Over the course of iAtlantic, more than 5 Tb of genomic data were obtained to study the genetic variations of 10 species or species complexes (cold-water corals, vent and seep molluscs, vent shrimp) on a genome-wide scale. These data have been used in population genetics to assess the degree of past and present gene flows between populations at the scale of the Atlantic Ocean, and for certain species (cold seep mussels) coupling results with large-scale larval dispersal modelling to better understand the dynamics of – and barriers to – ecosystem connectivity in the Atlantic.
Genetic analyses have enabled connectivity maps to be drawn up for all species, establishing past and present preferential migration routes between Atlantic regions. This information is of vital importance in conservation biology and may help in the development of sustainable management tools for deep- sea benthic communities living in fragmented and locally unstable environments.
The deep-sea species studied tend to be distributed in geographically isolated pockets, possibly linked by rare and sporadic migration events on a global scale. These species also have complex demographic histories, giving rise to cryptic species complexes that can hybridise locally following secondary contacts. Isolation by distance and the establishment of hydrographic and genetic barriers up to the closing of the Panama seaway has resulted in the regionalisation of most deep-sea species, a fact that must be considered in the current and future exploitation of biological and mineral resources from the deep ocean.
The main findings of this work are:
Elements of this work are summarised in a science brief:
‘Connecting the vents: Using genetics to understand ecosystem connectivity along the Mid-Atlantic Ridge‘.
Download the full report
iAtlantic Deliverable 1.5: Preferential pathways of dispersal and role of the AMOC in connectivity. Report by D. Jollivet et al. (March 2024) (PDF, 2,.2MB)
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This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 818123 (iAtlantic). This output reflects only the author’s view and the European Union cannot be held responsible for any use that may be made of the information contained therein.