Fish, macroinvertebrates and physical oceanography including CTD profiling data from the shallow water area of Kongsfjord, Svalbard from 2013 to 2014

• Main Authors: Fischer, Philipp, Schwanitz, Max, Loth, Reiner, Posner, Uwe, Brand, Markus, Schroeder, Friedhelm
• Format: Dataset
• Language: English
• Published: PANGAEA 2017
• Subjects: AWI_Coast; Coastal Ecology @ AWI; Svalbard; Norway; Kongsfjord; Arctic; Kongsfjord*; Kongsfjorden
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.874141; https://doi.org/10.1594/PANGAEA.874141

A combined year round assessment of selected oceanographic data and a macrobiotic community assessment was performed from October 2013 to November 2014 in the littoral zone of the polar fjord systems Kongsfjorden on the west coast of Svalbard (Norway). A state of the art remote controlled cabled underwater observatory technology was used for daily vertical profiles of temperature, salinity and turbidity together with a stereo-optical assessment of the macrobiotic community, including fish. The results reveal a distinct seasonal cycle in total species abundances with a significantly higher total abundance and species richness during the polar winter when no light is available under water compared to the summer months when 24-h light is available. During the winter months, a temporally highly segmented community was observed with respect to species occurrence with single species dominating the winter community for restricted times. In contrast, the summer community showed an overall lower total abundance, as well as a significantly lower number of species. The study clearly demonstrates the high potential of cable connected remote controlled digital sampling devices, especially in remote areas, such as the polar fjord systems, with harsh environmental conditions and limited accessibility. A smart combination of such new digital ?sampling? methods with classic sampling procedures can provide a possibility to significantly extend the sampling time and frequency especially in remote and difficult to access areas. This can help to provide a sufficient data density and therefore statistical power for a sound scientific analysis without increasing the invasive sampling pressure in ecologically sensitive environments.