Resource availability and disturbance shape maximum tree height across the Amazon.

Tall trees are key drivers of ecosystem processes in tropical forest, but the controls on the distribution of the very tallest trees remain poorly understood. The recent discovery of grove of giant trees over 80 meters tall in the Amazon forest requires a reevaluation of current thinking. We used high-resolution airborne laser surveys to measure canopy height across 282,750 ha of old-growth and second-growth forests randomly sampling the entire Brazilian Amazon. We investigated how resources and disturbances shape the maximum height distribution across the Brazilian Amazon through the relations between the occurrence of giant trees and environmental factors. Common drivers of height development are fundamentally different from those influencing the occurrence of giant trees. We found that changes in wind and light availability drive giant tree distribution as much as precipitation and temperature, together shaping the forest structure of the Brazilian Amazon. The location of giant trees should be carefully considered by policymakers when identifying important hot spots for the conservation of biodiversity in the Amazon.

A biomass map of the Brazilian Amazon from multisource remote sensing.

The Amazon Forest, the largest contiguous tropical forest in the world, stores a significant fraction of the carbon on land. Changes in climate and land use affect total carbon stocks, making it critical to continuously update and revise the best estimates for the region, particularly considering changes in forest dynamics. Forest inventory data cover only a tiny fraction of the Amazon region, and the coverage is not sufficient to ensure reliable data interpolation and validation. This paper presents a new forest above-ground biomass map for the Brazilian Amazon and the associated uncertainty both with a resolution of 250 meters and baseline for the satellite dataset the year of 2016 (i.e., the year of the satellite observation). A significant increase in data availability from forest inventories and remote sensing has enabled progress towards high-resolution biomass estimates. This work uses the largest airborne LiDAR database ever collected in the Amazon, mapping 360,000 km2 through transects distributed in all vegetation categories in the region. The map uses airborne laser scanning (ALS) data calibrated by field forest inventories that are extrapolated to the region using a machine learning approach with inputs from Synthetic Aperture Radar (PALSAR), vegetation indices obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, and precipitation information from the Tropical Rainfall Measuring Mission (TRMM). A total of 174 field inventories geolocated using a Differential Global Positioning System (DGPS) were used to validate the biomass estimations. The experimental design allowed for a comprehensive representation of several vegetation types, producing an above-ground biomass map varying from a maximum value of 518 Mg ha-1, a mean of 174 Mg ha-1, and a standard deviation of 102 Mg ha-1. This unique dataset enabled a better representation of the regional distribution of the forest biomass and structure, providing further studies and critical information for decision-making concerning forest conservation, planning, carbon emissions estimate, and mechanisms for supporting carbon emissions reductions.

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.

Occurrence records and metadata for sand flies (Diptera, Psychodidae, Phlebotominae) collected in the lands of indigenous people in the Brazilian Amazon.

To contribute to knowledge of the epidemiology of American cutaneous leishmaniasis (ACL) among indigenous people living in sylvatic regions, we studied the sand fly fauna collected in areas of disease transmission in the Brazilian Amazon. Here we report two datasets comprising occurrence data for sand flies from the Suruwaha Indigenous Land in the state of Amazonas collected in 2012-2013, and the Wajãpi Indigenous Land in the state of Amapá collected in 2013-2014. Sand flies were collected using unbaited CDC-like light traps at various sites within each study area and were identified to either genus or species-level by taxonomists with expertise in Amazonian fauna. A total of 4,646 records are reported: 1,428 from the Suruwaha and 3,218 from the Wajãpi. These records will contribute to a better understanding of ACL transmission dynamics, as well as the distribution of insect vectors, in these areas.

Airborne laser scanning for terrain modeling in the Amazon forest / Escaneamento laser aerotransportado para modelagem de terreno em floresta amazônica

Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.

São poucos os estudos dedicados a entender a criação de modelo digital de terreno (MDT) para florestas amazônicas. O MDT tem uma importante função quando o escaneamento laser aerotransportado é usado para estimar a biomassa da vegetação. Examinamos a relação da densidade de pulsos, resolução espacial, algoritmos de filtragem, densidade da vegetação e inclinação do terreno com a qualidade do MDT. Três áreas de floresta amazônica foram sobrevoadas usando LiDAR aerotransportado. Cada nuvem de dados original teve sua densidade reduzida objetivando 20; 15; 10; 8; 6; 4; 2; 1; 0,75; 0,5 e 0,25 pulsos por metro quadrado, utilizando um processo de reamostragem aleatória. Os MDTs das nuvens reamostradas foram comparados com o MDT de referência, produzido a partir da nuvem original, calculando o desvio pixel a pixel e resumindo-o por meio do erro padrão da estimativa (RMSE). Os MDTs das nuvens reamostradas também foram avaliados quanto ao nível de correspondência com o MDT de referência. Houve uma clara compensação entre densidade de pontos e resolução horizontal. Dosséis mais densos exigem uma maior densidade de retornos, ou MDT com menor resolução.