Secondary forests offset less than 10% of deforestation-mediated carbon emissions in the Brazilian Amazon.

Secondary forests are increasing in the Brazilian Amazon and have been cited as an important mechanism for reducing net carbon emissions. However, our understanding of the contribution of secondary forests to the Amazonian carbon balance is incomplete, and it is unclear to what extent emissions from old-growth deforestation have been offset by secondary forest growth. Using MapBiomas 3.1 and recently refined IPCC carbon sequestration estimates, we mapped the age and extent of secondary forests in the Brazilian Amazon and estimated their role in offsetting old-growth deforestation emissions since 1985. We also assessed whether secondary forests in the Brazilian Amazon are growing in conditions favourable for carbon accumulation in relation to a suite of climatic, landscape and local factors. In 2017, the 129,361 km2 of secondary forest in the Brazilian Amazon stored 0.33 ± 0.05 billion Mg of above-ground carbon but had offset just 9.37% of old-growth emissions since 1985. However, we find that the majority of Brazilian secondary forests are situated in contexts that are less favourable for carbon accumulation than the biome average. Our results demonstrate that old-growth forest loss remains the most important factor determining the carbon balance in the Brazilian Amazon. Understanding the implications of these findings will be essential for improving estimates of secondary forest carbon sequestration potential. More accurate quantification of secondary forest carbon stocks will support the production of appropriate management proposals that can efficiently harness the potential of secondary forests as a low-cost, nature-based tool for mitigating climate change.

Quantifying immediate carbon emissions from El Niño-mediated wildfires in humid tropical forests.

Wildfires produce substantial CO2 emissions in the humid tropics during El Niño-mediated extreme droughts, and these emissions are expected to increase in coming decades. Immediate carbon emissions from uncontrolled wildfires in human-modified tropical forests can be considerable owing to high necromass fuel loads. Yet, data on necromass combustion during wildfires are severely lacking. Here, we evaluated necromass carbon stocks before and after the 2015-2016 El Niño in Amazonian forests distributed along a gradient of prior human disturbance. We then used Landsat-derived burn scars to extrapolate regional immediate wildfire CO2 emissions during the 2015-2016 El Niño. Before the El Niño, necromass stocks varied significantly with respect to prior disturbance and were largest in undisturbed primary forests (30.2 ± 2.1 Mg ha-1, mean ± s.e.) and smallest in secondary forests (15.6 ± 3.0 Mg ha-1). However, neither prior disturbance nor our proxy of fire intensity (median char height) explained necromass losses due to wildfires. In our 6.5 million hectare (6.5 Mha) study region, almost 1 Mha of primary (disturbed and undisturbed) and 20 000 ha of secondary forest burned during the 2015-2016 El Niño. Covering less than 0.2% of Brazilian Amazonia, these wildfires resulted in expected immediate CO2 emissions of approximately 30 Tg, three to four times greater than comparable estimates from global fire emissions databases. Uncontrolled understorey wildfires in humid tropical forests during extreme droughts are a large and poorly quantified source of CO2 emissions.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Drivers of metacommunity structure diverge for common and rare Amazonian tree species.

We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.

Size and frequency of natural forest disturbances and the Amazon forest carbon balance.

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y(-1) over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y(-1), and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y(-1). Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests.

Ecological studies in tropical forests have long been plagued by difficulties associated with sampling the crowns of large canopy trees and large inaccessible regions, such as the Amazon basin. Recent advances in remote sensing have overcome some of these obstacles, enabling progress towards tackling difficult ecological problems. Breakthroughs have helped transform the dialog between ecology and remote sensing, generating new regional perspectives on key environmental gradients and species assemblages with ecologically relevant measures such as canopy nutrient and moisture content, crown area, leaf-level drought responses, woody tissue and surface litter abundance, phenological patterns, and land-cover transitions. Issues that we address here include forest response to altered precipitation regimes, regional disturbance and land-use patterns, invasive species and landscape carbon balance.