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The Amazon forest carbon sink is declining, mainly as a result of land-use and climate change1-4. Here we investigate how changes in law enforcement of environmental protection policies may have affected the Amazonian carbon balance between 2010 and 2018 compared with 2019 and 2020, based on atmospheric CO2 vertical profiles5,6, deforestation7 and fire data8, as well as infraction notices related to illegal deforestation9. We estimate that Amazonia carbon emissions increased from a mean of 0.24 ± 0.08 PgC year-1 in 2010-2018 to 0.44 ± 0.10 PgC year-1 in 2019 and 0.52 ± 0.10 PgC year-1 in 2020 (± uncertainty). The observed increases in deforestation were 82% and 77% (94% accuracy) and burned area were 14% and 42% in 2019 and 2020 compared with the 2010-2018 mean, respectively. We find that the numbers of notifications of infractions against flora decreased by 30% and 54% and fines paid by 74% and 89% in 2019 and 2020, respectively. Carbon losses during 2019-2020 were comparable with those of the record warm El Niño (2015-2016) without an extreme drought event. Statistical tests show that the observed differences between the 2010-2018 mean and 2019-2020 are unlikely to have arisen by chance. The changes in the carbon budget of Amazonia during 2019-2020 were mainly because of western Amazonia becoming a carbon source. Our results indicate that a decline in law enforcement led to increases in deforestation, biomass burning and forest degradation, which increased carbon emissions and enhanced drying and warming of the Amazon forests.
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Dióxido de Carbono , Secuestro de Carbono , Conservación de los Recursos Naturales , Política Ambiental , Aplicación de la Ley , Bosque Lluvioso , Biomasa , Brasil , Dióxido de Carbono/análisis , Dióxido de Carbono/metabolismo , Política Ambiental/legislación & jurisprudencia , Atmósfera/química , Incendios Forestales/estadística & datos numéricos , Conservación de los Recursos Naturales/estadística & datos numéricos , El Niño Oscilación del Sur , Sequías/estadística & datos numéricosRESUMEN
Amazonia hosts the Earth's largest tropical forests and has been shown to be an important carbon sink over recent decades1-3. This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change1-3. Here we investigate Amazonia's carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 20184. We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends5-9. We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia1,10.
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Ciclo del Carbono , Secuestro de Carbono , Cambio Climático/estadística & datos numéricos , Conservación de los Recursos Naturales/estadística & datos numéricos , Bosques , Atmósfera/química , Dióxido de Carbono/análisis , Monóxido de Carbono/análisis , Actividades Humanas , Fotosíntesis , Lluvia , Estaciones del Año , TemperaturaRESUMEN
The joint and relative effects of future land-use and climate change on fire occurrence in the Amazon, as well its seasonal variation, are still poorly understood, despite its recognized importance. Using the maximum entropy method (MaxEnt), we combined regional land-use projections and climatic data from the CMIP5 multimodel ensemble to investigate the monthly probability of fire occurrence in the mid (2041-2070) and late (2071-2100) 21st century in the Brazilian Amazon. We found striking spatial variation in the fire relative probability (FRP) change along the months, with October showing the highest overall change. Considering climate only, the area with FRP ≥ 0.3 (a threshold chosen based on the literature) in October increases 6.9% by 2071-2100 compared to the baseline period under the representative concentration pathway (RCP) 4.5 and 27.7% under the RCP 8.5. The best-case land-use scenario ("Sustainability") alone causes a 10.6% increase in the area with FRP ≥ 0.3, while the worse-case land-use scenario ("Fragmentation") causes a 73.2% increase. The optimistic climate-land-use projection (Sustainability and RCP 4.5) causes a 21.3% increase in the area with FRP ≥ 0.3 in October by 2071-2100 compared to the baseline period. In contrast, the most pessimistic climate-land-use projection (Fragmentation and RCP 8.5) causes a widespread increase in FRP (113.5% increase in the area with FRP ≥ 0.3), and prolongs the fire season, displacing its peak. Combining the Sustainability land-use and RCP 8.5 scenarios causes a 39.1% increase in the area with FRP ≥ 0.3. We conclude that avoiding the regress on land-use governance in the Brazilian Amazon (i.e., decrease in the extension and level of conservation of the protected areas, reduced environmental laws enforcement, extensive road paving, and increased deforestation) would substantially mitigate the effects of climate change on fire probability, even under the most pessimistic RCP 8.5 scenario.
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Cambio Climático , Conservación de los Recursos Naturales , Brasil , Probabilidad , Estaciones del AñoRESUMEN
Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.
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Bosques , Árboles/fisiología , Brasil , Intervalos de Confianza , Conservación de los Recursos Naturales , Ecosistema , Monitoreo del Ambiente , Geografía , Análisis de RegresiónRESUMEN
The strong El Niño Southern Oscillation (ENSO) event that occurred in 2015-2016 caused extreme drought in the northern Brazilian Amazon, especially in the state of Roraima, increasing fire occurrence. Here we map the extent of precipitation and fire anomalies and quantify the effects of climatic and anthropogenic drivers on fire occurrence during the 2015-2016 dry season (from December 2015 to March 2016) in the state of Roraima. To achieve these objectives we first estimated the spatial pattern of precipitation anomalies, based on long-term data from the TRMM (Tropical Rainfall Measuring Mission), and the fire anomaly, based on MODIS (Moderate Resolution Imaging Spectroradiometer) active fire detections during the referred period. Then, we integrated climatic and anthropogenic drivers in a Maximum Entropy (MaxEnt) model to quantify fire probability, assessing (1) the model accuracy during the 2015-2016 and the 2016-2017 dry seasons; (2) the relative importance of each predictor variable on the model predictive performance; and (3) the response curves, showing how each environmental variable affects the fire probability. Approximately 59% (132,900 km2 ) of the study area was exposed to precipitation anomalies ≤-1 standard deviation (SD) in January and ~48% (~106,800 km2 ) in March. About 38% (86,200 km2 ) of the study area experienced fire anomalies ≥1 SD in at least one month between December 2015 and March 2016. The distance to roads and the direct ENSO effect on fire occurrence were the two most influential variables on model predictive performance. Despite the improvement of governmental actions of fire prevention and firefighting in Roraima since the last intense ENSO event (1997-1998), we show that fire still gets out of control in the state during extreme drought events. Our results indicate that if no prevention actions are undertaken, future road network expansion and a climate-induced increase in water stress will amplify fire occurrence in the northern Amazon, even in its humid dense forests. As an additional outcome of our analysis, we conclude that the model and the data we used may help to guide on-the-ground fire-prevention actions and firefighting planning and therefore minimize fire-related ecosystems degradation, economic losses and carbon emissions in Roraima.
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Cambio Climático , El Niño Oscilación del Sur , Bosques , Incendios Forestales , Brasil , Sequías , Estaciones del Año , Factores de TiempoRESUMEN
Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the ratio between disturbed and deforested areas. Although the majority of the areas, which have been affected by selective logging during the period 2000-2014, were not deforested by 2015, more than 70% of the deforested areas in 2015 had been at least once identified as disturbed forest during that period.
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In less than 15 years, the Amazon region experienced three major droughts. Links between droughts and fires have been demonstrated for the 1997/1998, 2005, and 2010 droughts. In 2010, emissions of 510 ± 120 Tg C were associated to fire alone in Amazonia. Existing approaches have, however, not yet disentangled the proportional contribution of multiple land cover sources to this total. We develop a novel integration of multisensor and multitemporal satellite-derived data on land cover, active fires, and burned area and an empirical model of fire-induced biomass loss to quantify the extent of burned areas and resulting biomass loss for multiple land covers in Mato Grosso (MT) state, southern Amazonia-the 2010 drought most impacted region. We show that 10.77% (96,855 km2) of MT burned. We estimated a gross carbon emission of 56.21 ± 22.5 Tg C from direct combustion of biomass, with an additional 29.4 ± 10 Tg C committed to be emitted in the following years due to dead wood decay. It is estimated that old-growth forest fires in the whole Brazilian Legal Amazon (BLA) have contributed to 14.81 Tg of C (11.75 Tg C to 17.87 Tg C) emissions to the atmosphere during the 2010 fire season, with an affected area of 27,555 km2. Total C loss from the 2010 fires in MT state and old-growth forest fires in the BLA represent, respectively, 77% (47% to 107%) and 86% (68.2% to 103%) of Brazil's National Plan on Climate Change annual target for Amazonia C emission reductions from deforestation.
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*Remote sensing data are a key tool to assess large forested areas, where limitations such as accessibility and lack of field measurements are prevalent. Here, we have analysed datasets from moderate resolution imaging spectroradiometer (MODIS) satellite measurements and field data to assess the impacts of the 2005 drought in Amazonia. *We combined vegetation indices (VI) and climatological variables to evaluate the spatiotemporal patterns associated with the 2005 drought, and explore the relationships between remotely-sensed indices and forest inventory data on tree mortality. *There were differences in results based on c4 and c5 MODIS products. C5 VI showed no spatial relationship with rainfall or aerosol optical depth; however, distinct regions responded significantly to the increased radiation in 2005. The increase in the Enhanced VI (EVI) during 2005 showed a significant positive relationship (P < 0.07) with the increase of tree mortality. By contrast, the normalized difference water index (NDWI) exhibited a significant negative relationship (P < 0.09) with tree mortality. *Previous studies have suggested that the increase in EVI during the 2005 drought was associated with a positive response of forest photosynthesis to changes in the radiation income. We discuss the evidence that this increase could be related to structural changes in the canopy.
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Sequías , Hojas de la Planta/fisiología , Comunicaciones por Satélite , Árboles/fisiología , Brasil , Lluvia , Estaciones del Año , Luz Solar , Factores de Tiempo , AguaRESUMEN
Tropical carbon emissions are largely derived from direct forest clearing processes. Yet, emissions from drought-induced forest fires are, usually, not included in national-level carbon emission inventories. Here we examine Brazilian Amazon drought impacts on fire incidence and associated forest fire carbon emissions over the period 2003-2015. We show that despite a 76% decline in deforestation rates over the past 13 years, fire incidence increased by 36% during the 2015 drought compared to the preceding 12 years. The 2015 drought had the largest ever ratio of active fire counts to deforestation, with active fires occurring over an area of 799,293 km2. Gross emissions from forest fires (989 ± 504 Tg CO2 year-1) alone are more than half as great as those from old-growth forest deforestation during drought years. We conclude that carbon emission inventories intended for accounting and developing policies need to take account of substantial forest fire emissions not associated to the deforestation process.
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Intensive mechanized agriculture in the Brazilian Amazon grew by >3.6 million hectares (ha) during 2001-2004. Whether this cropland expansion resulted from intensified use of land previously cleared for cattle ranching or new deforestation has not been quantified and has major implications for future deforestation dynamics, carbon fluxes, forest fragmentation, and other ecosystem services. We combine deforestation maps, field surveys, and satellite-based information on vegetation phenology to characterize the fate of large (>25-ha) clearings as cropland, cattle pasture, or regrowing forest in the years after initial clearing in Mato Grosso, the Brazilian state with the highest deforestation rate and soybean production since 2001. Statewide, direct conversion of forest to cropland totaled >540,000 ha during 2001-2004, peaking at 23% of 2003 annual deforestation. Cropland deforestation averaged twice the size of clearings for pasture (mean sizes, 333 and 143 ha, respectively), and conversion occurred rapidly; >90% of clearings for cropland were planted in the first year after deforestation. Area deforested for cropland and mean annual soybean price in the year of forest clearing were directly correlated (R(2) = 0.72), suggesting that deforestation rates could return to higher levels seen in 2003-2004 with a rebound of crop prices in international markets. Pasture remains the dominant land use after forest clearing in Mato Grosso, but the growing importance of larger and faster conversion of forest to cropland defines a new paradigm of forest loss in Amazonia and refutes the claim that agricultural intensification does not lead to new deforestation.