Challenges to estimating carbon emissions from tropical deforestation (original) (raw)
Related papers
Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010
PLOS ONE, 2015
Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates-critical inputs for setting reference emission levels for REDD+-are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr −1 and 0.18 ± 0.07 Pg C•yr −1 respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha −1 ,~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha −1). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha −1 •yr −1 from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts.
Forest ecology and management, 1996
Carbon stocks in vegetation replacing forest in Brazilian Amazonia affect net emissions of greenhouse gases from land-use change. A Markov matrix of annual transition probabilities was constructed to estimate landscape composition in 1990 and to project future changes, assuming behavior of farmers and ranchers remains unchanged. The estimated 1990 landscape was 5.4% farmland, 44.8% productive pasture, 2.2% degraded pasture, 2.1 % •young' (1970 or later) secondary forest derived from agriculture, 28.1 % •young' secondary forest derived from pasture, and 17.4% 'old' (pre-1970) secondary forest. The landscape would eventually approach an equilibrium of 4.0% farmland, 43.8% productive pasture, 5.2% degraded pasture, 2.0% secondary forest derived from agriculture, and 44.9% secondary forest derived from pasture. An insignificant amount is regenerated 'forest' (defined as secondary forest over 100 years old). Average total biomass (dry matter, including below-ground and dead components) was 43.5 t ha-1 in 1990 in the 410 X 10 3 km 2 deforested by that year for uses other than hydroelectric dams. At equilibrium, average biomass would be 28.5 t ha -I over all deforested areas (excluding dams). These biomass values are more than double those forming the basis of deforestation emission estimates currently used by the Intergovernmental Panel on Climate Change (IPCC). Although higher replacement landscape biomass decreases net emissions from deforestation, these estimates still imply large net releases.
Estimating the multi-decadal carbon deficit of burned Amazonian forests
Environmental Research Letters, 2020
Wildfires in humid tropical forests have become more common in recent years, increasing the rates of tree mortality in forests that have not co-evolved with fire. Estimating carbon emissions from these wildfires is complex. Current approaches rely on estimates of committed emissions based on static emission factors through time and space, yet these emissions cannot be assigned to specific years, and thus are not comparable with other temporally-explicit emission sources. Moreover, committed emissions are gross estimates, whereas the long-term consequences of wildfires require an understanding of net emissions that accounts for post-fire uptake of CO2. Here, using a 30 year wildfire chronosequence from across the Brazilian Amazon, we calculate net CO2 emissions from Amazon wildfires by developing statistical models comparing post-fire changes in stem mortality, necromass decomposition and vegetation growth with unburned forest plots sampled at the same time. Over the 30 yr time perio...
Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates
Climatic Change, 2014
As land use change (LUC), including deforestation, is a patchy process, estimating the impact of LUC on carbon emissions requires spatially accurate underlying data on biomass distribution and change. The methods currently adopted to estimate the spatial variation of above-and below-ground biomass in tropical forests, in particular the Brazilian Amazon, are usually based on remote sensing analyses coupled with field datasets, which tend to be relatively scarce and often limited in their spatial distribution. There are notable differences among the resulting biomass maps found in the literature. These differences subsequently result in relatively high uncertainties in the carbon emissions calculated from land use change, and have a larger impact when biomass maps are coded into biomass classes referring to specific ranges of biomass values. In this paper we analyze the differences among recentlypublished biomass maps of the Amazon region, including the official information used by the Brazilian government for its communication to the United Nation Framework on Climate Change Convention of the United Nations. The estimated average pre-deforestation biomass in Climatic Change the four maps, for the areas of the Amazon region that had been deforested during the 1990-2009 period, varied from 205±32 Mg ha −1 during 1990-1999, to 216±31 Mg ha −1 during 2000-2009. The biomass values of the deforested areas in 2011 were between 7 and 24 % higher than for the average deforested areas during 1990-1999, suggesting that although there was variation in the mean value, deforestation was tending to occur in increasingly carbondense areas, with consequences for carbon emissions. To summarize, our key findings were: (i) the current maps of Amazonian biomass show substantial variation in both total biomass and its spatial distribution; (ii) carbon emissions estimates from deforestation are highly dependent on the spatial distribution of biomass as determined by any single biomass map, and on the deforestation process itself; (iii) future deforestation in the Brazilian Amazon is likely to affect forests with higher biomass than those deforested in the past, resulting in smaller reductions in carbon dioxide emissions than expected purely from the recent reductions in deforestation rates; and (iv) the current official estimate of carbon emissions from Amazonian deforestation is probably overestimated, because the recent loss of higher-biomass forests has not been taken into account.
Science Advances, 2020
Deforestation is the primary driver of carbon losses in tropical forests, but it does not operate alone. Forest fragmentation, a resulting feature of the deforestation process, promotes indirect carbon losses induced by edge effect. This process is not implicitly considered by policies for reducing carbon emissions in the tropics. Here, we used a remote sensing approach to estimate carbon losses driven by edge effect in Amazonia over the 2001 to 2015 period. We found that carbon losses associated with edge effect (947 Tg C) corresponded to one-third of losses from deforestation (2592 Tg C). Despite a notable negative trend of 7 Tg C year−1 in carbon losses from deforestation, the carbon losses from edge effect remained unchanged, with an average of 63 ± 8 Tg C year−1. Carbon losses caused by edge effect is thus an additional unquantified flux that can counteract carbon emissions avoided by reducing deforestation, compromising the Paris Agreement’s bold targets.
Land use change emission scenarios: anticipating a forest transition process in the Brazilian Amazon
Global Change Biology, 2016
Following an intense occupation process that was initiated in the 1960s, deforestation rates in the Brazilian Amazon have decreased significantly since 2004, stabilizing around 6000 km 2 yr À1 in the last 5 years. A convergence of conditions contributed to this, including the creation of protected areas, the use of effective monitoring systems, and credit restriction mechanisms. Nevertheless, other threats remain, including the rapidly expanding global markets for agricultural commodities, large-scale transportation and energy infrastructure projects, and weak institutions. We propose three updated qualitative and quantitative land-use scenarios for the Brazilian Amazon, including a normative 'Sustain-ability' scenario in which we envision major socioeconomic , institutional, and environmental achievements in the region. We developed an innovative spatially explicit modelling approach capable of representing alternative pathways of the clear-cut deforestation, secondary vegetation dynamics, and the old-growth forest degradation. We use the computational models to estimate net deforestation-driven carbon emissions for the different scenarios. The region would become a sink of carbon after 2020 in a scenario of residual deforestation (~1000 km 2 yr À1) and a change in the current dynamics of the secondary vegetation – in a forest transition scenario. However, our results also show that the continuation of the current situation of relatively low deforestation rates and short life cycle of the secondary vegetation would maintain the region as a source of CO 2 – even if a large portion of the deforested area is covered by secondary vegetation. In relation to the old-growth forest degradation process, we estimated average gross emission corresponding to 47% of the clear-cut deforestation from 2007 to 2013 (using the DEGRAD system data), although the aggregate effects of the post-disturbance regeneration can partially offset these emissions. Both processes (secondary vegetation and forest degradation) need to be better understood as they potentially will play a decisive role in the future regional carbon balance.
Background Different methods estimating the global anthropogenic land flux, which is dominated by forest-related activities, vary in magnitude and direction with respect to whether the land is a net source or sink. One reason for these variations is the extent to which methods consider land to be “managed”, thus contributing to the anthropogenic flux. Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent approach to flux estimations that can be compared against National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely monitoring, reporting and verification capacity. Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare EO-based estimates of forest fluxes to NGHGIs. Results Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (-0.2 GtCO2yr− 1), while Brazil’s NGHGI...