Publicações

This paper presents the integration details of an operational Atmospheric Electric Field Mill Sensor (EFM) Network for standardized and continuous operation in the region of Saõ José dos Campos, State of Saõ Paulo, Brazil, in order to collect and transmit real time data for studies of atmospheric electric field and support the development of a Lightning Warning System (LWS). Data collection equipments, including EFM sensors from different manufacturers, datalogger, telecommunication by 3G cellular modem and solar power energy subsystems and software were integrated. A set of graphs obtained by interpolating real time data collected by the integrated EFM network combined with lightning location data detected by the Brazilian Lightning Detection System (BrasilDAT) is also presented.

Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

At the nexus of watersheds, land, coastal areas, oceans, and human settlements, river delta regions pose specific challenges to environmental governance and sustainability. Using the Amazon Estuary-Delta region (AD) as our focus, we reflect on the challenges created by the high degree of functional interdependencies shaping socialecological dynamics of delta regions. The article introduces the initial design of a conceptual framework to analyze delta regions as coupled socialecological systems (SES). The first part of the framework is used to define a delta SES according to a problem and/or collective action dilemma. Five components can be used to define a delta SES: socialeconomic systems, governance systems, ecosystems-resource systems, topographic-hydrological systems, and oceanic-climate systems. These components are used in association with six types of telecoupling conditions: socio-demographic, economic, governance, ecological, material, and climatic-hydrological. The second part of the framework presents a strategy for the analysis of collective action problems in delta regions, from sub-delta/local to delta to basin levels. This framework is intended to support both case studies and comparative analysis. The article provides illustrative applications of the framework to the AD. First, we apply the framework to define and characterize the AD as coupled SES. We then utilize the framework to diagnose an example of collective action problem related to the impacts of urban growth, and urban and industrial pollution on small-scale fishing resources. We argue that the functional interdependencies characteristic of delta regions require new approaches to understand, diagnose, and evaluate the current and future impacts of socialecological changes and potential solutions to the sustainability dilemmas of delta regions.

The analysis of changes in species composition and vegetation structure in chronosequences improves knowledge on the regeneration patterns following land abandonment in the Amazon. Here, the objective was to perform floristic-structural analysis in mature forests (with/without timber exploitation) and secondary successions (initial, intermediate and advanced vegetation regrowth) in the Tapajós region. The regrowth age and plot locations were determined using Landsat-5/Thematic Mapper images (1984-2012). For floristic analysis, we determined the sample sufficiency and the Shannon-Weaver (H’), Pielou evenness (J), Value of Importance (VI) and Fisher’s alpha (α) indices. We applied the Non-metric Multidimensional Scaling (NMDS) for similarity ordination. For structural analysis, the diameter at the breast height (DBH), total tree height (Ht), basal area (BA) and the aboveground biomass (AGB) were obtained. We inspected the differences in floristic-structural attributes using Tukey and Kolmogorov-Smirnov tests. The results showed an increase in the H’, J and α indices from initial regrowth to mature forests of the order of 47%, 33% and 91%, respectively. The advanced regrowth had more species in common with the intermediate stage than with the mature forest. Statistically significant differences between initial and intermediate stages (p<0.05) were observed for DBH, BA and Ht. The recovery of carbon stocks showed an AGB variation from 14.97 t ha-1 (initial regrowth) to 321.47 t ha-1 (mature forests). In addition to AGB, Ht was also important to discriminate the typologies.

Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarem tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

In this work, we analyze the expansion of forestry activities with Eucalyptus in the Paraiba do Sul basin, region located in Sao Paulo, Brazil, from 1986 to 2010. In this region is situated the most important and largest extension of reminiscent of Mata Atlântica Biome reminiscent. This biome has been one the most exploited Brazilian biome since 1500, when Brazilian colonization begun. To achieve this goal, we use the GIS “SPRING” and images from Landsat 5 Satellite, TM sensor from 1986, 1990, 1995, 2000, 2005 and 2010, distributed by the Brazilian National Institute for Space Research – INPE. The non-supervised-classification was applied to images in order to produce land use and land cover maps. After that, we intersect each classification for each date with the precedent date, so we can analyze the paths of each land use change, focusing forestry expansion in native’s Mata Atlântica areas. The results show that eucalyptus plantations in the region have expanded mostly over fragments of Mata Atlântica. About 99.389 hectares of Mata Atlântica were transformed into forestry in 25 years, an average rate of 4000 ha per year. Clear-cut was largest between 1990 and 1995, when 22810 hectares of rain forest were cut, and between 1995 and 2000, when 21430 hectares were cut.

In this study, we investigated the different responses of Spondias tuberosa (umbu) trees, which grow in two different ecological life zones in northeast Brazil: tropical wet and tropical arid ecosystems. We evaluated the responses of plants grown under humid and dry conditions by measuring the photosynthesis, water status, fluorescence parameters, carbon isotopes and antioxidant system activity. The higher net photosynthesis values were recorded contemporaneously with the lower VPD values. The highest internal-to-ambient CO2 concentration and the absence of typical changes in the fluorescence parameters suggested an onset of a nonstomatal limitation in the photosynthesis. Our results showed that umbu plants can adjust their antioxidant activity during the dry season as a defensive strategy against the deleterious effects of water stress. This evidence is supported by the observed modifications in the pigment concentrations, increased accumulation of hydrogen peroxide and malondialdehyde, high levels of electrolyte leakage, increased antioxidant activity, and decreased carbon isotope discrimination in the umbu trees during the dry season. Supported by multivariate analysis of variance, significantly effect of interaction between categorical months of collect and location predicts a strong dry season effect on our dataset. Taken together, our data show that umbu trees grown in a wet tropical environment are more susceptible to drought, as compared with their tropical arid counterparts.

The radiative transfer model BRASIL-SR is used by Brazilian Institute for Space Research for the assessment of the solar irradiation in Brazil. The model parameterizes the influence of aerosols in the solar radiation transmittance using climate averages of horizontal visibility, which does not represent the actual atmospheric condition in Brazil, especially during dry season. In clear sky conditions, aerosols are a major source of bias in solar radiation models. Their concentration have large spatial and temporal variability particularly in the Brazilian Midwestern region from April until October, due to forest fires, and in Southeastern region due to pollution from megacities. In this study, meteorological data from METAR comprising the years of 2006, 2007 and 2008 were analyzed to evaluate the seasonal variability of the horizontal visibility in Brazil to better represent the influence of aerosols on the model estimations of surface solar irradiation. New horizontal visibility values was generated to each month simulated, to provide input data to the BRASIL-SR model and site specific ground data were used to validate the model estimates. The global, direct beam and diffuse solar irradiation estimates obtained by making use of the new horizontal visibility data presented an overall lower BIAS and RMSE deviations.

Eleven years of lightning data from the Brazilian Integrated National Lightning Detection Network were used to analyze the effects of the urban heat island (UHI) of Sao Paulo on lightning activity, extending the investigation of previous works. Cloud-To-ground lightning data were analyzed in both spatial and temporal perspectives, using different approaches: flash density, flash rate, thunderstorm hours (TH), and the cell initiation technique (CIT), which aims to identify the onset of thunderstorms. Land surface temperature (LST) from MODIS (Moderate Resolution Imaging Spectroradiometer) was used to analyze the UHI evolution over the years. MODIS data were validated using ground stations, distributed within the urban area. Different time intervals (seasonal and intraday) were used in an attempt to separate local convective systems from synoptic-scale events. The results indicate significant effects of the UHI (using LST) on THs and CIT. The CIT showed a nearly ring pattern, especially during the afternoon (14:00-18:00 LT) of summer months, reinforcing temperature contrast as a condition for storm initiation. The results also suggest an amplification of the UHI effects on thunderstorm activity by local factors (sea and country breeze, synoptic events, and terrain). Higher flash rates were also observed throughout the urban region, which influences the lightning density. Temporal analysis indicates that minimum temperature and lightning activity increase in wintertime. In summary, the results agree with previous studies about the UHI and indicate its importance on lightning occurrence, especially by increasing the temperature contrast and the instability in these regions.

Following an intense occupation process that was initiated in the 1960s, deforestation rates in the Brazilian Amazon have decreased significantly since 2004, stabilizing around 6000 km2 yr-1 in the last 5 years. A convergence of conditions contributed to this, including the creation of protected areas, the use of effective monitoring systems, and credit restriction mechanisms. Nevertheless, other threats remain, including the rapidly expanding global markets for agricultural commodities, large-scale transportation and energy infrastructure projects, and weak institutions. We propose three updated qualitative and quantitative land-use scenarios for the Brazilian Amazon, including a normative ‘Sustainability’ scenario in which we envision major socio-economic, institutional, and environmental achievements in the region. We developed an innovative spatially explicit modelling approach capable of representing alternative pathways of the clear-cut deforestation, secondary vegetation dynamics, and the old-growth forest degradation. We use the computational models to estimate net deforestation-driven carbon emissions for the different scenarios. The region would become a sink of carbon after 2020 in a scenario of residual deforestation (~1000 km2 yr-1) and a change in the current dynamics of the secondary vegetation – in a forest transition scenario. However, our results also show that the continuation of the current situation of relatively low deforestation rates and short life cycle of the secondary vegetation would maintain the region as a source of CO2 – even if a large portion of the deforested area is covered by secondary vegetation. In relation to the old-growth forest degradation process, we estimated average gross emission corresponding to 47% of the clear-cut deforestation from 2007 to 2013 (using the DEGRAD system data), although the aggregate effects of the postdisturbance regeneration can partially offset these emissions. Both processes (secondary vegetation and forest degradation) need to be better understood as they potentially will play a decisive role in the future regional carbon balance.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga.

Anthropogenic haze, caused at least in parts by forest and agricultural land clearing fires in Sumatra (Indonesia), is occasionally causing air quality issues in Singapore, located 150-300 km east of the majority of these “hot spots”. The resulting air pollution partially blocks sunlight from reaching the ground, and consequently affects the electric power generation of solar photovoltaic (PV) systems in Singapore. In this work, a methodology is presented to estimate the haze-induced reduction of the light intensity reaching PV panels and the corresponding loss in the electric energy yield. An assessment of a major haze event in June 2013 is the basis for the loss analysis, which takes into account data filtering techniques in order to isolate cloudless conditions for inter-comparison between clear and hazy days. Data from previous years in non-hazy conditions serve as baseline for the determination of the clear sky conditions for Singapore. The novel method is further applied to investigate the power output of ten PV systems in Singapore during the June 2013 haze event. It is found that poor air quality levels during this event caused yield losses of PV systems in Singapore in the range of 15-25%.