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The carbon balance of tropical ecosystems remains uncertain, with top-down atmospheric studies suggesting an overall sink and bottom-up ecological approaches indicating a modest net source. Here we use 12 years (2003 to 2014) of MODIS pantropical satellite data to quantify net annual changes in the aboveground carbon density of tropical woody live vegetation, providing direct, measurement-based evidence that the world’s tropical forests are a net carbon source of 425.2 ± 92.0 teragrams of carbon per year (Tg C year−1). This net release of carbon consists of losses of 861.7 ± 80.2 Tg C year−1 and gains of 436.5 ± 31.0 Tg C year−1. Gains result from forest growth; losses result from deforestation and from reductions in carbon density within standing forests (degradation or disturbance), with the latter accounting for 68.9% of overall losses.

Deforestation contributes 6–17% of anthropogenic carbon dioxide emissions. However, much uncertainty in the calculation of deforestation emissions stems from the inadequacy of forest carbon-density and deforestation data. Now an analysis provides the most-detailed estimate so far of the carbon density of vegetation and the associated carbon dioxide emissions from deforestation for ecosystems across the tropics. Deforestation contributes 6–17% of global anthropogenic CO 2 emissions to the atmosphere 1 . Large uncertainties in emission estimates arise from inadequate data on the carbon density of forests 2 and the regional rates of deforestation. Consequently there is an urgent need for improved data sets that characterize the global distribution of aboveground biomass, especially in the tropics. Here we use multi-sensor satellite data to estimate aboveground live woody vegetation carbon density for pan-tropical ecosystems with unprecedented accuracy and spatial resolution. Results indicate that the total amount of carbon held in tropical woody vegetation is 228.7 Pg C, which is 21% higher than the amount reported in the Global Forest Resources Assessment 2010 (ref.  3 ). At the national level, Brazil and Indonesia contain 35% of the total carbon stored in tropical forests and produce the largest emissions from forest loss. Combining estimates of aboveground carbon stocks with regional deforestation rates 4 we estimate the total net emission of carbon from tropical deforestation and land use to be 1.0 Pg C yr −1 over the period 2000–2010—based on the carbon bookkeeping model. These new data sets of aboveground carbon stocks will enable tropical nations to meet their emissions reporting requirements (that is, United Nations Framework Convention on Climate Change Tier 3) with greater accuracy.

Reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) is a crucial component of global climate change mitigation. Remote sensing can provide continuous and spatially explicit above-ground biomass (AGB) estimates, which can be valuable for the quantification of carbon stocks and emission factors (EFs). Unfortunately, there is little information on the fate of the land following tropical deforestation and of the associated carbon stock. This study quantified post-deforestation land use across the tropics for the period 1990-2000. This dataset was then combined with a pan-tropical AGB map at 30 m resolution to refine EFs from forest conversion by matching deforestation areas with their carbon stock before and after clearing and to assess spatial dynamics of EFs by follow-up land use. In Latin America, pasture was the most common follow-up land use (72%), with large-scale cropland (11%) a distant second. In Africa deforestation was often followed by small-scale cropping (61%) with a smaller role for pasture (15%). In Asia, small-scale cropland was the dominant agricultural follow-up land use (35%), closely followed by tree crops (28%). Deforestation often occurred in forests with lower than average carbon stocks. EFs showed high spatial variation within eco-zones and countries. While our EFs are only representative for the studied time period, our results show that EFs are mainly determined by the initial forest carbon stock. The estimates of the fraction of carbon lost were less dependent on initial forest biomass, which offers opportunities for REDD+ countries to use these fractions in combination with recent good quality national forest biomass maps or inventory data to quantify emissions from specific forest conversions. Our study highlights that the co-location of data on forest loss, biomass and fate of the land provides more insight into the spatial dynamics of land-use change and can help in attributing carbon emissions to human activities.

Tropical forests provide global climate regulation ecosystem services and their clearing is a significant source of anthropogenic greenhouse gas (GHG) emissions and resultant radiative forcing of climate change. However, consensus on pan-tropical forest carbon dynamics is lacking. We present a new estimate that employs recommended good practices to quantify gross tropical forest aboveground carbon (AGC) loss from 2000 to 2012 through the integration of Landsat-derived tree canopy cover, height, intactness and forest cover loss and GLAS-lidar derived forest biomass. An unbiased estimate of forest loss area is produced using a stratified random sample with strata derived from a wall-to-wall 30 m forest cover loss map. Our sample-based results separate the gross loss of forest AGC into losses from natural forests (0.59 PgC yr−1) and losses from managed forests (0.43 PgC yr−1) including plantations, agroforestry systems and subsistence agriculture. Latin America accounts for 43% of gross AGC loss and 54% of natural forest AGC loss, with Brazil experiencing the highest AGC loss for both categories at national scales. We estimate gross tropical forest AGC loss and natural forest loss to account for 11% and 6% of global year 2012 CO2 emissions, respectively. Given recent trends, natural forests will likely constitute an increasingly smaller proportion of tropical forest GHG emissions and of global emissions as fossil fuel consumption increases, with implications for the valuation of co-benefits in tropical forest conservation.

Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000–2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5Mgha−1 for a range of biomass between 0 and 454Mgha−1. Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R2 = 0.90) between the GLAS height metrics and predicted AGB.

The Hansen et al . critique centers on the lack of spatial agreement between two very different datasets. Nonetheless, properly constructed comparisons designed to reconcile the two datasets yield up to 90% agreement (e.g., in South America).

Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d'Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000-2010): a map-scale estimate (53.3 ± 9.8 Tg C yr−1) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr−1) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC.

The collapse of socialism in 1989 triggered a phase of institutional restructuring in Central and Eastern Europe. Several countries chose to privatize forests or to return them to pre-socialist owners. Here, we assess the implications of forest restitution on the terrestrial carbon balance. New forest owners have strong incentives to immediately clearcut their forests, resulting in increased terrestrial emissions. On the other hand, logging generally decreased after 1989 and forests are expanding on unused or abandoned farmland, both of which may offset increased logging on restituted forests. We mapped changes in forest cover for the entire country of Romania using Landsat satellite images from 1990 to 2010. We use our satellite estimates, together with historic data on logging rates and changes in forest cover, to parameterize a carbon book-keeping model for estimating the terrestrial carbon flux (above and below ground) as a consequence of land use change and forest harvest. High logging rates during socialism resulted in substantial terrestrial carbon emissions and Romania was a net carbon source until the 1980s. After the collapse of the Soviet Union forest harvest rates decreased dramatically, but since restitution laws were implemented they have increased by 60% (from 15 122 ± 5397hay − 1 in 2000 to 23 884 ± 11 510hay − 1 in 2010), but still remain lower than prior to 1989. Romania currently remains a terrestrial carbon sink, offsetting 7.6% ± 2.5% of anthropogenic carbon emissions. A further increase in logging could result in net emissions from terrestrial ecosystems during the coming decades. However, forest expansion on degraded land and abandoned farmland offers great potential for carbon sequestration.

Fire disturbance at high latitudes modifies a broad range of ecosystem properties and processes, thus it is important to monitor the response of vegetation to fire disturbance. This monitoring effort can be aided by lidar remote sensing, which captures information on vegetation structure, particularly canopy height metrics. We used lidar data acquired from the Geoscience Laser Altimetry System (GLAS) on ICESAT to derive canopy information for a wide range of burned areas across Alaska. The GLAS data aided our analysis of postfire disturbance and vegetation recovery by allowing us to derive returned energy height metrics within burned area perimeters. The analysis was augmented with MODIS reflectance data sets, which were used to stratify vegetation cover into cover type and density. We also made use of Landsat burn severity maps to further stratify the lidar metrics. Results indicate that canopy height decreases following fire, as expected, but height was not a good overall indicator of fire disturbance because many locations within the burned area perimeters either did not actually burn or experienced different levels of burn severity, typically leaving many standing trees or snags even after intensive burning. Because vegetation recovery following fire is differentially affected by burn severity, significantly greater height growth was documented in more severely burned areas due to a greater proportion of deciduous vegetation regrowth. When these factors were considered, GLAS height metrics were useful for documenting properties of regrowth in burned areas, thereby facilitating monitoring and mapping efforts following fire disturbance. A new satellite lidar sensor designed for vegetation studies would thus prove valuable information for improving ecosystem models that incorporate disturbance and recovery.