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At least 37 records · Page 2

Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

Guild, Liane S.↗

The Impact of Amazonian Deforestation on Dry-Season Rainfall

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

Negri, Andrew J.↗

The Effects of Amazon Deforestation on Rainfall

This study begins with the hypothesis that heavily deforested regions will experience increased surface heating, leading to local circulations that will ultimately enhance the rainfall, or at least, change the pattern of diurnal evolution of rainfall. This would be an important finding because several modeling studies have concluded that widespread deforestation would lead to decreased rainfall. Towards that end rain estimates from a combined GOES infrared/TRMM microwave technique were analyzed with respect to percent forest cover from Landsat data (courtesy of TRFIC at Michigan State University) and GOES visible channel data over a deforested area in Rondonia (southwest Brazil). Five 1" x 1" areas of varying forest cover were examined during the onset of the wet season in Amazonia (Aug-Sept), when the effects of the surface would not be dominated by large-scale synoptic weather patterns. Preliminary results revealed that: maximum rainfall fell in most deforested area; heavily forested areas received the least rainfall; cumulus cloud development initiated at borders; the amplitude of the diurnal cycle of precipitation was a function of th surface cover. Further work will be presented detailing effects of land surface cover on the GOES infrared-measured surface heating, GOES visible observed cumulus development, thunderstorm initiation based on the location of temperature minima in the infrared data, and estimated rainfall and its diurnal cycle from a combined GOES/TRMM technique. Rainfall estimates derived from non-geosynchronous microwave observations (i.e. Goddard Profiling Algorithm, GPROF) will also be examined.

Starr, David OC.↗

The Impact of a Amazonian Deforestation on Dry-Season Rainfall

Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect to percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, shallow cumulus cloudiness, deep convective cloudiness, and rainfall occurrence all are larger over the deforested and non-forested (savanna) regions than over areas of dense jungle. This difference is in response to a local circulation initiated by the differential heating of the region s varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift in the onset of convection toward afternoon hours in the deforested and towards the morning hours in the savanna regions when compared to the neighboring forested regions. Analysis of 14 years of monthly estimates from the Special Sensor Microwave/Imager data revealed that in only in August was there a pattern of higher monthly rainfall amounts over the deforested region.

Negri, Andrew J.↗

Hydrological Regimes of Small Catchments in the High Tatra Mountains Before and After Extraordinary Wind-Induced Deforestation

The paper presents the results of rainfall-runoff data analysis for small catchments of the upper Poprad River affected by wind-induced deforestation in November 2004. Before-event and afterevent measured data were compared in order to assess the impact of deforestation on hydrological regimes. Several characteristics were used including water balance, minimum and maximum runoff, runoff thresholds, number of runoff events, selected characteristics of events, runoff coefficients, and flashiness indices. Despite increased spring runoff minima, which in one catchment (Velick Creek) exceeded previously observed values after deforestation took place, it can be generally concluded that the impact of the deforestation was not clearly manifested in the analyzed hydrological data.

Holko, Ladislav↗

Soil Carbon and Nutrient Changes Associated with Deforestation for Pasture in Southern Costa Rica

We assessed the effects of deforestation on soil carbon (C) and nutrient stocks in the premontane landscape near Las Cruces Biological Station in southern Costa Rica, where forests were cleared for pasture in the mid-1960s. We excavated six soil pits to a depth of 1 m in both pasture and primary forest, and found that C stocks were ~20 kg C per square meters in both settings. Nevertheless, soil delta C-13 suggests ~50 percent of the forest-derived soil C above 40 cm depth has turned over since deforestation. Soil nitrogen (N) and phosphorus (P) stocks derived from the soil pits were not significantly different between land uses (P = 0.43 and 0.61, respectively). At a larger spatial scale, however, the ubiquity of ruts produced by cattle-induced erosion indicates that there are substantial soil effects of grazing in this steep landscape. Ruts averaged 13 cm deep and covered ~45 percent of the landscape, and thus are evidence of the removal of 0.7 Mg C/ ha/yr, and 70, 9 and 40 kg/ha/yr of N, P and potassium (K), respectively. Subsoils in this region are ~10 times less C- and N-rich, and ~2 times less P- and K-rich than the topsoil. Thus, rapid topsoil loss may lead to a decline in pasture productivity in the coming decades. These data also suggest that the soil C footprint of deforestation in this landscape may be determined by the fate of soil C as it is transported downstream, rather than C turnover in situ.

soil carbon↗

Future increases in Amazonia water stress from CO 2 physiology and deforestation

Several different drivers are contributing to climate change within the Amazon basin, including forcing from greenhouse gases and aerosols, plant physiology responses to rising CO 2 , and deforestation. Attribution among these drivers has not been quantified for Shared Socioeconomic Pathway (SSP) climate simulations. Here we identify the contribution of CO 2 physiology and deforestation to future hydroclimate change in the Amazon basin by combining information from four experiments and eight different Earth system models in Coupled Model Intercomparison Project Phase 6. Together, forcing from CO 2 physiology and deforestation account for about 44% of the projected annual precipitation decline, 48% of surface relative humidity decline and 11% of warming over the Amazon basin by 2100 for SSP3-7.0. Further, other Coupled Model Intercomparison Project Phase 6 SSP simulations have similar contributions from the two drivers. Insight from our attribution analysis can aid in identifying research priorities aimed at reducing uncertainty in future projections of water availability, carbon dynamics and wildfire risk.

54 ENVIRONMENTAL SCIENCES↗

A large net carbon loss attributed to anthropogenic and natural disturbances in the Amazon Arc of Deforestation

The Amazon forest contains globally important carbon stocks, but in recent years, atmospheric measurements suggest that it has been releasing more carbon than it has absorbed because of deforestation and forest degradation. Accurately attributing the sources of carbon loss to forest degradation and natural disturbances remains a challenge because of the difficulty of classifying disturbances and simultaneously estimating carbon changes. We used a unique, randomized, repeated, very high-resolution airborne laser scanning survey to provide a direct, detailed, and high-resolution partitioning of aboveground carbon gains and losses in the Brazilian Arc of Deforestation. Our analysis revealed that disturbances directly attributed to human activity impacted 4.2% of the survey area while windthrows and other disturbances affected 2.7% and 14.7%, respectively. Extrapolating the lidar-based statistics to the study area (544,300 km 2 ), we found that 24.1, 24.2, and 14.5 Tg C y −1 were lost through clearing, fires, and logging, respectively. The losses due to large windthrows (21.5 Tg C y −1 ) and other disturbances (50.3 Tg C y −1 ) were partially counterbalanced by forest growth (44.1 Tg C y −1 ). Our high-resolution estimates demonstrated a greater loss of carbon through forest degradation than through deforestation and a net loss of carbon of 90.5 ± 16.6 Tg C y −1 for the study region attributable to both anthropogenic and natural processes. This study highlights the role of forest degradation in the carbon balance for this critical region in the Earth system.

54 ENVIRONMENTAL SCIENCES↗

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↗

Surveying the area of deforestation of the Amazon by LANDSAT satellite imagery

LANDSAT imagery was used to determine the amount of deforestation in a study area comprising 55 million hectares of the Amazon region. Results show that more than 4 million hectares were deforested. Maps and pictures of the deforested area in relation to the total area of the Amazon are included.

Dejesusparada, N.↗

Roads Investments, Spatial Intensification and Deforestation in the Brazilian Amazon

Understanding the impact of road investments on deforestation is part of a complete evaluation of the expansion of infrastructure for development. We find evidence of spatial spillovers from roads in the Brazilian Amazon: deforestation rises in the census tracts that lack roads but are in the same county as and within 100 km of a tract with a new paved or unpaved road. At greater distances from the new roads the evidence is mixed, including negative coefficients of inconsistent significance between 100 and 300 km, and if anything, higher neighbor deforestation at distances over 300 km.

Pfaff, Alexander↗

Global Climate Forcing from Albedo Change Caused by Large-scale Deforestation and Reforestation: Quantification and Attribution of Geographic Variation

Large-scale deforestation and reforestation have contributed substantially to historical and contemporary global climate change in part through albedo-induced radiative forcing, with meaningful implications for forest management aiming to mitigate climate change. Associated warming or cooling varies widely across the globe due to a range of factors including forest type, snow cover, and insolation, but resulting geographic variation remain spoorly described and has been largely based on model assessments. This study provides an observation-based approach to quantify local and global radiative forcings from large-scale deforestation and reforestation and further examines mechanisms that result in the spatial heterogeneity of radiative forcing. We incorporate a new spatially and temporally explicit land cover-specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product). Spatial variation in radiative forcing was attributed to four mechanisms, including the change in snow-covered albedo, change in snow-free albedo, snow cover fraction, and incoming solar radiation. We find an albedo-only radiative forcing (RF) of -0.819 W m(exp -2) if year 2000 forests were completely deforested and converted to croplands. Albedo RF from global reforestation of present-day croplands to recover year 1700 forests is estimated to be 0.161 W m)exp -2). Snow-cover fraction is identified as the primary factor in determining the spatial variation of radiative forcing in winter, while the magnitude of the change in snow-free albedo is the primary factor determining variations in summertime RF. Findings reinforce the notion that, for conifers at the snowier high latitudes, albedo RF diminishes the warming from forest loss and the cooling from forest gain more so than for other forest types, latitudes, and climate settings.

Jiao, Tong↗

Future Increases in Amazonia Water 1 Stress from CO2 Physiology and Deforestation

Several different drivers are contributing to climate change within the Amazon basin, including forcing from greenhouse gases and aerosols, plant physiology responses to rising CO 2 , and deforestation. Attribution among these drivers has not been quantified for Shared Socioeconomic Pathway (SSP) climate simulations. Here we identify the contribution of CO 2 physiology and deforestation to future hydroclimate change in the Amazon basin by combining information from four experiments and eight different Earth system models in Coupled Model Intercomparison Project Phase 6. Together, forcing from CO 2 physiology and deforestation account for about 44% of the projected annual precipitation decline, 48% of surface relative humidity decline and 11% of warming over the Amazon basin by 2100 for SSP3-7.0. Other Coupled Model Intercomparison Project Phase 6 SSP simulations have similar contributions from the two drivers. Insight from our attribution analysis can aid in identifying research priorities aimed at reducing uncertainty in future projections of water availability, carbon dynamics and wildfire risk.

Yue Li↗

Thermal stress in degraded forests in the Brazilian Amazon Arc of Deforestation

Understanding thermal stress in tropical forests has taken on new urgency in light of accelerating climate change and expansion of deforestation and forest degradation. Degraded tropical forests in particular may be approaching critical temperature thresholds even more rapidly than intact forests, with implications for tree survival and ecosystem recovery. We investigate thermal stress in degraded tropical forests within the Brazilian Amazon Arc of Deforestation. Using land surface temperature data from the ECOsystem Spaceborne Thermal Radiometer Experiment on the international Space Station (ECOSTRESS), we compared canopy temperatures of intact, selectively logged, and burned forests in Feliz Natal, Mato Grosso, Brazil. Upper canopy temperatures in previously burned forests were 4.1% higher (mean = 36.5 °C) and 50.9% more variable compared to intact and logged forests, which showed remarkably similar temperature distributions (means of 34.9 °C and 35.1 °C, respectively). Modeled leaf temperature distributions based on canopy temperature measurements from one of the warmest days in a 2 year dry season record indicated that 87% of leaves in the warmest burned forest patches exceeded the temperature threshold where respiration surpasses photosynthesis, compared to approximately 72%–74% in intact and logged forests, respectively, in the same time period. After controlling for environmental factors, burned forests were predicted to be 2.6 °C warmer on average [1.39 °C–3.96 °C, 95% credible interval] than intact forests across a 5–40 m canopy height range. Burned forests showed modest thermal recovery over time, with temperatures decreasing by approximately 1.2 °C over a 30 year recovery period. In contrast, logged forests showed minimal thermal differences from intact forests (−0.353 on average, [−1.125–0.274, 95% credible interval]) and negligible change (0.15 °C) over the same timeframe. While the absolute probabilities of exceeding damaging thermal thresholds remain low across all forest types under current climate conditions, the probability of leaves exceeding temperatures that cause permanent leaf damage was ten times higher in burned forests, with implications for the future of burned forest regeneration in water-limited regions of the Amazon basin. In particular, the combination of higher mean temperatures, greater temperature variability, and more frequent exposure to damaging thermal thresholds implies that burned tropical forests will experience substantially higher mortality rates and slower biomass recovery compared to intact and selectively logged forests, especially in water-limited regions where trees cannot rely on evaporative cooling to moderate canopy temperatures.

Brazilian Amazon Arc of Deforestation↗

Emissions leakage and economic losses may undermine deforestation-linked oil crop import restrictions

Import restrictions on deforestation-linked commodities are being considered strategies to reduce global deforestation and emissions. However, limited market share of importers imposing such restrictions and the potential for emissions leakage could reduce their effectiveness. Moreover, they could result in negative economic implications for producers and consumers. We quantify future emissions and economic implications of oil palm and soybean import restrictions. Current EU restrictions will likely have minimal impact due to the EU’s otherwise small and diminishing share of global palm and soy demand. If extended beyond the EU, such import restrictions could drive reductions in cumulative LUC emissions by 2050 in key oil crop exporting regions— up to 0.9% in Indonesia, 1.5% in the rest of Southeast Asia, 3.8% in Argentina and 6.7% in Brazil, relative to a scenario with no import restrictions. However, these key exporters could also face losses ranging $\$$4.1-$\$$61 billion in cumulative agricultural production revenue by 2050.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation

Widespread expansion of agriculture and forestry has altered the surface of the Earth, the composition of the atmosphere, and as a result, the climate. Here we quantify the radiative forcing caused by the historical deforestation of an ecoregion in the U.S. Upper Midwest and the adoption of eight nature-based climate solutions. We combined regional forest inventory data with over three decades of remote sensing and in situ data from a replicated land use change experiment. Deforestation of the region caused net global warming (1626 ± 44 µW m -2 ), mainly from the 76 % reduction of ecosystem carbon stocks, but also from the 84 % reduction of the soil methane sink and the 115 % increase in soil nitrous oxide emissions. The associated albedo increase offset 24 % of this greenhouse gas induced warming. For the adoption of nature-based climate solutions, we found that conservation agriculture can provide -39 to -76 ± 31 µW m -2 of climate mitigation over a 100-year time period while short/medium length forestry rotations can provide more at -296 to -881 ± 44 µW m -2 and natural forest regeneration can provide the most at -1555 ± 44 µW m -2 . As the impacts of climate change on nature and society intensify, consideration should be given to the climate mitigation, habitat, and ecosystem services that nature-based climate solutions can provide.

54 ENVIRONMENTAL SCIENCES↗

Deforestation, floodplain dynamics, and carbon biogeochemistry in the Amazon Basin

Three aspects of the physical geographic environment of the Amazon Basin are considered: (1) deforestation and reforestation, (2) floodplain dynamics, and (3) fluvial geomorphology. Three independent projects are coupled in this experiment to improve the in-place research and to ensure that the Shuttle Imaging Radar-B (SIR-B) experiment stands on a secure base of ongoing work. Major benefits to be obtained center on: (1) areal and locational information, (2) data from various depression angles, and (3) digital radar signatures. Analysis will be conducted for selected sites to define how well SIR-B data can be used for: (1) definition of extent and location of deforestation in a tropical moist forest, (2) definition and quantification of the nature of the vegetation and edaphic conditions on the (floodplain) of the Amazon River, and (3) quantification of the accuracy with which the geometry and channel shifting of the Amazon River may be mapped using SIR-B imagery in conjunction with other remote sensing data.

Bryan, M. L.↗

Identifying deforestation in Brazil using multiresolution satellite data

The use of multiresolution satellite data to monitor deforestation on a continental/subcontinental scale is examined. MSS, local area coverage (LAC), global area coverage (GAC), and GOES data were applied to the study of deforestation in Rondonia, Brazil; the characteristics of these sensors are described. The probability thresholding and vegetation-index thresholding procedures used to process the data in order to differentiate between forest from nonforest are analyzed. The LAC, GAC, and GOES data are compared to MSS data. It is observed that GOES data is not useful for monitoring colonization projects due to excessive noise in the data; the GAC data is only applicable in large areas of contiguous forest clearing; the MSS data when available is applicable as a ground data reference source for differentiating cleared areas from primary; the LAC data are capable of delineating colonization clearings; and the probability thresholding procedure differentiates forest from nonforest more accurately than the vegetation-index procedure. The data reveal that the LAC data combined with the probability threshold procedure provide the best data-source/classification-procedure combination.

Nelson, R.↗