Overview
Research Role
NERC GW4+ PhD Student, University of Exeter 2019-2023
Prior Research
MSci Zoology, University of Bristol 2015-2019
I obtained an MSci Zoology from the University of Bristol back in 2019, with my master’s research project being ‘Lights Camouflage Action! The concealment of motion by dynamic caustic lighting’ which aimed to investigate whether sinusoidal motion enhances the motion masking effect of dynamic lighting
In my third year, I conducted a literature review ‘The Climb of Birds, the evolution of arboreality in theropod dinosaurs’ which reviewed when and where arboreality evolved in bird-line theropods. After my third year, I spent 6 weeks conducting an ASAB funded research project looking at the function of the ‘mesmerising display of the broad clubbed cuttlefish’ and whether it influences predator detection of shore crabs (Carcinus maenas).
Qualifications
2015-2019, MSci Zoology, University of Bristol
Research
Research interests
Project Title: The role of camouflage in the conservation and survival of ground-nesting birds.
Supervisors: Jolyon Troscianko, Martin Stevens, Innes Cuthill, Andy Hoodless
Funding Body: NERC GW4+, 2019-2023
Project Description: My project aims to determine whether different land-management techniques affect the camouflage efficacy of lapwing nests and how they might be modified to best compliment their camouflage and survival success. I will first investigate which aspects of camouflage, light environment and three-dimensional habitat structure, correlate best with nest survival by using calibrated animal-vision imaging and 3D scanning techniques to compare predicted camouflage efficacy with nest survival. Any causal-links found between land-management and camouflage efficacy will then be tested through controlled predation experiments, using 3D printed lapwing eggs with animal-vision calibrated colour printed patterns.
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Hancock GRA, Troscianko J (2022). CamoEvo: an open access toolbox for artificial camouflage evolution experiments.
Evolution,
76(5), 870-882.
Abstract:
CamoEvo: an open access toolbox for artificial camouflage evolution experiments.
Camouflage research has long shaped our understanding of evolution by natural selection, and elucidating the mechanisms by which camouflage operates remains a key question in visual ecology. However, the vast diversity of color patterns found in animals and their backgrounds, combined with the scope for complex interactions with receiver vision, presents a fundamental challenge for investigating optimal camouflage strategies. Genetic algorithms (GAs) have provided a potential method for accounting for these interactions, but with limited accessibility. Here, we present CamoEvo, an open-access toolbox for investigating camouflage pattern optimization by using tailored GAs, animal and egg maculation theory, and artificial predation experiments. This system allows for camouflage evolution within the span of just 10-30 generations (∼1-2 min per generation), producing patterns that are both significantly harder to detect and that are optimized to their background. CamoEvo was built in ImageJ to allow for integration with an array of existing open access camouflage analysis tools. We provide guides for editing and adjusting the predation experiment and GA as well as an example experiment. The speed and flexibility of this toolbox makes it adaptable for a wide range of computer-based phenotype optimization experiments.
Abstract.
Author URL.
Publications by year
2022
Hancock GRA, Troscianko J (2022). CamoEvo: an open access toolbox for artificial camouflage evolution experiments.
Evolution,
76(5), 870-882.
Abstract:
CamoEvo: an open access toolbox for artificial camouflage evolution experiments.
Camouflage research has long shaped our understanding of evolution by natural selection, and elucidating the mechanisms by which camouflage operates remains a key question in visual ecology. However, the vast diversity of color patterns found in animals and their backgrounds, combined with the scope for complex interactions with receiver vision, presents a fundamental challenge for investigating optimal camouflage strategies. Genetic algorithms (GAs) have provided a potential method for accounting for these interactions, but with limited accessibility. Here, we present CamoEvo, an open-access toolbox for investigating camouflage pattern optimization by using tailored GAs, animal and egg maculation theory, and artificial predation experiments. This system allows for camouflage evolution within the span of just 10-30 generations (∼1-2 min per generation), producing patterns that are both significantly harder to detect and that are optimized to their background. CamoEvo was built in ImageJ to allow for integration with an array of existing open access camouflage analysis tools. We provide guides for editing and adjusting the predation experiment and GA as well as an example experiment. The speed and flexibility of this toolbox makes it adaptable for a wide range of computer-based phenotype optimization experiments.
Abstract.
Author URL.
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