Jamie McCoy

Jamie McCoy


Graduated with 1st class honours BSc Marine Biology and Oceanography and with Distinction MRes Marine Biology at the University of Plymouth. My research interests lie within ecophysiology, specifically how factors associated with climate change influence morphology and physiology of marine invertebrates, across multiple life history stages and over multiple generations.

My undergraduate dissertation was titled “Scope for transgenerational acclimation to elevated temperatures in the brackish water amphipod Gammarus chevreuxi (Sexton, 1913)” and involved measuring levels of oxygen consumption through closed chamber respirometry as a proxy for metabolic rate. Masters thesis was titled “Both maternal and embryonic exposure to mild hypoxia influence embryonic development in the intertidal gastropod Littorina littorea (Linnaeus, 1758)”. Using high power microscopy and image analysis software I measured aspects of embryo morphology in developing embryos, and activity levels of hatched veliger larvae, to determine to what extent maternal and embryonic exposure to mild hypoxia (70% air saturation) influenced these traits. Thesis is currently in preparation for publication.

Jamie McCoy

Ecology and Biodiversity

University of Plymouth, School of Biological and Marine Sciences

PhD title: Using novel phenomics technology for environmental sensitivity prediction in marine invertebrates.

Phenomics is the acquisition of high-dimensional phenotypic data (morphology, physiology and behaviour) on an organism wide scale, with the aim of measuring biological responses more robustly.

This PhD will use advanced bio-imaging and image analysis software (EmbryoPhenomics) to measure the sensitivities of early developmental stages of aquatic invertebrates to stressors associated with climatic change, using species with differing modes of development (encapsulated and planktotrophic). Phenomic data will be used to determine lethal and sub-lethal endpoints which can be used as predictive tools.

This technology enabled approach not only allows for the high-throughput acquisition of phenomic data, but allows ‘proxy traits’, traits for which there is no manual equivalent, to be measured.