Strategic development of the innovative in-line plankton image analysis (PIA) system to fit policy and ecosystem modelling data needs

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Whilst zooplankton are critical for good functioning of marine food webs1 and sensitive to environmental changes2 they remain understudied because of the high costs of the methods generally used to monitor them3. The aim of this timely project is to deliver and prove a much-needed autonomous system for zooplankton analysis4. Primarily based at Cefas, the student will gain extensive experience in sea-going work through taking part in surveys on RV Cefas Endeavour. He/she will also spend at least 3 months with Phil Culverhouse on providing statistical post-processing of data to extend the PIA's utility to end-users. The student will gain in-depth understanding of the techniques and technology used to implement the PIA hardware and software, from optics and computer vision to AI and statistical methods, including Receiver Operator Curves (ROC). Robotics and autonomous systems are a priority for Plymouth University. The well-founded Centre for Robotics and Neural Systems (CRNS) is recognised for world-leading, international excellence in computer science, cognitive robotics and neural computation. CRNS's highly interdisciplinary approach includes collaboration with the Cognition and Marine Institutes. Pitois and Malin (Cefas, UEA) are essentially 'end-users' in this collaboration. They will also ensure the student adopts good scientific practice, and gains the taxonomic, experimental and statistical data analysis skills required to sample and identify marine zooplankton in PIA-derived data. She/he will have the opportunity to experience research application to policy requirements. The student will learn how to do ecological analysis on zooplankton taxonomic identity and abundance data and publish results thereby adding to the state of the art in marine ecology. The student will have access to the members, facilities and activities of all three Institutes. He/she will be encouraged to analyse complex situations and will have the exciting opportunity to drive the development of the PIA. A four-year duration studentship is appropriate given that the work is split between instrument development, field data collection, management and analysis, and theoretical modelling. The objectives in the advertising description above aredesigned to give substantial scope for both training and independent development. Alongside DTP-cohort and PPD training provided by UEA, the student will be part of the graduate programme overseen by Cefas' Science Development Panel. This ensures studentships are monitored individually, identified on Cefas management systems and subject to regular review procedures throughout the duration of the project. Development of the student's communication and networking skills will be furthered through giving presentations at national (e.g. CEFAS, Challenger Society) and international conferences (e.g. ICES), and local meetings and seminars at Cefas, UEA and those run by other stakeholders. Importantly, we will provide the student with training on translating research into practice. All Cefas students are invited to subscribe to the student's social network user-group. They also deliver an annual seminar at the annual student day, that includes their internal and external supervisors.