ABSTRACT
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.
Subject(s)
Acclimatization , Wind , Brazil , Rainforest , BiodiversityABSTRACT
The Amazon rainforest is a heterogeneous ecosystem and its soils exhibit geographically variable concentrations of trace elements. In this region, anthropic activities - e.g., agriculture and mining - are numerous and varied, and even natural areas are at risk of contamination by trace elements, either of geogenic or anthropogenic origin. A reliable dataset of benchmark values for selenium (Se), barium (Ba), and iodine (I) concentrations in soils is needed for use as a reference in research and public policies in the region. In this study, 9 selected sites in the Brazilian Amazon rainforest within areas represented by Oxisols and Ultisols were assessed for relevant soil physicochemical characteristics, along with the concentrations of total Se (SeTot), total Ba (BaTot), and sequentially-extracted soluble Se (SeSol) and adsorbed Se (SeAd) in 3 different soil layers (0-20, 20-40, and 40-60 cm). In addition, organically bound-Se (SeOrg) and total I (ITot) concentrations in the surface layer (0-20 cm) were measured. Soil Se concentrations (SeTot) were considered safe and are likely a result of contributions of sedimentary deposits from the Andes. Available Se (SeSol + SeAd) accounted for 4.5% of SeTot, on average, while SeOrg in the topsoil accounted for more than 50% of SeTot. Barium in the western Amazon (state of Acre) and central Amazon (Anori, state of Amazonas) exceeded national prevention levels (PVs). Furthermore, the average ITot in the studied topsoils (5.4 mg kg-1) surpassed the worldwide mean. Notwithstanding, the close relationship found between the total content of the elements (Se, Ba, and I) and soil texture (clay, silt, and sand) suggests their geogenic source. Finally, our data regarding SeTot, BaTot, and ITot can be used to derive regional quality reference values for Amazon soils and also for updating prevention (PV) and investigation (IV) values established for selected elements by the Brazilian legislation.
Subject(s)
Iodine , Selenium , Soil Pollutants , Trace Elements , Barium , Brazil , Ecosystem , Environmental Monitoring , Iodides , Rainforest , Selenium/analysis , Soil/chemistry , Soil Pollutants/analysisABSTRACT
AIM: Amazon-nut (Bertholletia excelsa) is a hyperdominant and protected tree species, playing a keystone role in nutrient cycling and ecosystem service provision in Amazonia. Our main goal was to develop a robust habitat suitability model of Amazon-nut and to identify the most important predictor variables to support conservation and tree planting decisions. LOCALIZATION: Amazon region, South America. METHODS: We collected 3,325 unique Amazon-nut records and assembled >100 spatial predictor variables organized across climatic, edaphic, and geophysical categories. We compared suitability models using variables (a) selected through statistical techniques; (b) recommended by experts; and (c) integrating both approaches (a and b). We applied different spatial filtering scenarios to reduce overfitting. We additionally fine-tuned MAXENT settings to our data. The best model was selected through quantitative and qualitative assessments. RESULTS: Principal component analysis based on expert recommendations was the most appropriate method for predictor selection. Elevation, coarse soil fragments, clay, slope, and annual potential evapotranspiration were the most important predictors. Their relative contribution to the best model amounted to 75%. Filtering of the presences within a radius of 10 km displayed lowest overfitting, a satisfactory omission rate and the most symmetric distribution curve. Our findings suggest that under current environmental conditions, suitable habitat for Amazon-nut is found across 2.3 million km2, that is, 32% of the Amazon Biome. MAIN CONCLUSION: The combination of statistical techniques with expert knowledge improved the quality of our suitability model. Topographic and soil variables were the most important predictors. The combination of predictor variable selection, fine-tuning of model parameters and spatial filtering was critical for the construction of a reliable habitat suitability model.
ABSTRACT
Arsenic (As) in native soils of the Amazon rainforest is a concern due to its likely origin from the Andean rivers, which transport loads of sediments containing substantial amounts of trace elements coming from the cordilleras. Yet, unveiling soil As baseline concentrations in the Amazon basin is still a need because most studies in Brazil have been performed in areas with predominantly high concentrations and cannot express a real baseline value for the region. In this study, 414 soil samples (0-20, 20-40 and 40-60â¯cm layers) were collected from different sites throughout the Amazon basin - including native Amazon rainforest and minimally disturbed areas - and used to determine total and extractable (soluble + available) As concentrations along with relevant soil physicochemical properties. Descriptive statistics of the data was performed and Pearson correlation supported by a Principal Component Analysis (PCA) provided an improved understanding of where and how As concentrations are influenced by soil attributes. Total As concentration ranged from 0.98 to 41.71â¯mgâ¯kg-1 with values usually increasing from the topsoil (0-20â¯cm) to the deepest layer (40-60â¯cm) in all sites studied. Considering the proportional contribution given by each fraction (soluble and available) on extractable As concentration, it is noticeable that KH2PO4-extractable As represents the most important fraction, with >70% of the As extracted on average in all the sites studied. Still, the extractable fractions (soluble + available) correspond to ~0.24% of the total As, on average. Total, available, and soluble As fractions were strongly and positively correlated with soil Al3+. The PCA indicated that soil pH in combination with CEC might be the key factors controlling soil As concentrations and the occurrence of each arsenic fraction in the soil layers.
ABSTRACT
Várzea forests of the Amazon estuary contain species of importance to riverine communities. For example, the oil extracted from the seeds of crabwood trees is traditionally used to combat various illnesses and as such artisanal extraction processes have been maintained. The objectives of this study were to (1) describe the process involved in artisanal extraction of crabwood oil in the Fazendinha Protected Area, in the state of Amapá; (2) characterise the processes of knowledge transfer associated with the extraction and use of crabwood oil within a peri-urban riverine community; and (3) discern medicinal uses of the oil. The data were obtained using semistructured interviews with 13 community members involved in crabwood oil extraction and via direct observation. The process of oil extraction is divided into four stages: seed collection; cooking and resting of the seeds; shelling of the seeds and dough preparation; and oil collection. Oil extraction is carried out within the home for personal use, with surplus marketed within the community. More than 90% of the members of the community involved in extraction of crabwood oil highlighted the use of the oil to combat inflammation of the throat. Knowledge transfer occurs via oral transmission and through direct observation.
ABSTRACT
The Brazil-nut tree (Bertholletia excelsa) is native to the Amazon rainforest, and its fruit production varies naturally with climatic conditions. Our aim was to evaluate the temporal variation in Brazil-nut production associated with climatic variables, including the strong El Niño of 2015/2016. The study was carried out in two 9-ha permanent plots in the northeastern Brazilian Amazon from 2007 to 2018: one in forest (12-year monitoring) and the other in savannah/forest transition (eight years). Overall, we monitored fruit production of 205 trees with diameter at breast height ≥ 50 cm. Annual fruit production was related to temporal series (2005-2018) of climatic data (the Oceanic Niño Index; and precipitation and air temperature from two local meteorological stations). Average fruit production per tree in 2017 was eight times lower than in 2015 and two times lower than the general average for both sites, and was significantly associated to the El Niño of 2015/2016, that increased average maximum monthly temperature and reduced the precipitation in the region, extending the dry season from three to six months. Years with higher and lower fruit production per tree coincided in both sites. Annual fruit production was significantly and negatively correlated with thermal anomalies that occurred in the third semester prior to harvest monitoring. Years with higher production were related with predominance of neutrality or the La Niña phenomenon at the global scale, and higher rainfall at the local scale. The relationship of fruit production with climate was independent of the local habitat.
A castanheira-da-amazônia (Bertholletia excelsa) é nativa da floresta amazônica e sua produção de frutos varia naturalmente com as condições climáticas. Nosso objetivo foi avaliar a variação temporal na produção de frutos da castanheira associada a variáveis climáticas, incluindo o forte El Nino de 2015/2016. O estudo foi realizado em parcelas permanentes de 9 ha de 2007 a 2018, uma localizada em floresta (12 anos de monitoramento) e a outra em transição floresta/savana (oito anos). Em total, monitoramos 205 castanheiras com diâmetro à altura do peito ≥ 50 cm. A produção anual de frutos foi relacionada a séries temporais (2005-2018) de dados climáticos (o Índice Oceânico Niño; e a precipitação e temperatura do ar de duas estações meteorológicas locais). A produção média por castanheira em 2017 foi oito vezes menor que em 2015 e duas vezes menor que a média geral nos dois sítios, e foi significativamente associada ao El Niño de 2015/2016, que causou aumento na temperatura máxima mensal e redução na precipitação regional, prolongando a estação seca de três para seis meses. Os anos com maior e menor produção média por castanheira foram os mesmos nos dois ambientes. A produção anual de frutos foi significativa e negativamente correlacionada com as anomalias térmicas ocorridas no terceiro semestre antes da colheita. Anos de maior produção foram relacionados com predominância de neutralidade ou do fenômeno La Niña em escala global, e aumento da precipitação em nível local. A relação entre produção de frutos e clima foi independente do ambiente local.
Subject(s)
Bertholletia , Fruit/growth & development , Climate ChangeABSTRACT
O objetivo geral do trabalho desenvolvido foi avaliar como o lodo de esgoto (biossólido) altera os estoques de C e N em plantação de eucalipto. O estudo foi conduzido com aplicação de doses até 40 t ha-1 de biossólido, em base seca, para cultivo de Eucalyptus grandis. Os eucaliptos que receberam 10 t ha-1 de biossólido apresentaram igual desenvolvimento aos que receberam adubação mineral completa, produzindo, em média, 107,5 t ha-1 de biomassa acima do solo, 63 por cento a mais do que a testemunha. Esses tratamentos apresentaram também maiores valores de conteúdo de C e N na biomassa. O biossólido tratado com cal, aplicado em superfície, apresentou baixas taxas de decomposição e não contribuiu para aumentar os estoques totais de C e N no solo. O efeito do resíduo sobre o desenvolvimento das árvores é mais importante para fornecer entradas de material orgânico no sistema do que sua própria aplicação.
The general aim of this research was to evaluate as the sewage sludge (biosolids) modify C and N stocks in eucalypt plantation. The study was installed with application rates up to 40 t h-1 of dry matter biosolids in Eucalyptus grandis plantation. The eucalypts that received 10 t h-1 of biosolids presented even development that it received full mineral fertilizer, producing, on average, 107,5 t ha-1 of aboveground biomass, 63 percent the more than control. Those treatments also presented larger values of C and N contents in the biomass. The biosolids treated with lime, applied in surface, showed low decomposition rates and it didnt contribute to increase C and N soil total stocks. The effect of residue on the development of trees is more important to supply input of organic material in system than own application.