The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed using logical operators and phrases embedded in quotation marks. Logical operators include AND, OR and NOT. Remember to add space around operators. Text strings that are not quoted are trated as separate words and will match any of the words (i.e. assuming the OR operator). E.g. in order to find WMO synoptic weather station data from Verlegenhuken use the search phrase: [synop AND verlegenhuken]. Searches are case insensitive.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column.
Collections
Collections allows the user to search in subsets of the existing catalogue. The collections are primarily data management projects that have been incorporated in the ADC catalogue after the project has ended. In this context the ADC is the long term access solution for these data. The collections currently served through ADC include (datasets may belong to multiple data collections):
ADC is the full collection of this service CC is the CryoClim collection
In order to search a specific data collection select that collection. If no data collection is selected all collections are searched.
AeN are data related to the Nansen Legacy project and are better explored through the SIOS Data Access Point using the collection defined there which is available through this URL.
SIOS, InfraNOR, SIOSCD, SIOSAP, SESS_* are collections related to SIOS. These are better explored through the SIOS Data Access Portal
Some cleaning is pending between InfraNOR and SIOSIN, for some of the SESS collections.
Citation of data and service
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
author,
title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the Norwegian Meteorological Institute/Arctic Data Centre.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Arctic ABC Development, Deep Impact, Centre for Autonomous Marine Operations and Systems (NFR grant 245929, NFR project no 300333, NFR project no 223254)
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
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Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of an array of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors is mounted on a tripod under a transparent dome. This dataset contains the data of the hyperspectral radiometer USSIMO (In-situ Marine Optics, Perth, WA, Australia), converted to E(PAR) by the following equation: PAR is approximated as an integral of micromolespersec=(uirr/(h*c/(lambda*1e-9)))/microavo for wavelengths(lambda) in range from 400 to 700nm, where: uirr = USSIMO irradiance for wavelength equal to lambda, h=6.63e-34 [Js], c=3.00e+08 [m/s], microavo=6.022e17. The sensor is equipped with a Zeiss MMS1 UV-VIS NIR detector with National Institute of Standards and Technology, USA traceable radiometric calibration between 380 and 900 nm. This instrument is used for time-series measurement of down-welling spectral irradiance in energy Wm-2 nm-1. Spectral resolution is 10 nm (3.3 nm pixel spacing) and a cosine-corrected polytetrafluoroethylene (PTFE) light diffusor with cosine error: <3% (0 - 60°), <10% (60 - 87.5°), is fitted. The device acquired measurements with a 16 bit analogue to digital converter. It samples continuously internally. Integration time is controlled by the sensor depending on the light intensity, with a maximum of 6 seconds. Actual integration time is stored with the data in each sample. The sensor output is saved on a PC with custom software which records 30 seconds of output data every 29:30 min. The number of samples collected in that period depends on the USSIMO integration time. The sensor is equipped with a pitch and roll sensor which is used to ensure that the spectroradiometer remains in the fixed position throughout the time-series acquisition. For re-use of the data, please refer to the dataset and the original publication. This is an aggregated dataset that combines the invidual datasets into a continous timeseries. For details check out https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00039,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00044,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00045 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00046.
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
Show more...
Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of a range of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors, including the camera, is mounted on a tripod under a transparent dome. This dataset contains the E(PAR) data derived from pictures taken during 2017 at hourly intervals by the all-sky-camera. The camera (Canon EOS 5D Mark III) is equipped with a fish-eye lens with a focal length set to 8 mm with aperture manually set to open (f/4) to ensure maximum sensitivity (Canon EF 8-15mm f/4L), providing a 180° image of the atmosphere (only possible with a full-size sensor). Both shutter speed (exposure time, ranging from 0.000125 to 30 seconds) and ISO (sensitivity, ranging from 100 at Midnight Sun period and up to 6400 during Polar Night) are set to auto. White balance manually set to “day light”. It is remotely controlled by a PC, pictures were stored in a cloud storage. Short gaps in the time series are due to power failures. In this dataset there are two large gaps: 2019-01-09 to 2019-03-08 and 2019-06-24 to 2019-09-25 caused by a crash of the controlling PC which was not monitored at that time. The equations for the picture-to-E(PAR) conversion can be found in: Johnsen et al 2021, An all-sky camera system providing high temporal resolution annual time-series of irradiance in the Arctic, Applied Optics. The pictures on which this dataset is based on can be found at . For re-use of the data, please refer to the dataset and the original publication. this is an aggregated dataset where the individual timeseries have been combined into a continous timeseries. For details on the dataset please check https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00040,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00041,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00042 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00043.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
Kartfestet inndeling av Svalbard i biogeografiske soner basert på variasjoner i tre ulike varmekjærhets- eller termofili-verdier som er beregnet på grunnlag av forekomsten av karplanter med ulik grad av varmekjærhet i 163 «floristiske områder».
Varmekjære planter er valgt som grunnlag for den biogeografiske inndelingen fordi de er gode indikatorer på temperaturforholdene. Som grunnlag for inndelingen er karplantene på Svalbard inndelt i fire ulike grupper mht. varmekjærhet (termofili), samt en gruppe med «temperaturavhengige» arter. Utbredelsen av de termofile artene i de 163 floristiske områdene på Svalbard og Jan Mayen gir ulike termofili (It) verdier for de ulike områdene. It-verdiene tar også hensyn til, og kompenserer for, variasjoner i arealene av isfrie lavlandsområder, hvor godt områdene er undersøkt og habitatvariasjonen i de ulike floristiske områdene. De It-verdiene som framkommer benyttes til å inndele Svalbard og Jan Mayen i tre biogeografiske soner og to subsoner:
Innenfor den mellomarktiske tundrasonen er det skilt ut en indre fjordsone (IFS) med et særlig gunstig klima. Den siste subsonen innenfor MTS - Sørlig Maritim Subsone (SMS) - omfatter kun Jan Mayen.
The data has been collected during the Nansen Legacy Joint Cruise 3, 19th February – 11th March 2022 on the research vessel RV Kronprins Haakon (cruise number 2022702), along a transect from 76N to 82N east of Svalbard. The dataset contains mesozooplankton occurrence. It has been sampled using a BongoNet, HydroBios 60 cm. Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton with a mesh-size 180 µm. All specimens are identified to the lowest taxonomical level and the occurrence is given for a specific species and stage or size group as ind/m3.
Sampling method:
The sampling covers a transect from 76 N to 82 N in the northern Barents Sea and Arctic Ocean. Zooplankton has been collected using a BongoNet 60 cm (HydroBios, opening: 0.2827 m2, net length: 250 cm). Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton with a mesh-size 180 µm. All samples were added 4 % formaldehyde free from acid.
PLEASE NOTE: THIS DATASET CONTAINS TWO COMPLETE DATASETS OF ZOOPLANKTON: ONE FOR SMALL MESOZOOPLANKTON (APPROX BODY SIZE BELOW 2 MM) COLLECTED WITH MULTINET 64 µM AND ONE FOR LARGE MESOZOOPLANKTON (APPROX BODY SIZE ABOVE 2 MM) COLLECTED WITH MULTINET 180 µM MESH SIZE. THE INFO ABOUT WHICH NET IS USED CAN BE FOUND IN gearType, USE EITHER 64 UM OR 180 UM DEPENDING ON WHETHER THE FOCUS IS SMALL OR LARGE MESOZOOPLANKTON
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under a stereomicroscope equipped with an ocular micrometer, according to standard procedures (Harris et al. 2000). Small-sized zooplankters (most of Copepoda, juvenile stages of Pteropoda, Euphausiacea, Ostracoda, Amphipoda and Chaetognatha) were identified and counted in sub-samples obtained from the fixed sample volume by automatic pipette (approximately 500 individuals). Large zooplankters (big Copepoda, Pteropoda, Euphausiacea, Ostracoda, Amphipoda, Decapoda, Appendicularia, Chaetognatha, and Pisces larvae) were sorted out and identified from the whole sample. Representatives of Calanus spp. were identified at the species level based on morphology and prosome lengths of individual copepodid stages (Kwasniewski et al. 2003).
Data structure:
The data is following Darwin Core nomenclature as far as possible but also include variables that aren’t supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts etc is located in event file while the result such as scientificName, lifeStage, occurrence etc. are found in the occurrence file
Header name index - events
- expedition: cruise number for R/V Kronprins Haakon
- eventID: UUID for the sampel
- parentID: UUID for the gear deployment (each MultiNet deployment has a unique parentID)
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: human-readable sample ID (e.g. ZOT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- maximumDepthInMeters: bottom depth of the sampled layer
- minimumDepthInMeters: top depth of the sampled layer
- sampleType: description of the sample type according to a standard list
- fieldSplit: info about whether the sample is splitted. If the sample was split in 2 then fieldSplit = 2
- initialSampleVolume: The volume of water filtered through the plankton net. (initialSampleVolume = (netOpeningArea * (maximumDepthInMeters – minimumDepthInMeters)/field Split), Bongonet opening area: 3.14*(0.3)^2=0.2826 m2
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- analysedFraction: fraction of the sampled volume that is examined for organism counted
- individualCount: the number of individuals present in the analysed volume (see extra information below)
- phylum, class, order, family, genus & taxonKey-LSID: Taxonomical information for given species according to Worms
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Calanus finmarchicus).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in mm.
- organismRemark: indicates whether it is mesozooplankton, macrozooplankton, rare species
- identificationRemarks: a free text field for adding information relevant to the analysis. Used to indicate the speciemen that were dead. When nothing was remarked they were alive.
- identifiedBy: person who did the lab-analyse
- sampleSizeValue: the sample volume used to calculate the organismQuantity (sampleSizeValue 0 initialSampleVolume *analysedFraction)
- sampleSizeUnit: m3
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: ind/m3
Additional information for some of the fields
individualCount: The number of (all) organisms found in the sample examined
- for “mesozooplankton”, the number of mesozooplankton (medium size zooplankton organisms) encountered in all sub-samples
- for “macrozooplankton”, the number of macrozooplankton (large size zooplankton organisms, total length > 5 mm) encountered, identified in the entire sample
- for “rare” zooplankton, we only enter information about the finding of “rare” zooplankton in the database template, and its absolute number (“organismQuantity”) is not estimated
Funding:
The Nansen Legacy is funded by the Research Council of Norway and the Norwegian Ministry of Education and Research. They provide 50% of the budget while the participating institutions contribute 50% in-kind. The total budget for the Nansen Legacy project is 740 mill. NOK.
This dataset consists of model outputs for the study “Quantifying circumpolar summer habitat for Antarctic krill and Ice krill, two key species of the Antarctic marine ecosystem” published in ICES Journal of Marine Science.
Quality
Methods for this dataset are available in the associated publication.
The data has been collected during the JC2-1: Nansen Legacy Joint Cruise 2-1 12th July - 29th July 2021 on the research vessel RV Kronprins Haakon (toktnummer 2021708), along a transect from 76N to 82N east of Svalbard. The dataset contains mesozooplankton occurrence. It has been sampled using a MultiNet Midi at 5 distinct depths. Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton were collected with a mesh-size 180 µm. All specimens are identified to the lowest taxonomical level and the occurrence is given for a specific species and stage or size group as ind/m3.
Quality
Sampling method:
The sampling covers a transect from the central Barents Sea (76N) to the Arctic Ocean (82N) east of Svalbard, including 7 stations (P1 to P7). Each sampling event includes 5 distinct depth layers The depth intervals were from the bottom-200, 200-100, 100-50, 50-20 and 20-0 m. At the deep stations, the sampling depths were from 1000-600, 600-200, 200-50, 50-20 and 20-0 m Zooplankton has been collected using a Multinet Midi (HydroBios, opening: 0.25m2, net length: 250 cm). Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton were collected with a mesh-size 180 µm. All samples were preserved in 4 % formaldehyde free from acid.
PLEASE NOTE: THIS DATASET CONTAINS TWO COMPLETE DATASETS OF ZOOPLANKTON: ONE FOR SMALL MESOZOOPLANKTON (APPROX BODY SIZE BELOW 2 MM) COLLECTED WITH MULTINET 64 µM AND ONE FOR LARGE MESOZOOPLANKTON (APPROX BODY SIZE ABOVE 2 MM) COLLECTED WITH MULTINET 180 µM MESH SIZE. THE INFO ABOUT WHICH NET IS USED CAN BE FOUND IN gearType in extendedMeasurment andFacts USE EITHER 64 UM OR 180 UM DEPENDING ON WHETHER THE FOCUS IS SMALL OR LARGE MESOZOOPLANKTON
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under a stereomicroscope equipped with an ocular micrometer, according to standard procedures (Harris et al. 2000). Small-sized zooplankters (most of Copepoda, juvenile stages of Pteropoda, Euphausiacea, Ostracoda, Amphipoda and Chaetognatha) were identified and counted in sub-samples obtained from the fixed sample volume by automatic pipette (approximately 500 individuals). Large zooplankters (big Copepoda, Pteropoda, Euphausiacea, Ostracoda, Amphipoda, Decapoda, Appendicularia, Chaetognatha, and Pisces larvae) were sorted out and identified from the whole sample. Representatives of Calanus spp. were identified at the species level based on morphology and prosome lengths of individual copepodid stages (Kwasniewski et al. 2003).
Data structure:
The data is following Darwin Core nomenclature as far as possible but also include variables that aren’t supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts etc is located in event file while the result such as scientificName, lifeStage, occurrence etc. are found in the occurrence file
Header name index - events
-
expedition: cruise number for R/V Kronprins Haakon
-
eventID: UUID for the sampel
-
parentID: UUID for the gear deployment (each MultiNet deployment has a unique parentID)
-
eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
-
fieldNumber: human-readable sample ID (e.g. ZOT-001)
-
locationID: station name
-
decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
-
decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
-
bottomDepthInMeters: bottom depth in meters
-
eventRemarks: comments or remarks about the event (free text field)
-
gearType: the gear used to take the sample e.g. MultiNet 200 µm
-
maximumDepthInMeters: bottom depth of the sampled layer
-
minimumDepthInMeters: top depth of the sampled layer
-
sampleType: description of the sample type according to a standard list
-
fieldSplit: info about whether the sample is splitted. If the sample was split in 2 then fieldSplit = 2
-
flowmeterStart: only recorded if a flowmeter is used
-
flowmeterStop: only recorded if a flowmeter is used
-
initialSampleVolume: The volume of water filtered through the plankton net. The initial sample volume can be calculated in three ways and should always divided by fieldSplit if the sample is split.
-
theoreticalSampleVolume: Calculated based on sample layer thickness and net opening area (initialSampleVolume = netOpeningArea * (maximumDepthInMeters – minimumDepthInMeters)) Bongonet opening area: 3.14*(0.3)^2=0.2826 m2 WP2 opening area: 3.14*(0.285)^2 = 0.2550 m2 Multinet Midi opening area: 0.25 m2
-
flowmeterSampleVolume: Calculated based on flow-meter readings (initialSampleVolume= (flowmeterStart- flowmeterStop )*( flowmeter pitch = meters/revolution )*netOpeningArea)
-
regressionMultiNetVolume: Calculated based on regression for MultiNet samples (initialSampleVolume = -1.2681+(0.3298*(maximumDepthInMeter – minimumDepthInMeter))
-
initialVolumeMethod: description of which of the three methods were used to calculate the initialSampleSizeValue
-
recordedBy: name of the person who took the samples
-
principalInvestigatorName: name of the person in charge of the sample collection
-
principalInvestigatorEmail: email address of the person in charge of the sample collection
-
principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- analysedFraction: fraction of the sampled volume that is examined for organism counted
- individualCount: the number of individuals present in the analysed volume (see extra information below)
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Calanus finmarchicus).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in mm.
- organismRemark: indicates whether it is mesozooplankton, macrozooplankton, rare species
- identificationRemarks: a free text field for adding information relevant to the analysis
- identifiedBy: person who did the lab-analyse
- sampleSizeValue: the sample volume used to calculate the organismQuantity (sampleSizeValue 0 initialSampleVolume *analysedFraction)
- sampleSizeUnit: m3
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: ind/m3
Additional information for some of the fields
individualCount: The number of (all) organisms found in the sample examined
- for “mesozooplankton”, the number of mesozooplankton (medium size zooplankton organisms) encountered in all sub-samples
- for “macrozooplankton”, the number of macrozooplankton (large size zooplankton organisms, total length > 5 mm) encountered, identified in the entire sample
- for “rare” zooplankton, we only enter information about the finding of “rare” zooplankton in the database template, and its absolute number (“organismQuantity”) is not estimated
** Obsolete:** The actual data are no longer available at the specified website.
Field work was conducted during three spring seasons in Vårsolbukta, a pre-breeding stopover site in Svalbard, Norway. Ring readings were conducted daily with telescopes (20-60 zoom) for barnacle geese, brent geese and pink-footed geese. Date, time and area of each observation was registered. In addition, abdominal profiles were registered.
The data has been collected during the JC2-1: Nansen Legacy Joint Cruise 2-1 12th July - 29th July 2021 on the research vessel RV Kronprins Haakon (cruise number 2021708), along a transect from 76N to 82N east of Svalbard. The dataset contains mesozooplankton occurrence. It has been sampled using a BongoNet, HydroBios 60 cm. Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton were collected with a mesh-size 180 µm. All specimens are identified to the lowest taxonomical level and the occurrence is given for a specific species and stage or size group as ind/m3.
Sampling method:
The sampling covers a transect from the central Barents Sea (76N) to the Arctic Ocean (82N) east of Svalbard, including 7 stations (P1 to P7). Zooplankton has been collected using a BongoNet 60 cm (HydroBios, opening: 0.2827 m2, net length: 250 cm). Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton were collected with a mesh-size 180 µm. All samples were added 1 ml of Neutral Red Stain stock solution and wait 20 minutes before the samples is rinsed briefly and preserved in 4 % formaldehyde free from acid. The NeutralRed Stain. The samples were analysed within two months after sampling. Neutral Red Stain make it possible to distinguish between dead and alive zooplankton (Elliot and Tang 2009).
PLEASE NOTE: THIS DATASET CONTAINS TWO COMPLETE DATASETS OF ZOOPLANKTON: ONE FOR SMALL MESOZOOPLANKTON (APPROX BODY SIZE BELOW 2 MM) COLLECTED WITH MESH SIZE 64 µM AND ONE FOR LARGE MESOZOOPLANKTON (APPROX BODY SIZE ABOVE 2 MM) COLLECTED WITH MESH SIZE 180 µM MESH SIZE. THE INFO ABOUT WHICH NET IS USED CAN BE FOUND IN gearType. USE EITHER 64 UM OR 180 UM DEPENDING ON WHETHER THE FOCUS IS SMALL OR LARGE MESOZOOPLANKTON
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under a stereomicroscope equipped with an ocular micrometer, according to standard procedures (Harris et al. 2000). Small-sized zooplankters (most of Copepoda, juvenile stages of Pteropoda, Euphausiacea, Ostracoda, Amphipoda and Chaetognatha) were identified and counted in sub-samples obtained from the fixed sample volume by automatic pipette (approximately 500 individuals). Large zooplankters (big Copepoda, Pteropoda, Euphausiacea, Ostracoda, Amphipoda, Decapoda, Appendicularia, Chaetognatha, and Pisces larvae) were sorted out and identified from the whole sample. Representatives of Calanus spp. were identified at the species level based on morphology and prosome lengths of individual copepodid stages (Kwasniewski et al. 2003).
Data structure:
The data is following Darwin Core nomenclature as far as possible but also include variables that aren’t supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts etc is located in event file while the result such as scientificName, lifeStage, occurrence etc. are found in the occurrence file
Header name index - events
- expedition: cruise number for R/V Kronprins Haakon
- eventID: UUID for the sampel
- parentID: UUID for the gear deployment (each MultiNet deployment has a unique parentID)
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: human-readable sample ID (e.g. ZOT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- maximumDepthInMeters: bottom depth of the sampled layer
- minimumDepthInMeters: top depth of the sampled layer
- sampleType: description of the sample type according to a standard list
- fieldSplit: info about whether the sample is splitted. If the sample was split in 2 then fieldSplit = 2
- initialSampleVolume: The volume of water filtered through the plankton net. (initialSampleVolume = (netOpeningArea * (maximumDepthInMeters – minimumDepthInMeters)/field Split), Bongonet opening area: 3.14*(0.3)^2=0.2826 m2
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- analysedFraction: fraction of the sampled volume that is examined for organism counted
- individualCount: the number of individuals present in the analysed volume (see extra information below)
- phylum, class, order, family, genus & taxonKey-LSID: Taxonomical information for given species according to Worms
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Calanus finmarchicus).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in mm.
- organismRemark: indicates whether it is mesozooplankton, macrozooplankton, rare species
- identificationRemarks: a free text field for adding information relevant to the analysis. Used to indicate the speciemen that were dead. When nothing was remarked they were alive.
- identifiedBy: person who did the lab-analyse
- sampleSizeValue: the sample volume used to calculate the organismQuantity (sampleSizeValue 0 initialSampleVolume *analysedFraction)
- sampleSizeUnit: m3
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: ind/m3
Additional information for some of the fields
individualCount: The number of (all) organisms found in the sample examined
- for “mesozooplankton”, the number of mesozooplankton (medium size zooplankton organisms) encountered in all sub-samples
- for “macrozooplankton”, the number of macrozooplankton (large size zooplankton organisms, total length > 5 mm) encountered, identified in the entire sample
- for “rare” zooplankton, we only enter information about the finding of “rare” zooplankton in the database template, and its absolute number (“organismQuantity”) is not estimated
Funding:
The Nansen Legacy is funded by the Research Council of Norway and the Norwegian Ministry of Education and Research. They provide 50% of the budget while the participating institutions contribute 50% in-kind. The total budget for the Nansen Legacy project is 740 mill. NOK.
We used an extensive dataset of GPS-collared adult Svalbard reindeer females (2009–2018; N = 268 individual-years) to model summer and winter habitat selection as a function of remotely sensed environmental variables, and subsequently built habitat suitability models using an ensemble modelling framework. The predictor variables used in the final ensemble models were total biomass, curvature, elevation, distance from bird cliff, NDVI, slope, vegetation type and ruggedness. The raster values in the final winter (mean_winter9vars) and summer (mean_summer9vars) habitat suitability maps range from 0-1 where values close to 0 indicate low habitat suitability and values closer to 1 indicate high habitat suitability. The spatial resolution for both maps is 30 m. The raster layers are provided with the coordinate system UTM 33N WGS 84 (CRS: 32633). For more information see Pedersen et al. (2023).
Å.Ø. Pedersen, E.M. Soininen, B.B. Hansen, M. Le Moullec, L.E. Loe, I.M.G. Paulsen, I. Eischeid, S.R. Karlsen, E. Ropstad, A. Stien, A. Tarroux,H. Tømmervik, and V. Ravolainen. 2023. High seasonal overlap in habitat suitability in a non-migratory High Arctic ungulate. Global Ecology and Conservation 45: e02528. DOI: 10.1016/j.gecco.2023.e02528
We followed line-transect distance sampling survey protocols for estimating abundance of Svalbard reindeer in Sassendalen, Svalbard in July 2021.
Rangifer tarandus
Quality
For the distance sampling survey, we allocated 10 transect lines in north-south direction, from the mountain foothills to the riverbanks, on each side of a large river in Sassendalen, Svalbard. We chose one random latitude for the first line and placed additional parallel transect lines systematically apart 2.5 km east or west from this latitude to reduce the potential of overlapping reindeer observations and violation of the assumption of independence for DS surveys. We chose this systematic orientation across the valley (i.e., riverbed to mountain side or vise-versa) to reduce any bias from potential gradients in animal density related to e.g., plant phenology and/or habitat configuration. The strip length of each of the transects varied depending on the length from the mountain side to the riverbank (1.2 km to 2.9 km). The survey was conducted within the same three-day period 14-17 July 2021.
The 10 transects were walked by one observer at a constant speed (2–3 km h-1) without stops, except during measurements. We used a handheld GPS and a compass to keep the line direction, and single reindeer or clusters were detected on both sides of the transect line with the naked eye. When a reindeer or reindeer group was spotted, the observer looked only in its direction until measurements were taken. To respect the assumption of constant detection along the transect line, no scanning of the surroundings was done when stopping to take measurements. Each observation was measured by laser binoculars (10×42 Leica Geovid) to the nearest meter and a compass was used to measure the angle from the observer to the reindeer. Note that this method only captures the total number of reindeer and no structural information on age and does not record the population structure (i.e., age and sex) of the reindeer. The geographic position of the observer was also recorded. For practical reasons using the laser, measurements were taken to the largest reindeer (e.g., a mother rather than her calf) or the middle individual of a group of adults. From the distance sampling survey, the GPS positions of reindeer groups was calculated and used in the final dataset. For further details and application of the method on Svalbard reindeer see Le Moullec et al. 2017, Le Moullec et al. 2019.