The cryptic and transboundary nature of ghost gear in the Maldivian Archipelago

• Main Author: Stelfox, Martin
• Other Authors: Sweet, Michael, Huck, Maren, Beaumont, Nel
• Format: Thesis
• Language: unknown
• Published: University of Derby 2019
• Subjects: fishing gear; abandonded; ghost gear; Arctic; Pacific; Indian; Ridley
• Online Access: https://repository.derby.ac.uk/download/b430d8874206767801e43cdb9b9243fae2222e4ae144d1c9edcc1d879ee7b680/1980/license.txt; https://repository.derby.ac.uk/download/0d2fd80601e2d032281dd3da2d08413cb6ebf6897f741d47b70821c19525dcb0/1031/license_rdf; https://repository.derby.ac.uk/download/5f5490556c04be8abc0c6e7b73cf0cf7fd4a6a4afef256055534549f9cda54c3/6653335/thesis_final.pdf

Abandoned, lost or discarded fishing gear (ALDFG), more commonly referred to as ghost gear, is a global issue that impacts many marine organisms worldwide. In the Maldivian archipelago a large number of olive ridley sea turtles (Lepidochelys olivacea) are found entangled in these nets (more commonly referred to as ghost nets) each year. However, the origin of these nets or turtles are unknown considering fishing with the use of nets is restricted to the bait fisheries within the exclusive economic zone of the Maldives. Therefore, ghost gear has a transboundary and cryptic nature, making it difficult to assess the environmental impact and origin of the gear. This thesis aimed to develop new tools and techniques which could be utilised to examine these unknowns. I revealed in a literature review (Chapter 1) that research in ghost gear entanglements amongst marine megafauna are predominantly focussed in the Atlantic and Pacific Ocean. However, Indian, Arctic and southern Oceans are far less studied. Additionally, the majority of strategies to tackle ghost gear were centred around curative measures, such as ghost gear retrieval. I advise that future solutions, best practices and research should favour preventative rather than curative methods in ghost gear management and research. Statistical classifies (Chapter 2) were built in R to predict the probability of a net entangling a turtle. It was highlighted that nets with larger mesh sizes and the absence of floats were major gear characteristics that increased the likelihood of turtle entanglement. In addition, the time of year was an important variable with a higher chance of turtle entanglements in nets found during the northeast monsoon (November – April). Unfortunately, grouping of the nets by fisheries was not possible, beyond a broad classification. This was likely a result of the wide variety of nets used in the region. However, gill and trawl nets were recognised as high-risk fisheries. Regardless of the difficulties of assigning an origin of the nets, I was ...