Citation:

PANGAEA.968625

Name: Abiotic data from Billefjorden Svalbard in August 2022
Published: 2024-12-19
License: https://creativecommons.org/licenses/by/4.0/
Keywords: kd; light intensity; Salinity; SST; turbidity

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Published: 2024-12-19 • DOI registered: 2025-01-17

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Abstract:

Kelps act as ecosystem engineers and foundation species, providing the food web basis for Arctic coastal, rocky shore ecosystems. Arctic fjords are undergoing large climatic changes, with the consequences of glacial and terrestrial run-off on kelp holobionts largely being unknown. We compared areas being influenced by either glacial or terrestrial run-off with a control area in Billefjorden, Svalbard in August 2022. In each area, we measured water parameters of the upper 10 m, taking CTD profiles (SWiFT CTDplus Turbidity, Valeport, St Peters Quay, United Kingdom). Further, we measured the underwater light climate (RAMSES-ACC-UV/VIS radiometer, TriOS Optical Sensor, Oldenburg, Germany). In each area, the water's trace elemental composition at 0 and 5 m water depth (Agilent 8900, Agilent Technologies; Tokyo, Japan) was analysed, as well as the relative abundance of the free-living microbial community at 5 m water depth (16S; Illumina Nova platform, Shanghai Hanyu Biotech lab, Shanghai, China).

Keyword(s):

kd; light intensity; Salinity; SST; turbidity

Related to:

Niedzwiedz, Sarina; Schmidt, Claudia Elena; Yang, Yunlan; Burgunter-Delamare, Bertille; Andersen, Sebastian; Hildebrandt, Lars; Pröfrock, Daniel; Thomas, Helmuth; Zhang, Rui; Damsgård, Børge; Bischof, Kai (2024): Run-off impacts on Arctic kelp holobionts have strong implications on ecosystem functioning and bioeconomy. Scientific Reports, 14(1), 30506, https://doi.org/10.1038/s41598-024-82287-w

Project(s):

Arctic Biodiversity & Livelihoods (FACE-IT)

Funding:

Horizon 2020 (H2020), grant/award no. 869383 : Arctic biodiversity change and its consequences: Assessing, monitoring and predicting the effects of ecosystem tipping cascades on marine ecosystem services and dependent human systems (ECOTIP)

National Key Research and Development Program of China, grant/award no. 2021YFE0193000

Southern Marine Science and Engineering Guangdong Laboratory, grant/award no. SML2023SP218

Coverage:

Median Latitude: 78.646003 * Median Longitude: 16.615834 * South-bound Latitude: 78.597389 * West-bound Longitude: 16.392889 * North-bound Latitude: 78.691111 * East-bound Longitude: 16.907861

Date/Time Start: 2022-08-22T00:00:00 * Date/Time End: 2022-08-30T00:00:00

Minimum DEPTH, water: 0.0 m * Maximum DEPTH, water: 11.0 m

Event(s):

Billefjorden * Latitude: 78.487000 * Longitude: 16.197000 * Location: Svalbard * Method/Device: Biological sample (BIOS)

Parameter(s):

#	Name	Short Name	Unit	Principal Investigator	Method/Device	Comment
1	DEPTH, water	Depth water	m	Niedzwiedz, Sarina		Geocode
2	DATE/TIME	Date/Time		Niedzwiedz, Sarina		Geocode
3	Sample position	Samp pos		Niedzwiedz, Sarina		Sampling area
4	LATITUDE	Latitude		Niedzwiedz, Sarina		Geocode
5	LONGITUDE	Longitude		Niedzwiedz, Sarina		Geocode
6	Station label	Station		Niedzwiedz, Sarina
7	Pressure, water	Press	dbar	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
8	Temperature, water	Temp	°C	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
9	Conductivity	Cond	mS/cm	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
10	Salinity	Sal		Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
11	Sound velocity in water	SV	m/s	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
12	Density, water vapour	Density H2O	kg/m³	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
13	Backscatter	Backsc	NTU	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)	Optics 1
14	Backscatter	Backsc	NTU	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)	Optics 2 [btu]
15	Turbidity (Nephelometric turbidity unit)	Turbidity	NTU	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
16	Radiation, photosynthetically active	PAR	µmol/m²/s	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
17	Light attenuation coefficient	Attenuation		Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)
18	Spectrum peak	Spec peak	nm	Niedzwiedz, Sarina	RAMSES hyperspectral radiometer (RAMSES)	Wavelength with the maximum light transmission through the water coloumn
19	Aluminium	Al	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
20	Titanium	Ti	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
21	Vanadium	V	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
22	Manganese	Mn	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
23	Iron	Fe	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
24	Cobalt	Co	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
25	Nickel	Ni	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
26	Copper	Cu	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
27	Zinc	Zn	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
28	Yttrium	Y	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
29	Cadmium	Cd	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
30	Lanthanum	La	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
31	Cerium	Ce	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
32	Praseodymium	Pr	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
33	Neodymium	Nd	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
34	Samarium	Sm	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
35	Europium	Eu	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
36	Gadolinium	Gd	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
37	Terbium	Tb	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
38	Dysprosium	Dy	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
39	Holmium	Ho	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
40	Erbium	Er	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
41	Thulium	Tm	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
42	Ytterbium	Yb	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
43	Lutetium	Lu	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
44	Lead	Pb	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
45	Thorium	Th	µg/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
46	Uranium	U	ng/l	Niedzwiedz, Sarina	Tandem Mass Spectrometry (ICP-MS/MS)
47	Amplicon sequence variant	ASV		Niedzwiedz, Sarina	Calculated	Observed features
48	Shannon Diversity Index	H'		Niedzwiedz, Sarina	Calculated
49	Pielou evenness index	J'		Niedzwiedz, Sarina	Calculated
50	Phylogenetic diversity	P div		Niedzwiedz, Sarina	Calculated
51	Proteobacteria	Proteobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
52	Bacteroidetes	Bacteroidetes	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
53	Actinobacteria	Actinobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
54	Alphaproteobacteria	Alphaproteobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
55	Flavobacteria	Flavobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
56	Gammaproteobacteria	Gammaproteobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
57	Actinobacteria	Actinobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
58	Betaproteobacteria	Betaproteobacteria	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
59	Rickettsiales	Rickettsiales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
60	Flavobacteriales	Flavobacteriales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
61	Oceanospirillales	Oceanospirillales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
62	Rhodobacterales	Rhodobacterales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
63	Actinomycetales	Actinomycetales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
64	Alteromonadales	Alteromonadales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
65	Methylophilales	Methylophilales	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
66	Pelagibacteraceae	Pelagibacteraceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
67	Flavobacteriacea	Flavobacteriacea	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
68	Halomonadaceae	Halomonadaceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
69	Rhodobacteraceae	Rhodobacteraceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
70	Microbacteriaceae	Microbacteriaceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
71	Cryomorphaceae	Cryomorphaceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
72	Alteromonadaceae	Alteromonadaceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
73	Methylophilaceae	Methylophilaceae	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]
74	Bacteria, unclassified	Bac unclassif	%	Niedzwiedz, Sarina	16S rRNA gene sequencing [V4-V5 variable regions]

License:

Creative Commons Attribution 4.0 International (CC-BY-4.0)

Status:

Curation Level: Enhanced curation (CurationLevelC)

Size:

2194 data points

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