Mercury Scenario in Fish from the Amazon Basin: Exploring the Interplay of Social Groups and Environmental Diversity

Abstract

The Amazon faces significant challenges related to mercury contamination, including naturally elevated concentrations and gold mining activities. Due to mercury's toxicity and the importance of fish as a protein source for local populations, assessing mercury levels in regional fish is crucial. However, there are gaps in knowledge regarding mercury concentrations in many areas of the Amazon basin. This study aims to synthesize the existing literature on mercury concentrations in fish and the exposure of urban and traditional social groups through fish consumption. A systematic review (1990-2022) was conducted for six fish genera (Cichla spp., Hoplias spp. and Plagioscion spp., Leporinus spp., Semaprochilodus spp., and Schizodon spp.) in the Web of Science (Clarivate Analytics) and Scopus (Elsevier) databases. The database consisted of a total of 46 studies and 455 reports. The distribution of studies in the region was not homogeneous. The most studied regions were the Madeira River sub-basin, while the Paru-Jari basin had no studies. Risk deterministic and probabilistic assessments based on Joint FAO/WHO Expert Committee on Food Additives (JECFA, 2007) guidelines showed high risk exposure, especially for traditional communities. Carnivorous fish from lakes and hydroelectric reservoirs, as well as fish from black-water ecosystems, exhibited higher mercury concentrations. In the Amazon region, even if mercury levels in fish muscle do not exceed regulatory limits, the high fish consumption can still elevate health risks for local populations. Monitoring mercury levels across a broader range of fish species, including both carnivorous and non-carnivorous species, especially in communities heavily reliant on fish for their diet, will enable a more accurate risk assessment and provide an opportunity to recommend fish species with lower mercury exposure risk for human consumption. The present study emphasizes the need to protect regions that already exhibit higher levels of mercury-such as lakes, hydroelectric reservoirs, and black-water ecosystems-to ensure food safety and safeguard public health.

Keywords: fish consumption; methylmercury; risk calculation; systematic review; traditional communities; urban communities.

Figure 1

Number of studies published per year (left) and number of studies conducted in each country (right) with data on mercury concentration in six fish genera (Cichla spp., Hoplias spp. and Plagioscion spp., Leporinus spp., Semaprochilodus spp., and Schizodon spp.) in the Amazon basin. Although the research period spans from 1990 to 2022, no studies were conducted before 1995; therefore, data from this period is not included in the graph.

Figure 2

Distribution of studies on mercury concentrations in the six genera (Cichla spp., Hoplias spp. and Plagioscion spp., Leporinus spp., Semaprochilodus spp., and Schizodon spp.) of fish examined in the Amazon basin.

Figure 3

Deterministic and probabilistic indices for mercury exposure through fish consumption, considering fish consumption values for the North Region of Brazil [5] and traditional and urban social groups of the Amazon region [7].

Figure 4

Mercury concentrations in the muscle of fish from the Amazon basin according to their sampling site. Lake: natural lentic aquatic ecosystems. Hydroelectric: lakes and downstream hydroelectric reservoirs. w.w.: wet weight. Feeding habits (carnivorous and non-carnivorous) were analyzed separately. The Hg data were log-transformed to meet the assumptions of the ANOVA. Different letters indicate significant differences according to Tukey’s test, considering a type I error of 5% (α = 0.05).

Figure 5

Mercury concentrations in the muscle of fish from the Amazon basin according to the type of water of the aquatic ecosystem [23]. w.w.: wet weight. Feeding habits (carnivorous and non-carnivorous) were analyzed separately. The Hg data were log-transformed to meet the assumptions of ANOVA. Different letters indicate significant differences according to Tukey’s test, considering a type I error of 5% (α = 0.05).

Figure 6

Relationship between mercury concentration in the muscle of fish and their total size in the Amazon basin. X and Y error bars represent the standard deviation, when available. The Hg data were log-transformed to meet the assumptions of regression. Regression statistics are as follows: carnivores = log (Y) = 4.5 + 0.03X; R² = 0.23; p < 0.00001; non-carnivores= log (Y) = 7.2 − 0.09X; R² = 0.17; p < 0.00001 w.w.: wet weight.

Figure 7

Greater exposure to mercury through fish consumption primarily occurs due to the consumption of carnivorous species, fish from lakes and reservoirs, and fish from black-water ecosystems. Protective factors can mitigate mercury toxicity, including metabolic detoxification processes, the protective role of selenium, a diverse diet rich in protective nutrients (such as Brazil nuts and fruits), and the elimination of mercury through excretory pathways (such as urine, hair, and, mainly, feces). All these factors will determine the toxicity of mercury in the organism.