How will climate change affect foraging decisions and the evolution of personalities in marine predators?

Lead Research Organisation: University of Sheffield
Department Name: Mathematics and Statistics

Abstract

Background: How will animals find food as their environment changes? In marine environments, animals must search across a seemingly featureless ocean, yet successful strategies have evolved. Although recent technology has uncovered fine-details of movement paths, our ability to infer foraging strategies is under-developed. Integration between marine biology and mathematical theory is lacking. Current foraging theory assumes animals have either total (optimal foraging theory, OFT) or zero (random search theory, RST) knowledge of their environment. Yet most animals actually have partial information.

Objectives: We will build models of search with partial information, based on seabird study systems with extensive pre-existing movement data. We will apply our models to these data to answer:
1. Given partial information, what is the optimal foraging strategy for an individual?
2. How important is information in these decisions and how do they vary with the availability of information?
3. Why do different optimal foraging strategies emerge between individuals?
4. What explains these individual differences, including factors such as age, sex, and personality?
5. Which individual strategies are most likely to persist under different climate change scenarios?
Ultimately, we will use our results to predict how personalities within marine communities might evolve as a result of environmental change.

Novelty: (a) By pursuing the mid-point between the OFT and RST we will build a new foraging theory, better suited to real biological systems and accurate predictions. (b) We will shed light on how and why individual differences evolve and are maintained.

Timeliness: Recently, there has been a rapid increase in high-resolution data on seabirds. This makes it possible to develop realistic models of foraging decisions, building on OFT and RST. Despite rapid increases in tracking data, development of models in this area has been slow and now is an ideal time to change this.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S00713X/1 01/10/2019 30/09/2027
2114749 Studentship NE/S00713X/1 01/10/2018 15/07/2024 Poppy Jeffries