Publicações

Poucas ferramentas de análise de sustentabilidade têm sido aplicadas na Amazônia, em particular no Estado do Pará. Os municípios paraenses inseridos no Polo Biodiesel, com destaque para Moju, vivem uma fase de intensos investimentos agroindustriais com vistas à produção de palma de óleo (óleo de dendê), e de firme inserção da agricultura familiar nesse processo. Nesse contexto, surgem questionamentos acerca da capacidade desse município em receber uma política pública como essa, que se configura em novas dinâmicas territoriais e que requer uma forte capacidade de gestão ambiental municipal para direcionar as atividades produtivas e sociais em direção à sustentabilidade. Este trabalho visa avaliar a dimensão institucional da sustentabilidade em Moju, verificando as condições apresentadas pelo município quanto à gestão ambiental. Utilizaram-se para essa análise o Barômetro da Sustentabilidade (BS), considerando cinco temas (estrutura institucional, estrutura operacional, termo de ajuste de conduta, cadastro ambiental rural e regularização fundiária) e 33 indicadores, e também entrevistas com gestores e empreendedores locais. Os resultados mostram que esse município está habilitado para exercer a gestão ambiental plena, mas também que sua estrutura operacional ainda é deficiente, o que certamente trará problemas para a condução de tal política.

A 10-year study of lightning fatalities in Brazil is presented. It is the most complete study undertaken in South America. The study indicates the death rates in the country sorted by season, state, city, type of region, age, gender and circumstances. Ten years of data were collected from the Federal Civil Defense Agency, the Ministry of Health and the media press. The circumstances of lightning fatalities in Brazil were compared with other countries that have this information available. It also includes an analysis of the differences involved in lightning deaths in each region of Brazil. The results suggest that specific actions should be adopted in terms of lightning protection to minimize risks. Finally, this study provides useful information in order to identify the most important lightning safety rules for the country.

This study presents a methodology for susceptibility mapping of shallow landslides just from data and software from the public domain. The study was conducted in a mountainous region located on the southeastern Brazilian coast, in the state of São Paulo. The proposal is that the methodology can be replicated in a practical and reliable way in several other municipalities that do not have such mappings and that often suffer from landslide-related disasters. The susceptibility mapping was generated based on the following maps: geological, soils, slope, horizontal and vertical curvatures, and land use. The thematic classes of these maps were weighted according to technical and scientific criteria related to the triggering of landslides, and were crossed by the fuzzy gamma technique. The mapping was compared with the risk sector survey made by the Brazilian Geological Survey (CPRM), which is the official database used by municipalities and civil defense in risk management. The results showed positive correlations, so that the critical risk sectors had higher proportions for the more susceptible classes. To compare the approach with other studies using landslide-scar maps, correlated indices were evaluated, which also showed satisfactory results, thus indicating that the methodology presented is appropriate for risk assessment in urban areas.

Latin America encompasses a dizzying array of ecosystems and socioeconomic models, and the region will be highly vulnerable to the projected impacts of climate change in the next century. At the same time, Latin America can significantly contribute to the mitigation of greenhouse gases (GHG) emissions within a sustainable development framework. Land use conversion with associated biomass burning, agriculture with N fertilizers and animal waste are the main anthropogenic sources of nitrous oxide (N2O) emissions in the region, and have increased markedly in the last decades. Effective sustainable management for the mitigation of N2O emissions requires the proper evaluation of all sources, many of which are still roughly estimated or unknown, testing alternatives to reduce primary sources, and technological innovation for higher resource-use efficiency within the farm. Current barriers might be overcome through policies that support sustainable practices that reduce negative environmental impacts and simultaneously maintaining ecosystem function and services.

The climate in the Caatinga, especially precipitation, influences the pattern of spatial and temporal distribution of the vegetation that in turn influences the regional climate from the feedback mechanism of energy flows, water and momentum. This climate-vegetation interaction in the Caatinga is differentiated depending on the type of climatic pattern in the region. The objective of this work is to identify the main phenological features of the annual growth cycles of vegetation and characteristics of the seasonal rainfall in five climatic regions in the Caatinga biome. We use time series (2001-2008) of vegetation indices such as NDVI and LSWI, and precipitation that was derived of TRMM satellite data and surface station data. The results indicate that precipitation variability in the rainy season influences directly the variability of vegetation growing cycles. That influence is not linear but adjusted to a logarithmic function being the best fit with the index LSWI (r2 = 0.67) than with NDVI (r2 = 0.54). The influence of precipitation on vegetation, using phenological metrics such as start, end, peak and length of the vegetation growing cycles showed greater lag in climatic regions with higher precipitation in the Caatinga region.

Density maps are one of the most common and powerful lightning data applications, and they are more efficient the more detailed they are. When working with CG lightning data from lightning location systems, some aspects must be included in the analysis to overcome network performance variations. Two parameters are typically used to evaluate system performance: detection efficiency (DE) and location accuracy (LA). For the Brazilian National Integrated Lightning Detection Network, DE is typically evaluated by models, and LA is analyzed through confidence ellipses. This paper presents climatological analysis of lightning activity, including the most recent relative DE model developed in Brazil, as well as an adapted kernel smoothing method based on confidence ellipses [called Gaussian kernel based on confidence ellipses (GKBCE)] as approaches to minimize and/or include the spatial variation of the systems performance in the analysis. The maps are produced over the central-south portion of Brazil (mainly along ITAIPU power transmission lines), using 11 years of data available from the network (from January 1999 to December 2009). The model increased density by ~20% over the entire region, without making considerable changes to the spatial pattern. The GKBCE seems to work well in smoothing, obtaining better results than the standard cell count (quadrat) method, by working independently of the grid size (allowing the creation of high-resolution maps), and by including location errors in the analysis. The use of these procedures might result in more detailed maps and more suitable results when analyzing lightning data.

Intraseasonal rainfall variability of the South American monsoon system is characterized by a pronounced dipole between southeastern South America and southeastern Brazil. Here we analyze the dynamical properties of extreme rainfall events associated with this dipole by combining a nonlinear synchronization measure with complex networks. We make the following main observations: (i) Our approach reveals the dominant synchronization pathways of extreme events for the two dipole phases, (ii) while extreme rainfall synchronization in the tropics is directly driven by the trade winds and their deflection by the Andes mountains, extreme rainfall propagation in the subtropics is mainly dictated by frontal systems, and (iii) the well-known rainfall dipole is, in fact, only the most prominent mode of an oscillatory pattern that extends over the entire continent. This provides further evidence that the influence of Rossby waves, which cause frontal systems over South America and impact large-scale circulation patterns, extends beyond the equator. Key PointsComplex networks substitute EOFs for spatial analysis of extreme rainfallReveal drivers of extreme rainfall related to South American rainfall dipoleExtreme events controlled by Rossby oscillation extending over the entire continent.

Despite increased intellectual and conceptual consideration of the linkages between ecosystem service (ES) provisions and poverty alleviation (PA) globally, there has been limited analysis of how these paradigms are used and framed in the regional context of policy-making. In this paper, we address this question by eliciting perspectives on the historical evolution of policies addressing the environment and poverty nexus in the Brazilian Amazon. Our analysis is twofold. First, through an analysis of policy context, we explore how multilateral and international programs have influenced and helped shape national and regional policy-making in the Amazon. Second, through our analysis of policy content, we provide an in-depth discussion of key ES and/or PA policies implemented in the Amazon. Furthermore, we analyze the operationalization of the policy, describe management options, and highlight their impacts on ES and PA. Our results show dichotomies between environmental programs and their social effectiveness, and between environmental and developmental agendas. More recently, however, some attempts have been made at delivering ES protection and PA jointly in policy-making. In conclusion, we provide a framework for policy analysis that can be applied to other tropical countries in the world. If Brazil is to keep its leading role in addressing the challenges of maintaining ecosystem service provision, while alleviating poverty in the Amazon, it must learn from its own experiences.

As land use change (LUC), including deforestation, is a patchy process, estimating the impact of LUC on carbon emissions requires spatially accurate underlying data on biomass distribution and change. The methods currently adopted to estimate the spatial variation of above- and below-ground biomass in tropical forests, in particular the Brazilian Amazon, are usually based on remote sensing analyses coupled with field datasets, which tend to be relatively scarce and often limited in their spatial distribution. There are notable differences among the resulting biomass maps found in the literature. These differences subsequently result in relatively high uncertainties in the carbon emissions calculated from land use change, and have a larger impact when biomass maps are coded into biomass classes referring to specific ranges of biomass values. In this paper we analyze the differences among recently-published biomass maps of the Amazon region, including the official information used by the Brazilian government for its communication to the United Nation Framework on Climate Change Convention of the United Nations. The estimated average pre-deforestation biomass in the four maps, for the areas of the Amazon region that had been deforested during the 19902009 period, varied from 205 ± 32 Mg ha−1 during 19901999, to 216 ± 31 Mg ha−1 during 20002009. The biomass values of the deforested areas in 2011 were between 7 and 24 % higher than for the average deforested areas during 19901999, suggesting that although there was variation in the mean value, deforestation was tending to occur in increasingly carbon-dense areas, with consequences for carbon emissions. To summarize, our key findings were: (i) the current maps of Amazonian biomass show substantial variation in both total biomass and its spatial distribution; (ii) carbon emissions estimates from deforestation are highly dependent on the spatial distribution of biomass as determined by any single biomass map, and on the deforestation process itself; (iii) future deforestation in the Brazilian Amazon is likely to affect forests with higher biomass than those deforested in the past, resulting in smaller reductions in carbon dioxide emissions than expected purely from the recent reductions in deforestation rates; and (iv) the current official estimate of carbon emissions from Amazonian deforestation is probably overestimated, because the recent loss of higher-biomass forests has not been taken into account.

Ionospheric scintillation refers to amplitude and phase fluctuations in radio signals due to electron density irregularities associated to structures named ionospheric plasma bubbles. The phenomenon is more pronounced around the magnetic equator where, after sunset, plasma bubbles of varying sizes and density depletions are generated by plasma instability mechanisms. The bubble depletions are aligned along Earth’s magnetic field lines, and they develop vertically upward over the magnetic equator so that their extremities extend in latitude to north and south of the dip equator. Over Brazil, developing bubbles can extend to the southern peak of the Equatorial Ionization Anomaly, where high levels of ionospheric scintillation are common. Scintillation may seriously affect satellite navigation systems, such as the Global Navigation Satellite Systems. However, its effects may be mitigated by using a predictive model derived from a collection of extended databases on scintillation and its associated variables. This work proposes the use of a classification and regression decision tree to perform a study on the correlation between the occurrence of scintillation at the magnetic equator and that at the southern peak of the equatorial anomaly. Due to limited size of the original database, a novel resampling heuristic was applied to generate new training instances from the original ones in order to improve the accuracy of the decision tree. The correlation analysis presented in this work may serve as a starting point for the eventual development of a predictive model suitable for operational use. Key Points Analyzes correlation between scintillation occurrence at different stations Includes the selection of attributes for the proposed correlation analysis Employs decision tree to analyze the correlation of scintillation occurrences.

Evapotranspiration (E) in the Amazon connects forest function and regional climate via its role in pre-cipitation recycling However, the mechanisms regulating water supply to vegetation and its demand forwater remain poorly understood, especially during periods of seasonal water deficits In this study, we efficiencyaddress two main questions: First, how do mechanisms of water supply (indicated by rooting depth andgroundwater) and vegetation water demand (indicated by stomatal conductance and intrinsic water useefficiency) control evapotranspiration (E) along broad gradients of climate and vegetation from equatorialAmazonia to Cerrado, and second, how do these inferred mechanisms of supply and demand compareto those employed by a suite of ecosystem models? We used a network of eddy covariance towers inBrazil coupled with ancillary measurements to address these questions With respect to the magnitudeand seasonality of E, models have much improved in equatorial tropical forests by eliminating most dryseason water limitation, diverge in performance in transitional forests where seasonal water deficits aregreater, and mostly capture the observed seasonal depressions in E at Cerrado However, many mod-els depended universally on either deep roots or groundwater to mitigate dry season water deficits, therelative importance of which we found does not vary as a simple function of climate or vegetation In addi-tion, canopy stomatal conductance (gs) regulates dry season vegetation demand for water at all exceptthe wettest sites even as the seasonal cycle of E follows that of net radiation In contrast, some models sim-ulated no seasonality in gs, even while matching the observed seasonal cycle of E. We suggest that canopydynamics mediated by leaf phenology may play a significant role in such seasonality, a process poorlyrepresented in models Model bias in gsand E, in turn, was related to biases arising from the simulatedlight response (gross primary productivity, GPP) or the intrinsic water use efficiency of photosynthesis(iWUE). We identified deficiencies in models which would not otherwise be apparent based on a simplecomparison of simulated and observed rates of E. While some deficiencies can be remedied by parame-ter tuning, in most models they highlight the need for continued process development of belowgroundhydrology and in particular, the biological processes of root dynamics and leaf phenology, which via theircontrols on E, mediate vegetation-climate feedbacks in the tropics.

In their seminal lightning studies using streak cameras, Schonland et al. (1938) identified four negative stepped leader events that they term β2, a rather rare variant of the type β leader, and in it, the second and slower stage of the leader is associated with the appearance of one or more fast dart streamers, which travel rapidly down from the cloud along the previously formed track and cease when they have caught up with the slower leader tip. Seven negative downward leaders that agreed with the description given by Schonland et al. for type β2 were recorded in Tucson, Arizona, USA, and in São José dos Campos, São Paulo, Brazil. All cases were recorded by a high-speed camera operating at 4000 frames per second, and electric field changes were measured for three of them. Their dart streamers had speeds between 106 and 107 m s−1, compatible with previous observations of recoil leaders (RLs). Also, during the development of the three cases with correlated electric field changes, it was possible to identify sequences of microsecond-scale pulses preceding the propagation of a dart streamer in the channel. It is proposed that the luminous process that occurs during the development of a type β2 stepped leader is the visible manifestation of one or more RLs that begin inside the cloud and connect to the in-cloud, positive portion of the bipolar, bidirectional leader, and then travel downward to the lower end of the negative stepped leader path.