• Energy Research

Abstract Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.

Extreme weather events and the presence of mega-hydroelectric dams, when combined, present an emerging threat to natural habitats in the Amazon region. To understand the magnitude of these impacts, we used remote sensing data to assess forest loss in areas affected by the extreme 2014 flood in the entire Madeira River basin, the location of two mega-dams. In addition, forest plots (26 ha) were monitored between 2011 and 2015 (14,328 trees) in order to evaluate changes in tree mortality, aboveground biomass (AGB), species composition and community structure around the Jirau reservoir (distance between plots varies from 1 to 80 km). We showed that the mega-dams were the main driver of tree mortality in Madeira basin forests after the 2014 extreme flood. Forest loss in the areas surrounding the reservoirs was 56 km2in Santo Antônio, 190 km2in Jirau (7.4–9.2% of the forest cover before flooding), and 79.9% above that predicted in environmental impact assessments. We also show that climatic anomalies, albeit with much smaller impact than that created by the mega-dams, resulted in forest loss along different Madeira sub-basins not affected by dams (34–173 km2; 0.5–1.7%). The impact of flooding was greater invárzeaand transitional forests, resulting in high rates of tree mortality (88–100%), AGB decrease (89–100%), and reduction of species richness (78–100%). Conversely,campinaranaforests were more flood-tolerant with a slight decrease in species richness (6%) and similar AGB after flooding. Taking together satellite and field measurements, we estimate that the 2014 flood event in the Madeira basin resulted in 8.81–12.47 ∙ 106tons of dead biomass. Environmental impact studies required for environmental licensing of mega-dams by governmental agencies should consider the increasing trend of climatic anomalies and the high vulnerability of different habitats to minimize the serious impacts of dams on Amazonian biodiversity and carbon stocks.