Spatial Analysis of Volcano Distribution in the Hawaii-Emperor Seamount Chain

Abstract

The distribution of ocean island Volcanoes is a topic surrounded with much uncertainty. We employ spatial recognition algorithms utilising the Hough Transform to determine the best fitting geometry of the Hawaii-Emperor Seamount Chain. Through the use of statistical analysis algorithms such as the Akaike Information Criterion (AIC), we demonstrate that the best fitting geometry of these seamount chains is a segmented great circle, in comparison to single and segmented small circle distributions, both of which have previously been proposed as a best fitting model. We show that the Hawaiian Chain is segmented into 10 great circles, and the Emperor Chain, is best described by 5 great circles. We also identified through the use of the AIC, that the Emperor Seamount chain is significantly better fitted to a segmented great circle distribution in comparison to the Hawaiian Chain. After consulting plate reconstructions, we propose that the segmentation of the Hawaiian Emperor seamount chain is influenced by tectonic events at the edge of the Pacific plate which are contemporaneous with ocean island magmatism, which we refer to as ‘neo-tectonic events’. These neo-tectonic events are believed to affect the stress regimes within the plates, for example over the Hawaiian mantle plume. This can then lead to a preferential area for the intrusion of magma into the oceanic lithosphere, creating these focused zones of magmatism we observe as segmented great circles. We also show that controls which may be linked to the creation of segments are not linked to the formation and creation of seamounts and that these are likely to be under the influence of local forces such as gravitational loads. Finally, we note that due to the complexity, intricacy and lack of data surrounding the Hawaii-Emperor Bend, our model may not be the best fitting for this part of the Seamount Chain.