e(lasmo)DNA : the role of environmental DNA (eDNA) analysis in marine fish biodiversity assessment, with special focus on elasmobranchs

Knowledge of spatial and temporal variation in abundance is critical for the implementation of effective protective measures for organisms that are both naturally rare and vulnerable to exploitation. Therefore, the development of management and conservation strategies for taxa like teleosts and elasmobranchs, depends on the accurate assessment and monitoring of the distribution and abundance of target species. However, detecting species occurrences is often even more challenging in the aquatic environment than on land. Consequently, as is the case for many mobile, and often rare, vertebrates, fish (and particularly shark) detection is inherently difficult. Environmental DNA metabarcoding, based on the retrieval of genetic traces (skin cells, metabolic waste, etc.) naturally released in the environment, is emerging as a non-invasive method for the detection and identification of rare and elusive species in a wide range of ecosystems, including aquatic environments. My thesis addresses the development and application of an environmental DNA (eDNA) approach for the assessment of marine communities, and particularly of elasmobranch species. This novel eDNA approach was developed to investigate elasmobranch diversity in order to assess species richness in areas of special conservation concern. While simultaneously examining the influence of interacting factors such as habitat type and conservation regime in determining diversity and abundance. Additionally, the performance of eDNA analysis was compared with more traditional sampling methods. Moreover, the performances of multiple markers for the detection and characterization of both elasmobranch and teleost diversity were tested and evaluated. The potential implications of eDNA for fish, and larger scale marine community assessment and monitoring, spatial planning and fisheries management are significant.

Level dc:type.qualificationlevel

Doctoral (Level 8)

Year dc:date.issued

2026

Author dc:creator

• Bakker, J

Language dc:language

en

Identifier

oai:salford-repository.worktribe.com:1382225

Author Identifier

0000-0001-7163-6565

OAI identifier oai:identifier

oai:salford-repository.worktribe.com:1382225