Date of Award


Document Type

Open Access Thesis




Geological Sciences

First Advisor

Scott White


The Alarcon Rise is the only submarine oceanic spreading ridge setting where rhyolitic lavas have been found. This intermediate-rate spreading ridge provides a unique natural laboratory for studying the geomorphology of felsic submarine lava flows at oceanic spreading ridges. Seafloor observations of felsic lava indicate the flow morphology differs from typical submarine basaltic lava at the few other oceanic spreading ridges where differentiated compositions have been recorded. Morphologic variation between mafic and felsic lava flows, especially rhyolites, was also observed at Alarcon Rise.

The Monterey Bay Aquarium Research Institute conducted mapping surveys with autonomous underwater vehicle D Allan B. in 2012 and 2015. The 1 m lateral resolution bathymetry produced from these surveys allowed sampling expeditions with the remotely operated vehicle Doc Ricketts in 2012 and 2015. We recovered all felsic lava samples along a ridge at the heavily-faulted north end of Alarcon, just south of the Pescadero Transform Fault. The ridge included a steep sloping, sub-rectangular rhyolitic complex. Angular, blocky spires at this complex are spaced ~10 m apart, appearing jagged in the 1 m resolution bathymetry.

To determine if morphology can be used to identify compositional variation in lava, we produced a semi-automated pixel-based classification that identifies geomorphic characteristics we believe to be indicative of felsic lava flows. We constructed an adaptive-neuro fuzzy inference system to distinguish between the jagged, rough lava flows produced by felsic lavas and smooth basaltic lava flows. To capture the steep sloping high-silica dome features, we derived local max slope over a 3 m distance from the 1 m resolution bathymetry. We also calculated bathymetric position index at a 0.5 km radius to distinguish the surface roughness in the felsic region from smoother basaltic flows at Alarcon Rise. Our classification is the first attempt at automating recognition of compositional variation of lava erupted at oceanic ridges.

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