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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗
NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗
DOE OSTI2025

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar ( Control ) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation ( Recovery ) and (2) expansion of selective logging and deforestation ( Degradation ). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted gross primary productivity (GPP) and evapotranspiration (ET). Moreover, both GPP and ET respond negatively to extremes in vapor pressure deficit and downwelling shortwave irradiance in degraded forests in Eastern and Southern Amazon, indicating high sensitivity to droughts. Locally high-biomass forest patches showed little or no negative response of GPP and ET to extreme drought conditions whereas low-biomass forest patches in the same locations—typically degraded forest canopies—responded negatively to higher moisture stress. The results from the Recovery scenario showed similar results to simulations with observed structure; however, under the Degradation scenario, low-biomass forest patches became more abundant, resulting in more regions where GPP and ET are negatively impacted by hot drought conditions according to the ED2 model. Our results suggest that local forest structure is a critical determinant of an ecosystem’s response to climate variability, and that the loss of canopy trees in the Amazon through forest degradation could increase and expand forest vulnerability to droughts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Daytime turbulent exchange between the Amazon forest and the atmosphere

Detailed observations of turbulence just above and below the crown of the Amazon rain forest during the wet season are presented. The forest canopy is shown to remove high frequency turbulent fluctuations while passing lower frequencies. Filter characteristics of turbulent transfer into the Amazon rain forest canopy are quantified. Simple empirical relations that relate observed turbulent heat fluxes to horizontal wind variance are presented. Changes in the amount of turbulent coupling between the forest and the boundary layer associated with deep convective clouds are presented both as statistical averages and as a series of case studies. These convective processes during the rainy season are shown to alter the diurnal course of turbulent fluxes. In wake of giant coastal systems, no significant heat or moisture fluxes occur for up to a day after the event. Radar data is used to demonstrate that even small raining clouds are capable of evacuating the canopy of substances normally trapped by persistent static stability near the forest floor. Recovery from these events can take more than an hour, even during mid-day. In spite of the ubiquitous presence of clouds and frequent rain during this season, the average horizontal wind speed spectrum is well described by dry CBL similarity hypotheses originally found to apply in flat terrain.

Fitzjarrald, David R.↗
NASA NTRS1990

Daytime turbulent exchange between the Amazon forest and the atmosphere

Detailed observations of turbulence just above and below the crown of the Amazon rain forest during the wet season are presented. The forest canopy is shown to remove high frequency turbulent fluctuations while passing lower frequencies. Filter characteristics of turbulent transfer into the Amazon rain forest canopy are quantified. Simple empirical relations that relate observed turbulent heat fluxes to horizontal wind variance are presented. Changes in the amount of turbulent coupling between the forest and the boundary layer associated with deep convective clouds are presented both as statistical averages and as a series of case studies. These convective processes during the rainy season are shown to alter the diurnal course of turbulent fluxes. In wake of giant coastal systems, no significant heat or moisture fluxes occur for up to a day after the event. Radar data is used to demonstrate that even small raining clouds are capable of evacuating the canopy of substances normally trapped by persistent static stability near the forest floor. Recovery from these events can take more than an hour, even during mid-day. In spite of the ubiquitous presence of clouds and frequent rain during this season, the average horizontal wind speed spectrum is well described by dry CBL similarity hypotheses originally found to apply in flat terrain.

Fitzjarrald, David R.↗
DOE OSTI2023

Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point

Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001–2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015–2016 El Niño drought and La Niña 2008–2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration ( ET ) leading to large increases in sensible heat fluxes ( H ). Partitioning ET by an approach that assumes transpiration ( T ) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance ( G s ) drove T declines partly compensated by higher evaporation ( E ). By contrast, the abnormally wet La Niña period gave higher T and lower E , with little change in seasonal ET . Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015–2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of G s and significant leaf shedding). Drought-reduced T and G s , higher H and E , amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. In conclusion, identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Turbulent transport observed just above the Amazon forest

Observations of turbulent heat, moisture, and momentum transport made at two levels, approximately 5 and 10 m above the Amazon rain forest canopy, are presented. 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 differences in dissipation scales was seen at two observed levels. 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. Time series of some of the terms in the turbulence budgets of vertical velocity variance and kinematic heat flux are presented.

Fitzjarrald, David R.↗
DOE OSTI2023

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Abstract Tropical forests face increasing climate risk 1,2 , yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, $$\varPsi $$ Ψ 50 ) and hydraulic safety margins (for example, HSM 50 ) are important predictors of drought-induced mortality risk 3–5 , little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters $$\varPsi $$ Ψ 50 and HSM 50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both $$\varPsi $$ Ψ 50 and HSM 50 influence the biogeographical distribution of Amazon tree species. However, HSM 50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM 50 are gaining more biomass than are low HSM 50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM 50 in the Amazon 6,7 , with strong implications for the Amazon carbon sink.

Science & Technology - Other Topics↗
DOE OSTI2023

Adjustments to the law of the wall above an Amazon forest explained by a spectral link

Modification to the law of the wall represented by a dimensionless correction function ϕ RSL (z/h) is derived using atmospheric turbulence measurements collected at two sites in the Amazon in near-neutral stratification, where z is the distance from the forest floor and h is the mean canopy height. The sites are the Amazon Tall Tower Observatory for z/h∈ [1,2.3] and the Green Ocean Amazon (GoAmazon) site for z/h∈ [1,1.4]. Here, a link between the vertical velocity spectrum E ww (k) (k is the longitudinal wavenumber) and ϕ RSL is then established using a co-spectral budget (CSB) model interpreted by the moving-equilibrium hypothesis. The key finding is that ϕ RSL is determined by the ratio of two turbulent viscosities and is given as ν t,BL /ν t,RSL, where ν t,RSL = (1/A)∫$^{∞}_{0}$ τ(k)E ww (k)dk, ν t,BL = k v (z−d)u * , τ(k) is a scale-dependent decorrelation time scale between velocity components, A = C R /(1−C I ) = 4.5 is predicted from the Rotta constant C R = 1.8, and the isotropization of production constant C I = 3/5 given by rapid distortion theory, k v is the von Kármán constant, u * is the friction velocity at the canopy top, and d is the zero-plane displacement. Because the transfer of energy across scales is conserved in E ww (k) and is determined by the turbulent kinetic energy dissipation rate (ε), the CSB model also predicts that ϕ RSL scales with L BL /L d , where L BL is the length scale of attached eddies to z = d, and L d = u$_{*}^{3}$/ε is a macro-scale dissipation length.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Non-structural carbohydrates mediate seasonal water stress across Amazon forests

Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSC T ) concentrations in both organs were remarkably similar across communities. However, NSC T and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSC T in the form of SS (SS:NSC T ) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of -4.14 +/- 0.76 MgC/hay. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

Pinage, Ekena Rangel↗
NASA NTRS1987

C-13/C-12 ratio in methane from the flooded Amazon forest

The C1-C4 hydrocarbon concentrations and the C-13/C-12 ratio in CH4 detected in air samples collected in the Amazon region (3.5 deg S latitude and 5.9 deg W longitude) are analyzed. It is observed that the CH4 concentrations of each sample are enhanced over the background concentration for remote locations, and the C-13/C-12 ratio in this biogenic methane is depleted in C-13 relative to atmospheric CH4. It is concluded, from the C2-C4 hydrocarbon data, that minor yields of C2-C4 hyrocarbons are released coincident with CH4; however, the minor yields do not contribute to the regionally enhanced concentrations of hydrocarbons found in Amazonia and the global atmosphere release of C2-C4 compounds.

Tyler, Stanley C.↗
DOE OSTI2021

Canopy position influences the degree of light suppression of leaf respiration in abundant tree genera in the Amazon Forest

Leaf respiration in the dark (R dark ) and light (R day ) is poorly characterized in diverse tropical ecosystems, and little to no information exists on the degree of light suppression in common tree species within the Amazon basin, and their dependences upon plant functional traits and position within the canopy. We quantified R dark and apparent R day using the Kok method and measured key leaf traits in 26 tree individuals of different species distributed in three different canopy positions: canopy, lower canopy, and understory. To explore the relationships between the leaf traits we used the standardized major axis (SMA). We found that canopy trees had significantly higher rates of R dark and R day than trees in the understory. The difference between R dark and R day (the light suppression of respiration) was greatest in the understory (68 ± 9%, 95% CI) and lower canopy (49 ± 9%, 95% CI) when compared to the canopy (37 ± 10%, 95% CI). We also found that R day was significantly and strongly correlated with R dark (p < 0.001) for all the canopy positions. Also, leaf mass per area (LMA) and leaf Phosphorus concentration (P) had a significant relationship with R dark (p < 0.001; p = 0.003), respectively. In addition, a significant relationship was found for LMA in the canopy and lower canopy positions (p = 0.009; p = 0.048) while P was only significant in the canopy (p = 0.044). Finally, no significant relationship was found between R dark and nitrogen, sugars, and starch. Our results highlight the importance of including representation of the light suppression of leaf respiration in terrestrial biosphere models and also of accounting for vertical gradients within forest canopies and connections with functional traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Laurance, William F.↗