Abstract:
Comparable deep-water benthos datasets collected by epibenthic sledges (EBS) with an epibenthic and a suprabenthic netsampler in the Atlantic Ocean have been gathered since 2006. They were collected during the international research expeditions: ANDEEP-SYSTCO II, BIOPEARL I, DIVA1-3, IceAGE1-3&RR, IceDIVA1,2, JR275 and Vema-TRANSIT. While EBS diversity data at high taxon level were published for ANDEEP_SYSTCO II, DIVA1-3 and Vema-TRANSIT, unpublished diversity data for BIOPEARL I, IceAGE1-3&RR, IceDIVA1, 2 and JR275 came from sample databases at DZMB Senckenberg and British Antarctic Survey, and are published here for the first time. In total, diversity data for 143 EBS deployments from 13 expeditions were available for analyses based on identification on 50 taxon levels, including phyla, subphyla, classes and orders. During all 13 expeditions EBS with an epibenthic and a suprabenthic netsampler following sampler sizes and height , enabling comparability of samples. This type of EBS was a suitable device for sampling small benthic fauna on and above the seabed, including macrofauna and small-sized megafauna. We analyse pan-Atlantic benthic data from a range (119m - 8338m) of depths. For the pan-Atlantic analyses we defined seven regions to pool EBS locations based on their position North and South of the Equator and to the mid-Atlantic Ridge (MAR): East and West of the MAR, the Vema Fracture Zone as a gap in the MAR, the Southern Ocean south of the MAR and the Puerto Rico Trench as a deep-sea trench. In this study we included data for 41 higher taxa of the initially separated 50 taxa ranging from phyla to orders. The environmental parameters for this study were provided by Bio-ORACLE, which identifies mean values for different physical and chemical variables over a 14 year time period through a combination of satellite and in-situ measurements (2000 - 2014), at a resolution of 5 arcmin. 4 multivariate analyses (principal components analysis, analysis of similarities, similarity of percentages and BioEnv BEST) were carried out on standardised abundances using PRIMER software, the results and parameters of which are presented in this dataset.
Funding over the years for the sample collection and analyses was provided by multiple NERC grants and international grants. Katrin Linse, Peter Enderlein and Huw J. Griffiths were part of the British Antarctic Survey Polar Science for Planet Earth Programme funded by The Natural Environment Research Council (NERC) [NC-Science] and included the funding for the RSS James Clark Ross expeditions BIOPEARL I and JR275. This study was directly funded by the IceAGE_RR and IceDIVA grants by the German Science Foundation (DFG) and Bundesministerium fur Bildung und Forschung (BMBF) under grant numbers MSM75 (MerMet17-5), SO280 and SO286 to PIs Saskia Brix, James Taylor and Katrin Linse. Funding for previous expeditions that provided data were: IceAGE1-3, BR3843-3-1& 4-1, & SO276 (MerMet17-6). James Taylor and Karlotta Kurzel were supported via DFG grant GPF 20-3_087 as part of the IceDiva project 2021 - 2022 by DFG. Anne-Nina Lorz was funded by the German Science Foundation Project IceAGE Amphipoda, LO2543/1-1. Additionally, Angelika Brandt was granted funding (SO 237, Forderziffer 03G0237A) by the Bauer Foundation for the VEMA-Transit project. Inmaculada Frutos was supported through the junior research group''Vema TRANSIT. Puerto Rico Trench, Vema Fracture Zone and Abyssal Atlantic Biodiversity Study'' as part of the project ''Biodiversitatnachhaltige Ressourcennutzun'' (Aktenzeichen T237/25054/).
Keywords:
Deep sea, Southern ocean, benthic biodiversity, environmental biogeography, macrobenthos
Kuerzel, K., Linse, K., Brandt, A., Brenke, N., Enderlein, P., Griffiths, H., Kaiser, S., Svavarsson, J., Loerz, A.-N., Frutos, I., Taylor, J., & Brix, S. (2023). Pan-Atlantic comparison of deep-water macrobenthos diversity collected by epibenthic sledge sampling and analysis of patterns and environmental drivers. (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/58080F33-884C-4E13-A419-C00CF1BAB6A6
| Access Constraints: | No restrictions apply. |
|---|---|
| Use Constraints: | Data released under Open Government Licence V3.0: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2023-03-14 |
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| Dataset Progress: | Complete |
| Dataset Language: | Abkhazian, Afar, Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Avestan, Aymara |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK Polar Data Centre |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Karlotta Kurzel |
| Role(s) | Investigator |
| Organisation | Insitute of Marine Ecosystem and Fishery research, University of Hamburg |
| Name | Dr Katrin Linse |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Prof Angelika Brandt |
| Role(s) | Investigator |
| Organisation | Senckenberg Research Institute |
| Name | Nils Brenke |
| Role(s) | Investigator |
| Organisation | Scientific Marine Service |
| Name | Dr Peter Enderlein |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Huw J Griffiths |
| Role(s) | Investigator |
| Organisation | British Antarctic Survey |
| Name | Stefanie Kaiser |
| Role(s) | Investigator |
| Organisation | Senckenberg Research Institute |
| Name | Jorundur Svarvason |
| Role(s) | Investigator |
| Organisation | University of Iceland |
| Name | Anne-Nina Lorz |
| Role(s) | Investigator |
| Organisation | Institute of Marine Ecosystem and Fishery Science (IMF, University of Hamburg) |
| Name | Inmaculada Frutos |
| Role(s) | Investigator |
| Organisation | University of Lodz |
| Name | James Taylor |
| Role(s) | Investigator |
| Name | Saskia Brix |
| Role(s) | Investigator |
| Organisation | German Centre for Marine Biodiversity Research (DZMB) |
| Parent Dataset: | N/A |
| Reference: | Associated publication: Kurzel K, Brix S, Brandt A, Brenke N, Enderlein P, Griffiths HJ, Kaiser S, Svavarsson J, Lorz A-N, Frutos I, et al. Pan-Atlantic Comparison of Deep-Sea Macro- and Megabenthos. Diversity. 2023; 15(7):814. https://doi.org/10.3390/d15070814 References: Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrao, E. A., & De Clerck, O. (2018). Bio-ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284. DOI: 10.1111/geb.12693 Brandt, A., & Wurzberg, L. (2014). The Southern Ocean deep sea-A benthic view to pelagic processes. Deep Sea Research Part II: Topical Studies in Oceanography, 108, 1-5. DOI: 10.1016/j.dsr2.2014.07.011 Brandt, A., Havermans, C., Janussen, D., Jorger, K. M., Meyer-Lobbecke, A., Schnurr, S., & Wurzberg, L. (2014). Composition and abundance of epibenthic-sledge catches in the South Polar Front of the Atlantic. Deep Sea Research Part II: Topical Studies in Oceanography, 108, 69-75. DOI: 10.1016/j.dsr2.2014.08.017 Brandt, A., Frutos, I., Bober, S., Brix, S., Brenke, N., Guggolz, T., & Linse, K. (2018). Composition of abyssal macrofauna along the Vema Fracture Zone and the hadal Puerto Rico Trench, northern tropical Atlantic. Deep Sea Research Part II: Topical Studies in Oceanography, 148, 35-44. DOI: 10.1016/j.dsr2.2017.07.014 Brandt, A., & Barthel, D. (1995) An improved supra- and epibenthic sledge for catching Peracarida (Crustacea, Malacostraca), Ophelia, 43:1, 15-23, DOI: 10.1080/00785326.1995.10430574 Brenke, N. (2005). An epibenthic sledge for operations on marine soft bottom and bedrock. Marine Technology Society Journal, (2). DOI: 10.4031/002533205787444015 Brix, S.,Bauernfeind, W., Brenke, N., Bazewicz, M., Borges, V., Buldt, K., Cannon, J., Diaz-Agras, G., Fiege, D., Fiorentino, D., Haraldsdottir, S., Hoffmann, S., Holst, S., Huettmann, F., Jeskulke, K., Jennings, R., Kocot, K., Khodami, S., Rodriguez, Y., & Yasuhara, M. (2011). Cruise Report M85/3 IceAGE1 2011 with RV Meteor. DOI: 10.13140/RG.2.2.17251.76322. Brix, S., Meissner, K., Stransky, B., Halanych, K., Jennings, R., Kocot, K. & Svavarsson, J. (2014). The IceAGE project - a follow up of BIOICE. Polish Polar Research. 35. DOI: 10.2478/popore-2014-0010. Brix, S., Martinez, P., Svavarsson, J., Kenning, M., Jennings, R., Holst, S., Cannon, J., Eilertsen, M., Schnurr, S., Jeskulke, K., and Hoffmann, S.. (2013) IceAGE - Icelandic marine Animals: Genetics and Ecology, Cruise No. POS456, IceAGE2, 20.07.2013 - 04.08.2013, Kiel (Germany) - Reykjavik (Iceland). Deutsche Zentrum fur Marine Biodiversitatsforschung, Senckenberg am Meer, Wilhelmshaven, Germany, 17 pp. DOI: 10.3289/CR_POS456. Brix, S., Taylor, J. (2022): Master track of SONNE cruise SO286 in 1 sec resolution (zipped, 16.7 MB). Senckenberg am Meer, Wilhelmshaven, PANGAEA, DOI: 10.1594/PANGAEA.942626. Brix, S., Taylor, J., Le Saout, M., Mercado-Salas, N., Kaiser, S., Lorz, A.-N., Gatzemeier, N., Jeskulke, K., Kurzel, K., Neuhaus, J. Depth Transects and Connectivity along Gradients in the North Atlantic and Nordic Seas in the Frame of the IceAGE Project (Icelandic Marine Animals: Genetics and Ecology), Cruise No. SO276 (MerMet17-06), 22.06. 2020-26.07. 2020, Emden (Germany)-Emden https://www.researchgate.net/publication/369782778_Depth_transects_and_connectivity_along_gradients_in_the_North_Atlantic_and_Nordic_Seas_in_the_frame_of_the_IceAGE_project_Icelandic_marine_Animals_Genetics_and_Ecology Brix, S., Taylor, J., Short Cruise Report R/V SONNE, cruise SO280 (GPF 20-3_087) Emden-Emden (Germany) 08.01.2021-07.02.2021; Universitat Hamburg: Hamburg, Germany. https://www.ldf.uni-hamburg.de/sonne/wochenberichte/wochenberichte-sonne/so279-282/so280-scr.pdf Clarke, K. R., & Gorley, R. N. (2005). PRIMER: Getting started with v6. PRIMER-E Ltd: Plymouth, UK, 931, 932. Devey, C., Brandt, A., Arndt, H., Augustin, N., Bober, S., Borges, V., Brenke, N., Brix, S., Elsner, N., Frutos, I., et al. RV SONNE Fahrtbericht/Cruise Report SO237 Vema-TRANSIT; GEOMAR Helmholtz-Zentrum fur Ozeanforschung Kiel: Kiel, Germany , 2015. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://oceanrep.geomar.de/id/eprint/28317/1/geomar_rep%20NS_23.pdf Hong, Z., Zhinan, Z. (2003). Rationale of the multivariate statistical software PRIMER and its application in benthic community ecology. Journal of Ocean University of Qingdao. 33(1):58-64. Linse, K., Griffiths, H. J., Barnes, D. K., & Clarke, A. (2006). Biodiversity and biogeography of Antarctic and sub-Antarctic mollusca. Deep sea research Part II: Topical studies in oceanography, 53(8-10), 985-1008. DOI: 10.1016/j.dsr2.2006.05.003 Riehl, T., 2018. The effects of depth, distance, and the Mid-Atlantic Ridge on genetic differentiation of abyssal and hadal isopods (Macrostylidae). Deep-Sea Res. Pt. II. Martinez Arbizu, P., Brix, S., Kaiser, S., Brandt, A., George, K.H., Arndt, H., Hausmann, K., Turkay, M., Renz, J., Hendrycks, E., et al. Deep-Sea Biodiversity, Current Activity, and Seamounts in the Atlantic-Cruise No. M79/1-June 10-August 26, 2009-Montevideo Uruguay) - Ponta Delgada (Portugal); 2195-8475; DFG-Senatskommission fur Ozeanographie;: Bremen, 2015; pp. 1-92. Tyberghein, L., Verbruggen, H., Pauly, K., Troupin, C., Mineur, F. and De Clerck, O. (2012) Bio-ORACLE: a global environmental dataset for marine species distribution modelling. Global Ecology and Biogeography 21, 272-281. DOI: 10.1111/j.1466-8238.2011.00656.x |
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| Quality: | Standard protocols for EBS deployment were followed. Data entry of EBS deployment data was linked to vessels' positioning or USBL system. | |
| Lineage: | Epibenthic samples were collected during the following research expeditions: ANDEEP-SYSTCO II, BIOPEARL I, DIVA1-3, IceAGE1-3&RR, IceDIVA1,2, JR275 and Vema-TRANSIT (Brandt & Wuerzberg 2014, Linse 2006, DIVA cruise reports, Brix et al. 2014, Devey & Brix 2017 cruise report, Brix & Taylor 2022, 2023, Griffiths 2012, Rhiel et al. 2018). While EBS diversity data at high taxon level were published for ANDEEP_SYSTCO II, DIVA1-3 and Vema-TRANSIT (Brandt et al 2014, Kaiser et al. in review, Brandt et al 2018), unpublished diversity data for BIOPEARL I, IceAGE1-3&RR, IceDIVA1, 2 and JR275 came from sample databases at DZMB Senckenberg and British Antarctic Survey, and are published here for the first time. During all 13 expeditions EBS with an epibenthic and a suprabenthic netsampler following the sampler sizes and height defined by Brandt and Barthel (1995) and Brenke (2005) were used, enabling comparability of samples. This type of EBS was a suitable device for sampling small benthic fauna on and above the seabed, including macrofauna and small-sized megafauna. The EBS holds an epi-and a suprabenthic netsampler (Brenke, 2005). Each of these nets has an opening of 100x33 cm and net mesh size of 500 micrometers. The cod ends are equipped with net-buckets containing 300 micrometer mesh windows. On deployment 1.5 times cable length to water depth were laid out and then EBS was trawled with 1 kn for 10 minutes on the seabed at a 1 knot for deployments in 500 m to 1500 m. Once on the deck, the content of the samplers was immediately fixed in 96 percent undenaturated and pre-cooled (at -20 degrees Celsius) ethanol. Samples were stored in a -20 degrees Celsius freezer for at least 48 h to reduce degradation of DNA for subsequent genetic studies. During this time, samples were gently rolled every three to six hours. Ethanol was changed once for all sub-fractions. In the laboratory, samples were initially sorted under a stereomicroscope to higher taxonomic ranks, lowest were class level for this analysis. Live specimen numbers were counted for abundance data and thanatocoenosis were not taken into account. For comparison between stations abundance data were standardised to 1000 m2 trawled area. The haul distances were calculated based on equation (4) in Brenke (2005). For comparison between stations abundance data were standardised to 1000 m2 trawled area. In this study we included data for 41 higher taxa of the initially separated 50 taxa ranging from phyla to orders. We excluded Foraminifera, Bryozoa, and fish. Brachiopoda, Chaetognatha, Echiura, Hemichordata, Nematoda, Nemertea, Phoronida, Platyhelminthes, Porifera and Priapulida were not identified beyond phylum level. Annelida were separated into Polychaeta, Sipunculida, Oligochaeta and Hirudinea. The phylum Arthropoda was split into the subphylum Chelicerata and Crustacea, with the former comprising Pycnogonida and Acarina and the latter crustacean order levels. Chordata only consisted of Tunicates. Echinodermata and Mollusca were separated into classes. For the DIVA1 & 2 data sets, Cnidaria and Echinodermata were not further discriminated into classes. For the DIVA-1, IceAGE 1-3 &_RR and IceDIVA1,2 data sets, Aplacophora were not separated into Caudofoveata and Solenogastres. So, if corresponding data on class assignment were available, these were reported separately, but for all univariate and multivariate analyses, classes within Aplacophora, Cnidaria and Echinodermata were grouped. The environmental parameters for this study were provided by Bio-ORACLE (http://www.bio-oracle.org/; Tyberghein et al., 2012; Assis et al., 2018). Bio-ORACLE identifies average (mean) values for different physical and chemical variables over a 14-year time period through a combination of satellite and in-situ measurements (2000 - 2014; Assis et al., 2018), at a resolution of 5 arcmin. In this study, surface and benthic (maximum depth) values were used for the following variables: salinity (PSS), silicate (mol/m3), iron (mmol/m3; mol/m3), phosphate (mmol/ m3; mol/ m3), nitrate (mmol/ m3; mol/ m3), chlorophyll-a (mg/m3; mg/cm3) and primary production (g/m3/day). Additionally, benthic data for temperature (degrees Celsius) and current velocity (m/s) as well as surface data for calcite (mol/ m3) and dissolved oxygen (mol/ m3) were included. This dataset outlines each EBS event along with temporal and spatial data. Abundances are reported raw and standardised /1000m2. PRIMER v6.0 (Clarke and Gorley, 2005) was used to perform a suite of multivariate statistical analyses: Similarity Percentage (SIMPER), Analysis of Similarities (ANOSIM), Biota-Environment Stepwise Analysis (BioEnv BEST) and Principal Components Analysis (PCA) (Hong and Zhinan, 2003). Analyses use taxonomic classification at the phyla level and at the multitaxon level (highest taxonomic classification achievable for each sample). 2 SIMPER analyses were conducted using standardised abundances to assess the contribution of taxa (at the phyla and 'multitaxon' level) to similarity analyses. A Bray-Curtis similarity matrix was used, and 90 percent was the cut off for low contributions to similarity. They used depth and region as factors. Depth split into the following factors using bins: abyssal (4000m-6000m), hadal (>6000m), shelf (<200m), bathyal (1000-4000m) and slope (200-1000m). Region is split into Vema Fracture Zone, Puerto Rico Trench, South West Atlantic, South East Atlantic, Southern Ocean, North West Atlantic and North West Atlantic. ANOSIM was conducted using standardised abundances from EBS sample to test whether there was a significant difference between samples based on different factors. 4 ANOSIMs were carried out: one for each depth and region (splitting samples as for SIMPER) at the phyla and 'multitaxon' level. PCA analysis is used to understand the associations between community composition and environmental factors, using standardised abundances. 2 PCA analyses were performed: one including 21 environmental variables (all factors: depth (m), latitude (decimal degrees), longitude (decimal degrees), temperature - mean at max dept (degrees Celsius), chlorophyll-a - mean at max depth (mg/m^3), dissolved oxygen concentration - mean at max depth (mmol/m^3), dissolved iron concentration- mean at max depth (mol/m^3), nitrate - mean at max depth (mmol/m^3), phosphate - mean at max depth (mol/m^3), salinity - mean at max depth (PSS), silicate - mean at max depth (mmol/m^3), current velocity - mean at max depth (m/s) primary productivity - mean at max depth, chlorophyll - mean at surface (mg/cm^3), calacite - mean at surface (mol/cm^3), dissolved iron concentration - mean at surface (mol/m^3), nitrate - mean at surface (mol/m^3), phosphate - mean at surface (mol/m^3), primary productivity - mean at surface, salinity - mean at surface (PSS), silicate - mean at surface (mol/m^3)) and one including 11 environmental variables (main factors: depth (m), latitude (decimal degrees), longitude (decimal degrees), temperature - mean at max depth (degrees Celsius), chlorophyll-a - mean at max depth (mg/m^3), dissolved oxygen concentration - mean at max depth (mmol/m^3), dissolved iron concentration- mean at max depth (mmol/m^3), nitrate - mean at max depth (mmol/m^3), phosphate - mean at max depth (mmol/m^3), salinity - mean at max depth (PSS), silicate - mean at max depth (mmol/m^3), current velocity - mean at max depth (m/s) primary productivity - mean at max depth). BioEnv analysis were conducted to test which environmental variables (up to 5 variables) best explain patterns in abundances. Spearman rank correlation method was used. Euclidean distance was used for resemblance analysis. 2 analyses were performed: one at the phyla level and one at the ''multitaxon' level. The following environmental variables were included in the analyses: depth (m), latitude (decimal degrees), longitude (decimal degrees), temperature - mean at max depth (degrees Celsius), chlorophyll-a - mean at max depth (mg/cm^3), dissolved oxygen concentration - mean at max depth (mol/m^3), dissolved iron concentration- mean at max depth (mol/m^3), nitrate - mean at max depth (mol/m^3), phosphate - mean at max depth (mol/m^3), salinity - mean at max depth (PSS), silicate - mean at max depth (mol/m^3), current velocity - mean at max depth (m/s) primary productivity - mean at max depth, chlorophyll - mean at surface (mg/cm^3), calacite - mean at surface (mol/m^3), dissolved iron concentration - mean at surface (mol/m^3), nitrate - mean at surface (mol/m^3), phosphate - mean at surface (mol/m^3), primary productivity - mean at surface, salinity - mean at surface (PSS), silicate - mean at surface (mol/m^3). |
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| Temporal Coverage: | |
|---|---|
| Start Date | 2011-08-27 |
| End Date | 2011-09-28 |
| Start Date | 2013-07-20 |
| End Date | 2023-08-04 |
| Start Date | 2020-06-22 |
| End Date | 2020-07-26 |
| Start Date | 2018-06-29 |
| End Date | 2018-08-08 |
| Start Date | 2021-01-08 |
| End Date | 2021-02-07 |
| Start Date | 2021-11-05 |
| End Date | 2021-12-08 |
| Start Date | 2000-07-06 |
| End Date | 2000-08-02 |
| Start Date | 2005-01-24 |
| End Date | 2005-03-30 |
| Start Date | 2014-12-14 |
| End Date | 2015-01-26 |
| Start Date | 2012-01-07 |
| End Date | 2012-03-22 |
| Start Date | 2006-02-26 |
| End Date | 2006-04-17 |
| Start Date | 2012-02-07 |
| End Date | 2012-03-22 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | -77.3569 |
| Northernmost | 69.11483 |
| Longitude | |
| Westernmost | -67.17032 |
| Easternmost | 10.06 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | 119 |
| Max Depth | 8338 |
| Location: | |
| Location | N/A |
| Detailed Location | Argulhas Basin |
| Location | N/A |
| Detailed Location | Argentine Basin |
| Location | N/A |
| Detailed Location | Prince Gustav Channel, Antarctic Peninsula |
| Location | N/A |
| Detailed Location | Cape Basin |
| Location | N/A |
| Detailed Location | Falkland Trough |
| Location | N/A |
| Detailed Location | Labrador Sea |
| Location | N/A |
| Detailed Location | Porcupine Abyssal Plane |
| Location | N/A |
| Detailed Location | Puerto Rico Trench |
| Location | N/A |
| Detailed Location | Duse Bay |
| Location | N/A |
| Detailed Location | Livingston Island |
| Location | N/A |
| Detailed Location | Elephant Island |
| Location | N/A |
| Detailed Location | Deception Island |
| Location | N/A |
| Detailed Location | Vema transform |
| Location | N/A |
| Detailed Location | Antarctic peninsula |
| Location | N/A |
| Detailed Location | Scotia Sea |
| Location | N/A |
| Detailed Location | South Orkney Islands, South Sandwich Islands |
| Location | N/A |
| Detailed Location | Southern Thule |
| Location | N/A |
| Detailed Location | South Georgia |
| Location | N/A |
| Detailed Location | Shag Rocks |
| Location | N/A |
| Detailed Location | Weddell Sea |
| Location | N/A |
| Detailed Location | Vestkapp |
| Location | N/A |
| Detailed Location | Halley Bay |
| Location | N/A |
| Detailed Location | Kap Norvegia |
| Location | N/A |
| Detailed Location | Powell Basin |
| Location | N/A |
| Detailed Location | Brunt Shelf |
| Location | N/A |
| Detailed Location | Reykjanes Ridge |
| Location | N/A |
| Detailed Location | Icelandic Basin |
| Location | N/A |
| Detailed Location | Denmark Strait |
| Location | N/A |
| Detailed Location | Norwegian Basin |
| Location | N/A |
| Detailed Location | Norwegian Channel |
| Location | N/A |
| Detailed Location | Faroe Channel |
| Location | N/A |
| Detailed Location | Faroe Ridge |
| Location | N/A |
| Detailed Location | West European Basin |
| Location | N/A |
| Detailed Location | Iberian Plaine |
| Location | N/A |
| Detailed Location | Labrador Sea |
| Location | N/A |
| Detailed Location | Greenland Fracture Zone |
| Location | N/A |
| Detailed Location | Azores |
| Data Collection: | BAS and DZMB Senckenberg edited and built the EBS design by Brenke (2005). PRIMER v6.0 (Clarke and Gorley, 2005) was utilized for statistical analysis and statistical visualisations. |
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| Distribution: | |
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| Distribution Media | N/A |
| Distribution Size | 30 files, 383 KB |
| Distribution Format | N/A |
| Fees | N/A |
| Data Storage: | This dataset consists of 30 files (383 KB): BioOracle - BIOOracle_factors.csv EBS_and_abundances - abundances_standardised_1000m2.csv - EBS_events_READ_ME.txt - EBSevents.csv - raw_abundances.csv ANOSIM - ANOSIM_depth_factors.csv - ANOSIM_depth_multitaxon_results.csv - ANOSIM_depth_multitaxon_READ_ME.txt - ANOSIM_depht_phylum_READ_ME.txt - ANOSIM_depth_phylum_results.csv - ANOSIM_region_factors.csv - ANOSIM_rebion_multitaxon_results.csv - ANOSIM_region_multitaxon_READ_ME.txt - ANOSIM_rebion_phylum_results.csv - ANOSIM_region_phylum_READ_ME.txt BioENV_BEST - BioENV_BEST_multitaxon.csv - BioENV_BEST_multitaxon_READ_ME.txt - BioENV_BEST_phylum.csv - BioENV_BEST_phylum_READ_ME.txt PCA - PCA_allfactors_eigenvalues.csv - PCA_allfactors_eigenvectors.csv - PCA_allfactors_principal_components_scores.csv - PCA_mainfactors_eigenvalues.csv - PCA_mainfactors_eigenvectors.csv - PCA_mainfactors_principal_components_scores.csv - PCA_READ_ME.txt SIMPER - SIMPER_factors.csv - SIMPER_multitaxa_results.csv - SIMPER_phylum_results.csv - SIMPER_READ_ME.txt |