Bio-tracking, bio-monitoring and bio-magnification interdisciplinary studies to assess cyanobacterial harmful algal blooms (cyanoHABs)’ impact in complex coastal systems

Abstract

Cyanobacterial Harmful Algal Blooms (cyanoHABs) represent significant threats to human health and environmental sustainability. These blooms, characterized by the rapid proliferation of toxic species, can release harmful toxins into aquatic environments, with severe consequences for ecosystems and human populations. Traditional research on cyanoHABs faces several limitations, including the lack of standardized detection methods, environmental variability, and low awareness of the associated risks. Most studies rely on conventional laboratory techniques, which are often resource-intensive and not widely accessible. Additionally, the complex dynamics of cyanoHABs, influenced by factors such as temperature, nutrients, and bloom evolution, make it difficult to establish consistent regulatory and monitoring frameworks.

This paper presents a new integrated strategy that combines advanced technologies (remote sensing, in-situ multispectral analysis, mass spectrometry) with bio-monitoring and bio-tracking. This interdisciplinary approach improves the monitoring of cyanoHAB spread, tracks bioaccumulation in the food chain, and provides timely warnings for public health protection.

The case study focuses on the Campi Flegrei area, an active volcanic region in Southern Italy, where Lake Avernus, a volcanic lake, has experienced periodic cyanobacterial blooms. This region also hosts mussel aquaculture and recreational activities. Remote sensing allowed the tracking of the 2022 bloom from the lake to the sea, reaching a mussel farm along the coast. Rapid detection and quantification of anabaenopeptins in bivalves enabled timely alerts to local authorities, prompting an assessment of contamination risks.

The study demonstrates how the integration of remote sensing and molecular analysis enhances environmental monitoring by providing real-time, high-resolution data. This approach supports a better understanding of bloom dynamics, bioaccumulation, and impacts on the food chain, informing risk management and regulatory strategies. The research highlights the value of combining advanced technologies to improve the management of cyanoHAB-related risks, protecting both human health and ecosystem sustainability.