Journal articles and Discussion papers
Abstract
Predictive habitat models are increasingly being used by conservationists, researchers and governmental bodies to identify vulnerable ecosystems and species’ distributions in areas that have not been sampled. However, in the deep sea, several limitations have restricted the widespread utilisation of this approach. These range from issues with the accuracy of species presences, the lack of reliable absence data and the limited spatial resolution of environmental factors known or thought to control deep-sea species’ distributions.
Recent revisions to the satellite-derived vertical gravity gradient (VGG) data reveal more detail of the ocean bottom and have allowed us to develop a non-linear inversion method to detect seamounts in VGG data. We approximate VGG anomalies over seamounts as sums of individual, partially overlapping, elliptical polynomial functions, which allows us to form a non-linear inverse problem by fitting the polynomial model to the observations.
Keynote address at 2021 Science to Policy meeting
