20 Oct 2022

The aim of this project is to characterize the megabenthic communities associated to cold-water coral reefs in the Porcupine Seabight off Ireland (Northeast Atlantic), off Angola (Southeast Atlantic) and the Campeche Bank (Gulf of Mexico). These sites were selected based on their geographic distribution range, allowing for the first Atlantic-wide (East – West and North – South) comparison of the megabenthic community structure of cold-water coral reefs. Further, this project will contribute to enlarge our knowledge on the biology and ecology of these three cold-water coral reefs, as they are all scarcely explored for deep-sea benthic communities. The candidate will use previously acquired seabed imagery (video transects acquired with ROVs), bathymetry data (acquired by MBES) and environmental data (temperature, salinity, oxygen obtained by conventional CTD, CTD attached to the ROV, and benthic landers) to 1) describe the megabenthic community composition and structure, 2) determine the relation between environmental parameters and occurrence of structuring species, and 3) build species distribution models for selected structuring species (i.e., Desmophyllum pertusum), at regional/local level.

This workplan will be carried out in the Centre for Environmental and Marine Studies (CESAM) of the University of Aveiro, the Gijon Oceanographic Centre of the Spanish Institute of Oceanography (IEO), and the Center for Marine Environmental Sciences (MARUM) of the University of Bremen. The selected candidate will work within the framework of the UN Ocean Decade programme “Challenger 150 – A decade to study deep-sea life” (www.challenger150.world (http://www.challenger150.world/)) and will benefit from its vast network of the deep-sea experts.

This work is supported by SCOR (Scientific Committee on Oceanic Research) and progress will be presented regularly to the Portuguese Committee of this research organisation.

Profile of applicants

The candidates should have an academic background in marine science or marine biology, with prior experience in deep-sea ecosystems. Skills and experience in seabed imagery analyses are required and good knowledge in spatial data analyses, GIS and R will be a plus.