Forecasting Amazon Rain-Forest Deforestation Using a Hybrid Machine Learning Model

The present work aims to carry out an analysis of the Amazon rain-forest deforestation, which can be analyzed from actual data and predicted by means of artificial intelligence algorithms. A hybrid machine learning model was implemented, using a dataset consisting of 760 Brazilian Amazon municipalities, with static data, namely geographical, forest, and watershed, among others, together with a time series data of annual deforestation area for the last 20 years (1999–2019). The designed learning model combines dense neural networks for the static variables and a recurrent Long Short Term Memory neural network for the temporal data. Many iterations were performed on augmented data, testing different configurations of the regression model, for adjusting the model hyper-parameters, and generating a battery of tests to obtain the optimal model, achieving a R-squared score of 87.82%. The final regression model predicts the increase in annual deforestation area (square kilometers), for a decade, from 2020 to 2030, predicting that deforestation will reach 1 million square kilometers by 2030, accounting for around 15% compared with the present 1%, of the between 5.5 and 6.7 millions of square kilometers of the rain-forest. The obtained results will help to understand the impact of man’s footprint on the Amazon rain-forest.

A Model-Based and Goal-Oriented Approach for the Conceptual Design of Smart Grid Services

A solid demand to integrate energy consumption and co-generation emerged worldwide, motivated, on one hand, by the need to diversify and enhance energy supply, and, one the other hand, by the pressure to attend to the requirements of a heterogeneous class of users. The coupling between energy service provision and final users also includes balancing user needs, eliminating excesses, and optimizing energy supply while avoiding blackouts. Another motivation is the challenge of having sustainable sources and many adapted to the user ecosystem. Altogether, these motivations lead to more abstract design approaches to co-generation-distributed systems, such as those based on goal-oriented requirements used to model smart grids. This work considers the available design practices and its difficulties in proposing a new method capable of producing a flexible requirement model that could serve for design and maintenance purposes. We suggest coupling the approach based on goal-oriented requirements with model-based engineering to support such a model. The expected result is a sound and flexible requirements model, including a model for the interaction with the final user (now being considered a producer and consumer simultaneously). A case study is presented, wherein a small energy service system in an isolated community in the Amazon rain forest was designed.

Extracts of Amazonian Fungi With Larvicidal Activities Against Aedes aegypti

The global increase in diseases transmitted by the vector Aedes aegypti, new and re-emerging, underscores the need for alternative and more effective methods of controlling mosquitoes. Our aim was to identify fungal strains from the Amazon rain forest that produce metabolites with larvicidal activity against Aedes aegypti. Thirty-six fungal strains belonging to 23 different genera of fungi, isolated from water samples collected in the state of Amazonas, Brazil were cultivated. The liquid medium was separated from the mycelium by filtration. Medium fractions were extracted with ethyl acetate and isopropanol 9:1 volume:volume, and the mycelia with ethyl acetate and methanol 1:1. The extracts were vacuum dried and the larvicidal activity was evaluated in selective bioassays containing 500 μg/ml of the dried fungal extracts. Larval mortality was evaluated up to 72 h. None of the mycelium extracts showed larvicidal activity greater than 50% at 72 h. In contrast, 15 culture medium extracts had larvicidal activity equal to or greater than 50% and eight killed more than 90% of the larvae within 72 h. These eight extracts from fungi belonging to seven different genera (Aspergillus, Cladosporium, Trichoderma, Diaporthe, Albifimbria, Emmia, and Sarocladium) were selected for the determination of LC50 and LC90. Albifimbria lateralis (1160) medium extracts presented the lowest LC50 value (0.268 μg/ml) after 24 h exposure. Diaporthe ueckerae (1203) medium extracts presented the lowest value of LC90 (2.928 μg/ml) at 24 h, the lowest values of LC50 (0.108 μg/ml) and LC90 (0.894 μg/ml) at 48 h and also at 72 h (LC50 = 0.062 μg/ml and LC90 = 0.476 μg/ml). Extracts from Al. lateralis (1160) and D. ueckerae (1203) showed potential for developing new, naturally derived products, to be applied in integrated vector management programs against Ae. aegypti.

New Report Puts the Amazon Rain Forest on the Main Stage at COP26

The Science Panel for the Amazon prepares to launch its first report, the most comprehensive document on the rain forest so far.

Lead Isotopes in North American Precipitation record the presence of Saharan Dust

Atmospheric dust is an important mass transfer and nutrient supply process in Earth surface ecosystems. For decades, Saharan Dust has been hypothesized as a supplier of nutrients to the Amazon Rain Forest and Eastern North America. However, isotope studies aimed at detecting Saharan dust in the American sedimentary record have been ambiguous. A large Saharan dust storm emerged off the coast of Africa in June 2020 and extended into southeastern United States. This storm provided a means to evaluate the influence of Saharan dust in North America confirmed by independent satellite and ground observations. Precipitation samples from 17 sites within the National Atmospheric Deposition Program (NADP) were obtained from throughout the southeastern United States prior to, during, and after the arrival of Saharan dust. Precipitation samples were measured for their lead (Pb) isotopic composition, total Pb content, and 210Pb activity using multi-collector inductively coupled plasma mass spectrometry. We measured a significant isotopic shift (approximately 0.7 % in the 208Pb/206Pb relative to the 207Pb/206Pb) in precipitation that peaked in late June 2020 when the dust blanketed the southeastern US. However, the magnitude and short time period of the isotopic shift would make it difficult to detect in sedimentary records.

Bioaerosols in the Amazon rain forest: temporal variations and vertical profiles of Eukarya, Bacteria, and Archaea

The Amazon rain forest plays a major role in global hydrological cycling, and biogenic aerosols are likely to influence the formation of clouds and precipitation. Information about the sources and altitude profiles of primary biological aerosol particles, however, is sparse. We used fluorescence in situ hybridization (FISH), a molecular biological staining technique largely unexplored in aerosol research, to investigate the sources and spatiotemporal distribution of Amazonian bioaerosols on the domain level. We found wet season bioaerosol number concentrations in the range of 1–5 × 105 m−3 accounting for > 70 % of the coarse mode aerosol. Eukaryotic and bacterial particles predominated, with fractions of ∼ 56 % and ∼ 26 % of the intact airborne cells. Archaea occurred at very low concentrations. Vertical profiles exhibit a steep decrease in bioaerosol numbers from the understory to 325 m height on the Amazon Tall Tower Observatory (ATTO), with a stronger decrease in Eukarya compared to Bacteria. Considering earlier investigations, our results can be regarded as representative for near-pristine Amazonian wet season conditions. The observed concentrations and profiles provide new insights into the sources and dispersion of different types of Amazonian bioaerosols as a solid basis for model studies on biosphere–atmosphere interactions such as bioprecipitation cycling.

DEFORESTASI AMAZON PADA ERA BOLSONARO (2019)

This article was written with the aim of knowing the dynamics of deforestation in Brazil, especially the Amazon forest, and to find out the driving factors for deforestation in the Amazon rainforest in 2019 from a critical perspective. The Amazon rain forest is reported to have led to massive deforestation using massive forest burning instruments in 2019, sparking reactions from various international elements. To simplify the analysis in this article, the author uses the concept of captal expansion from David Harvey and to further clarify the problem in this article the author adds the concept of deforestation from William Laurance, the writer uses descriptive analytical research methods and uses secondary data sources. In this article, the authors find various correlations between the interests of the Brazilian government and the interests of multinational companies that lead to encouragement of land clearing in various forests, especially the Amazon, on the pretext of meeting world food demand and efforts to restore Brazilian economic instability as justification.

Chemical Composition and Biological Activities of Essential Oils from Fresh Vismia guianensis (Aubl.) Choisy and Vismia cayennensis (Jacq.) Pers. Leaves

The Vismia Vand. genus encompasses many species indigenous to the Amazon rain forest where they are popularly known as “Lacre” bark and leaves are widely employed by locals to treat dermatophytoses. The aim of this study was to investigate the chemical composition of essential oils (EOs) extracted from the aerial parts of the species Vismia guianensis (Aubl.) Choisy and Vismia cayennensis (Jacq.) Pers. and to assess their antimicrobial activity against the bacteria Staphylococcus aureus Rosenbach 1884 and Escherichia coli (Migula 1895) Castellani and Chalmers 1919 as well as the fungi Candida albicans (C.P. Robin) Berkhout 1923 and Candida parapsilosis (Ashford) Langeron & Talice 1932. The analysis of the chemical composition of the essential oil extracted from V. guianensis leaves (EOVg) indicated 46 components, of which three sesquiterpenes predominated, namely: (E)-caryophyllene (10.40%), α-copaene (29.45%), and (E)-nerolidol (24.06%). As to the essential oil from V. cayennensis leaves (EOVc), 61 components were identified, of which two oxygenated sesquiterpenes stood out as the main components, namely, germacrone (25.42%) and curzerene (25.29%). EOVg exhibited Minimum Inhibitory Concentration (MIC) of 1.56 µg/mL against the yeast C. parapsilosis whereas EOVc was active against the bacteria E. coli and S. aureus as well as the yeast C. parapsilosis. The results obtained in this study strongly recommend further research on the essential oils in question with a view to isolating and identifying the components responsible for their observed antimicrobial activities.

Case Report: Evidence of Tungiasis in the Amazon Rain Forest of Ecuador

Tungiasis occurs in tropical and subtropical areas in Central and South America and sub-Saharan Africa and is a Neglected Tropical Disease. We diagnosed three cases of tungiasis in a Dutch family visiting indigenous communities in the Amazon basin of Ecuador. Eight days after returning, they presented papular, pruritic, and painful lesions on the feet, with a whitish halo and a blackish central point with abundant whitish eggs upon extraction. For the first time, we demonstrate that Tunga spp. transmission is present in remote indigenous communities in the Amazon rainforest of Ecuador. It will be important to investigate the occurrence of tungiasis and associated morbidity among local inhabitants and consider prevention measures among locals and travelers to these areas.