USA - Robotics and deep learning to revolutionize seagrass monitoring

Seagrass meadows play an invaluable role as critical ecosystems that contribute significantly to marine biodiversity, carbon sequestration and coastal protection. In recent years, the importance of these underwater habitats has gained widespread recognition, and they have been increasingly studied and documented in ocean scientific research. Nevertheless, observation and monitoring remain significantly challenging and cost-intensive endeavours.

As a natural solution to combat climate change and protect against marine biodiversity loss, seagrass meadows contribute vital ecosystem services both to coastal communities and to society as a whole. Acting as nurseries to marine species, they offer shelter and food sources to fish and other marine organisms, purify seawater and stabilize the seabed, reducing the effects of coastal erosion. They are perhaps gaining most attention from scientists and policymakers for their ability to sequester carbon at rates surpassing terrestrial rainforests, making them a prime example of a nature-based solution to address climate change.

However, there is a significant obstacle standing in the way of developing protection and restoration schemes for these valuable ecosystems, and that is the sporadic and often incomplete observation evidence currently available to characterize and monitor meadow sites. Since today’s monitoring programmes remain heavily reliant on diver-based methods, spatial coverage and precision of repeatability are constrained, and labour-intensity inevitably puts pressure on the budgets available.

Fundamentally, knowledge gaps continue to hamper efforts to gather the essential evidence that informs planning and decision-making for protection and restoration. Consequently, stakeholders fail to reach the tipping points of scale where the value of the ecosystem services provided can be converted into fiscal mechanisms that provide the sustained funding needed to manage these important natural capital assets.

Enhancing our monitoring techniques, data collection and management processes is vital to facilitate effective conservation strategies, especially at a time when these invaluable natural assets are exposed to an array of environmental threats. Time is of the essence to deliver trusted, validated solutions to the practitioners who need them.

Non-invasive, budget-friendly robots

In October 2022, Hydro International published an article that featured the collaborative research and development work being undertaken by HydroSurv, working with the University of Plymouth and Valeport. Central to their approach was the deployment of small, battery-powered uncrewed surface vessels (USVs) as a non-invasive data acquisition platform capable of surveying wide spatial areas rapidly. At 2.8m long, HydroSurv’s REAV-28 is a multi-purpose vessel capable of rapid deployment and recovery from beaches and foreshores adjacent to work sites, with optimized sea-keeping for operations in the coastal environment and daywork endurance. Leveraging this platform to substitute the work performed by small workboats and divers has the potential to reduce CO₂-equivalent emissions by up to 97%, while slashing the cost of project execution.