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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Carbon Emissions from Deforestation in the Brazilian Amazon Region

A simulation model based on satellite observations of monthly vegetation greenness from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2002. The NASA-CASA (Carnegie Ames Stanford Approach) model estimates of annual forest production were used for the first time as the basis to generate a prediction for the standing pool of carbon in above-ground biomass (AGB; gC/sq m) for forested areas of the Brazilian Amazon region. Plot-level measurements of the residence time of carbon in wood in Amazon forest from Malhi et al. (2006) were interpolated by inverse distance weighting algorithms and used with CASA to generate a new regional map of AGB. Data from the Brazilian PRODES (Estimativa do Desflorestamento da Amazonia) project were used to map deforested areas. Results show that net primary production (NPP) sinks for carbon varied between 4.25 Pg C/yr (1 Pg=10(exp 15)g) and 4.34 Pg C for the region and were highest across the eastern and northern Amazon areas, whereas deforestation sources of CO2 flux from decomposition of residual woody debris were higher and less seasonal in the central Amazon than in the eastern and southern areas. Increased woody debris from past deforestation events was predicted to alter the net ecosystem carbon balance of the Amazon region to generate annual CO2 source fluxes at least two times higher than previously predicted by CASA modeling studies. Variations in climate, land cover, and forest burning were predicted to release carbon at rates of 0.5 to 1 Pg C/yr from the Brazilian Amazon. When direct deforestation emissions of CO2 from forest burning of between 0.2 and 0.6 Pg C/yr in the Legal Amazon are overlooked in regional budgets, the year-to-year variations in this net biome flux may appear to be large, whereas our model results implies net biome fluxes had actually been relatively consistent from year to year during the period 2000-2002. This is the first study to use MODIS data to model all carbon pools (wood, leaf, root) dynamically in simulations of Amazon forest deforestation from clearing and burning of all kinds.

Potter, C.↗
NASA NTRS1987

Measurement of heat and moisture fluxes at the top of the rain forest during ABLE

Observations are presented of turbulent heat, moisture, and momentum transport made at two levels, approximately 5 and 10 m above the Amazon rain forest canopy. Data acquired at 10 Hz included variances and some mixed third moments of vertical velocity, temperature, and humidity. Two features of the data appear to question the displacement height hypothesis: (1) The characteristic dissipation length scale in the near-canopy layer varied between 20 m in stable conditions to approximately 150 m during afternoon convective conditions, generally larger scales than would be expected; and (2) No appreciable difference in dissipation scales was seen at the two observed levels. Observed peaks in vertical velocity-temperature cospectra lead to similar length scale estimates for dominant eddies. Heat budgets on selected days show that frequent periods with negative heat flux concurrent with continuing positive moisture flux occur in early afternoon, and this is believed to indicate the patchy nature of canopy-atmosphere coupling. Vertical velocity skewness was observed to be negative on three successive days and exhibited a sharp positive gradient.

Fitzjarrald, David R.↗
NASA NTRS1988

Regional aerosol chemistry of the Amazon Basin during the dry season

The distribution and chemical composition of the atmospheric aerosol over the Amazon Basin forest were determined during the 1985 July-August dry season, using data on the aerosol chemical constituent concentration collected during the NASA Global Tropospheric Experiment Amazon Boundary Layer Experiment 2A mission. The results of the analyses suggest that there is a remarkable compositional and spatial homogeneity of the atmospheric aerosol on an extensive regional scale. Particulate organic carbon is the dominant component of the atmospheric aerosol, exhibiting an average concentration of about 740 nmol/cu m in the mixed layer and about 220 nmol/cu m in free tropospheric air. Oxalate and SO4(2-) exhibited the greatest enrichment in the mixed layer, while Cl(-) showed essentially no enrichment. The aerosol in the Amazonian atmosphere is essentially acid-base neutral, primarily as a result of incorporation of NH(+), which is presumably derived from NH3 released by the forest ecosystem.

Talbot, R. W.↗
NASA NTRS2007

Distribution of Aboveground Live Biomass in the Amazon Basin

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

rainforest↗
NASA NTRS2004

The Net Carbon Flux due to Deforestation and Forest Re-Growth in the Brazilian Amazon: Analysis using a Process-Based Model

We developed a process-based model of forest growth, carbon cycling, and land cover dynamics named CARLUC (for CARbon and Land Use Change) to estimate the size of terrestrial carbon pools in terra firme (non-flooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study of the impact of Amazonian deforestation, selective logging, and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re-growth over the period from 1970-1998. We calculate that the net flux to the atmosphere during this period reached a maximum of approx. 0.35 PgC/yr (1PgC = 1 x 10(exp I5) gC) in 1990, with a cumulative release of approx. 7 PgC from 1970- 1998. The net flux is higher than predicted by an earlier study by a total of 1 PgC over the period 1989-1 998 mainly because CARLUC predicts relatively high mature forest carbon storage compared to the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by approx. 1 PgC from 1970-1998, while different assumptions about land cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte-Carlo approach, is roughly 35% of the mean value (1 SD).

Hirsch, A. I.↗
NASA NTRS1980

The SASS scattering coefficient algorithm

This paper describes the algorithms used to convert engineering unit data obtained from the Seasat-A satellite scatterometer (SASS) to radar scattering coefficients and associated supporting parameters. A description is given of the instrument receiver and related processing used by the scatterometer to measure signal power backscattered from the earth's surface. The applicable radar equation used for determining scattering coefficient is derived. Sample results of SASS data processed through current algorithm development facility (ADF) scattering coefficient algorithms are presented which include scattering coefficient values for both water and land surfaces. Scattering coefficient signatures for these two surface types are seen to have distinctly different characteristics. Scattering coefficient measurements of the Amazon rain forest indicate the usefulness of this type of data as a stable calibration reference target.

Bracalente, E. M.↗
NASA NTRS1993

The Amazon river breeze and the local boundary layer. I - Observations

Observations of the diurnal evolution of the planetary boundary layer over the Amazon rain forest, made at sites close to the confluence of the Solimoes and Negro rivers (approximately at 3 deg S, 60 deg W) near Manaus, Amazonas, Brazil, show the existence of a diurnal rotation of the wind near the surface and the frequent presence of low-level nocturnal wind maxima. These circulations are shown to be plausibly explained as elements of a river and land breeze circulation induced by the thermal contrast between the rivers and the adjacent forest.

De Oliveira, Amauri P.↗
NASA NTRS1994

TOPEX/POSEIDON microwave radiometer performance and in-flight calibration

Results of the in-flight calibration and performance evaluation campaign for the TOPEX/POSEIDON microwave radiometer (TMR) are presented. Intercomparisons are made between TMR and various sources of ground truth, including ground-based microwave water vapor radiometers, radiosondes, global climatological models, special sensor microwave imager data over the Amazon rain forest, and models of clear, calm, subpolar ocean regions. After correction for preflight errors in the processing of thermal/vacuum data, relative channel offsets in the open ocean TMR brightness temperatures were noted at the approximately = 1 K level for the three TMR frequencies. Larger absolute offsets of 6-9 K over the rain forest indicated a approximately = 5% gain error in the three channel calibrations. This was corrected by adjusting the antenna pattern correction (APC) algorithm. AS 10% scale error in the TMR path delay estimates, relative to coincident radiosondes, was corrected in part by the APC adjustment and in part by a 5% modification to the value assumed for the 22.235 FGHz water vapor line strength in the path delay retrieval algorithm. After all in-flight corrections to the calibration, TMR global retrieval accuracy for the wet tropospheric range correction is estimated at 1.1 cm root mean square (RMS) with consistent peformance under clear, cloudy, and windy conditions.

Ruf, C. S.↗
NASA NTRS1992

STS-46 Post Flight Press Conference

At a post flight press conference, the flight crew of the STS-46 mission (Cmdr. Loren Shriver, Pilot Andrew Allen, Mission Specialists Claude Nicollier (European Space Agency (ESA)), Marsha Ivins (Flight Engineer), Jeff Hoffman (Payload Commander), Franklin Chang-Dias, and Payload Specialist Franco Malerba (Italian Space Agency (ISA))) discussed their roles in and presented video footage, slides and still photographs of the different aspects of their mission. The primary objectives of the mission were the deployment of ESA's European Retrievable Carrier (EURECA) satellite and the joint NASA/ISA deployment and testing of the Tethered Satellite System (TSS). Secondary objectives included the IMAX Camera, the Limited Duration Space Environment Candidate Materials Exposure (LDVE), and the Pituitary Growth Hormone Cell Function (PHCF) experiments. Video footage of the EURECA and TSS deployment procedures are shown. Earth views were extensive and included Javanese volcanoes, Amazon basin forest ground fires, southern Mexico, southern Bolivian volcanoes, south-west Sudan and the Sahara Desert, and Melville Island, Australia. Questions from reporters and journalists from Johnson Space Center and Kennedy Space Center were discussed.

Source record↗
NASA NTRS2000

Precipitation Signatures Observed by EDOP, AMPR and MIR During TRMM-LBA

During the TRMM-LBA (Tropical Rainfall Measuring Mission - Large-Scale Biosphere-Atmosphere Experiment in Amazonia) field campaign of January - February 1999, EDOP (ER-2 Doppler Radar), AMPR (Advanced Microwave Precipitation Radiometer), and MIR (Millimeter-wave Imaging Radiometer) on board the NASA ER-2 aircraft made a number of flights over the same Amazon area for studies of precipitation signatures. It is generally perceived that AMPR, with measurements at the frequencies of 10.7, 19.35, 37.0, and 85 GHz, is not sensitive to precipitation over land; a possible exception is detection through electromagnetic wave scattering at 85 GHz by frozen hydrometeors aloft above the freezing level. Analysis of the combined data sets from these instruments shows that, in the Amazon highly forested areas where the surface emissivity is high and uniform, direct detection of rain by a radiometer at frequencies less than or equal to 37 GHz is possible. The detection of rain is reflected by a depression in brightness temperature, which amounts to as much as 20 K at 19.35 GHz. Measurements at higher frequencies by the MIR help delineate the regions of scattering signatures above the freezing level. Implications of the combined wideband measurements from AMPR and MIR will be discussed.

Wang, J. R.↗
NASA NTRS2020

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Airborne lidar↗
NASA NTRS1988

Trace gas exchanges and convective transports over the Amazonian rain forest

The NASA Amazon Boundary Layer Experiment (ABLE 2A) based in Manaus, Brazil, in July and August 1985, is used to examine meteorological processes responsible for the vertical and horizontal transport of biogenic and anthropogenic trace gases generated over the Amazon basin. Direct sampling of the surrounding environment of deep convective clouds shows marked changes in the vertical distribution of the lower and midtroposphere concentration of O3 and such surface-derived species as CO, CO2, and NO. Thermodynamic observations, together with two-dimensional cloud model simulations, confirm vertical transports within the convection and provide a basis for an estimation of the magnitude and efficiency of cloud upward and downward exchanges. A distinction is drawn between local changes due to convective updrafts and downdrafts and convective overturning as a net result of the storm processes. Marked variability is seen in trace gas concentrations along horizontal flight paths in the vicinity of the convection. Interpretation of simultaneously measured thermodynamic quantities and trace gas concentrations provide the information to infer the presence and direction of atmospheric transports and/or the presence of anthropogenic influences.

Garstang, Michael↗
NASA NTRS2021

Mapping Global Forest Age from Forest Inventories, Biomass and Climate Data

Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. However, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. This study provides a new global distribution of forest age circa 2010, estimated using a machine learning approach trained with more than 40 000 plots using forest inventory, biomass and climate data. First, an evaluation against the plot-level measurements of forest age reveals that the data-driven method has a relatively good predictive capacity of classifying old-growth vs. non-old-growth (precision = 0.81 and 0.99 for old-growth and non-old-growth, respectively) forests and estimating corresponding forest age estimates (NSE = 0.6 – Nash–Sutcliffe efficiency – and RMSE = 50 years – root-mean-square error). However, there are systematic biases of overestimation in young- and underestimation in old-forest stands, respectively. Globally, we find a large variability in forest age with the old-growth forests in the tropical regions of Amazon and Congo, young forests in China, and intermediate stands in Europe. Furthermore, we find that the regions with high rates of deforestation or forest degradation (e.g. the arc of deforestation in the Amazon) are composed mainly of younger stands. Assessment of forest age in the climate space shows that the old forests are either in cold and dry regions or warm and wet regions, while young–intermediate forests span a large climatic gradient. Finally, comparing the presented forest age estimates with a series of regional products reveals differences rooted in different approaches and different in situ observations and global-scale products. Despite showing robustness in cross-validation results, additional methodological insights on further developments should as much as possible harmonize data across the different approaches. The forest age dataset presented here provides additional insights into the global distribution of forest age to better understand the global dynamics in the forest water and carbon cycles. The forest age datasets are openly available at https://doi.org/10.17871/ForestAgeBGI.2021 (Besnard et al., 2021).

Simon Besnard↗
NASA NTRS1988

Boundary layer ozone - An airborne survey above the Amazon Basin

Ozone data obtained over the forest canopy of the Amazon Basin during July and August 1985 in the course of NASA's Amazon Boundary Layer Experiment 2A are discussed, and ozone profiles obtained during flights from Belem to Tabatinga, Brazil, are analyzed to determine any cross-basin effects. The analyses of ozone data indicate that the mixed layer of the Amazon Basin, for the conditions of undisturbed meteorology and in the absence of biomass burning, is a significant sink for tropospheric ozone. As the coast is approached, marine influences are noted at about 300 km inland, and a transition from a forest-controlled mixed layer to a marine-controlled mixed layer is noted.

Gregory, Gerald L.↗
NASA NTRS1994

Human impacts on soil carbon dynamics of deep-rooted Amazonian forests

Deforestation and logging degrade more forest in eastern and southern Amazonia than in any other region of the world. This forest alteration affects regional hydrology and the global carbon cycle, but our current understanding of these effects is limited by incomplete knowledge of tropical forest ecosystems. It is widely agreed that roots are concentrated near the soil surface in moist tropical forests, but this generalization incorrectly implies that deep roots are unimportant in water and C budgets. Our results indicate that half of the closed-canopy forests of Brazilian Amazonic occur where rainfall is highly seasonal, and these forests rely on deeply penetrating roots to extract soil water. Pasture vegetation extracts less water from deep soil than the forest it replaces, thus increasing rates of drainage and decreasing rates of evapotranspiration. Deep roots are also a source of modern carbon deep in the soil. The soils of the eastern Amazon contain more carbon below 1 m depth than is present in above-ground biomass. As much as 25 percent of this deep soil C could have annual to decadal turnover times and may be lost to the atmosphere following deforestation. We compared the importance of deep roots in a mature, evergreen forest with an adjacent man-made pasture, the most common type of vegetation on deforested land in Amazonia. The study site is near the town of Paragominas, in the Brazilian state of Para, with a seasonal rainfall pattern and deeply-weathered, kaolinitic soils that are typical for large portions of Amazonia. Root distribution, soil water extraction, and soil carbon dynamics were studied using deep auger holes and shafts in each ecosystem, and the phenology and water status of the leaf canopies were measured. We estimated the geographical distribution of deeply-rooting forests using satellite imagery, rainfall data, and field measurements.

Nepstad, Daniel C.↗
NASA NTRS2023

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗