A Meta-Review on New Technologies for Marine Biodiversity Monitoring and Assessment

Effective biodiversity monitoring and management play a key role in understanding ecosystems, especially in the light of increasing environmental challenges and biodiversity loss. Traditional monitoring methods often face limitations in terms of spatial and temporal coverage, efficiency, and ability to identify cryptic or rare species. Fortunately, technological advancements are enabling the collection of a new generation of ecological data, with the application of these technologies in biodiversity conservation being a rapidly growing area. Key technological approaches include molecular techniques such as environmental DNA (eDNA), metabarcoding, and genomics for non-invasive genetic assessments. Remote sensing, from satellites and airborne platforms to LiDAR, RADAR, and sonar, enables large-scale habitat and environmental monitoring. Robotic systems, including autonomous and hybrid platforms, extend access coverage of remote areas by carrying sensors and sampling tools. AI and machine learning enhance data analysis and computer vision, while automated sensor networks and animal tracking technologies provide continuous insights into ecosystem dynamics and species behavior. This meta-review synthesizes findings from diverse research efforts, highlighting how emerging technologies are reshaping biodiversity monitoring. These tools offer greater efficiency, lower deployment costs, and adaptability to varied ecological contexts compared to traditional methods. However, the literature also underlines significant challenges that remain unresolved. Despite these hurdles, the field appears poised for major breakthroughs that could transform how we monitor and protect biodiversity. Realizing these opportunities will depend on continued investment in research and technology development.