Modeling Polyp Activity of Paragorgia arborea using Supervised Learning

Johanson, Arne, Flögel, Sascha, Dullo, Wolf-Christian, Linke, Peter and Hasselbring, Wilhelm (2017) Modeling Polyp Activity of Paragorgia arborea using Supervised Learning Ecological Informatics, 39 . pp. 109-118. DOI 10.1016/j.ecoinf.2017.02.007.

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While the distribution patterns of cold-water corals, such as Paragorgia arborea, have received increasing attention in recent studies, little is known about their in situ activity patterns. In this paper, we examine polyp activity in P. arborea using machine learning techniques to analyze high-resolution time series data and photographs obtained from an autonomous lander cluster deployed in the Stjernsund, Norway. An interactive illustration of the models derived in this paper is provided online as supplementary material.

We find that the best predictor of the degree of extension of the coral polyps is current direction with a lag of 3h. Other variables that are not directly associated with water currents, such as temperature and salinity, offer much less information concerning polyp activity. Interestingly, the degree of polyp extension can be predicted more reliably by sampling the laminar flows in the water column above the measurement site than by sampling the more turbulent flows in the direct vicinity of the corals.

Our results show that the activity patterns of the P. arborea polyps are governed by the strong tidal current regime of the Stjernsund. It appears that P. arborea does not react to shorter changes in the ambient current regime but instead adjusts its behavior in accordance with the large-scale pattern of the tidal cycle itself in order to optimize nutrient uptake.

Document Type: Article
Additional Information: FO Sust. - Digital Ocean
Keywords: Cold water corals, polyp behavior, currents, MoLab, Norwegian Sea, Stjernsund, POS434, POS438, ROV PHOCA
Research affiliation: Kiel University > Software Engineering
OceanRep > The Future Ocean - Cluster of Excellence > FO-R10
OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-MG Marine Geosystems
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
OceanRep > GEOMAR > FB1 Ocean Circulation and Climate Dynamics > FB1-P-OZ Paleo-Oceanography
Refereed: Yes
DOI etc.: 10.1016/j.ecoinf.2017.02.007
ISSN: 1574-9541
Projects: Future Ocean
Date Deposited: 08 Dec 2016 10:19
Last Modified: 10 Apr 2018 10:33

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