A biogeography of the mesopelagic community
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There are a large number of research vessels and fishing vessels equipped with echosounders plying the world ocean, making continual observations of the ocean interior. Developing data collation programmes (e.g. Integrated Marine Observing System) and automated, repeatable analyses techniques enable the upper c. 1,200 meters of the world ocean to be sampled routinely, and for their characteristic deep scattering layers (DSLs) to be compared. Deep scattering layers are comprised of zooplankton (e.g. euphausiids) and fish, particularly myctophids or lantern fish, and comprise the majority of sub-surface biomass. Here we present, by the analysis of a global acoustic dataset, a mesopelagic biogeography of the sea. This was accomplished by (i) the collation and processing of a global active acoustic dataset, (ii) the development of a standardised and automated method of sound scattering layer (SSL) extraction and description, (iii) the derivation of the environmental drivers of DSL depth and biomass, (iv) the definition of a mesopelagic biogeography based on the drivers of DSL metrics and (v) the prediction, using output from the NEMO-MEDUSA-2.0 coupled model, of how the metrics and biogeography may change by 2100. Key findings include, the development of the Sound Scattering Layer Extraction Method (SSLEM) the inference that primary production, water temperature and wind stress are key drivers in DSL depth and biomass and that mesopelagic fish biomass may increase by 2100. Such an increase is a result of increased trophic efficiency from the shallowing of DSLs and rising water temperatures, suggesting, that as the climate warms the ocean is becoming more efficient. The biophysical relationships and biogeography derived here, serve to improve our understanding of mesopelagic mid-trophic level dynamics in open-ocean ecosystems. This will aid both fisheries and conservation management, which now adopt more holistic approaches when monitoring and evaluating ecosystem health and stability.
Thesis, PhD Doctor of Philosophy
Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/
Embargo Date: 2017-08-30
Embargo Reason: Thesis restricted in accordance with University regulations. Print and electronic copy restricted until 30th August 2017
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