Postgraduate research opportunities

On the edge of the abyss: Mathematical modelling of salmon energetics and marine migration

This project combines mathematical modelling of Atlantic salmon migration, foraging, and growth with long-term observational data and high-resolution 3D ocean models to test hypotheses about how climate change, ocean currents, and plankton ecology come together to shape the salmon’s past and future.

Number of places

One

Funding

Home fee, Stipend

Opens

9 December 2020

Deadline

31 January 2021

Duration

42 months

Eligibility

A strong quantitative background (maths, programming) is required, and some knowledge of ecology or oceanography is preferred but not required. The position is suitable for a student with a background in physics, computer science, or an allied field who wants to move into ecological applications, as well as students from a biology or earth-science background with some modelling experience.

Project Details

About the Project

This project combines mathematical modelling of Atlantic salmon migration, foraging, and growth with long-term observational data and high-resolution 3D ocean models to test hypotheses about how climate change, ocean currents, and plankton ecology come together to shape the salmon’s past and future.

Wild Atlantic salmon have played a culturally iconic and economically important role in Scotland and beyond for thousands of years. They are also ecological integrators, moving between freshwater and wide-ranging ocean habitats during their life cycles, and so their population successes or declines offer a window into changing aquatic food webs that also support many other fish, birds, and mammals. In recent decades salmon from UK rivers and farther south in Europe have declined dramatically, despite international agreements regulating fishing and conservation efforts focused on improving freshwater conditions. The main factor behind these declines is thought to be reduced survival during their time in the ocean, and specifically shifts in the diverse zooplankton and small fish that form their diet.

A recent initiative by the international Missing Salmon Alliance (The Likely Suspects Framework, https://missingsalmonalliance.org/likely-suspects-framework) has identified growth during the initial 2-3 months of the salmon’s marine migration as particularly critical. This studentship will assemble a new agent-based model of salmon during their first summer at sea out of three existing sub-models, previously developed for related species or applications:

i) bioenergetics, to integrate the direct dependence of vital rates (ingestion, growth, etc.) on temperature with their dependence on the prey field;

ii) movement strategy, represented as a family of possibilities, including both mechanistic models of directed response to local cues and bounding scenarios (e.g., instant teleportation to the maximum prey concentration within a certain radius),

iii) visual foraging, to encapsulate the dependence on prey size and abundance as well as water clarity

The student will then drive the agent-based model with prey fields assembled from Continuous Plankton Recorder observations, along with outputs from two high-resolution ocean-model hindcasts: the Scottish Shelf Model and the larger-scale AMM7 Northeast European Shelf model.

Specific questions to be addressed by this project include: How variable is the salmons’ prey field during their transit across the continental shelf (i.e. the right taxa in the right region at the right time) and what oceanographic patterns is it associated with? Which of these patterns of variation correlate with historical changes in salmon marine survival? How much do the choices that salmon make—what prey to focus on, which ocean-current system to enter after leaving the continental shelf—matter to survival compared with large-scale changes in their environment? This project is designed to sit at the interface of oceanography and population biology, giving the student transferable skills that will let them carry on to other model- and big-data-based oceanographic problems (water quality, renewable energy planning) or to other problems in conservation and fisheries science.

The project is a partnership between academic ecological modellers at University of Strathclyde in Glasgow, UK, where the position is based; oceanographers with the Scottish Government (Marine Scotland Science); and the conservation NGO Atlantic Salmon Trust. Marine science at Strathclyde consists of an active community of approximately 30 researchers and PhD students from a variety of backgrounds. Tbe student will be encouraged to attend local, European, and overseas conferences and become part of international networks. The studentship is part of the NERC SUPER Doctoral Training Partnership.

The position comes with 3.5 years of support (details below). The start date is 27 Sep 2021.

A strong quantitative background (maths, programming) is required, and some knowledge of ecology or oceanography is preferred but not required. The position is suitable for a student with a background in physics, computer science, or an allied field who wants to move into ecological applications, as well as students from a biology or earth-science background with some modelling experience.

To apply, please start by sending 1) a letter explaining your background and interest, 2) a full CV, and 3) the names and contact info for three references to Dr Neil Banas (details below) by 31 Jan 2021. We will conduct interviews by Zoom in early Feb, and invite successful candidates to apply formally through the Strathclyde U web portal afterwards.

Funding Details

The position provides 3.5 years of support, including a stipend of £14,000 per year, funds to fully cover fees at the UK-student level, and additional funds for travel and other research expenses. We welcome applications from international applicants, but please note that fees for international students exceed the funding available by approximately £10,000 per year. Part-time study is an option, with a minimum of 50% of full-time effort required

Supervisor

The supervisor for this project will be Dr Neil Banas

Further information

For further information please contact Dr Neil Banas

How to apply

To apply, please start by sending 1) a letter explaining your background and interest, 2) a full CV, and 3) the names and contact info for three references to Dr Neil Banas (details below) by 31 Jan 2021. We will conduct interviews by Zoom in early Feb, and invite successful candidates to apply formally through the Strathclyde U web portal afterwards.