Biogeographical patterns in the deep ocean: environmental, biological, and historical drivers in the North Atlantic.

The goal of the PhD project is to create a dynamic new deep ocean biogeographic classification tool depicting biogeographic patterns over space and time under present-day and under future climate change scenarios. This will be conducted through validation and refinement of the existing marine biogeography classification system for the deep ocean, GOODS (Global Open Oceans and Deep Seabed) tool developed by IOC-UNESCO (UNESCO, 2009).

The health and wealth of nations bordering the world’s seas and oceans depend on the sustainable management of marine resources. Atlantic economies looking to Blue Growth opportunities for resource exploitation are gathering interests in harvesting these resources from the deep ocean. Yet vast areas of the deep sea are inhabited by fragile ecosystems and long-lived, late-maturing species that need protection from exploitation. Biogeographical information helps policy-makers prioritise areas and species for protection (Rice et al. 2011), while vastly improving the understanding of how the environment, ocean history, and the inherent biological properties of the species themselves shape the distribution of marine life.

A major goal of the EU Horizon 2020 Project “ATLAS” (www.eu-atlas.org) is to provide robust new adaptive decision-making tools for policy makers in an era marked by rapid climate change and evolving resource exploitation scenarios. This PhD project is designed to work with ATLAS partners in Canada, the USA and Europe to help fill this gap in policy provision for deep ocean resources.

With a special focus on the North Atlantic Ocean, the PhD candidate will integrate the latest sources of biological information (ground-truthed taxonomic samples, deep-sea video, and predicted species distribution models) under present-day and future climate scenarios to validate the biogeographic provinces delineated by GOODS. Currently, the GOODS tool is based on the distribution of a range of physico-chemical variables. It lacks validation with species data particularly from complex seabed habitats (Watling et al., 2013), and is not dynamic with respect to how environmental variables will change under the future climate regimes predicted by the Intergovernmental Panel on Climate Change (IPCC).

The candidate will also use this species information to statistically model the importance of environmental variables including water mass structure, the biological traits of the species themselves, and the impact of historical factors such as glacial cycles (Henry et al., 2014) to improve the understanding of drivers of biogeographic patterns in the deep ocean.

A special emphasis of the PhD project will be placed on the biogeography of fauna from complex seabed habitats such as cold-water coral habitats, cold seeps, hydrothermal vents, sponge grounds and Vulnerable Marine Ecosystem (VME) indicator species to validate GOODS with respect to benthos. The candidate will also be given the flexibility to choose an additional group of marine fauna to validate and refine the GOODs model. This could include migratory or sessile species, pelagic or benthic, from sharks to sponges, allowing the PhD candidate to validate GOODS in either the pelagic open ocean or deep seabed and to model the environmental, biological, and historical factors that shape this biogeography.