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
Extreme droughts associated with changes in the climate have occurred every 5 years in the Amazon during the 21st century, with the most severe being in 2015. The increase in biomass burning (BB) events that occurred during the 2015 drought had several negative socioeconomic and environmental impacts, one of which was a decrease in the air quality. This study is an investigation into the air quality in the Manaus Metropolitan Region (MMR) (central Amazon, Brazil) during the dry (September to October) and wet (April to May) seasons of 2015 and 2016. A strong El Niño event began during the wet season of 2015 and ended during the wet season of 2016. Particulate matter samples were collected in the MMR during 2015 and 2016, and analyses of the satellite-estimated total carbon monoxide (CO) column and observed levoglucosan concentrations were carried out. Levoglucosan has been shown to be significantly correlated with regional fires and is a well-established chemical tracer for the atmospheric particulates emitted by BB, and CO can be treated as a gaseous-phase tracer for BB. The number of BB events increased significantly during the El Niño period when compared to the average number during 2003-2016. Consequently, the total CO column and levoglucosan concentration values in the MMR increased by 15% and 500%, respectively, when compared to the normal conditions. These results indicate that during the period that was analyzed, the impacts of BB were exacerbated during the strong El Niño event as compared to the non-El Niño period. In this study, we provided evidence that the air quality in the MMR will degrade in the future if droughts and BB occurrences continue to increase.