International Journal of Aquaculture, 2024, Vol.14, No.2, 101-111 http://www.aquapublisher.com/index.php/ija 102 Additionally, this study discusses the challenges and opportunities associated with implementing these advanced methods in the context of global environmental change, particularly in maintaining the biodiversity and ecosystem services of lakes and other freshwater bodies. Through this comprehensive analysis, the study seeks to provide actionable insights for policymakers, researchers, and practitioners dedicated to the sustainable management of aquatic ecosystems. 2 Technological Advances in Monitoring 2.1 Remote sensing technologies Remote sensing technologies have significantly advanced the monitoring of aquatic ecosystems, providing critical data for managing water quality and ecosystem health. Hyperspectral sensors, such as PRISMA and DESIS, have been utilized to retrieve water quality parameters across various aquatic environments, including deep clear lakes and river dammed reservoirs. These sensors offer high spatial and spectral resolution, enabling detailed analysis of water bio-physical parameters and supporting management decision-making (Bresciani et al., 2022). Additionally, remote sensing has been applied to monitor submerged aquatic vegetation (SAV), which is crucial for ecosystem health but challenging to study due to water column effects. Techniques to correct for these effects have been developed, enhancing the accuracy of remote sensing in aquatic environments. 2.2 In-situ monitoring tools In-situ monitoring tools have evolved to provide real-time data on water quality and ecosystem health. Biological early warning systems (BEWS) that monitor the behavior and physiological parameters of aquatic bioindicator species have been developed to detect sudden changes in water quality. These systems offer continuous monitoring and early warning capabilities, which are essential for timely management interventions (Bownik and Wlodkowic, 2021). Additionally, high-frequency environmental sensing tools have expanded the ability to measure aquatic ecosystem metabolism, providing insights into gross primary productivity and ecosystem respiration. These measurements are valuable for understanding ecosystem function and informing environmental management (Jankowski et al., 2021). 2.3 Molecular and genetic techniques Molecular and genetic techniques, such as environmental DNA (eDNA) sequencing, have become integral to monitoring aquatic ecosystems. These techniques allow for the detection and monitoring of a wide range of organisms, including those that are difficult to observe using traditional methods. eDNA sequencing can trace the presence of various species, providing comprehensive data on biodiversity and ecosystem health. This approach is particularly useful in deep-sea ecosystems, where traditional monitoring methods are challenging and costly (Aguzzi et al., 2019). 2.4 Data analytics and artificial intelligence The integration of data analytics and artificial intelligence (AI) has revolutionized the monitoring and management of aquatic ecosystems. AI and machine learning algorithms can process large datasets from remote sensing and in-situ monitoring tools, providing actionable insights for conservation and management. Automated monitoring systems facilitated by AI reduce data processing bottlenecks and long-term monitoring costs, enabling more effective and timely decision-making. Furthermore, advances in machine learning and cloud computing allow for the exploitation of the full electromagnetic spectrum, enhancing the ability to monitor and assess aquatic environments (Dierssen et al., 2021). 3 Policy Frameworks for Aquatic Ecosystem Management 3.1 International policies and agreements International policies and agreements play a crucial role in the management and conservation of aquatic ecosystems. The United Nations' Sustainable Development Goals (SDGs), particularly SDG6 (clean water and sanitation) and SDG15 (life on land), provide a global framework for sustainable water management and the protection of terrestrial and freshwater ecosystems (Forio and Goethals, 2020). These goals emphasize the need for integrated monitoring and assessment methods to support sustainable development and ensure the health of
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