Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also re...

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Bibliographic Details
Main Authors: Jerosch, Kerstin, Scharf, Frauke Katharina, Pehlke, Hendrik, Weber, Lukas, Abele, Doris
Format: Dataset
Language:English
Published: PANGAEA 2016
Subjects:
Carlini/Jubany Station
IMCOAST/IMCONet
Impact of climate induced glacier melt on marine coastal systems
Antarctica
Jubany_Dallmann
MULT
Multiple investigations
PotterCove
Potter Cove
King George Island
Antarctic Peninsula
Antarctic
Antarc*
Online Access:https://doi.pangaea.de/10.1594/PANGAEA.856971
https://doi.org/10.1594/PANGAEA.856971
Description
Summary:This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

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