83 research outputs found
Use of MODIS sensor images combined with reanalysis products to retrieve net radiation in Amazonia
This is the final version of the article. Available from the publisher via the DOI in this record.In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001-December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.Gabriel de Oliveira acknowledges the Brazilian Ministry of Science and Technology and Brazilian
Ministry of Education for providing research fellowships through the CNPq (Grant No. 52521/2012-7) and CAPES
(Grant No. 8210/2014-4) agencies, respectively. Luiz E. O. C. Aragão acknowledges the support of FAPESP
(Grant No. 50533-5) and CNPq (Grant No. 304425/2013-3) agencies
Disentangling the contribution of multiple land covers to fire-mediated carbon emissions in Amazonia during the 2010 drought
This is the final version of the article. Available from the publisher via the DOI in this record.In less than 15 years, the Amazon region experienced three major droughts. Links between droughts and fires have been demonstrated for the 1997/1998, 2005, and 2010 droughts. In 2010, emissions of 510 ± 120 Tg C were associated to fire alone in Amazonia. Existing approaches have, however, not yet disentangled the proportional contribution of multiple land cover sources to this total. We develop a novel integration of multisensor and multitemporal satellite-derived data on land cover, active fires, and burned area and an empirical model of fire-induced biomass loss to quantify the extent of burned areas and resulting biomass loss for multiple land covers in Mato Grosso (MT) state, southern Amazonia - the 2010 drought most impacted region. We show that 10.77% (96,855 km2) of MT burned. We estimated a gross carbon emission of 56.21 ± 22.5 Tg C from direct combustion of biomass, with an additional 29.4 ± 10 Tg C committed to be emitted in the following years due to dead wood decay. It is estimated that old-growth forest fires in the whole Brazilian Legal Amazon (BLA) have contributed to 14.81 Tg of C (11.75 Tg C to 17.87 Tg C) emissions to the atmosphere during the 2010 fire season, with an affected area of 27,555 km2. Total C loss from the 2010 fires in MT state and old-growth forest fires in the BLA represent, respectively, 77% (47% to 107%) and 86% (68.2% to 103%) of Brazil's National Plan on Climate Change annual target for Amazonia C emission reductions from deforestation.This work was supported
by UK NERC Amazonica grant
NE/F005482/1, Brazil MCTI-PCI (302541/
2014-4), CNPq grants 458022/2013-6
and 400640/2012-0, and NASA-IDS
grant NNX14AD31G
Investigating interactions between epicardial adipose tissue and cardiac myocytes: what can we learn from different approaches?
Heart disease is a major cause of morbidity and mortality throughout the world. Some cardiovascular conditions can be modulated by lifestyle factors such as increased exercise or a healthier diet, but many require surgical or pharmacological interventions for their management. More targeted and less invasive therapies would be beneficial. Recently it has become apparent that epicardial adipose tissue plays an important role in normal and pathological cardiac function, and it is now the focus of considerable research. Epicardial adipose tissue can be studied by imaging of various kinds, and these approaches have yielded much useful information. However at a molecular level it is more difficult to study as it is relatively scarce in animal models and, for practical and ethical reasons, not always available in sufficient quantities from patients. What is needed is a robust model system in which the interactions between epicardial adipocytes and cardiac myocytes can be studied, and physiologically relevant manipulations performed. There are drawbacks to conventional culture methods, not least the difficulty of culturing both cardiac myocytes and adipocytes, each of which has special requirements. We discuss the benefits of a three-dimensional co-culture model in which in vivo interactions can be replicated
Metformin Attenuates Palmitate-Induced Endoplasmic Reticulum Stress, Serine Phosphorylation of IRS-1 and Apoptosis in Rat Insulinoma Cells
Lipotoxicity refers to cellular dysfunctions caused by elevated free fatty acid levels playing a central role in the development and progression of obesity related diseases. Saturated fatty acids cause insulin resistance and reduce insulin production in the pancreatic islets, thereby generating a vicious cycle, which potentially culminates in type 2 diabetes. The underlying endoplasmic reticulum (ER) stress response can lead to even β-cell death (lipoapoptosis). Since improvement of β-cell viability is a promising anti-diabetic strategy, the protective effect of metformin, a known insulin sensitizer was studied in rat insulinoma cells. Assessment of palmitate-induced lipoapoptosis by fluorescent microscopy and by detection of caspase-3 showed a significant decrease in metformin treated cells. Attenuation of β-cell lipotoxicity was also revealed by lower induction/activation of various ER stress markers, e.g. phosphorylation of eukaryotic initiation factor 2α (eIF2α), c-Jun N-terminal kinase (JNK), insulin receptor substrate-1 (IRS-1) and induction of CCAAT/enhancer binding protein homologous protein (CHOP). Our results indicate that the β-cell protective activity of metformin in lipotoxicity can be at least partly attributed to suppression of ER stress
Spatial resolution influence on the identification of land cover classes in the Amazon environment
Advanced remote sensing techniques for global changes and Amazon ecosystem functioning studies
This paper aims to assess the contribution of remote sensing technology in addressing key questions raised by the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The answers to these questions foster the knowledge on the climatic, biogechemical and hydrologic functioning of the Amazon, as well as on the impact of human activities at regional and global scales. Remote sensing methods allow integrating information on several processes at different temporal and spatial scales. By doing so, it is possible to perceive hidden relations among processes and structures, enhancing their teleconnections. Key advances in the remote sensing science are summarized in this article, which is particularly focused on information that would not be possible to be retrieved without the concurrence of this technolog
Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia
In this study we investigate the potential of fraction images derived from a linear spectral mixture model to detect vegetation phenology in Amazonia, and evaluate their relationships with the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices. Time series ofMODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land covermap and a forest inventory survey to support the interpretation of our findings. Each vegetation physiognomy was characterized by a particular intra-annual variability detected by a combination of the fraction images. Both vegetation and shade fractions were important to evaluate the seasonality of the open tropical forest (OTF). The association of these results with forest inventory data and the literature suggests that Enhanced Vegetation Index (EVI) and vegetation fraction images are sensitive to structural changes in the canopy of OTF. In cerrado grassland (CG) the phenology was better characterized by combined soil and vegetation fractions. Soybean (SB) areas were characterized by the highest ranges in the vegetation and soil fraction images. Vegetation fraction and vegetation indices for the OTF showed a significant positive relationship with EVI but not with Normalized Difference Vegetation Index (NDVI). Significant relationships for vegetation fraction and vegetation indices were also found for the CG and soybean areas. In contrast to vegetation index approaches to monitoring phenology, fraction images provide additional information that allows amore comprehensive exploration of the spectral and structural changes in vegetation formations. © 2011 Taylor & Francis
A comparison of sampling designs for estimating deforestation from Landsat imagery: A case study of the Brazilian Legal Amazon
Three sampling designs - simple random, stratified random, and systematic sampling - are compared on the basis of precision of estimated loss of intact humid tropical forest area in the Brazilian Legal Amazon from 2000 to 2005. MODIS-derived deforestation is used to partition the study area into strata to intensify sampling within forest clearing hotspots. The precision of the estimator of deforestation area for each design is calculated from a population of wall-to-wall PRODES deforestation data available for the study area. Both systematic and stratified sampling yield smaller standard errors than simple random sampling, and the stratified design has smaller standard errors than the systematic design at each sample size evaluated. The results of this case study demonstrate the utility of a stratified design based on MODIS-derived deforestation data to improve precision of the estimated loss of intact forest area as estimated from sampling Landsat imagery
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