PLEASE NOTE: Application deadline date 08 Jan 2024. Applications are no longer being accepted for this project
Project Overview
This project will determine present-day habitats of oceanic pelagic sharks from modelling satellite-tracked animal space-use and environmental data. Future predictions of shark habitat suitability will then be made using Earth System Models and climate projection datasets to provide new understanding of how climate change will alter distributions of threatened species.
Project Description
Shifts in abundance and distributions of marine organisms are occurring globally as a major consequence of climate change. Marine fish are no exception, with significant changes documented across broad taxa. However, the effects of climate change on the habitats of oceanic sharks are poorly understood. For example, in the North Atlantic Ocean, there are currently no whole-ocean predictions available for how pelagic sharks may respond to future environmental changes. Additionally, overfishing of many pelagic shark species by high-seas fisheries has resulted in dramatic declines in relative abundance documented for many species. Consequently, there is an urgent need to understand how ocean climate change will affect shark habitats, which may interact with fisheries to further impact future sustainability of populations. The aim of this project is to use a unique database of the movements of 2,000 satellite-tracked pelagic sharks (focusing on key species including blue and shortfin mako sharks) and 3-D environmental variables from oceanographic databases, to predict ocean-wide or global habitat suitability of shark species. Validated present-dayhabitat suitability maps will be then be used to model future shark habitats by applying Earth System Models and climate projection datasets (e.g. CMIP6), with a focus on ocean regions undergoing more rapid warming and deoxygenation (e.g. eastern tropical Atlantic). The planned outputs will provide new estimations of future shark distributions at ocean scales and what this might mean for shark conservation given potential increased overlap with current distributions of human-induced threats such as fishing.
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 Marine Biological Association.
Specific training will include:
- Programming, testing and deploying telemetry and bio-logging tag devices on sharks
- Satellite track processing methods, track reconstruction and statistical and spatial analysis of movement data
- Working with large environmental datasets including processing, management, mapping and spatial analyses
- Species distribution modelling (using methods such as Generalised Additive Models or Bayesian Additive Regression Trees) with a focus on animal datasets
- Working with Earth System Models and climate projection datasets (e.g. CMIP6) including sourcing, processing and mapping projections.
Vedor, M., Queiroz, N., Mucientes, G., Couto, A., da Costa, I., dos Santos, A.M., Vandeperre, F., Afonso, P., Fontes, J., Rosa, R., Humphries, N.E., Sims, D.W. (2021) Climate-driven deoxygenation elevates fishing vulnerability for the ocean’s widest ranging shark. eLife 10, e62508. https://elifesciences.org/articles/62508
Braun, C.D., Farchadi, N., Alexander, M., Afonso, P., Allyn, A., Bograd, S., Brodie, S., Crear, D.P., Culhane, E.F., Curtis, T.H., Hazen, E.L., Kerney, A., Lezama-Ochoa, N., Mills, K.E., Pugh, D., Queiroz, N., Scott, J.D., Skomal, G.B., Sims, D.W., Thorrold, S., Welch, H., Young-Morse, R., Lewison, R. (2023) Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications 33, e2893. https://doi.org/10.1002/eap.2893
Braun, C.D. et al. (2023) Widespread habitat loss and redistribution of marine top predators in a changing ocean. Science Advances 9, eadi2718.
https://www.science.org/doi/10.1126/sciadv.adi2718
