Since 2011 the appearance of large amounts of seaweed (various species of Sargassum) on the beaches of the Caribbean Sea has become an annual problem e.g. in Barbados and Trinidad and Tobago. Small amounts of Sargassum reaching shores has beneficial effects – fertilising plants that strengthen shorelines, providing food for local species, etc., but the recent massive landings damage local ecology and economies and is challenging to clear up.
On shore, as well as blocking beaches and discouraging swimmers, the Sargassum releases sulphurous odours as it decomposes. Removal is time-consuming, expensive and can damage the beaches. Incoming rafts smother sea grasses and coral reefs, while local fishermen struggle to get into the water, with the huge rafts of seaweed blocking their engines and fishing gear. There is also the risk to the sea turtle population, which comes ashore to nest. Nesting sites can be blocked by the Sargassum or damaged by removal work – and the turtles may become entangled and die.
The new source of Sargassum appears to be in the tropical central Atlantic (the Great Atlantic Sargassum Belt, GASB e.g. Wang et al., 2019). Some possible causes have been suggested, such as the increase in discharge of nutrients from the Amazon, due to deforestation and increased use of agricultural fertiliser, as well as changes in sea surface temperature (SST) due to global warming and the biochemical composition of the seawater. The Sargassum has been observed in satellite images (e.g. MODIS) to extend from Brazil to West Africa (Wang et al., 2019), and it is then transported NW by the Guiana Current along the Lesser Antilles Island arc and into the Caribbean Sea.
This project is an exciting opportunity to get involved in interdisciplinary research in marine science, exploring the connections between physics, biogeochemistry and ecology, to address a real problem in managing our oceans. It will equip you with important skills in remote sensing and modelling, as well as management of Big Data, with opportunities to learn about AI and machine learning.
Here we propose to examine the transport of Sargassum by a regional numerical model of the 3D baroclinic hydrodynamic circulation (using a regional NEMO model embedded in the global NEMO model: Wilson et al., 2019), modulated by the Stokes’ drift caused by wind waves (from the WAVEWATCH III™ model, hereafter referred to as WW3, see Bricheno and Wolf, 2018). The model can capture the 3D circulation (driven by tides, winds, freshwater discharge from rivers and heat fluxes), as well as surface temperature and salinity, allowing us to explore the variability of the source conditions and transport and dispersion within the Atlantic Ocean and the Caribbean Sea. This may also provide a useful predictive tool for occurrence of the nuisance seaweed and help understand the mechanisms and impacts of options that may be applied to its management.
We will explore the following questions:
What is the likely cause of this recent phenomenon e.g. extra nutrients, increased SST?
Can we explain the variability, due to inter-annual variation in freshwater discharge, heat flux, nutrients and transport, using a coupled hydrodynamic-wave model? Is this dominated by freshwater discharge, nutrients, temperature or wind-driven variability?
Do we need also to use a biogeochemistry/ecosystem model like ERSEM or MEDUSA to explore the new source of Sargassumg. due to increased warming or discharge of nutrients?
Can we develop appropriate source terms for growth and decay of Sargassum to implement into the particle-tracking tool?
The beaching phenomenon of Sargassum, and its impacts, will be examined. What are the potential management options for prevention of the beaching and/or uses of the Sargassum recovered from beaches or offshore? Mass harvesting of Sargassum at sea can have negative consequences for important marine species that use Sargassum mats as refuges, nurseries, and foraging areas – including several threatened species of turtle, blue fin tuna, and several other commercial fish species.
This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See http://www.eo-cdt.org