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NASA NTRS2011

Decoupling of Deforestation and Soy Production in the Southern Amazon During the Late 2000s

From 2006-2010 deforestation in the Amazon frontier state of Mato Grosso decreased to 30% of its historical average (1996-2005) while agricultural production reached an all time high, achieving the oft-cited objective of increasing production while maintaining forest cover. This study combines satellite data with government deforestation and production statistics to assess land-use transitions and potential market and policy drivers associated with these trends. In the forested region of the state, increased soy production from 2001-2005 was entirely due to cropland expansion into previously cleared areas (74%) or forests (26%). From 2006-2010, 78% of production increases were due to expansion (22% to yield increases), with 91% on previously cleared land. Cropland expansion fell from 10% to 2% of deforestation between the two periods, with pasture expansion accounting for most remaining deforestation. Declining deforestation coincided with a collapse of commodity markets and implementation of policy measures to reduce deforestation. Soybean profitability has since increased to pre-2006 levels while deforestation continued to decline, suggesting that anti-deforestation measures may have influenced the agricultural sector. We found little evidence of leakage of soy expansion into cerrado in Mato Grosso or forests in neighboring Amazon states during the late 2000s, although leakage to more distant regions is possible. This study provides empirical evidence that reduced deforestation and increased agricultural production can occur simultaneously in tropical forest frontiers through productive use of already cleared lands. It remains uncertain whether government and industry-led policies can contain deforestation when market conditions again favor a boom in agricultural expansion.

Macedo, Marcia N.↗

DOE OSTI2012

Exploring Surface Biophysical-Climate Sensitivity to Tropical Deforestation Rates Using a GCM: A Feasibility Study

Deforestation perturbs both biophysical and carbon feedbacks on climate. However, biophysical feedbacks operate at temporally immediate and spatially focused scales and thus may be sensitive to the rate of deforestation rather than just to total forest-cover loss. Explored here is a method for simulating annual tropical deforestation in the fully coupled Community Climate System Model, version 3.0 (CCSM3) with the Dynamic Global Vegetation Model (DGVM) for testing biosphere climate sensitivity to “preservation pathways.” Two deforestation curves were simulated—a 10% deforestation curve with a 10% preservation target (DFC10-PT10) versus a 1% deforestation curve with a 10% preservation target (DFC1-PT10). During active deforestation, albedo, net radiation, latent heat flux, and climate variables were compared for time dependence and sensitivity to tropical tree cover across the tropical band and the Amazon basin, central African, and Southeast Asian regions. The results demonstrated the feasibility of modeling incremental deforestation and detecting both transient and long-term impacts, although a warm/dry bias in CCSM3–DGVM and the absence of carbon feedbacks preclude definitive conclusions on the magnitude of sensitivities. The deforestation rates produced characteristic trends in biophysical variables with DFC10-PT10 resulting in rapid increase/decrease during the initial 10–30 years before leveling off, whereas DFC1-PT10 exhibits gradual changes. The rate had little effect on biophysical and climate sensitivities when averaged over tropical land but produced significant differences at a regional level. Over the long term, the rates produced dissimilar vegetation distributions, despite having the same preservation target in both cases. Overall, these results indicate that the question of rates is one worth further analysis.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

Historic Emissions from Deforestation and Forest Degradation in Mato Grosso, Brazil: 1. Source Data Uncertainties

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

Morton, Douglas C.↗

NASA NTRS1994

Sensitivity of Regional Climate to Deforestation in the Amazon Basin

The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem.

Eltahir, Elfatih A. B.↗

DOE OSTI2019

Improving Representation of Deforestation Effects on Evapotranspiration in the E3SM Land Model

Abstract Evapotranspiration (ET) plays an important role in land‐atmosphere coupling of energy, water, and carbon cycles. Following deforestation, ET is typically observed to decrease substantially as a consequence of decreases in leaf area and roots and increases in runoff. Changes in ET (latent heat flux) revise the surface energy and water budgets, which further affects large‐scale atmospheric dynamics and feeds back positively or negatively to long‐term forest sustainability. In this study, we used observations from a recent synthesis of 29 pairs of adjacent intact and deforested FLUXNET sites to improve model parameterization of stomatal characteristics, photosynthesis, and soil water dynamics in version 1 of the Energy Exascale Earth System Model (E3SM) Land Model (ELMv1). We found that default ELMv1 predicts an increase in ET after deforestation, likely leading to incorrect estimates of the effects of deforestation on land‐atmosphere coupling. The calibrated model accurately represented the FLUXNET observed deforestation effects on ET. Importantly, the search for global optimal parameters converged at values consistent with recent observational syntheses, confirming the reliability of the calibrated physical parameters. Applying this improved model parameterization to the globe scale reduced the bias of annual ET simulation by up to ~600 mm/year. Analysis on the roles of parameters suggested that future model development to improve ET simulation should focus on stomatal resistance and soil water‐related parameterizations. Finally, our predicted differences in seasonal ET changes from deforestation are large enough to substantially affect land‐atmosphere coupling and should be considered in such studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Deforestation reshapes land-surface energy-flux partitioning

Land-use and land-cover change significantly modify local land-surface characteristics and water/energy exchanges, which can lead to atmospheric circulation and regional climate changes. In particular, deforestation accounts for a large portion of global land-use changes, which transforms forests into other land cover types, such as croplands and grazing lands. Many previous efforts have focused on observing and modeling land–atmosphere–water/energy fluxes to investigate land–atmosphere coupling induced by deforestation. However, interpreting land–atmosphere–water/energy-flux responses to deforestation is often complicated by the concurrent impacts from shifts in land-surface properties versus background atmospheric forcings. In this study, we used 29 paired FLUXNET sites, to improve understanding of how deforested land surfaces drive changes in surface-energy-flux partitioning. Each paired sites included an intact forested and non-forested site that had similar background climate. We employed transfer entropy, a method based on information theory, to diagnose directional controls between coupling variables, and identify nonlinear cause–effect relationships. Transfer entropy is a powerful tool to detective causal relationships in nonlinear and asynchronous systems. The paired eddy covariance flux measurements showed consistent and strong information flows from vegetation activity (gross primary productivity (GPP)) and physical climate (e.g. shortwave radiation, air temperature) to evaporative fraction (EF) over both non-forested and forested land surfaces. More importantly, the information transfers from radiation, precipitation, and GPP to EF were significantly reduced at non-forested sites, compared to forested sites. We then applied these observationally constrained metrics as benchmarks to evaluate the Energy Exascale Earth System Model (E3SM) land model (ELM). ELM predicted vegetation controls on EF relatively well, but underpredicted climate factors on EF, indicating model deficiencies in describing the relationships between atmospheric state and surface fluxes. Moreover, changes in controls on surface energy flux partitioning due to deforestation were not detected in the model. We highlight the need for benchmarking model simulated surface-energy fluxes and the corresponding causal relationships against those of observations, to improve our understanding of model predictability on how deforestation reshapes land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Deforestation triggering irreversible transition in Amazon hydrological cycle

The Amazon is hypothesized to reach an irreversible ‘tipping point’ when deforestation slows the hydrological cycle sufficiently that tropical forest ecosystems cannot be sustained. However, inception of such a tipping point has not been supported by observations and the relevant links between deforestation and atmospheric moisture recycling are poorly understood. Here we show that reduction in evapotranspiration from 20 years of deforestation dried the atmosphere persistently and caused moisture decoupling, i.e. an opposite sign of moisture change between the lower and middle troposphere. Increased deforestation exacerbated the lower troposphere drying and caused it to penetrate deeper into the middle troposphere in the dry and transition seasons over monsoon forests and savannas. Deforestation induced warming-enhanced buoyant updrafts, elevated hot and dry air and thereby reduced downward mixing of water supplies from the tropical Atlantic that normally moisten the Amazon forests. The severe atmospheric desiccation in the southern and eastern Amazon cannot be compensated by enhanced water supplies from the Atlantic Ocean, demonstrating an irreversible transition in Amazon hydrological cycle exacerbated by rapid deforestation. The more recent drying through the seasons over rainforests and during the wet season over the transition zones from rainforests to monsoon forests and savannas, however, suggests a window of opportunity for preventing ecosystem collapse with forest conservation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Psychosocial drivers of land management behaviour: How threats, norms, and context influence deforestation intentions

Understanding how private landholders make deforestation decisions is of paramount importance for conservation. Behavioural frameworks from the social sciences have a lot to offer researchers and practitioners, yet these insights remain underutilised in describing what drives landholders' deforestation intentions under important political, social, and management contexts. Using survey data of private landholders in Queensland, Australia, we compare the ability of two popular behavioural models to predict future deforestation intentions, and propose a more integrated behavioural model of deforestation intentions. We found that the integrated model outperformed other models, revealing the importance of threat perceptions, attitudes, and social norms for predicting landholders' deforestation intentions. Social capital, policy uncertainty, and years of experience are important contextual moderators of these psychological factors. Here, we conclude with recommendations for promoting behaviour change in this deforestation hotspot and highlight how others can adopt similar approaches to illuminate more proximate drivers of environmental behaviours in other contexts.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Tropical deforestation and habitat fragmentation in the Amazon - Satellite data from 1978 to 1988

Landsat satellite imagery covering the entire forested portion of the Brazilian Amazon Basin was used to measure, for 1978 and 1988, deforestation, fragmented forest, defined as areas less than 100 square kilometers surrounded by deforestation, and edge effects of 1 kilometer into forest from adjacent areas of deforestation. Tropical deforestation increased from 78,000 square kilometers in 1978 to 230,000 square kilometers in 1988 while tropical forest habitat, severely affected with respect to biological diversity, increased from 208,000 to 588,000 square kilometers. Although this rate of deforestation is lower than previous estimates, the effect on biological diversity is greater.

Skole, David↗

NASA NTRS1994

Albedo as a modulator of climate response to tropical deforestation

An atmospheric general circulation model with land surface properties represented by the simplified Simple Biosphere model is used to investigate the effects on local climate due to tropical deforestation for the Amazon basin. One control and three anomaly integrations of 4 years' duration are performed. In the anomaly integrations, rain forest in South America is replaced by degraded grassland. The anomaly integrations differ only in the optical properties of the grassland vegetation, with net surface albedos ranging from the same as to 0.09 lighter than that of rain forest. It is found that the change in climate, particularly rainfall, is strongly dependent on the change in surface albedo that accompanies deforestation. Replacement of forest by grass causes a reduction in transpiration and reduces frictional convergence by decreasing surface roughness. However, precipitation averaged over the deforested area is not necessarily reduced. Average precipitation decreases when the increase in albedo is greater than 0.03. If surface albedo is not increased appreciably as a result of deforestation, moisture flux convergence driven by the increase in surface temperature can offset the other effects, and average precipitation increases. As albedo is increased, surface temperature does not change, but surface latent and sensible heat flux decreases due to reduced radiational energy absorbed at the surface, resulting in a reduction in convection and precipitation. A change in the distribution of precipitation due to deforestation that appears to be independent of the albedo is observed.

Dirmeyer, Paul A.↗

NASA NTRS1995

Impact of the ongoing Amazonian deforestation on local precipitation: A GCM simulation study

Numerical simulation experiments were conducted to delineate the influence of in situ deforestation data on episodic rainfall by comparing two ensembles of five 5-day integrations performed with a recent version of the Goddard Laboratory for Atmospheres General Circulation Model (GCM) that has a simple biosphere model (SiB). The first set, called control cases, used the standard SiB vegetation cover (comprising 12 biomes) and assumed a fully forested Amazonia, while the second set, called deforestation cases, distinguished the partially deforested regions of Amazonia as savanna. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both sets of integrations. The differential analyses of these five cases show the following local effects of deforestation. (1) A discernible decrease in evapotranspiration of about 0.80 mm/d (roughly 18%) that is quite robust in the averages for 1-, 2-, and 5-day forecasts. (2) A decrease in precipitation of about 1.18 mm/d (roughly 8%) that begins to emerge even in 1-2 day averages and exhibits complex evolution that extends downstream with the winds. (3) A significant decrease in the surface drag force (as a consequence of reduced surface roughness of deforested regions) that, in turn, affects the dynamical structure of moisture convergence and circulation. The surface winds increase significantly during the first day, and thereafter the increase is well maintained even in the 2- and 5-day averages.

Walker, G. K.↗

NASA NTRS2000

Tropical Deforestation in the Bolivian Amazon

Landsat satellite images from the mid-1980s and early 1990s were used to map tropical forest extent and deforestation in approximately 800,000 sq km of Amazonian Bolivia. Forest cover extent, including tropical deciduous forest, totalled 472,000 sq km while the area of natural non-forest formations totalled 298,000 sq km. The area deforested totalled 15,000 sq km in the middle 1980s and 28,800 sq km by the early 1990s. The rate of tropical deforestation in the >1,000 mm/y precipitation forest zone of Bolivia was 2,200 sq km/y from 1985-1986 to 1992-1994. We document a spatially-concentrated "deforestation zone" in Santa Cruz Department where >60% of the Bolivian deforestation is occurring at an accelerating rate in areas of tropical deciduous dry forest.

Tucker, Compton J.↗

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.↗

DOE OSTI2018

Deforestation decreases spatial turnover and alters the network interactions in soil bacterial communities

Despite important progress in understanding the influence of deforestation on the bacterial α diversity and community structure at local scales, little is known about deforestation impacts in terms of spatial turnover and soil bacterial community network interactions, especially at regional or global scales. In this study, to address this research gap, we examined the bacterial spatial turnover rate and the species networks in paired primary and secondary forest soils along a 3700-km north-south transect in eastern China using high-throughput 16S rRNA gene sequencing. The spatial turnover rate of bacterial communities was higher in primary forests than in secondary, suggesting deforestation increased biotic homogenization at a large geographic scale. Multiple regression on matrices analysis revealed that both geographic distance and soil properties (especially soil pH and organic matter availability) strongly affected bacterial spatial turnover. Through the phylogenetic molecular ecological network approach, we demonstrate that the bacterial network of primary forests was more intricate than in secondary forests. This suggests that microbial species have greater niche-sharing and more interactions in primary forests as compared to secondary forests. On the other hand, the bacterial network in secondary forests was more modular, and the taxa tended to co-occur, with positive correlations accounting for 82% of all potential interactions. Lastly, our findings demonstrate that anthropogenic deforestation has clear effects on bacterial spatial turnover and network interactions, with potential for serious consequences such as microbial diversity loss in primary forests.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

A Sensitivity Analysis of Surface Biophysical, Carbon, and Climate Impacts of Tropical Deforestation Rates in CCSM4-CNDV*

The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also explore responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm 2 ) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Furthermore, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. While it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Deforestation strengthens atmospheric transport of mineral dust and phosphorus from North Africa to the Amazon

Phosphorus contained in atmospheric mineral dust aerosol originating from Africa fertilizes tropical forests in Amazonia. However, the mechanisms influencing this nutrient transport pathway remain poorly understood. Here we use the Community Earth System Model to investigate how large-scale deforestation affects mineral dust aerosol transport and deposition in the tropics. We find that the surface biophysical changes that accompany deforestation produce a warmer, drier and windier surface environment that perturbs atmospheric circulation and enhances long-range dust transport from North Africa to the Amazon. Tropics-wide deforestation weakens the Hadley circulation, which in turn, leads to a northward expansion of the Hadley cell and increases surface air pressure over the Sahara Desert. Additionally, the high pressure anomaly over the Sahara, in turn, increases northeasterly winds across North Africa and the tropical North Atlantic Ocean, which subsequently increases dust transport to the South America continent. We estimate that the annual atmospheric phosphorus deposition from dust significantly increases by 27% (P < 0.01) in the Amazon under a scenario of complete deforestation. These interactions exemplify how land surface changes can modify tropical nutrient cycling, which in turn, may have consequences for long-term changes in tropical ecosystem productivity and biodiversity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Deforestation-induced climate change reduces carbon storage in remaining tropical forests

Abstract Biophysical effects from deforestation have the potential to amplify carbon losses but are often neglected in carbon accounting systems. Here we use both Earth system model simulations and satellite–derived estimates of aboveground biomass to assess losses of vegetation carbon caused by the influence of tropical deforestation on regional climate across different continents. In the Amazon, warming and drying arising from deforestation result in an additional 5.1 ± 3.7% loss of aboveground biomass. Biophysical effects also amplify carbon losses in the Congo (3.8 ± 2.5%) but do not lead to significant additional carbon losses in tropical Asia due to its high levels of annual mean precipitation. These findings indicate that tropical forests may be undervalued in carbon accounting systems that neglect climate feedbacks from surface biophysical changes and that the positive carbon–climate feedback from deforestation-driven climate change is higher than the feedback originating from fossil fuel emissions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

On the response of the tropical atmosphere to large-scale deforestation

Recent studies on the Amazon deforestation problem predict that removal of the forest will result in a higher surface temperature, a significant reduction in evaporation and precipitation, and possibly significant changes in the tropical circulation. Here, we discuss the basic mechanisms contributing to the response of the tropical atmosphere to deforestation. A simple linear model of the tropical atmosphere is used in studying the effects of deforestation on climate. It is suggested that the impact of large-scale deforestation on the circulation of the tropical atmosphere consists of two components: the response of the tropical circulation to the negative change in precipitation (heating), and the response of the same circulation to the positive change in surface temperature. Owing to their different signs, the changes in predicted temperature and precipitation excite competing responses working in opposite directions. The predicted change in tropical circulation determines the change, if any, in atmospheric moisture convergence, which is equivalent to the change in run-off. The dependence of run-off predictions on the relative magnitudes of the predicted changes in precipitation and surface temperature implies that the predictions about run-off are highly sensitive, which explains, at least partly, the disagreement between the different models concerning the sign of the predicted change in Amazonian run-off.

Eltahir, E. A. B.↗