term biodiversity programs and the metadata generated by them. Using a unique dataset containing 1904 metadata, we identified patterns of metadata distribution and intensity of research conducted in Brazil, as well as where we should concentrate research efforts in the next decades. We found that the majority of metadata were about vertebrates, followed by plants, invertebrates, and fungi. Caatinga was the biome with least metadata, and that there's still a lack of information regarding all biomes in Brazil, with none of them being sufficiently sampled. We hope that these results will have implications for broader conservation and management guiding, as well as to funding allocation programs.

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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.

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Long-term-ecological-research (LTER) faces many challenges, including the difficulty of obtaining long-term funding, changes in research questions and sampling designs, keeping researchers collecting standardized data for many years, impediments to interactions with local people, and the difficulty of integrating the needs of local decision makers with "big science". These issues result in a lack of universally accepted guidelines as to how research should be done and integrated among LTER sites. Here we discuss how the RAPELD (standardized field infrastructure system), can help deal with these issues as a complementary technique in LTER studies, allowing comparisons across landscapes and ecosystems and reducing sampling costs. RAPELD uses local surveys to understand broad spatial and temporal patterns while enhancing decision-making and training of researchers, local indigenous groups and traditional communities. Sampling of ecological data can be carried out by different researchers through standardized protocols, resulting in spatial data that can be used to answer temporal questions, and allow new questions to be investigated. Results can also be integrated into existing biodiversity networks. Integrated systems are the most efficient way to save resources, maximize results, and accumulate information that can be used in the face of the unknown unknowns upon which our future depends.

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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.

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Although inoculating soybean with rhizobia for biological nitrogen fixation is a common practice in agriculture, rhizobia are also known to associate with grasses. In this study, we evaluate the potential utility of the rhizobial strains SEMIA 587 and 5019 (Bradyrhizobium elkanii), 5079 (Bradyrhizobium japonicum), and 5080 (Bradyrhizobium diazoefficiens), recommended for Brazilian soybean inoculation, in colonizing black oat plants and promoting growth in black and white oats, and ryegrass. Inoculation of white oats with SEMIA 587 increase the seed germination (SG) by 32.09%, whereas the SG of black oats inoculated with SEMIA 587 and 5019 increased by 40.38% and 37.85%, respectively. Similarly, inoculation of ryegrass with all strains increased SG values between 24.63 and 27.59%. In addition, white oats with SEMIA 587 and 5080 had root areas significantly superior to those in other treatments, whereas inoculation with SEMIA 5079 and 5080 resulted in the highest volume of roots. Likewise, SEMIA 5079 and 5080 significantly increased the length, volume, and area of black oats roots, whereas SEMIA 587 increased the volume, area, and dry mass of roots and shoot. Inoculation in ryegrass with SEMIA 587 significantly increased the root volume. Moreover, most strains transformed with gfp and gus were observed to colonize the roots of black oats. Collectively, the findings of this study indicate that rhizobial strains recommended for inoculation of soybean can also be used to promote the growth of the three assessed grass species, and are able to colonize the roots of black oats.

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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.

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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.

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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.

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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.

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Elasmobranchs, the group of cartilaginous fishes that include sharks and rays, are especially vulnerable to overfishing due to low fecundity and late sexual maturation. A significant number of elasmobranch species are currently overexploited or threatened by fisheries activities. Additionally, several recent reports have indicated that there has been a reduction in regional elasmobranch population sizes. Brazil is an important player in elasmobranch fisheries and one of the largest importers of shark meat. However, carcasses entering the shark meat market have usually had their fins and head removed, which poses a challenge to reliable species identification based on the morphology of captured individuals. This is further complicated by the fact that the internal Brazilian market trades several different elasmobranch species under a common popular name: "cação." The use of such imprecise nomenclature, even among governmental agencies, is problematic for both controlling the negative effects of shark consumption and informing the consumer about the origins of the product. In this study, we used DNA barcoding (mtDNA, COI gene) to identify, at the species level, "cação" samples available in local markets from Southern Brazil. We collected 63 samples traded as "cação," which we found to correspond to 20 different species. These included two teleost species: Xiphias gladius (n = 1) and Genidens barbus (n = 6), and 18 species from seven elasmobranch orders (Carcharhiniformes, n = 42; Squaliformes, n = 3; Squatiniformes, n = 2; Rhinopristiformes, n = 4; Myliobatiformes, n = 3; Rajiformes, n = 1; and Torpediniformes, n = 1). The most common species in our sample were Prionace glauca (n = 15) and Sphyrna lewini (n = 14), while all other species were represented by four samples or less. Considering IUCN criteria, 47% of the elasmobranch species found are threatened at the global level, while 53% are threatened and 47% are critically endangered in Brazil. These results underline that labeling the meat of any shark species as "cação" is problematic for monitoring catch allocations from the fishing industry and discourages consumer engagement in conservationist practices through informed decision-making.

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Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

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The vast extent of the Amazon Basin has historically restricted the study of its tree communities to the local and regional scales. Here, we provide empirical data on the commonness, rarity, and richness of lowland tree species across the entire Amazon Basin and Guiana Shield (Amazonia), collected in 1170 tree plots in all major forest types. Extrapolations suggest that Amazonia harbors roughly 16,000 tree species, of which just 227 (1.4%) account for half of all trees. Most of these are habitat specialists and only dominant in one or two regions of the basin. We discuss some implications of the finding that a small group of species--less diverse than the North American tree flora--accounts for half of the world's most diverse tree community.

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Este estudo descreve uma modificação do método de parcelas de 0.1 ha desenvolvido por Gentry, que nós adaptamos para sítios de pesquisa ecológica de longa-duração na Amazônia brasileira. Nosso objetivo foi desenvolver um método que fosse apropriado para pesquisas ecológicas de longa-duração (componente PELD), mas que permitissem inventários rápidos para avaliação da complementaridade biótica e planejamento do uso da terra na Amazônia (componente RAP). A filosofia por trás do método é a de maximizar a probabilidade de amostrar adequadamente as comunidades biológicas, para o que são necessárias áreas amostrais grandes, e ao mesmo tempo minimizar a variação nos fatores abióticos que afetam estas comunidades, o que requer amostragem de áreas pequenas. Para conseguir isto, as parcelas são longas e estreitas, com seu maior eixo orientado ao longo das curvas de nível do terreno. Este desenho minimiza a variação interna de topografia e solo em cada parcela, e permite o uso destas variáveis como preditoras das distribuições de espécies. O desenho pode ser usado para vários taxa e estágios de vida, ajustando a largura da parcela ou distribuindo sub-amostras ao longo da parcela. As parcelas são distribuídas sistematicamente em uma grade de trilhas, que é usada para amostrar taxa que não podem ser amostrados em parcelas pequenas. Cada grade de trilhas e parcelas constitui um sítio de pesquisa. A distribuição sistemática de parcelas na paisagem permite estimativas não tendenciosas da distribuição, abundância e biomassa das espécies em cada sítio, e comparações biogeográficas entre sítios. Os custos de implementação são moderados, considerando a grande produção gerada pelos estudos integrados.