Drivers of life history complexity in the world’s longest living algae

Overview

Marine calcifying ‘ecosystem engineers’ such as corals and red coralline algae support ecosystem services and provisions worth $billions every year. The defining physical feature that enables these benefits is a complex 3-dimensional calcium carbonate skeleton. However, it remains unclear what controls skeletal complexity, preventing us from understanding how, why and where these habitats form. This is despite their global biological and biogeochemical importance, and the severe threat posed by our rapidly changing climate.

Free-living red coralline algae are the most widely distributed habitat-forming marine algae (found from the poles to the tropics, and from the intertidal to 300+ m below the ocean surface). However, meaningful growth experiments on calcifying marine organisms are impossible due to their slow growth rates (<1 mm per year) and long lifespans (decades-centuries). An alternative computational approach is therefore needed that doesn’t rely on real-time experimentation.

The aim of this project is to determine the importance of environmental variability in the complexity of red coralline algal growth, utilising an innovative multidisciplinary approach that translates recent developments in medical imaging to answer an ecological question. Results of this work will progress our fundamental understanding of algal reef formation, with important implications for the impact of climate change and their future conservation.

Methodology

The student will have the opportunity to support field collection of different red coralline algal species for subsequent analysis and comparison. Comparison in growth patterns between and within species will be possible through the acquisition of samples from colleagues in Europe and Brazil. Life history complexity analyses will be achieved through the development of a novel methodology that combines micro-Computed Tomography and machine learning algorithms to reconstruct the algal structure and growth over time. Time series analyses will enable the student to identify the key environmental drivers controlling algal growth, utilising already-available records of various environmental parameters (e.g. temperature, salinity, pH, cloud cover). Habitat-scale analyses may also be possible by scaling up the analytical pipelines to 3D habitat models of the natural algal reefs. Projected changes in algal growth and complexity will be modelled using IPCC climate projection scenarios, enabling visualisation of future algal reef structures and significantly improving our understanding of how climate change will impact calcified algae and the services they provide.

Project Timeline

Year 1

Literature review, field sample collection, analytical pipeline technique development

Year 2

Pipeline optimisation, sample analysis & interpretation, presentation at a national conference

Year 3

Sample analysis & interpretation, write-up for publication, presentation at an international conference

Year 3.5

Writing-up of results and completion of thesis, submission of papers for publication

Training
& Skills

Project support: The facilities, equipment and expertise available within the institutions and supervisory team provide a combination of world-leading analytical, field and laboratory capability and technical support that ideally fits this PhD project, maximising the expert training that will be available. In particular, the Lyell Centre’s 3D visualisation suite provides a unique facility for data analysis and interpretation.

This project will equip the student with a range of skills, including and multidisciplinary. Specific research skills will include:
• Machine learning
• Convolutional neural networking
• High performance computing
• Time series analysis
• Micro-Computed Tomography
• Environmental statistics

Student support: The Lyell Centre has a large research student cohort that will provide peer-support throughout the studentship, including participation in the annual post-graduate research conference. All project supervisors are also highly research-active: the student will interact with all members of their research groups through lab-group meetings at the Lyell Centre, the School of Mathematical and Computer Sciences at Heriot-Watt University and the University of Glasgow, providing an opportunity to learn about other techniques and research areas which may be applicable to their research. All supervisors are based in research-active departments that span a broad range of ecological, environmental, geoscience and mathematical research, exposing the student to a range of other research areas. Active participation in these research groups will provide the opportunity to discuss cutting-edge topics in the field, review recent papers and to present current research plans to academics/researchers with a common research interest in an informal and supportive atmosphere.

Where required, and to maintain continued professional development, the scholar will be supported to attend specialist courses directly aligned to the project:
• Machine learning
• Parallel optimisation
• 3D data visualisation
• Analytical training will be provided by the supervisors and / or specialist technicians for each methodology required.
• The project supervisors will also support and encourage the scholar’s attendance on transferable skills training such as data management, scientific writing and science communication. These are provided for free within Heriot-Watt University’s ‘Research Futures Academy’.

References & further reading

Zeleznik R, Foldyna B, Eslami P, Weiss J, Alexander I, Taron J, Parmar C, Alvi RM, Banerji D, Uno M, Kikuchi Y. Deep convolutional neural networks to predict cardiovascular risk from computed tomography. Nature communications. 2021 Jan 29;12(1):1-9.

Zawada KJ, Madin JS, Baird AH, Bridge TC, Dornelas M. Morphological traits can track coral reef responses to the Anthropocene. Functional Ecology. 2019 Jun;33(6):962-75.

McCoy SJ, Kamenos NA. Coralline algae (Rhodophyta) in a changing world: integrating ecological, physiological, and geochemical responses to global change. Journal of phycology. 2015 Feb;51(1):6-24.

Further Information

In the first instance, enquiries should be directed to the primary supervisor, Dr Heidi Burdett (h.burdett@hw.ac.uk). Please indicate why you are interested in this project.

For eligible candidates, funding is available to cover tuition fees, stipend and research costs. However, please note that this project is in competition with others for funding, and success will depend on the quality of applications received.

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