Artisanal small-scale gold mining (ASGM) is the main source of anthropogenic mercury emissions and contamination in Latin America. In the Brazilian northern Amazon, ASGM has contaminated the environment and people over the past century. The main contamination route is through fish consumption, which endangers the food security and livelihoods of traditional communities. Our study aims to assess the potential toxicological health risks caused by the consumption of Hg-contaminated fish across five regions in Amapá State. We sampled 428 fish from 18 sites across inland and coastal aquatic systems. We measured the total mercury content in fish samples, and the results were applied to a mercury exposure risk assessment targeting three distinct groups (adults, women of childbearing age, and children). Mercury contamination was found to exceed the World Health Organization’s safe limit in 28.7% of all fish samples, with higher prevalence in inland zones. Moreover, the local preference for carnivorous fish species presents a serious health risk, particularly for communities near inland rivers in the region. This is the first study to provide clear recommendations for reducing the mercury exposure through fish consumption in Amapá State. It builds scientific evidence that helps decision-makers to implement effective policies for protecting the health of riverine communities.
Tropical forests are often located in difficult-to-access areas, which make high-quality forest structure information difficult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-efficient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal differences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 ± 1.8 vs. 381.2 ± 58 pts/m2). Differences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 ± 0.09 vs. 0.42 ± 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior.
In recent decades, widespread and uncontrolled use of mercury (Hg) in artisanal small-scale gold mining has released thousands of tons of mercury-contaminated waste in the Amazon biome, endangering the largest tropical rainforest worldwide. In this study, we assessed and compared blood Hg levels in individuals living in urban and riverine areas in the lower Tapajós basin and examined the association between Hg exposure and specific biochemical parameters. In total, 462 adults from eight riverine communities and one urban area were assessed. Overall, 75.6% of the participants exhibited Hg concentrations exceeding the safe limit (10 µg/L). Hg exposure was higher in the riverine population (90%) than in urban areas (57.1%). Mean Hg levels were 21.8 ± 30.9 µg/L and 50.6 µg/L in urban and riverine residents, respectively. The mean Hg level was higher in those aged 41–60 years in both urban and riparian areas, with riparian residents exhibiting a mean double that of urban residents. The highest glucose and hepatic biomarker levels were detected in the urban area, whereas the highest levels of renal biomarker occurred in the riverine population. Our results indicate that Hg contamination remains a persistent challenge for the urban population of Santarém, a major city in the Brazilian Amazon.
Studying the variables that describe the spatial ecology of threatened species allows us to identify and prioritize areas that are critical for species conservation. To estimate the home range and core area of the Endangered (EN) Amazon river dolphin Inia geoffrensis, 23 individuals (6♀, 17♂) were tagged during the rising water period in the Amazon and Orinoco river basins between 2017 and 2018. The satellite tracking period ranged from 24 to 336 d (mean ± SE = 107 ± 15.7 d), and river dolphin movements ranged from 7.5 to 298 km (58 ± 13.4 km). Kernel density estimates were used to determine minimum home ranges at 95% (K95 = 6.2 to 233.9 km2; mean = 59 ± 13.5 km2) and core areas at 50% (K50 = 0.6 to 54.9 km2; mean = 9 ± 2.6 km2). Protected areas accounted for 45% of the K50 estimated core area. We observed dolphin individuals crossing country borders between Colombia and Peru in the Amazon basin, and between Colombia and Venezuela in the Orinoco basin. Satellite tracking allowed us to determine the different uses of riverine habitat types: main rivers (channels and bays, 52% of recorded locations), confluences (32%), lagoons (9.6%), and tributaries (6.2%). Satellite monitoring allowed us to better understand the ecological preferences of the species and demonstrated the importance of maintaining aquatic landscape heterogeneity and spatial connectivity for effective river dolphin conservation.
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