Samuel Shrimpton

Profile

Project title: Predicting the response of endangered sea turtles to a changing climate

Summary: Rapid climate change is associated with the alteration of species’ distributions. Marine turtles are disproportionately vulnerable to changes in climate as temperature plays a significant role in dispersal, foraging migration and sex determination. As sea turtles display high site fidelity to natal breeding areas, they are vulnerable to both habitats becoming climatically unsuitable, and climate-induced biogeographic range shifts pushing foraging locations beyond the reach of swimming capacity. Understanding the degree to which climate change alters population movements and dynamics will be critical to ascertain how the distribution of global turtle populations may change in the future. 

In order to predict how the biogeographic distributions and habitat utilization of metapopulations may change in the face of climate change, my project will focus on the behavioural and environmental determinants of turtle movements. Specifically, I will use newly developed affordable GMS-relayed tags on nesting loggerhead turtles in Cabo Verde to capture both environmental and social determinants of movement off the coast from their nesting habitats. This will be achieved by tagging all turtles nesting on a given beach on a single night. The interactions among those turtles will then be modelled to understand the contribution of social interaction to the population movement. Following this experiment, turtles across multiple islands will be tagged to assess how local environmental conditions impact species movement. Behavioural, social, and environmental data will be collated to parametrise an individual-based model that will be used to the predict the spatial movement/displacement of turtles. Existing predictions for future change in ocean environments will subsequently be used to forecast future whereabouts of turtles, considering all environmental and social components of their movements. There are accurate descriptions of turtle populations across the globe. Our models will be applied to all rookeries to obtain a better representation of the risks of local population extinctions.

Supervisors

• Dr Axel Rossberg
• Dr Christophe Eizaguirre

Research