The Plankton Imager. a novel tool for the automated and continuous sampling of zooplankton.

Scott, James (2023) The Plankton Imager. a novel tool for the automated and continuous sampling of zooplankton. Doctoral thesis, University of East Anglia.

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Abstract

Marine zooplankton have global ubiquitous distribution and are fundamental in the ocean carbon cycle, as prey for planktivores and use as indicators for ecosystem health. Recent impetus has been on developing cost effective methods to better sample the plankton. As a result, imaging devices are becoming synonymous with plankton sampling. This study contributes to the development, and demonstrates the ecological application, of a novel plankton imaging instrument: the Plankton Imager (PI). The PI is a continuous, automated instrument that uses water pumped onboard a ship and images all particles present. The images can be resolved to a moderate (family-level) taxonomic resolution by experts. This method revealed strong temporal changes in the zooplankton community of the Celtic Sea where interannual variation was greater than seasonal. In order to better harness the continuous nature of the PI, temporal subsampling (classifying 1 in 10 images) allowed for greater spatial coverage at finer resolution. This approach revealed that the choice of sampling resolution must be appropriate to the scale of the ecological process as decreasing spatial resolution had a considerable effect on the strength and significance of the relationship between zooplankton biomass and their phytoplankton prey. Concurrently with development of the instrument, machine learning classifiers, capable of classifying the millions of images the PI collects per day, have been developed. Application of a machine learning classifier to PI images resulted in zooplankton dataset with very fine spatiotemporal scales where data could be resolved to minutes or meters. These data were aligned with other continuous datasets to re-evaluate relationships with predatory commercial pelagic fish using finer scale data. This thesis demonstrates the PI, and similar instruments, are a cost effective method that can provide a similar description to existing methods as well as provide new insight into plankton ecology by yielding fine spatiotemporal data.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Environmental Sciences
Depositing User:	Chris White
Date Deposited:	29 Mar 2023 08:49
Last Modified:	29 Mar 2023 08:49
URI:	https://ueaeprints.uea.ac.uk/id/eprint/91701
DOI:

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