Universidade Federal Rural da Amazônia

Introduction Recent decades have seen a major international effort to inventory tree communities in the Amazon Basin and Guiana Shield (Amazonia), but the vast extent and record diversity of these forests have hampered an understanding of basinwide patterns. To overcome this obstacle, we compiled and standardized species-level data on more than half a million trees in 1170 plots sampling all major lowland forest types to explore patterns of commonness, rarity, and richness. Methods The ~6-million-km 2 Amazonian lowlands were divided into 1° cells, and mean tree density was estimated for each cell by using a loess regression model that included no environmental data but had its basis exclusively in the geographic location of tree plots. A similar model, allied with a bootstrapping exercise to quantify sampling error, was used to generate estimated Amazon-wide abundances of the 4962 valid species in the data set. We estimated the total number of tree species in the Amazon by fitting the mean rank-abundance data to Fisher’s log-series distribution. Results Our analyses suggest that lowland Amazonia harbors 3.9 × 10 11 trees and ~16,000 tree species. We found 227 “hyperdominant” species (1.4% of the total) to be so common that together they account for half of all trees in Amazonia, whereas the rarest 11,000 species account for just 0.12% of trees. Most hyperdominants are habitat specialists that have large geographic ranges but are only dominant in one or two regions of the basin, and a median of 41% of trees in individual plots belong to hyperdominants. A disproportionate number of hyperdominants are palms, Myristicaceae, and Lecythidaceae. Discussion The finding that Amazonia is dominated by just 227 tree species implies that most biogeochemical cycling in the world’s largest tropical forest is performed by a tiny sliver of its diversity. The causes underlying hyperdominance in these species remain unknown. Both competitive superiority and widespread pre-1492 cultivation by humans are compelling hypotheses that deserve testing. Although the data suggest that spatial models can effectively forecast tree community composition and structure of unstudied sites in Amazonia, incorporating environmental data may yield substantial improvements. An appreciation of how thoroughly common species dominate the basin has the potential to simplify research in Amazonian biogeochemistry, ecology, and vegetation mapping. Such advances are urgently needed in light of the >10,000 rare, poorly known, and potentially threatened tree species in the Amazon.

The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies. Over the past decades, rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats. Yet, in spite of the progress of molecular methods, knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging. In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels. Combining the information from previous efforts such as FUNGuild and FunFun together with involvement of expert knowledge, we reannotated 10,210 and 151 fungal and Stramenopila genera, respectively. This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera, designed for rapid functional assignments of environmental studies. In order to assign the trait states to fungal species hypotheses, the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences. On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1% dissimilarity threshold.

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Abstract Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate‐induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long‐term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO 2 concentrations): maximum tree size, biogeographic water‐deficit affiliation and wood density. Tree communities have become increasingly dominated by large‐statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry‐affiliated genera have become more abundant, while the mortality of wet‐affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry‐affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate‐change drivers, but yet to significantly impact whole‐community composition. The Amazon observational record suggests that the increase in atmospheric CO 2 is driving a shift within tree communities to large‐statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate.

Estimates of extinction risk for Amazonian plant and animal species are rare and not often incorporated into land-use policy and conservation planning. We overlay spatial distribution models with historical and projected deforestation to show that at least 36% and up to 57% of all Amazonian tree species are likely to qualify as globally threatened under International Union for Conservation of Nature (IUCN) Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We show that the trends observed in Amazonia apply to trees throughout the tropics, and we predict that most of the world's >40,000 tropical tree species now qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if these areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century.

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazônia Sustentável, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.

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.

A large fraction of the organic carbon derived from land that is transported through inland waters is decomposed along river systems and emitted to the atmosphere as carbon dioxide (CO2). The Amazon River outgasses nearly as much CO2 as the rainforest sequesters on an annual basis, representing ~25% of global CO2 emissions from inland waters. However, current estimates of CO2 outgassing from the Amazon basin are based on a conservative upscaling of measurements made in the central Amazon, meaning both basin and global scale budgets are likely underestimated. The lower Amazon River, from Óbidos to the river mouth, represents ~13% of the total drainage basin area, and is not included in current basin-scale estimates. Here, we assessed the concentration and evasion rate of CO2 along the lower Amazon River corridor and its major tributaries, the Tapajós and Xingu Rivers. Evasive CO2 fluxes were directly measured using floating chambers and gas transfer coefficients (k600) were calculated for different hydrological seasons. Temporal variations in pCO2 and CO2 emissions were similar to previous observations throughout the Amazon (e.g. peak concentrations at high water) and CO2 outgassing was lower in the clearwater tributaries compared to the mainstem. However, k600 values were higher than previously reported upstream likely due to the generally windier conditions, turbulence caused by tidal forces, and an amplification of these factors in the wider channels with a longer fetch. We estimate that the lower Amazon River mainstem emits 0.2 Pg C yr-1 within our study boundaries, or as much as 0.48 Pg C yr-1 if the entire spatial extent to the geographical mouth is considered. Including these values with updated basin scale estimates and estimates of CO2 outgassing from small streams we estimate that the Amazon running waters outgasses as much as 1.39 Pg C yr-1, increasing the global emissions from inland waters by 43% for a total of 2.9 Pg C yr-1. These results highlight a large missing gap in basin-scale carbon budgets along the complete continuum of the Amazon River, and likely most other large river systems, that could drastically alter global scale carbon budgets.

Several hundred species are hunted for wild meat in the tropics, supporting the diets, customs, and livelihoods of millions of people. However, unsustainable hunting is one of the most urgent threats to wildlife and ecosystems worldwide and has serious ramifications for people whose subsistence and income are tied to wild meat. Over the past 18 years, although research efforts have increased, scientific knowledge has largely not translated into action. One major barrier to progress has been insufficient monitoring and evaluation, meaning that the effectiveness of interventions cannot be ascertained. Emerging issues include the difficulty of designing regulatory frameworks that disentangle the different purposes of hunting, the large scale of urban consumption, and the implications of wild meat consumption for human health. To address these intractable challenges, wepropose eight new recommendations for research and action for sustainable wild meat use, which would support the achievement of the United Nations Sustainable Development Goals.

In the last two decades, the strong increase of pasturelands over former rainforest areas has raised concerns about the climate change that such change in land cover might cause. In recent years, though, expansion of soybean croplands has been increasingly important in the agricultural growth in Amazonia. In this paper we use the climate model CCM3 to investigate whether the climate change due to soybean expansion in Amazonia would be any different from the one due to pastureland expansion. The land component of the model has been updated with new findings from the Large‐Scale Biosphere Experiment in Amazonia (LBA), and a new soybean micrometeorological experiment in Amazonia. Results show that the decrease in precipitation after a soybean extension is significantly higher when compared to the change after a pastureland extension, a consequence of the very high albedo of the soybean.

In tropical agroecosystems, limited N availability remains a major impediment to increasing yield. A 15 N‐recovery experiment was conducted in 13 diverse tropical agroecosystems. The objectives were to determine the total recovery of one single 15 N application of inorganic or organic N during three to six growing seasons and to establish whether the losses of N are governed by universal principles. Between 7 and 58% (average of 21%) of crop N uptake during the first growing season was derived from fertilizer. On average, 79% of crop N was derived from the soil. When 15 N‐labeled residues were applied, in the first growing season 4% of crop N was derived from the residues. Average recoveries of 15 N‐labeled fertilizer and residue in crops after the first growing season were 33 and 7%, respectively. Corresponding recoveries in the soil were 38 and 71%. An additional 6% of the fertilizer and 9.1% of the residue was recovered by crops during subsequent growing seasons. There were no significant differences in total 15 N recovery (average 54%) between N from fertilizer and N from residue. After five growing seasons, more residue N (40%) than fertilizer N (18%) was recovered in the soil, better sustaining the soil organic matter N content. Long‐term total recoveries of 15 N‐labeled fertilizer or residue in the crop and soil were similar. Soil N remained the primary source of N for crops. As higher rainfall and temperature tend to cause higher 15 N losses, management practices to improve N use efficiency and reduce losses in wet tropical regions will remain a challenge.

The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted-modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster-growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits. These results provide not only a holistic pan-Amazonian picture of tree death but large-scale evidence for the overarching importance of the growth-survival trade-off in driving tropical tree mortality.

Chitosan is a biopolymer with high added value, and its properties are related to its molecular weight. Thus, high molecular weight values provide low solubility of chitosan, presenting limitations in its use. Based on this, several studies have developed different hydrolysis methods to reduce the molecular weight of chitosan. Acid hydrolysis is still the most used method to obtain low molecular weight chitosan and chitooligosaccharides. However, the use of acids can generate environmental impacts. When different methods are combined, gamma radiation and microwave power intensity are the variables that most influence acid hydrolysis. Otherwise, in oxidative hydrolysis with hydrogen peroxide, a long time is the limiting factor. Thus, it was observed that the most efficient method is the association between the different hydrolysis methods mentioned. However, this alternative can increase the cost of the process. Enzymatic hydrolysis is the most studied method due to its environmental advantages and high specificity. However, hydrolysis time and process cost are factors that still limit industrial application. In addition, the enzymatic method has a limited association with other hydrolysis methods due to the sensitivity of the enzymes. Therefore, this article seeks to extensively review the variables that influence the main methods of hydrolysis: acid concentration, radiation intensity, potency, time, temperature, pH, and enzyme/substrate ratio, observing their influence on molecular weight, yield, and characteristic of the product.

Resumo No final da década de 1960, pesquisadores do Museu Paraense Emílio Goeldi (MPEG) iniciaram as coletas botânicas na Serra dos Carajás, resultando em um expressivo acervo e interessantes descobertas sobre a flora local, marcada por endemismos e pressão por atividades mineradoras. Em 2014, foi estabelecido o projeto "Flora das cangas da Serra dos Carajás" através da cooperação entre o MPEG e o Instituto Tecnológico Vale de Desenvolvimento Sustentável (ITVDS), visando especialmente a elaboração da flora das cangas da FLONA Carajás. Um acervo de cerca de quinze mil exsicatas, depositadas principalmente nos herbários MG e BHCB além de HCJS, INPA, IAN, NY e RB constitui a base para o desenvolvimento da flora. Até o momento, a flora inclui 151 famílias de angiospermas, gimnospermas, licófitas e samambaias e briófitas (musgos e hepáticas). Neste trabalho apresentamos um breve histórico dos estudos botânicos na região, caracterização da área de estudo, e procedimentos metodológicos adotados no desenvolvimento do projeto. Também, constitui a introdução para o volume 1 da Flora das cangas de Carajás composto por 55 famílias, sendo quatro de briófitas, duas de licófitas, oito de samambaias, uma de gimnospermas e 40 de angiospermas, incluindo 139 gêneros e 248 espécies.

Medicinal and aromatic plants present important active compounds that have potential for use in food, pharmaceutical, and agriculture industries. In this sense, the present work aimed to conduct a literature review on the potential applications of essential oils from Lamiaceae species. Antioxidant, anti-inflammatory, and antimicrobial activities were evaluated. The importance of this study is demonstrated as a way to theoretically provide information on the use of different plants belonging to the Lamiaceae family, especially with regard to the physical, chemical, and biological properties of its essential oils.

Dairy farmers across Brazil were invited to participate in a study on silage production and utilization practices. Two hundred sixty farmers filled out a questionnaire, which was made available on a website. The questionnaire consisted of 14 questions, including information about the characteristics of the herd (n=3), the crop(s) used in the ensiling process, the use of additives, the harvest (n=3), the type of silo (n=1), aspects related to sealing (n=2), and management practices applied during feed-out (n=3). Farmers were also asked a final question about the main barriers they faced when producing and using silage. The main dairy-producing regions of Brazil had a strong influence on the number of participants. The profiles of farmers were heterogeneous and divided into 5 groups, which was considered a positive attribute of the study, allowing better analysis and assessment of current circumstances. Corn was the most widely grown crop for silage. Sorghum, tropical grasses, and sugarcane were the other species most cited. Additives were used by a small number of farmers (27.7%). Approximately 40% of farmers still depended on loaned equipment or outsourced services. The pull-type forage harvester was the main piece of equipment used on dairy farms (90.4%). Only 54.6% of respondents answered that they sharpen their harvester knives daily. Horizontal silos (bunker and stack) were the structures most commonly used to store silage. Most farmers sealed silos with double-sided plastic film (black-on-white) and with soil. However, almost one-fifth of all farmers still use black plastic. Manual removal of silage from the silos was practiced at most farms (i.e., the lack of equipment was also reflected in the stage of silage utilization). Disposal of spoiled silage before inclusion in the livestock feed was not a common practice on the farms. The main barriers encountered on the farms were lack of equipment, lack of manpower, and climatic variations. The results of this research may guide researchers, industries, extension workers, and governments to seek efficiency in milk production on farms using silage in the diet of livestock throughout the year or during part of the year in Brazil.

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.

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.

The Brazilian Cerrado is one of the most biodiverse savannas in the world, yet 46% of its original cover has been cleared to make way for crops and pastures. These extensive land-use transitions (LUTs) are expected to influence regional climate by reducing evapotranspiration (ET), increasing land surface temperature (LST), and ultimately reducing precipitation. Here, we quantify the impacts of LUTs on ET and LST in the Cerrado by combining MODIS satellite data with annual land use and land cover maps from 2006 to 2019. We performed regression analyses to quantify the effects of six common LUTs on ET and LST across the entire gradient of Cerrado landscapes. Results indicate that clearing forests for cropland or pasture increased average LST by ~3.5°C and reduced mean annual ET by 44% and 39%, respectively. Transitions from woody savannas to cropland or pasture increased average LST by 1.9°C and reduced mean annual ET by 27% and 21%, respectively. Converting native grasslands to cropland or pasture increased average LST by 0.9 and 0.6°C, respectively. Conversely, grassland-to-pasture transitions increased mean annual ET by 15%. To date, land changes have caused a 10% reduction in water recycled to the atmosphere annually and a 0.9°C increase in average LST across the biome, compared to the historic baseline under native vegetation. Global climate changes from increased atmospheric greenhouse gas concentrations will only exacerbate these effects. Considering potential future scenarios, we found that abandoning deforestation control policies or allowing legal deforestation to continue (at least 28.4 Mha) would further reduce yearly ET (by -9% and -3%, respectively) and increase average LST (by +0.7 and +0.3°C, respectively) by 2050. In contrast, policies encouraging zero deforestation and restoration of the 5.2 Mha of illegally deforested areas would partially offset the warming and drying impacts of land-use change.