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Acoustic predictors of active fluid expulsion from a hydrothermal vent field, offshore Taupo; Volcanic Zone, New Zealand


Spain, EA and Lamarche, G and Lucieer, V and Watson, SJ and Ladroit, Y and Heffron, E and Pallentin, A and Whittaker, JM, Acoustic predictors of active fluid expulsion from a hydrothermal vent field, offshore Taupo; Volcanic Zone, New Zealand, Frontiers in Earth Science, 9 Article 785396. ISSN 2296-6463 (2022) [Refereed Article]

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2022. The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License ( The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

DOI: doi:10.3389/feart.2021.785396


Understanding fluid expulsion is key to estimating gas exchange volumes between the seafloor, ocean, and atmosphere; for locating key ecosystems; and geohazard modelling. Locating active seafloor fluid expulsion typically requires acoustic backscatter data. Areas of very-high seafloor backscatter, or "hardgrounds," are often used as first-pass indicators of potential fluid expulsion. However, varying and inconsistent spatial relationships between active fluid expulsion and hardgrounds means a direct link remains unclear. Here, we investigate the links between water-column acoustic flares to seafloor backscatter and bathymetric metrics generated from two calibrated multibeam echosounders. Our site, the Calypso hydrothermal vent field (HVF) in the Bay of Plenty, Aotearoa/New Zealand, has an extensive catalogue of vents and seeps in <250 m water depth. We demonstrate a method to quantitatively link active fluid expulsion (flares) with seafloor characteristics. This allows us to develop predictive spatial models of active fluid expulsion. We explore whether data from a low (30 kHz), high (200 kHz), or combined frequency model increases predictive accuracy of expulsion locations. This research investigates the role of hardgrounds or surrounding sediment cover on the accuracy of predictive models. Our models link active fluid expulsion to specific seafloor characteristics. A combined model using both the 30 and 200 kHz mosaics produced the best results (predictive accuracy: 0.75; Kappa: 0.65). This model performed better than the same model using individual frequency mosaics as input. Model results reveal active fluid expulsion is not typically associated with the extensive, embedded hardgrounds of the Calypso HVF, with minimal fluid expulsion. Unconsolidated sediment around the perimeter of and between hardgrounds were more active fluid expulsion sites. Fluids exploit permeable pathways up to the seafloor, modifying and refashioning the seafloor. Once a conduit self-seals, fluid will migrate to a more permeable pathway, thus reducing a one-to-one link between activity and hardgrounds. Being able to remotely predict active and inactive regions of fluid expulsion will prove a useful tool in rapidly identifying seeps in legacy datasets, as well as textural metrics that will aid in locating nascent, senescent, or extinct seeps when a survey is underway.

Item Details

Item Type:Refereed Article
Keywords:hydrothermal vent areas, New Zealand, seeps, random forest, seafloor, calypso vents, acoustic seafloor backscatter
Research Division:Earth Sciences
Research Group:Geology
Research Field:Marine geoscience
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Marine systems and management not elsewhere classified
UTAS Author:Spain, EA (Miss Erica Spain)
UTAS Author:Lucieer, V (Associate Professor Vanessa Lucieer)
UTAS Author:Whittaker, JM (Associate Professor Jo Whittaker)
ID Code:148598
Year Published:2022
Funding Support:Australian Research Council (SR200100008)
Web of Science® Times Cited:1
Deposited By:Ecology and Biodiversity
Deposited On:2022-01-27
Last Modified:2022-10-13
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