Amazon deforestation causes strong regional warming.

Tropical deforestation impacts the climate through complex land-atmosphere interactions causing local and regional warming. However, whilst the impacts of deforestation on local temperature are well understood, the regional (nonlocal) response is poorly quantified. Here, we used remote-sensed observations of forest loss and dry season land-surface temperature during the period 2001 to 2020 to demonstrate that deforestation of the Amazon caused strong warming at distances up to 100 km away from the forest loss. We apply a machine learning approach to show nonlocal warming due to forest loss at 2-100 km length scales increases the warming due to deforestation by more than a factor 4, from 0.16 K to 0.71 K for each 10-percentage points of forest loss. We estimate that rapid future deforestation under a strong inequality scenario could cause dry season warming of 0.96 K across Mato Grosso state in southern Brazil over the period 2020 to 2050. Reducing deforestation could reduce future warming caused by forest loss to 0.4 K. Our results demonstrate the contribution of tropical deforestation to regional climate warming and the potential for reduced deforestation to deliver regional climate adaptation and resilience with important implications for sustainable management of the Amazon.

Increased Amazon carbon emissions mainly from decline in law enforcement.

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.

The drivers and impacts of Amazon forest degradation.

Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

Projections of future forest degradation and CO2 emissions for the Brazilian Amazon.

In recent years, the area affected by forest degradation in the Brazilian Amazon has frequently been higher than deforestation. From August 2006 to July 2019, the degraded area totaled 194,058 km2, representing almost two times the 99,630 km2 deforested in the same period. The impacts of degradation include biodiversity loss and changes in the carbon stocks, affecting the CO2 balance and future climate changes. This paper aims to explore socioeconomic and environmental factors that influence forest degradation, project future scenarios, and assess the impact on the regional carbon balance, combining forest degradation and deforestation-related processes (clear-cut deforestation and secondary vegetation dynamics). We show that, while net CO2 emissions from 2020 to 2050 are 0.74 Gt CO2 in the Sustainable scenario, this value reached 22.63 Gt CO2 in the Fragmentation scenario, an increasingly plausible scenario given the recent trends in the region.

New land-use change scenarios for Brazil: Refining global SSPs with a regional spatially-explicit allocation model.

The future of land use and cover change in Brazil, particularly due to deforestation and forest restoration processes, is critical for the future of global climate and biodiversity, given the richness of its five biomes. These changes in Brazil depend on the interlink between global factors due to its role as one of the main exporters of commodities globally and the national to local institutional, socioeconomic, and biophysical contexts. Aiming to develop scenarios that consider the balance between global (e.g., GDP growth, population growth, per capita consumption of agricultural products, international trade policies, and climatic conditions) and local factors (e.g., land use, agrarian structure, agricultural suitability, protected areas, distance to roads, and other infrastructure projects), a new set of land-use change scenarios for Brazil were developed that aligned with the global structure Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathway (RCPs) developed by the global change research community. The narratives of the new scenarios align with SSP1/RCP 1.9 (Sustainable development scenario), SSP2/RCP 4.5 (Middle of the road scenario), and SSP3/RCP 7.0 (Strong inequality scenario). The scenarios were developed by combining the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model to incorporate the climatic variables in water deficit. Based on detailed biophysical, socioeconomic, and institutional factors for each biome in Brazil, we have created spatially explicit scenarios until 2050, considering the following classes: forest vegetation, grassland vegetation, planted pasture, agriculture, a mosaic of small land uses, and forestry. The results aim to detail global models regionally. They could be used regionally to support decision-making and enrich the global analysis.

Amazonia as a carbon source linked to deforestation and climate change.

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.

Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison.

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn ), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

Widespread reduction in sun-induced fluorescence from the Amazon during the 2015/2016 El Niño.

The tropical carbon balance dominates year-to-year variations in the CO2 exchange with the atmosphere through photosynthesis, respiration and fires. Because of its high correlation with gross primary productivity (GPP), observations of sun-induced fluorescence (SIF) are of great interest. We developed a new remotely sensed SIF product with improved signal-to-noise in the tropics, and use it here to quantify the impact of the 2015/2016 El Niño Amazon drought. We find that SIF was strongly suppressed over areas with anomalously high temperatures and decreased levels of water in the soil. SIF went below its climatological range starting from the end of the 2015 dry season (October) and returned to normal levels by February 2016 when atmospheric conditions returned to normal, but well before the end of anomalously low precipitation that persisted through June 2016. Impacts were not uniform across the Amazon basin, with the eastern part experiencing much larger (10-15%) SIF reductions than the western part of the basin (2-5%). We estimate the integrated loss of GPP relative to eight previous years to be 0.34-0.48 PgC in the three-month period October-November-December 2015.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'.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

Variability of carbon and water fluxes following climate extremes over a tropical forest in southwestern Amazonia.

The carbon and water cycles for a southwestern Amazonian forest site were investigated using the longest time series of fluxes of CO2 and water vapor ever reported for this site. The period from 2004 to 2010 included two severe droughts (2005 and 2010) and a flooding year (2009). The effects of such climate extremes were detected in annual sums of fluxes as well as in other components of the carbon and water cycles, such as gross primary production and water use efficiency. Gap-filling and flux-partitioning were applied in order to fill gaps due to missing data, and errors analysis made it possible to infer the uncertainty on the carbon balance. Overall, the site was found to have a net carbon uptake of ≈5 t C ha(-1) year(-1), but the effects of the drought of 2005 were still noticed in 2006, when the climate disturbance caused the site to become a net source of carbon to the atmosphere. Different regions of the Amazon forest might respond differently to climate extremes due to differences in dry season length, annual precipitation, species compositions, albedo and soil type. Longer time series of fluxes measured over several locations are required to better characterize the effects of climate anomalies on the carbon and water balances for the whole Amazon region. Such valuable datasets can also be used to calibrate biogeochemical models and infer on future scenarios of the Amazon forest carbon balance under the influence of climate change.

Estimativa do Índice de Área Foliar (IAF) e Biomassa em pastagem no estado de Rondônia, Brasil / Estimate of the Leaf Area Index (LAI) and Biomass in pasture in the state of Rondônia - Brazil

Medidas mensais da altura da pastagem, biomassa total, variações de biomassa viva e morta, a área específica foliar (SLA) e o Índice de Área de Folha (IAF) de fevereiro de 1999 a janeiro de 2005 na Fazenda Nossa Senhora (FNS) e em Rolim de Moura (RDM) entre Fevereiro a Março de 1999, Rondônia, Brasil. A pastagem predominante é Urochloa brizantha (Hochst. ex A. Rich) R. D. Webster (99 por cento na FNS e 76 por cento em RDM), com pequenas manchas de Urochloa humidicula (Rendle). A altura média anual da grama foi de ~0,16 m. Com o pastejo, o mínimo mensal foi de 0,09 m (estação seca) e máximo de 0,3 m sem pastejo (estação úmida). O IAF, biomassa total, material morto, vivo e SLA tiveram valores médios de 2,5 m² m-2 , 2202 kg ha-1, 2916 kg ha-1 e 19 m² kg-1 respectivamente. A média mensal da biomassa foi 4224 kg ha-1 em 2002 e 6667 kg ha-1 em 2003. Grande variação sazonal do material vivo e morto, sendo mais alto o vivo durante a estação úmida (3229 contra 2529 kg ha-1), sendo o morto maior durante a seca (2542 contra 1894 kg ha-1). O nível de água no solo variou de -3,1 a -6,5 m durante as estações. Em médias anuais os IAF foram de 1,4 em 2000 a 2,8 em 2003 e o SLA entre 16,3 m² kg-1 em 1999 e 20,4 m² kg-1 em 2001. As observações do Albedo variaram de 0,18 para 0,16 em relação aos altos valores de IAF.

Monthly measurements of the grass height, total above-ground biomass and the proportions of live and dead biomass, Specific Leaf Area (SLA) and Leaf Area Index (LAI) were made in one cattle ranch at the Fazenda Nossa Senhora (FNS) (February of 1999 to January of 2005) and also in Rolim de Moura (RDM) (February to March of 1999) in Rondônia state. The predominant grass species is Urochloa brizantha (Hochst. ex A. Rich) R. D. Webster (covering 99 percent of the area in FNS and 76 percent in RDM), with minor patches of Urochloa humidicula. This pasture was regularly grazed. The average grass height was 0.16 m but monthly value varied between 0.09 m after intensive grazing in the dry season to 0.32 m in a wet season without grazing. The LAI, total biomass, dead plant material, live above-ground plant material and SLA average 2,5 m² m-2, 2202 kg ha-1, 2916 kg ha-1 and 19 m² kg-1 respectively. The monthly average above-ground biomass showed little seasonal variation, but annual averages ranged from 4224 kg ha-1 in 2002 to 6667 kg ha-1 in 2003. Live biomass was significantly higher during the wet season than during the dry season (3229 versus 2529 kg ha-1) whereas dead biomass was higher during the dry season than during the wet season (2542 versus 1894 kg ha-1). The groundwater levels changes from -3.1 m to -6.5 m during the wet and dry seasons, respectively. The annual average of SLA was 16.3 m² kg-1 in 1999 and 20.4 m² kg-1 in 2001. And for LAI was 1.5 in 2000 to 2.8 in 2003. The Albedo changes from 0.18 down to 0.16 at higher values of LAI.