Beyond species on the move: characterising Southern Ocean bioregions and communities under present and future climates

Jennifer Freer, British Antarctic Survey (BAS); Ryan Reisinger, University of Southampton,; Sophie Fielding, BAS

PLEASE NOTE:  Application deadline date 08 Jan 2024.  Applications are no longer being accepted for this project

Project Overview 

Using the latest climate models and novel spatial analyses, this PhD will investigate the biogeographic and ecological characteristics of pelagic bioregions in the Southern Ocean. Projecting these bioregions under future climate storylines will identify ecological risks, climate winners and losers, and provide outputs that can guide climate-smart ecosystem management.

Project Description 

Throughout the ocean, many taxa have, and will continue to, undergo poleward shifts in distributions in line with climate warming. While predictions of species distributions now exist for various Southern Ocean pelagic species (including zooplankton, fish [1] and top predators [2]), effective conservation and management of this unique region requires a holistic understanding of how communities as a whole will respond. The aim of this PhD is to delineate and assess climate impacts on “bioregions”, defined as geographic areas with distinct assemblages and ecological communities [3].

The project will have a strong emphasis on “big data” analysis, spatial statistics and habitat mapping. It will involve compiling available range maps across diverse trophic levels, complementing these with the creation of novel outputs for under-represented trophic groups and life-history stages via methods such as ecological niche modelling. Statistical clustering analyses will be performed to define bioregions and to investigate their underlying environmental correlates (e.g. temperature, primary productivity). Projecting bioregion shifts under future conditions will use climate models taken from Coupled Model Intercomparison Project (CMIP6) model reanalysis. Analysis of climate impacts between present and future conditions (e.g. bioregion extent, connectivity, and community structure) will be conducted in a programming environment such as R. There is potential to explore the integration of novel machine learning or AI methods, including processing primary datasets or developing visualization tools. There may be opportunities to attend and present at national and international stakeholder meetings in collaboration with the conservation and management team within BAS Ecosystems.  

British Antarctic Survey, Cambridge

The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted at the British Antarctic Survey. Specific training will include:

  • General scientific computing and data analysis
  • Application of machine-learning tools to large datasets
  • Handling and analysis of oceanographic and biological datasets
  • Ecological and spatial statistics, including species distribution modelling
  • Handling and application of Coupled Model Intercomparison Project (CMIP6) model outputs with subsequent forecasting.

Preparation of scientific outputs that are policy-relevant.

Eligibility & Funding Details: 
Background Reading: 

[1] Freer JJ, Tarling GA, Collins MA, Partridge JC, Genner MJ. Predicting future distributions of lanternfish, a significant ecological resource within the Southern Ocean. Diversity and Distributions. 2019; 25: 1259– 1272.

[2] Reisinger RR, Corney S, Raymond B, Lombard AT, Bester MN et al. (2022). Habitat model forecasts suggest potential redistribution of marine predators in the southern Indian Ocean. Diversity and Distributions, 28, 142– 159.

[3] Reisinger RR, Brooks C, Raymond B, Freer JJ, et al. (2022) Predator-derived bioregions in the Southern Ocean: Characteristics, drivers and representation in marine protected areas. Biological Conservation, 272:109630