Microplastic levels and sentinel species used to monitor the environmental quality of lagoons: A state of the art in Italy

Bruschi, Raffaele; Pastorino, Paolo; Barceló, Damià; Renzi, Monia

doi:10.1016/j.ecolind.2023.110596

Cited by 5 publications

(3 citation statements)

References 97 publications

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“…Among recent environmental problems of coastal lagoons are affected biodiversity patterns and loss of habitats and rare species [23,24], as well as disrupted land cover patterns due to climate effects. Examples of pollution include organic, chemical, and biological types such as microplastic [25,26] or heavy metals [27].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Lemenkova

2024

JMSE

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This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.

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Section: Introduction 1backgroundmentioning

confidence: 99%

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Lemenkova

2024

JMSE

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“…Sand banks, reefs, or barrier islands create this unique, brackish environment teeming with life [ 9 ]. This is the essence of a coastal lagoon, a vibrant transitional environment shaped by the interplay of land and sea, rich in biodiversity and with a high productivity [ 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…These lagoons, renowned for their unique geomorphological features, are crucial transitional ecosystems rich in habitats and biodiversity. They also support intensive aquaculture and fishery activities [ 12 , 19 , 20 ]. Due to their contrasting morphologies and hydrological regimes, the lagoons experience anthropogenic pollution from shell farming activities to varying degrees [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Navigating a Microplastic Sea: How the Pacific Cupped Oyster (Magallana gigas) Respond to Microplastic Pollution in Lagoons

De Rinaldis,

Pastorino,

Scirocco

et al. 2024

Toxics

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Microplastic pollution poses an escalating concern, particularly in coastal lagoons rich in biodiversity. This study delved into the occurrence of microplastics (MPs) in Magallana gigas (formerly Crassostrea gigas) from the Orbetello and Varano coastal lagoons (Italy), also investigating the response of these filter-feeding organisms to various colors (P = pink; B = blue; W = white) of high-density polyethylene (HDPE) MP fragments. Oysters were exposed for 7 days under controlled conditions. Subsequently, the oysters underwent analysis for both MP presence and biochemical markers of oxidative stress. Diverse ingestion rates of HDPE were noted among oysters from the two lagoons, eliciting antioxidant responses and modifying baseline activity. The two-way ANOVA revealed the significant effects of treatment (control; HDPE_B; HDPE_P; HDPE_W), site, and the interaction between treatment and site on all biomarkers. Non-metric multidimensional scaling showed a divergent effect of HDPE color on biomarkers. Further investigation is warranted to elucidate the mechanisms underlying the influence of MP color, dose-dependent effects, and the long-term impacts of exposure. Comprehending these intricacies is imperative for devising effective strategies to mitigate plastic pollution and safeguard marine health.

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Effect of urbanization and water quality on microplastic distribution in Conceição Lagoon watershed, Brazil

de Castro,

Lemes da Silva,

das Neves Lopes

et al. 2024

Environ Sci Pollut Res

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Urbanization in watersheds leads to the introduction of sources of microplastics and other pollutants in water bodies. However, the effect of urbanization on microplastic pollution and the relationship between microplastics and water quality are not well understood. We assessed the distribution of microplastics in tributaries urbanized, non-urbanized and in the receiving lagoon body of Conceição Lagoon watershed.The results show that urbanization signi cantly affects water quality but does not differentiate tributaries in terms of microplastic concentrations. Microplastic concentrations were lower in the receiving lagoon body compared with the tributaries, highlighting their importance in microplastic pollution in the studied lagoon. Microplastic concentration was correlated with low N:P ratios in the lagoon and associated with high levels of total phosphorus, which indicate the discharge of e uents. The correlations between microplastic concentration, water temperature, and dissolved oxygen in the lagoon were based on the temporal variations of these variables. Precipitation and wind velocity had in uence on microplastic distribution in the watershed. Our ndings underscore the importance of evaluating water quality parameters and meteorological variables to comprehend the microplastic distribution at small watersheds.

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Microplastic levels and sentinel species used to monitor the environmental quality of lagoons: A state of the art in Italy

Cited by 5 publications

References 97 publications

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

Navigating a Microplastic Sea: How the Pacific Cupped Oyster (Magallana gigas) Respond to Microplastic Pollution in Lagoons

Effect of urbanization and water quality on microplastic distribution in Conceição Lagoon watershed, Brazil

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