Quantifying Long-Term Changes in Carbon Stocks and Forest Structure from Amazon Forest Degradation

Despite sustained declines in Amazon deforestation, forest degradation from logging and firecontinues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arcof deforestation. Limited data on the magnitude of carbon losses and rates of carbon recoveryfollowing forest degradation have hindered carbon accounting efforts and contributed to incompletenational reporting to reduce emissions from deforestation and forest degradation (REDD+). Wecombined annual time series of Landsat imagery and high-density airborne lidar data to characterizethe variability, magnitude, and persistence of Amazon forest degradation impacts on abovegroundcarbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of thecarbon stocks in intact forests, and differences persisted even after 15 years of regrowth. Incomparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD.Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a historyof one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD,respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires,selective logging before burning did not explain additional variability in modeled ACD loss andrecovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure thatcan aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recoveredfaster than attributes of canopy structure that are critical for biodiversity in tropical forests, includingthe abundance of tall trees. We provide the first comprehensive look-up table of emissions factors forspecific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon lossand recovery trajectories provide an important foundation for assessing the long-term contributionsfrom forest degradation to regional carbon cycling and advance our understanding of the currentstate of frontier forests

Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

©2016. American Geophysical Union. All Rights Reserved. Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained 70% of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 ± 2.5 and 31.9 ± 10.8 kg C m−2. Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 ± 0.7 kg C m−2 (94%) of ACD. Forests that burned nearly 15 years ago had between 4.1 ± 0.5 and 6.8 ± 0.3 kg C m−2 (22–40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 ± 0.3 and 4.4 ± 0.4 kg C m−2 (4–21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pantropical products consistently overestimated ACD in degraded forests, underestimated ACD in intact forests, and showed little sensitivity to fires and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation (REDD+)

Toward Content-Driven Intelligent Authoring of Mulsemedia Applications

Improvement of Higher Education Personnel—Brazil; 10.13039/501100004586-Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; 10.13039/501100003593-Conselho Nacional de Desenvolvimento Científico e Tecnológico; CAPES PRINT

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 67 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

Antimicrobial activity of Byrsonima species (Malpighiaceae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Byrsonima species, family Malpighiaceae, is popularly known as 'murici'. There are several properties attributed to the leaves of Byrsonima species including febrifuge, to treat gastrointestinal dysfunctions and skin diseases. In this work, the antimicrobial activity of Byrsonima fagifolia, B. basiloba and B. intermedia extracts obtained from the leaves were evaluated by using the disc-diffusion method. The results obtained showed that the methanol extracts of leaves had presented antimicrobial activity against all the microorganisms tested.18690695Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Human aging and somatic point mutations in mtDNA: A comparative study of generational differences (grandparents and grandchildren)

The accumulation of somatic mutations in mtDNA is correlated with aging. In this work, we sought to identify somatic mutations in the HVS-1 region (D-loop) of mtDNA that might be associated with aging. For this, we compared 31 grandmothers (mean age: 63 ± 2.3 years) and their 62 grandchildren (mean age: 15 ± 4.1 years), the offspring of their daughters. Direct DNA sequencing showed that mutations absent in the grandchildren were detected in a presumably homoplasmic state in three grandmothers and in a heteroplasmic state in an additional 13 grandmothers; no mutations were detected in the remaining 15 grandmothers. However, cloning followed by DNA sequencing in 12 grandmothers confirmed homoplasia in only one of the three mutations previously considered to be homoplasmic and did not confirm heteroplasmy in three out of nine grandmothers found to be heteroplasmic by direct sequencing. Thus, of 12 grandmothers in whom mtDNA was analyzed by cloning, eight were heteroplasmic for mutations not detected in their grandchildren. In this study, the use of genetically related subjects allowed us to demonstrate the occurrence of age-related (> 60 years old) mutations (homoplasia and heteroplasmy). It is possible that both of these situations (homoplasia and heteroplasmy) were a long-term consequence of mitochondrial oxidative phosphorylation that can lead to the accumulation of mtDNA mutations throughout life

Insertion of heterometals into the NifEN-associated iron–molybdenum cofactor precursor

The cofactors of Mo-, V-, Fe-dependent nitrogenases are believed to be highly homologous in structure despite the different types of heterometals (Mo, V, and Fe) they contain. Previously, a precursor form of the FeMo cofactor (FeMoco) was captured on NifEN, a scaffold protein for FeMoco biosynthesis. This all-Fe precursor closely resembles the Fe/S core structure of the FeMoco and, therefore, could reasonably serve as a precursor for all nitrogenase cofactors. Here, we report the heterologous incorporation of V and Fe into the NifEN-associated FeMoco precursor. EPR and activity analyses indicate that V and Fe can be inserted at much reduced efficiencies compared with Mo, and incorporation of both V and Fe is enhanced in the presence of homocitrate. Further, native polyacrylamide gel electrophoresis experiments suggest that NifEN undergoes a significant conformational rearrangement upon metal insertion, which allows the subsequent NifEN–MoFe protein interactions and the transfer of the cofactor between the two proteins. The combined outcome of these in vitro studies leads to the proposal of a selective mechanism that is utilized in vivo to maintain the specificity of heterometals in nitrogenase cofactors, which is likely accomplished through the redox regulation of metal mobilization by different Fe proteins (encoded by nifH, vnfH, and anfH, respectively), as well as the differential interactions between these Fe proteins and their respective scaffold proteins (NifEN and VnfEN) in the Mo-, V-, and Fe-dependent nitrogenase systems