My work focuses on the use of machine learning approaches to understand the drivers of the movements of sharks and tuna, then predictively map these species to inform conservation management. I have developed software that automates and facilitates the use of Boosted Regression Tree techniques to ecological data, advancing the use of this approach among the shark community. Areas of study have been sharks off the coast of southern England, rays in the Irish Sea, lemon sharks in the Bahamas, anchovy off California, tuna in the North Atlantic, and sawfish off Florida.
Queiros, A. M., Talbot, E., Beaumont, N. J., Somerfield, P. J., Kay, S., Pascoe, C., … Nic Aonghusa, C. (2021). Bright spots as climate-smart marine spatial planning tools for conservation and blue growth. Global Change Biology.
Bangley, C. W., Paramore, L., Dedman, S., & Rulifson, R. A. (2018). Delineation and mapping of coastal shark habitat within a shallow lagoonal estuary. PloS One, 13(4), e0195221.
Dedman, S., Officer, R., Clarke, M., Reid, D. G., & Brophy, D. (2017). Gbm.auto: A software tool to simplify spatial modelling and Marine Protected Area planning. PloS One, 12(12), e0188955.