Dynamics of exposure to mercury in a population of the upper Madeira River, Rondônia – Brazil

This work evaluates the influence of cognitive and sociodemographic functions on the dynamics of human exposure to mercury in communities on the upper Madeira River in the state of Rondônia, Brazil. In this longitudinal epidemiological study of convenience sampling (2009 to 2019), semi-structured questionnaires on cognitive and sociodemographic aspects were applied to 1,089 participants (646 men and 443 women) divided into 6 groups with distinct geographic characteristics and lifestyles. Total mercury concentrations in hair samples were determined by direct analysis using atomic spectroscopy. In this population, cognitive (memory, attention span, concentration and difficulties in reading, writing and mathematical calculations) and sociodemographic (location, gender, age, education, alcohol consumption, smoking habits, time of residence in the region, occupation) grouping showed the differentiation between the groups with lifestyle directly related and dependent on extractivism/gold mining dispersed along the Madeira River (G1 and G2), and the groups that have urban dynamics on the margins of the federal highway BR-364 (G3, G4, G5 and G6). Sex, age and lifestyle (groups) were significant indicators of total mercury concentrations in hair. The organization of participants according to cognitive and sociodemographic profiles, regardless of geographic location, highlights the contribution of individualized social dynamics to mercury exposure in the Madeira River basin region. Despite socio-historical and socio-economic similarities, cognitive and sociodemographic functions show individualized social behaviors within communities, which may influence the process of exposure to THg.

Impacts of a large hydroelectric dam on the Madeira River (Brazil) on floodplain avifauna

ABSTRACT Hydroelectric dams represent an important threat to seasonally flooded environments in the Amazon basin. We aimed to evaluate how a dam in the Madeira River, one of the largest tributaries of the Amazonas River, affected floodplain avifauna. Bird occurrence was recorded through simultaneous passive acoustic monitoring in early successional vegetation and floodplain forest downstream from the dam and upstream in sites impacted by permanent flooding after dam reservoir filling. Species were identified through manual inspection and semi-automated classification of the recordings. To assess the similarity in vegetation between downstream and upstream sites, we used Landsat TM/ETM+ composite images from before (2009-2011) and after (2016-2018) reservoir filling. Downstream and upstream floodplain forest sites were similar before, but not after dam construction. Early successional vegetation sites were already different before dam construction. We recorded 195 bird species. While species richness did not differ between upstream and downstream sites, species composition differed significantly. Ten species were indicators of early successional vegetation upstream, and four downstream. Ten species were indicators of floodplain forest upstream, and 31 downstream. Seven of 24 floodplain specialist species were detected by the semi-automated classification only upstream. While we found some bird species characteristic of early successional vegetation in the upstream sites, we did not find most species characteristic of tall floodplain forest. Predominantly carnivorous, insectivorous, and nectarivorous species appear to have been replaced by generalist and widely distributed species.

Water Flow Forecasting Based on River Tributaries Using Long Short-Term Memory Ensemble Model

Water flow forecasts are an essential information for energy production, management and hydropower control. Advanced actions to optimize electricity production can be taken based on predicted information. This work proposes an ensemble strategy using recurrent neural networks to generate a forecast of water flow at Jirau Hydroelectric Power Plant (HPP), installed on the Madeira River in Brazil. The ensemble strategy consists of combining three long short-term memory (LSTM) networks that model the Madeira River and two of its tributaries: Mamoré and Abunã rivers. The historical data from streamflow of the Madeira river and its tributaries are used to validate the ensemble LSTM model, where each time series of river tributaries are modeled separated by LSTM models and the result used as input for another LSTM model in order to forecast the streamflow of the main river. The experimental results present low errors for training and test sets for individual LSTM networks and ensemble model. In addition, these results were compared with the operational forecasts performed by Jirau HPP. The proposed model showed better accuracy in four of the five scenarios tested, which indicates a promising approach to be explored in water flow forecasting based on river tributaries.

Database of the historical series of fisheries production in the middle Madeira River region, southwest of the Amazon, from 2001 to 2013

The Amazon is very important regarding the continental extractive fishing as it has the greatest diversity of freshwater fish in the world. Some factors can contribute to identify significant changes in fish production, such as characterization based on common names, and synonyms or classifications only at the genus level. This creates noise in different types of analyzes and mistakes in determining effective productions, as well as levels of exploitation for management. Thus, this study aims to demonstrate the variation in fish production over the years 2001 and 2013, using control data from the fishing colony "Dr. Renato Pereira Gonçalves Z-31" in the municipality of Humaitá, southern Amazonas. These data were analyzed by collaborators from the Laboratory of Ichthyology and Fisheries Management of the Madeira River Valley, at the Federal University of Amazonas. The fish landing monitoring allowed the determination of the species caught in the regional fishery and evaluated the effect of the hydrological level and the pre- and post-installation periods of the Santo Antônio and Jirau HPPs in Rondônia, on the total production. The data set showed the significant decrease in fish production between 2008 and 2013. Among the factors that explain the observed changes are the mistakes in determining the effective production due to the lack of criteria in the grouping of many species, the absence of regulations, such as the "Portaria IBAMA Nº 48" which was created only in 2007, in addition to the installation period of the HPPs on the Madeira River. It was also possible to verify the effect of seasonality through hydrological quotas on fish production, with the highest values observed in July, August and September of the years analyzed.

The Role of the Rainfall Variability in the Decline of the Surface Suspended Sediment in the Upper Madeira Basin (2003–2017)

The Madeira River rises in the Andes, draining the southwestern Amazon basin and contributing up to 50% of the Amazon River sediment load. The Porto Velho station monitors the Upper Madeira basin and is located just downstream of the Jirau and Santo Antonio hydropower dams. At this station, decreasing trend (p < 0.10) of the surface suspended sediment concentration (SSSC) has been documented during the sediment peak season (December to February) for the 2003–2017 period. This study aims to evaluate the role of the rainfall variability on this documented decreasing trend. For this purpose, we applied correlation and trend analysis in water discharge, SSSC and rainfall time series over the main tributaries of the Upper Madeira basin. The decline of SSSC in December is attributed to the reduction of rainfall in the Madre de Dios sub-basin from the start of the rainy season in October. However, the SSSC negative trend (p < 0.10) in January and February is associated with a shift in the magnitude of rainfall during these months in the Andean region after 2008, and the dilution associated with base flow. These results reveal that the decline of SSSC in the Madeira River should not be evaluated just on the basis of the data downstream from the dams, but also of the processes upstream in the Andean part of the basin. In a context of drastic anthropogenic climate and environmental changes, understanding the combined influence of regional hydroclimate variability and human actions on erosion and sediment transport remains a critical issue for the conservation of the Amazon-Andes system.