Abstract

The abyssal environment remains one of the most poorly studied parts of the planet. While predominantly an environment dominated by soft sediments, some abyssal regions are known to harbour potato-sized, rock-like formations known as polymetallic nodules. These nodule provinces are now the subject of exploration by nations and their nominated contractors keen to develop a new deep-sea mining industry. This new industry has the potential for large-scale environmental impacts, but at present these impacts are difficult to predict, and therefore mitigate, as a result of the lack of ecological data and scientific understanding of these areas. The studies carried out in this thesis aimed to contribute to our understanding of the epibenthic megafauna communities in areas targeted for mining, and to support the environmental management of mining activities through informing recommendations on environmental survey design and spatial planning. Imagery from nine transects of 800 m2 in the central Clarion Clipperton Fracture Zone (CCZ) were analysed to describe the epibenthic megafaunal communities at both regional (>1 000 km) and local (2 km) scales. The relationship between biological data derived from image analysis and modelled environmental data was examined to determine potential drivers of community composition and diversity, and rarefaction and extrapolation curves were used to assess levels of sampling required to establish baseline faunal assessments. Finally, clustering algorithms were used to classify broad-scale, modelled environmental data into different habitat types, to assess the effectiveness of the existing protected area network in the CCZ. Megafauna morphotypes most vulnerable to mining, including rare, nodule-specific, suspension feeding, and sessile organisms, formed a large proportion of the CCZ epibenthic megafauna. Several dominant morphotypes were homogenous over large scales, but there was high turnover of rare morphotypes at regional and local scales. In addition, broad-scale bathymetric position index was identified as an important driver of both megafauna and metazoan diversity at regional scales. To characterise the community at 99% sample coverage, sampling units of ~2 800 - 4 600 m2, or 780 - 960 individuals, were required, with 26 - 27 x 800 m2 replicate transects. This sampling effort was much greater than is generally used in the deep sea. Finally, a top-down, broad-scale habitat classification of the CCZ identified 46 habitat types and revealed that many of these were underrepresented in the current protected area network, with several occurring almost exclusively in mining areas. The body of research contained in this thesis suggests that 1) those morphotypes most vulnerable to mining form a substantial proportion of the megafauna communities in the CCZ, 2) greater sampling effort is required to fully characterise baseline environmental conditions of the CCZ, and 3) the current protected area network established in the CCZ does not adequately capture the range of habitats present. This thesis advocates for the use of Regional Environmental Assessment to address some of the pressing issues preventing progress in environmental management of deep-sea mining.

Keywords

Deep-sea, Ecology, Abyss, Polymetallic nodule, Deep-sea mining, CCZ, Habitat classification, Megafauna, Marine Spatial Planning, Environmental Management

Document Type

Thesis

Publication Date

2020

DOI

10.24382/469

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