IAN R. BRADBURY

Canada

BIOGRAPHY

Dr Ian Bradbury is a research scientist with the Department of Fisheries and Oceans and is the Cox Fisheries Scientist in residence at Dalhousie University. Originally from Newfoundland he completed his PhD in 2007 at Dalhousie University and started with DFO in 2010. His research uses genomic tools to inform the conservation and management of both marine and anadromous species from throughout Atlantic Canada. Specific work focuses on identifying the genomic basis of marine climate associated adaptation, developing genetic baselines for individual identification in multiple species, and quantifying the impacts of escaped farmed salmon on wild populations. 

Advances in DNA sequencing technology have fundamentally changed the field of population genetics, allowing genome-wide patterns of spatial divergence and linkage disequilibrium to be examined on scales previous impossible. This presents huge potential for application to marine conservation and fisheries management, but also brings challenges both logistical and theoretical.  Here I explore potential advances that the emerging field of population genomics may hold for fisheries management, focusing on the benefits, limitations, and the challenges that remain. Specifically, I will examine how a high resolution genome-wide perspective can alter our interpretation of marine population structure, contributes to our understanding of fishery associated exploitation, and enhances predictions of future stock productivity and distribution patterns. Genomic studies increasingly report cryptic diversity in exploited marine species, which is  revealing a need for changes in the geographic scales of management, but also complicated by substantial variation in differentiation across the genome and among methods. Using new genomics-based descriptions of stock structure, stock specific exploitation can be resolved at spatial scales previously not possible. However, logistical challenges such as the design and assessment of informative panels of loci from huge datasets remains a source of significant bias and error. Similarly, marine genomic data integration with high resolution environmental and habitat data are allowing the prediction of future distribution patterns under marine climate change scenarios. In the near future, environmental DNA (eDNA) may enable monitoring of species distribution and abundance changes as they occur.  Genomic applications in fisheries science offer the potential for significant advances to the management of marine resources, yet will undoubtedly require continued consideration of the logistical and theoretical limitations if potential gains are to be fully realized. 

KEYNOTE ADDRESS