Evaluating the abundance of abyssal megafauna using an autonomous imaging platform

Evaluating the abundance of abyssal megafauna using an autonomous imaging platform

Bailey

A major limitation in the study of the ecology of the deep-sea is the collection of sufficient data for quantitative analysis. High-quality data on the abundance and distribution of deep-sea life are essential to understand the role of the abyss in the climate and carbon cycle. The vast majority of life in the deep sea depends on food inputs of particulate organic carbon (POC) that sink from productive surface waters. Fauna on the seafloor thousands of metres below have been shown to be readily influenced by climate-driven changes in food quantity and quality (e.g. Ruhl et al. 2008, Smith et al. 2009) and the influence of fishery activity (e.g. Bailey et al. 2009). Understanding what controls the distribution and abundance of the abyssal benthos is important because these fauna influence how much of the POC that sinks to the seabed remains in the ocean or becomes buried in sediments for eons. Animals living on the abyssal seafloor thus play an important role in the global carbon cycle over the majority of Earths surface, but our understanding of the distribution, abundance, and ecological function of these fauna remains among the lowest of any habitat.

We propose a solution to help overcome this problem by utilising a newly developed autonomous vehicle to collect high-quality data at an unprecedented range of scales on the type, location, size, abundance, and distribution of deep-sea megafauna. Information about spatial variation in taxon-specific abundance, community composition and structure, and biodiversity will be collected synoptically with bathymetric and other environmental data over a range of scales previously impractical in abyssal research. We will be able to quantify gaps in understanding of spatial patterns in deep-sea ecology in a way not formerly possible. Enhanced understanding of spatial relationships will improve assessments of anthropogenic impacts on oceanic carbon budgets. The techniques proposed here will enhance national capability in habitat mapping and ecological research over vast areas of the ocean, including the Arctic frontier.