Reproduction in a deep-sea coral

Reproduction in a deep-sea coral

Reproduction in a deep-sea coral

Lead supervisor: Dr Michelle Taylor

Location: School of Life Sciences, University of Essex

Duration: 7 weeks

Project background

Deep-sea coral reefs are vulnerable marine ecosystems which provide important ecological services, such as habitat for a variety of deep-sea animals. They are under threat from ocean acidification, climate change, and destruction from contact with fishing trawls. One such coral, Acanella arbuscula (full colony in image a), unusually, grows in soft sediments (rather than on hard surfaces); soft sedimentary plains are the largest habitat in the world, mostly found between 60 and 2,000 metres in depth. They grow shallow root-like holdfasts (see image c) which help anchor them in the sediment; consequently, this leaves the corals vulnerable to being uprooted and destroyed when struck by heavy bottom fishing gear (as has happened in image d). Coral are particularly aged animals with some being found to be over 4500 years old. Understanding their resilience and vulnerability to disturbances is crucial, and one aspect of this is to further understand and investigate their reproduction potential, their fecundity.

Project research

Several hundred preserved Acanella arbuscula specimens are available to explore their fecundity. Individual coral polyps (image b) will need to be removed from each specimen and dissected to look for the presence of coral eggs. When eggs are found, they will need to be photographed under a stereoscope with a scale bar, and later their diameter measured using the program ImageJ. The size of coral eggs will be linked with collection data to determine if there is any correlation to egg size with date of collection (season), depth, and location. This data will used to determine peak spawning time for the target coral which will be used in planned larval connectivity oceanographic models. Dispersal potential and population connectivity in the deep-sea is rarely studied and models are poorly constrained due to the lack of such data.

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