Machine learning sheds light on physical-chemical and biological parameters leading to Abrolhos coral reef microbialization.

Microbes play a central role in coral reef health. However, the relative importance of physical-chemical and biological processes in the control of microbial biomass are unknown. Here, we applied machine learning to analyze a large dataset of biological, physical, and chemical parameters (N = 665 coral reef seawater samples) to understand the factors that modulate microbial abundance in the water of Abrolhos reefs, the largest and richest coral reefs of the Southwest Atlantic. Random Forest (RF) and Boosted Regression Tree (BRT) models indicated that hydrodynamic forcing, Dissolved Organic Carbon (DOC), and Total Nitrogen (TN) were the most important predictors of microbial abundance. The possible cumulative effects of higher temperatures, longer seawater residence time, higher nutrient concentration, and lower coral and fish biomass observed in coastal reefs resulted in higher microbial abundance, potentially impacting coral resilience against stressors.

Optimisation and control of the supply of blood bags in hemotherapic centres via Markov decision process with discounted arrival rate.

Running a cost-effective human blood transfusion supply chain challenges decision makers in blood services world-wide. In this paper, we develop a Markov decision process with the objective of minimising the overall costs of internal and external collections, storing, producing and disposing of blood bags, whilst explicitly considering the probability that a donated blog bag will perish before demanded. The model finds an optimal policy to collect additional bags based on the number of bags in stock rather than using information about the age of the oldest item. Using data from the literature, we validate our model and carry out a case study based on data from a large blood supplier in South America. The study helped achieve an overall increase of 4.5% in blood donations in one year.

Elaboração e análise de indicadores sociais para o apoio à tomada de decisão no processo de despoluição da Baía de Guanabara / Elaboration and analysis of social indicators as an instrument to support decision making in the process of depollution of the Guanabara Bay

Resumo Apesar dos esforços de despoluição desde os anos 1990, não houve percepção, por parte da opinião pública, de que houve evolução do deteriorado quadro social da região da bacia da Baía de Guanabara (RJ). A importância dos indicadores sociais emerge em um momento em que se faz necessário prestar contas à população quanto aos investimentos e resultados obtidos, direcionar as ações às questões sociais e locais em situação de maior urgência e acompanhar os resultados para a identificação de ajustes nas ações para o alcance de melhores resultados. A atual agenda de discussão das questões sociais do entorno da baía configurou a base para a elaboração de um sistema de indicadores sociais. Três bacias hidrográficas em processo de despoluição também foram estudadas, com foco em suas abordagens quanto às questões sociais. Um modelo teórico de indicadores foi elaborado e testado em um recorte da bacia da Baía de Guanabara, por intermédio da utilização de dados públicos disponíveis. O modelo se mostrou ferramenta útil para uma abordagem holística da bacia ao informar sobre o melhor direcionamento de ações de despoluição para resultados mais efetivos em ambas as questões, sociais e ambientais.

Abstract Despite the efforts in the depollution since the 1990s, evolution of the damaged social scenario in the region of the watershed of the Guanabara Bay is not perceived by the public opinion. The importance of social indicators emerges in a moment in which rendering account to the population regarding investiments and results obtained, orienting actions for emergency social and local issues and monitoring results for identification of adjustments to the actions for the achievement of better results is necessary. The current agenda for debating social issues of the region of the bay represented the basis for the creation of a system of social indicators. Three watersheds in depollution process were also studied, focusing on their approaches regarding social issues. A theoretical model of indicators was developed and tested in a draft of the Guanabara Bay watershed, using the public data available. The model proved to be a useful tool for an holistic approach of the bay by providing information on the better orientation of depollution actions for more effective results in both social and environmental issues.

Insights on the freshwater microbiomes metabolic changes associated with the world's largest mining disaster.

To evaluate the impacts of the Fundão tailings dam failure (Minas Gerais, Brazil) on water quality of the Doce River, we analyzed metagenomics and physicochemical parameters during the month of the disaster and again 6 and 10 months after the disaster. To compare dam conditions before and after the failure, we performed a meta-analysis of physicochemical data from a public database. Immediately after the failure, suspended particulate matter (SPM) in the Doce River was 225-1877 mg L-1. Turbidity and dissolved aluminum and iron concentrations were extremely high, whereas dissolved oxygen was below Brazilian legislation norm (<5 mg L-1) in several locations. Six months later, physicochemical values were below thresholds set by Brazilian guidelines (e.g., SPM = 8-166 mg L-1). Short-term impacts on microbial communities included an increase in Actinobacteria and Bacteroidetes and gene sequences related to microbial virulence, motility, respiration, membrane transport, iron and nitrogen metabolism, suggesting changes in microbial metabolic profiles. The 11 recovered partial genomes from metagenomes (MAGs) had genes related to Fe cycle and metal resistance.

Remote sensing, isotopic composition and metagenomics analyses revealed Doce River ore plume reached the southern Abrolhos Bank Reefs.

On November 5th, 2015, the Fundão dam rupture released >50 million m3 of ore tailings into the Doce River, Minas Gerais State, Brazil. The huge volume of mud spread along the river and reached the sea, 17 days after the disaster, in Regência, Espírito Santo State (ES). In 2018, after three years of the disaster, the impacts of the ore tailings in the marine environment are still unclear. This study aims to investigate possible short-term impacts in marine biodiversity caused by the ore tailings' mud over the reef ecosystems that are closest to the disaster area: i.e. recently discovered reefs in the southern Abrolhos Bank. A remote sensing surveillance including winds, sea surface temperature, total suspended material and watercolor (MODIS Aqua data) indicated that the iron tailings plume reached the southern portion of Abrolhos Bank on June 16th, 2016. Subsequently, to obtain further evidence of the presence of the tailings in the coral reefs, water samples were collected in a gradient spanning from the river estuary to the reefs in southern Abrolhos Bank, we also analyzed the isotopic and microbial composition of the samples, as well as the reef benthic composition. Despite no clues of negative impact on benthic (coral) communities, isotopic analysis confirmed the presence of the plume over the reefs area. This study serves as a baseline for future long-term impact assessments of the health of coral reefs in the Abrolhos Bank.