The field of aquatic ecosystem monitoring is witnessing a transformative shift with the advent of innovative hybrid systems that merge advanced sensing technologies with biological indicators. Traditional aquatic monitoring techniques have often faced limitations in capturing the full dynamism of aquatic environments, particularly in the context of hydrodynamic stressors. By integrating technologies like remote sensing and machine learning with biotic systems researchers are seeking to develop systems capable of providing real-time, comprehensive insights into the effects of fluctuations in water flow and quality. Recent studies highlight the incremental progress in this area, showing promising results in capturing minute changes in environmental conditions that were previously unobservable with conventional methods. However, a gap still exists in refining these emerging methodologies to ensure accuracy, resilience, and applicability across diverse ecosystems.

This Research Topic aims to push the boundaries of aquatic ecosystem monitoring by devising and refining systems that blend biological and technological elements for a multi-faceted understanding of ecosystem dynamics. The core goal is to employ this integrated approach to identify and test the responses of aquatic environments to various stressors, developing predictive models to forecast possible changes in ecosystem dynamics under different scenarios. This can potentially lead to proactive strategies in ecosystem conservation and water resource management, improving adaptive responses to climate variations and anthropogenic impacts. Key questions involve determining the thresholds and limitations of these hybrid systems in variable contexts, the scalability of such approaches across different geographies, and how reliably these systems can be used in long-term monitoring programs.

The scope of this Research Topic encompasses the development, application, and evaluation of hybrid systems leveraging biotic communities and advanced sensing technologies. The initial focus lies on the convergence of state-of-the-art methodologies capable of enhancing our understanding of aquatic habitats on a real-time basis, with a specific emphasis on freshwater environments. Key themes to explore include:

o Development of hybrid systems integrating biological indicators with technologically advanced sensors.

o Methodological advancements in freshwater mussel valvometry and its applications in ecosystem monitoring.

o Application of machine learning and algorithmic models to interpret complex data from hybrid monitoring systems.

o Evaluation of ecosystem responses to hydrodynamic stressors and translating findings into actionable water management practices.

o Impacts of climate change on aquatic ecosystems and the role of hybrid systems in facilitating adaptive management strategies.

By focusing on these areas, this research topic endeavors to establish a foundation for revolutionary improvements in the field of aquatic ecosystem monitoring, ultimately contributing towards the sustainability and resilience of vital aquatic resources.

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Fusion of Sensing and Biotic Systems for Aquatic Ecosystem Monitoring