Publicações

Computational analysis of electroencephalographic (EEG) signals have shown promising results in detecting brain disorders, such as Alzheimer’s disease (AD). AD is a progressive neurological illness that causes neuron cells degeneration, resulting in cognitive impairment. While there is no cure for AD, early diagnosis is critical to improving the quality of life of affected individuals. Here, we apply six computational time-series analysis methods (wavelet coherence, fractal dimension, quadratic entropy, wavelet energy, quantile graphs and visibility graphs) to EEG records from 160 AD patients and 24 healthy controls. Results from raw and wavelet-filtered (alpha, beta, theta and delta bands) EEG signals show that some of the time-series analysis methods tested here, such as wavelet coherence and quantile graphs, can robustly discriminate between AD patients from elderly healthy subjects. They represent a promising non-invasive and low-cost approach to the AD detection in elderly patients.

This paper introduces the gtfs2emis model, a bottom-up method available as an R package to estimate emissions of public transport systems. The method uses General Transit Feed Specification (GTFS) data, a standard format for public transport data widely adopted worldwide, which makes the method easily applicable to cities with limited data. The model requires a GTFS feed of a given transport system and a table with general characteristics of the vehicle fleet profile. The package can estimate over 16 pollutants and energy consumption based on emission factor models from Europe, the United States, and Brazil. It also includes functions to help users examine how emissions are distributed across space, at different times of the day, and by types of vehicles. This paper presents a reproducible example of the city of S ao Paulo (Brazil) to demonstrate the gtfs2emis package and to discuss the potential applications and limitations of the proposed model.

over the past few decades, a significant amount of agricultural land has been lost due to soil degradation/desertification. in addition, the increasing frequency of extreme events, such as intense droughts and forest fires, has negatively impacted various ecosystem services. two of the main brazilian biomes-the cerrado and the caatinga-have been affected by increased rainfall variability, leading to desertification, increased fire frequency, and, consequently, rising concerns regarding the water and food security of the local population. in this study, we develop a methodology to assess these impacts using a socio-environmental vulnerability index (sevi) that combines physical, environmental, and socio-economic indicators related to exposure, sensitivity, and adaptation, as well as including socio-environmental feedback. the developed sevi is then applied to the sao francisco and parnaiba river basins. the proposed index is based on the medalus methodology and is adapted to include multiple biological, physical, and socio-economic indicators, allowing for the discrimination of areas characterized by different levels of vulnerability. we also analyze the effectiveness of governmental policies, such as the creation of conservation areas and the rural registration of properties, in reducing vulnerability. the sevi analysis highlights that adaptive capacity is the main constraint for reducing socio-environmental vulnerability in the parnaiba basin, while exposure and sensitivity are the greater challenges in the sao francisco basin. the results of this study are crucial for the prioritization of recovery actions in degraded areas.

The joint effects of climate change and landscape fragmentation to the genetic viability of isolated populations has barely been addressed for the Atlantic Forest fauna. Therefore, this work explored the potential habitat suitability for the southern muriqui (Brachyteles arachnoides), by modeling climate change, landscape fragmentation, and genetic diversity loss of the species. Maxent was used to model its potential distribution in 2050, with two climate change scenarios. A land use and land cover change model was applied to describe current and future forest fragmentation patterns, and a Population and Habitat Viability Analysis (PHVA) was used to describe the retention of genetic diversity of the southern muriqui. Although PHVA modeling provided a low risk of extinction of the southern muriqui, climate change and fragmentation could result in the loss of >65% of the suitable forest patches, and reduce the habitat suitability to only 11% of the potential distribution area, which could lead to future genetic diversity loss and decreased capacity of self-sustained populations. In both climate change scenarios, the suitable areas for the southern muriqui in Paraná and Rio de Janeiro states will decrease more drastically. Areas where the primate occurs in the interior of São Paulo and Rio de Janeiro states will disappear or be climatically disconnected from the core potential habitat. Alike preventing further deforestation, Atlantic Forest restoration actions are needed to connect the viable populations for compensating the projected land use and climate change impacts to the long term persistence of the southern muriqui.

The southeastern Amazon has recently been shown to be a net carbon source, which is partly caused by drying conditions. Drying depends on a number of factors, one of which is the land cover at the locations where the moisture has originated as evaporation. Here we assess for the first time the origins of the moisture that precipitates in the Amazon carbon source region, using output from a Lagrangian atmospheric moisture tracking model. We relate vegetation productivity in the Amazon carbon source region to precipitation patterns and derive land-cover data at the moisture origins of these areas, allowing us to estimate how the carbon cycle and hydrological cycle are linked in this critical part of the Amazon. We find that, annually, 13% of the precipitation in the Amazon carbon source region has evaporated from that same area, which is half of its land-derived moisture. We further find a moisture-recycling-mediated increase in gross primary productivity of roughly 41 Mg carbon km(-2) yr(-1) within the Amazon carbon source region if it is fully forested compared to any other land cover. Our results indicate that the parts of the Amazon forest that are already a net carbon source, still help sustain their own biomass production. Although the most degraded parts of the Amazon depend mostly on oceanic input of moisture, further degradation of this region would amplify carbon losses to the atmosphere.

The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020-2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities.

The terrestrial water cycle links the soil and atmosphere moisture reservoirs through four fluxes: precipitation, evaporation, runoff, and atmospheric moisture convergence (net import of water vapor to balance runoff). Each of these processes is essential for sustaining human and ecosystem well-being. Predicting how the water cycle responds to changes in vegetation cover remains a challenge. Recently, changes in plant transpiration across the Amazon basin were shown to be associated disproportionately with changes in rainfall, suggesting that even small declines in transpiration (e.g., from deforestation) would lead to much larger declines in rainfall. Here, constraining these findings by the law of mass conservation, we show that in a sufficiently wet atmosphere, forest transpiration can control atmospheric moisture convergence such that increased transpiration enhances atmospheric moisture import and results in water yield. Conversely, in a sufficiently dry atmosphere increased transpiration reduces atmospheric moisture convergence and water yield. This previously unrecognized dichotomy can explain the otherwise mixed observations of how water yield responds to re-greening, as we illustrate with examples from China’s Loess Plateau. Our analysis indicates that any additional precipitation recycling due to additional vegetation increases precipitation but decreases local water yield and steady-state runoff. Therefore, in the drier regions/periods and early stages of ecological restoration, the role of vegetation can be confined to precipitation recycling, while once a wetter stage is achieved, additional vegetation enhances atmospheric moisture convergence and water yield. Recent analyses indicate that the latter regime dominates the global response of the terrestrial water cycle to re-greening. Evaluating the transition between regimes, and recognizing the potential of vegetation for enhancing moisture convergence, are crucial for characterizing the consequences of deforestation as well as for motivating and guiding ecological restoration.

Subpolar coastal waters are key hotspots in the global carbon cycle. However, the small-scale distribution of partial pressure of carbon dioxide (pCO2) in these environments and the physical and biological controls underlying this variability are still poorly understood. Here, we examine simultaneous high-resolution spatial measurements of wind speed and pCO(2), temperature, salinity, and in-vivo chlorophyll-a fluorescence (chl-a fluo, a proxy of phytoplankton biomass) in surface waters that were obtained during an oceanographic survey in the Argentinian Beagle Channel (subantarctic Atlantic Patagonian) in early fall 2017. The 240 km study transect (centered at 55 degrees S – 67 degrees W) was divided into two zones: (A1) The Beagle Channel innermost portion, semi-enclosed and subject to strong continental influence and (A2) its eastern outlet towards the open Southwest Atlantic. Discrete seawater samples were also collected for apparent oxygen utilization (AOU), nutrients and pH measurements. High-resolution spatial measurements revealed the persistence of pCO(2) below atmospheric equilibrium, increasing in median (interquartile range 25-75%) from 314 mu atm in the inner Beagle Channel (A1) to 348 mu atm towards the adjacent open sea (A2). A decrease in atmospheric CO2 sequestration was associated with an increase in water temperature from 9.5 degrees C to 10.7 degrees C, salinity from 30.8 to 32.5, and chl-a fluo from 2.24 to 2.91 mg m(-3) along the coastal-offshore gradient. Low AOU and nutrient levels were found in regions inside the channel. Indeed, the relationships between CO2 and temperature or salinity were significantly different from those expected from the theoretical solubility effect, indicating a dominance of metabolic over physicochemical controls on this gas. Moreover, physical factors such as vertical stratification contributed to the variable surface pCO2 values. These findings reveal the existence of short-scale spatial variability of CO2 in the Beagle Channel, improving our understanding of the multiple controls on atmospheric carbon sequestration in extensive subpolar continental shelves.

Green crimes are violations of environmental laws that aim to protect human well-being, natural resources, and ecosystems. Brazil has recorded an increase in green crimes in recent years. In this study, we used Spatial Durbin and other regression models to analyze the relationship between land use and green crime. We test whether there is a positive association between green crimes and the following land uses: urban edge areas, rural edge areas, and mixed urban uses. The results show that green crimes are spatially related to areas of high contact and exposure between human activity and the natural environment (urban and rural mixed uses), but that human presence by itself (presence of industrial activity) is not particularly associated with the occurrence of green crimes. These findings can serve to design and deploy data-driven policies and policing of green crimes.

Global air temperature increase has caused changes in the global climate such as droughts, floods and severe events. Land cover shifts and the increase in greenhouse gas emissions can intensify these impacts. Therefore, the application of Specific Warming Level 2 (SWL2) technique has been considered to evaluate the global warming issue in various climate scales, which may induce different responses in the climate system. The objective of this study is to evaluate the impacts of a doubling of current atmospheric CO2 concentrations as well as the influence of deforestation of the Amazon Forest on the climate of South America. In this study, the CPTEC-BAM1.2 global model was used to simulate these processes. The first scenario of simulations considered doubled atmospheric CO2 concentration (2XCO2 = 776 ppm) and the second scenario is the total conversion of the Amazon Forest to pasture (DEF). In the third scenario both CO2 and deforestation are considered simultaneously (2XCO2 + DEF). A control simulation considers the natural Amazon Forest shape and a steady CO2 concentration of 388 ppm. Results suggest that the temperature increased in all scenarios, the highest increment in the 2XCO2 + DEF experiment (5.4°C in 2XCO2 + DEF, 5.1°C in DEF and 3.2°C in 2XCO2). The model simulated drastic negative rainfall anomalies in each of three scenarios (2XCO2 + DEF: −2.1 mm day−1, 2XCO2: −1.3 mm day−1 and DEF: −0.9 mm day−1). Besides less precipitation and evapotranspiration, shifts in moisture transport were identified in each of the three scenarios. The effect of doubled atmospheric CO2 produces results similar to deforestation for hydrological water budget changes, and total pasture conversion may intensify such changes.

Over 150 species of earthworms are known from the Brazilian Atlantic rainforest, but many more are expected to live in this megadiverse biome. In the present study, we evaluated earthworm species occurrence and diversity in native and reforested areas in four National Forests in three Brazilian states: Três Barras National Forest (Santa Catarina), Irati and Piraí do Sul National Forests (Paraná) and Capão Bonito National Forest (São Paulo) using formalin and hand sorting methods. A total of 13 species were found, five exotic and eight natives (of which four were new, undescribed species), belonging to six genera and five families (Rhinodrilidae, Glossoscolecidae, Ocnerodrilidae, Benhamiidae, Megascolecidae). In general, higher number of earthworms were collected in Araucaria plantations, except in Capão Bonito where Pinus sp. plantations had higher abundance. Hand sorting also collected more species in all forests, so this should be the preferred sampling method to evaluate earthworm communities. Formalin extraction was efficient only for epi-endogeic earthworms, most of them exotic species. Exotic pine species plantations tend to reduce species richness and abundance, compared with native forests and Araucaria plantations, and substitution of native vegetation for pine plantations should consider potential negative effects on soil animal populations.