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.

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.

Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison.

To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, 'soil water stress' and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re ) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.

Patterns of land use, extensification, and intensification of Brazilian agriculture.

Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940-2012) and productivity (1990-2012) in Brazil using a new high-resolution (approximately 1 km(2) ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.

Modeling the impact of net primary production dynamics on post-disturbance Amazon savannization.

Amazon tropical forests are being replaced by pasturelands and croplands, but they sometimes revert to regrowth forest when abandoned after a period of agricultural use. Research suggests that this secondary regrowth is limited by climate and nutrient availability and, using a coupled biosphere-atmosphere model, we investigated patterns in the regrowth of the Amazon rainforest after a full deforestation event, considering different types of nutrient stress. We found that, over a 50 year regrowth period, the reduction of precipitation caused by large-scale deforestation was not sufficient to prevent secondary forest regrowth, but this decrease in precipitation combined with nutrient limitation, due to logging and frequent fires, did indeed prevent forest regrowth in central and southern Amazonia, leading to a savannization. These results are concerning, as the northern Mato Grosso region has the highest clearing rate in Amazonia. The low resilience of the forest under nutrient stress indicates that a large scale disturbance could greatly expand the area suitable for cropland, accelerating forest disappearance.

Dependence of hydropower energy generation on forests in the Amazon Basin at local and regional scales.

Tropical rainforest regions have large hydropower generation potential that figures prominently in many nations' energy growth strategies. Feasibility studies of hydropower plants typically ignore the effect of future deforestation or assume that deforestation will have a positive effect on river discharge and energy generation resulting from declines in evapotranspiration (ET) associated with forest conversion. Forest loss can also reduce river discharge, however, by inhibiting rainfall. We used land use, hydrological, and climate models to examine the local "direct" effects (through changes in ET within the watershed) and the potential regional "indirect" effects (through changes in rainfall) of deforestation on river discharge and energy generation potential for the Belo Monte energy complex, one of the world's largest hydropower plants that is currently under construction on the Xingu River in the eastern Amazon. In the absence of indirect effects of deforestation, simulated deforestation of 20% and 40% within the Xingu River basin increased discharge by 4-8% and 10-12%, with similar increases in energy generation. When indirect effects were considered, deforestation of the Amazon region inhibited rainfall within the Xingu Basin, counterbalancing declines in ET and decreasing discharge by 6-36%. Under business-as-usual projections of forest loss for 2050 (40%), simulated power generation declined to only 25% of maximum plant output and 60% of the industry's own projections. Like other energy sources, hydropower plants present large social and environmental costs. Their reliability as energy sources, however, must take into account their dependence on forests.

Modeling radiative transfer in tropical rainforest canopies: sensitivity of simulated albedo to canopy architectural and optical parameters.

This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS) to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS) and near-infrared (NIR) spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia) Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (χup) and to the reflectivity in the near-infrared spectral band (ρNIR,up), a smaller sensitivity to the reflectivity in the visible spectral band (ρVIS,up) and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are χup = 0.86, ρVIS,up = 0.062 and ρNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.

Modeling radiative transfer in tropical rainforest canopies: sensitivity of simulated albedo to canopy architectural and optical parameters

This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS) to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS) and near-infrared (NIR) spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia) Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (x up) and to the reflectivity in the near-infrared spectral band (rNIR,up), a smaller sensitivity to the reflectivity in the visible spectral band (rVIS,up) and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are Xup = 0.86, rVIS,up = 0.062 and rNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.

Este estudo avalia a sensibilidade do albedo da superfície pelo Simulador Integrado da Biosfera (IBIS) a um conjunto de parâmetros que representam algumas propriedades arquitetônicas e óticas do dossel da floresta tropical Amazônica. Os parâmetros testados neste estudo são a orientação e refletância das folhas do dossel superior e inferior nas bandas espectrais do visível (VIS) e infravermelho próximo (NIR). Os resultados são avaliados contra observações feitas no sítio K34 pertencente ao Instituto Nacional de Pesquisas da Amazônia (INPA) na Reserva Biológica de Cuieiras. A análise de sensibilidade indica uma forte resposta aos parâmetros de orientação das folhas do dossel superior (x up ) e à refletância na banda do infravermelho próximo (pNIR,up), uma menor sensibilidade à refletância na banda espectral do visível (pVISup) e nenhuma sensibilidade aos parâmetros da parte inferior do dossel, o que é consistente com a estrutura do dossel. A combinação de parâmetros que minimizaram a raiz do erro quadrado médio e o erro relativo médio são Xup= 0, 86, pVISup = 0, 062 e pNIR,up = 0, 275. As parametrizações realizadas resultaram em simulações bem sucedidas do albedo de floresta tropical pelo IBIS, indicando seu potencial para simular a transferência radiativa do dossel para bandas espectrais estreitas, permitindo a comparação com produtos de sensoriamento remoto.

Simulations of tropical rainforest albedo: is canopy wetness important?

Accurate information on surface albedo is essential for climate modelling, especially for regions such as Amazonia, where the response of the regional atmospheric circulation to the changes on surface albedo is strong. Previous studies have indicated that models are still unable to correctly reproduce details of the seasonal variation of surface albedo. Therefore, it was investigated the role of canopy wetness on the simulated albedo of a tropical rainforest by modifying the IBIS canopy radiation transfer code to incorporate the effects of canopy wetness on the vegetation reflectance. In this study, simulations were run using three versions of the land surface/ecosystem model IBIS: the standard version, the same version recalibrated to fit the data of albedo on tropical rainforests and a modified version that incorporates the effects of canopy wetness on surface albedo, for three sites in the Amazon forest at hourly and monthly scales. The results demonstrated that, at the hourly time scale, the incorporation of canopy wetness on the calculations of radiative transfer substantially improves the simulations results, whereas at the monthly scale these changes do not substantially modify the simulated albedo.

A informação precisa do albedo superficial é essencial para a modelagem climática, especialmente para regiões, tais como a Amazônia, onde a resposta da circulação atmosférica regional às mudanças do albedo superficial é forte. Estudos preliminares têm indicado que os modelos ainda não são capazes de reproduzir corretamente os detalhes da variação sazonal do albedo superficial. Portanto, investigou-se o papel do molhamento foliar sobre o albedo simulado de uma floresta tropical por meio da modificação do código de transferência radiativa no dossel do IBIS para incorporar os efeitos do molhamento do dossel sobre a refletância da vegetação. Neste estudo, procederamse simulações usando três versões do modelo superfície terrestre/ ecossistema IBIS: a versão padrão, a mesma versão recalibrada para ajustar aos dados de albedo de florestas tropicais e, uma versão modificada que incorpora os efeitos do molhamento do dossel sobre o albedo superficial, para três sítios da floresta amazônica em escalas horária e mensal. Os resultados demonstraram que, em escala horária, a incorporação do molhamento do dossel sobre os cálculos de transferência radiativa melhora substancialmente os resultados simulados, enquanto que, em escala mensal, essas mudanças não modificam substancialmente o albedo simulado.

Simulations of tropical rainforest albedo: is canopy wetness important?

Accurate information on surface albedo is essential for climate modelling, especially for regions such as Amazonia, where the response of the regional atmospheric circulation to the changes on surface albedo is strong. Previous studies have indicated that models are still unable to correctly reproduce details of the seasonal variation of surface albedo. Therefore, it was investigated the role of canopy wetness on the simulated albedo of a tropical rainforest by modifying the IBIS canopy radiation transfer code to incorporate the effects of canopy wetness on the vegetation reflectance. In this study, simulations were run using three versions of the land surface/ecosystem model IBIS: the standard version, the same version recalibrated to fit the data of albedo on tropical rainforests and a modified version that incorporates the effects of canopy wetness on surface albedo, for three sites in the Amazon forest at hourly and monthly scales. The results demonstrated that, at the hourly time scale, the incorporation of canopy wetness on the calculations of radiative transfer substantially improves the simulations results, whereas at the monthly scale these changes do not substantially modify the simulated albedo.

Comment on "Drought-induced reduction in global terrestrial net primary production from 2000 through 2009".

Zhao and Running (Reports, 20 August 2010, p. 940) reported a reduction in global terrestrial net primary production (NPP) from 2000 through 2009. We argue that the small trends, regional patterns, and interannual variations that they describe are artifacts of their NPP model. Satellite observations of vegetation activity show no statistically significant changes in more than 85% of the vegetated lands south of 70°N during the same 2000 to 2009 period.