Contaminant signatures and stable isotope values qualify European conger (Conger conger) as a pertinent bioindicator to identify marine contaminant sources and pathways

Dron, Julien; Revenko, G. P.; Chamaret, Philippe; Chaspoul, Florence; Wafo, Emmanuel; Harmelin-Vivien, Mireille

doi:10.1016/j.ecolind.2019.105562

Cited by 18 publications

(13 citation statements)

References 36 publications

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“…In the aquatic environment, fish have been widely utilized as environmental bioindicators of microplastic pollution [ 3 , 4 , 5 , 6 ] metal pollution [ 1 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ], sewage sludge pollution [ 17 ], suspended solid pollution [ 18 ], polychlorinated biphenyl (PCBs) pollution, and polycyclic aromatic hydrocarbon (PAH) pollution [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues

Petrea

Costache²,

Moga

et al. 2020

Molecules

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Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (Psetta maxima maeotica), are accepted by the scientific communities as suitable bioindicators of heavy metal pollution in the aquatic environment. The present study uses a machine learning approach, which is based on multiple linear and non-linear models, in order to effectively estimate the concentrations of heavy metals in both turbot muscle and liver tissues. For multiple linear regression (MLR) models, the stepwise method was used, while non-linear models were developed by applying random forest (RF) algorithm. The models were based on data that were provided from scientific literature, attributed to 11 heavy metals (As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Ni, Zn) from both muscle and liver tissues of turbot exemplars. Significant MLR models were recorded for Ca, Fe, Mg, and Na in muscle tissue and K, Cu, Zn, and Na in turbot liver tissue. The non-linear tree-based RF prediction models (over 70% prediction accuracy) were identified for As, Cd, Cu, K, Mg, and Zn in muscle tissue and As, Ca, Cd, Mg, and Fe in turbot liver tissue. Both machine learning MLR and non-linear tree-based RF prediction models were identified to be suitable for predicting the heavy metal concentration from both turbot muscle and liver tissues. The models can be used for improving the knowledge and economic efficiency of linked heavy metals food safety and environment pollution studies.

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Section: Introductionmentioning

confidence: 99%

“…The response of fish to environmental pollution is species specific. It is important that the chosen bioindicator fish species is not migratory and, thus, can accurately indicate pollution levels in a certain study area, have a superior trophic level (carnivorous or piscivorous) [ 9 , 10 , 14 , 15 ] and a specific diet [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues

Petrea

Costache²,

Moga

et al. 2020

Molecules

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“…The European conger (Conger Conger) is a benthic and sedentary fish, at the top of the trophic level in the Gulf of Fos. Its characteristics make it a reliable bioindicator for marine pollutants monitoring, including TBP, at fine spatial scales (Dron et al, 2019). The specimens were captured by means of bottom long-lines, measured and weighted, and immediately brought to the laboratory to remove muscle tissues which were stored at -40°C.…”

Section: Marine Organisms' Samplesmentioning

confidence: 99%

“…As in previous works (Dron et al, 2019), the Gulf of Fos was divided into three areas (harbor, east and west), on the basis of isotope ratios δ 13 C and δ 15 N adjusted to fish length in European conger muscle tissues (Figure 1). The geographical discrimination was very comparable to what obtained in European conger fished 5 years earlier (Dron et al, 2019), corroborating the specificity of the 3 areas, in particular among freshwater inputs (Supporting Information S3).…”

Section: Data Analysesmentioning

confidence: 99%

Assessment of the contamination by 2,4,6-tribromophenol of marine waters and organisms exposed to chlorination discharges

Dron

Demelas

Mas

et al. 2022

Environmental Pollution

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“…Being carnivorous, they gave a more precise account of what other species, their prey, are exposed to. The scientific evidence they helped produce was judged robust enough to be submitted to a high-ranking, academic, peer-reviewed journal specializing in marine pollution (Dron et al In Press).…”

Section: Introductionmentioning

confidence: 99%

Looking for the Cosmopolitical Fish: Monitoring Marine Pollution with Anglers and Congers in the Gulf of Fos, Southern France

Gramaglia

Mélard

2019

Science, Technology, & Human Values

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Following a controversy over the construction of a waste incinerator in the Fos-sur-Mer industrial area (France), residents pointed to the lack of knowledge of the industry’s cumulative impact on their health and environment. Under pressure, some of their elected representatives supported the creation of an independent scientific organization, the Ecocitizen Institute for Pollution Awareness ( Institut écocitoyen pour la connaissance des pollutions [IECP]). Its objective was to conduct localized scientific research on the effects of pollution and to lobby the administration to change its regulatory practices. This paper examines the efforts made to ensure that the “undone science” gets done, by focusing on the specificities of this industrialized site. We look at a participatory biomonitoring experiment that aimed to document pollution in the Gulf of Fos where scientists working for the IECP accepted anglers’ requests and switched from an acknowledged sentinel species to another species. We tell the many stories that were shared with us about how conger qualified as a more suitable “cosmopolitical fish” in the study of pollution. Elaborating on actor–network theory and multispecies ethnographies, we discuss the appropriateness of congers as the newly appointed sentinel species. We argue that this demonstrates the importance of the “ecology of relations” in maintaining the livability of the area.

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Contaminant signatures and stable isotope values qualify European conger (Conger conger) as a pertinent bioindicator to identify marine contaminant sources and pathways

Cited by 18 publications

References 36 publications

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues

Assessment of the contamination by 2,4,6-tribromophenol of marine waters and organisms exposed to chlorination discharges

Looking for the Cosmopolitical Fish: Monitoring Marine Pollution with Anglers and Congers in the Gulf of Fos, Southern France

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