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197 results for “Canadian Arctic”
Arctic vegetation cover fractions derived from Landsat time series (1984-2020) for the greater Mackenzie Delta Region (Western Canadian Arctic)
<p>Data to the publication by Nill et al. (2022) "<em>Arctic shrub expansion revealed by Landsat-derived multitemporal<br> vegetation cover fractions in the Western Canadian Arctic"</em></p> <p>The dataset features Landsat-derived fractional cover estimates of Arctic plant functional types (shrub, evergreen trees, herbaceous, lichen) and other land cover (barren, water) in the greater Mackenzie Delta Region, Canada.<br> We utilized regression-based unmixing based on synthetic training data in order to build multitemporal Kernel Ridge Regression (KRR) models for estimating fractional cover and validated our predictions based on independent very-high-resolution imagery (please be referred to publication for details).<br> <br> <strong>Dataset information</strong><br> The fraction cover predictions ("krr-avg") are provided separately for each epoch (1984-1990, 1991-1996, ..., 2015-2020) and class/cover type. The decadal change images ("dec-cng") between 1984 and 2020 are provided separately for each class/cover type. The naming convention of the files is as follows:</p> <p>XXXX-XXXX_YYY-YYY_int16-10e3_class-Z-Z</p> <ul> <li>XXXX-XXXX = epoch, e.g. 2015-2020</li> <li>YYY-YYY = dataset ("krr-avg" = fraction cover, "dec-cng" = decadal fraction cover change)</li> <li>Z-Z = class ID and associated class name (sh = shrub, cf = coniferous, hb = herbaceous, lc = lichen, wt = water, br = barren)</li> </ul> <p>The fraction cover values are % scaled by 10,000. For instance, a value of 1234 refers to 12.34%. Further image metadata:</p> <ul> <li><strong>Datatype:</strong> Signed 16-bit integer (Int16) </li> <li><strong>Data format: </strong>GeoTiff (.tif)</li> <li><strong>No data value:</strong> -9999</li> <li><strong>Projection:</strong> EPSG:3573 with custom central meridian; WKT string: 'PROJCS["WGS 84 / North Pole LAEA Canada",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Lambert_Azimuthal_Equal_Area"],PARAMETER["latitude_of_center",90],PARAMETER["longitude_of_center",-135],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1],AXIS["Easting",EAST],AXIS["Northing",NORTH]]'</li> </ul> <p><strong>Publication</strong><br> Nill, L., Grünberg, I., Ullmann, T., Gessner, M., Boike, J. & Hostert, P. (2022): Arctic shrub expansion revealed by Landsat-derived multitemporal vegetation cover fractions in the Western Canadian Arctic. Remote Sensing of Environment, 2022, 281. https://doi.org/10.1016/j.rse.2022.113228</p> <p><strong>Further information</strong><br> For further information, please see the publication or contact Leon Nill (leon.nill@geo.hu-berlin.de).<br> A web-visualization of this dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/arctic-shrub/">here</a>.</p>
Spectral albedo and summer ground temperature of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic
<p>These data are in support of a preprint: </p><p>Comparing spectral albedo and NDVI of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic</p><p>Florent Domine, Maria-Belke-Brea, Ghislain Picard, Laurent Arnaud, and Esther Lévesque</p><p>To be submitted in 2023. </p><p>The spectral albedo of several vegetation assemblages on Bylot Island and in Mala River valley on nearby Baffin Island were recorded between 10 and 18 July 2015. The spectral range covered was 346 to 2400 nm. Surfaces were classified according to the main vegetation types. Classes used are graminoids, moss, Salix arctica, soil, and Salix richardsonii. S. richardsonii is the only truly erect species on Bylot Island. Transmission spectra of radiation through the S. richardsonii canopy were also recorded. S. richardsonii spectra were different depending on the location where they were measured and we present spectra for sites in active parts of an alluvial fan (Salix-G2), an inactive part of an alluvial fan (Salix-D1) and in a mesic area on Mala River Valley (Salix-M). We also present typical relative solar irradiance spectra recorded at Bylot Island during the campaign, under clear and overcast conditions. In conjunction with spectral albedo data, these irradiance spectra allow the calculation of the broadband (BB) albedo of the vegetation types and to compare BB albedo values under identical irradiance conditions. 83 spectra were recorded: 39 for S. richardsonii and 44 for low vegetation and soil. 17 transmission spectra under S. richardsonii were recorded. We present here only averages for each vegetation type. We also present averages for all low vegetation types and for all S. richardsonii spectra, to allow the calculation of the radiative impact of erect shrubs at Bylot Island. </p><p>We also present soil temperature data at 15 cm depth for the spots GRASS (mostly Salix Arctica), TUNDRA (Mostly moss), SALIX-D1 (Salix richardsonii) and SALIX-F (Salix richardsonii). SALIX-F is similar to SALIX-G2. The data are during summer 2020. </p><p>The locations of the various spots investigated are: </p><p><strong>Spot name Latitude Longitude Vegetation types found</strong></p><p>TUNDRA 73.150° -80.004° Humid and moist polygons with low vegetation dominated by mosses, graminoids, S. arctica and S. herbacea.</p><p>PLAINE 73.167° -79.915° Low vegetation and bare soil patches caused by cryoturbation (mudboils) with mosses, graminoids and S. arctica.</p><p>GRASS 73.158° -79.907° Low vegetation between patches of S. richardsonii dominated by S. arctica, with litter, mosses, graminoids and occasional bare soil. </p><p>SALIX-D1 73.158° -79.907° Scattered patches of S. richardsonii <35 cm tall. Understory is mosses, graminoids, litter, S. arctica and bare soil.</p><p>SALIX-M 73.006° -80.685° Mesic area with patches of S. richardsonii 35 to 40 cm tall. Understory includes moss, graminoids and litter. Between patches: herb tundra with graminoids and mosses. The area is not within an alluvial fan.</p><p>SALIX-G2 73.168° -79.812° Extended area in an alluvial fan with S. richardsonii >40 cm. Understory includes litter, mosses, graminoids, bare soil, S. arctica and S. reticulata.</p><p>SALIX-F 73.182° -79.745° Similar to SALIX-G2. Ground temperature is monitored there. No spectral data were recorded at that site. </p><p> </p><p> </p>
Figure 5 in A gall mite, Aceria rhodiolae (Acari: Eriophyidae), altering the phytochemistry of a medicinal plant, Rhodiola rosea (Crassulaceae), in the Canadian Arctic
Figure 5. Coxigenital region of Aceria rhodiolae females from (A) Russia, and (B,C,E) Nunavik, Canada. (A,B) Differential interference contrast light microscopy, (C,E) scanning electron micrograph, (D) line drawing. Scale on (B) also applies to (A). Notations on (D) indicate palp, leg and idiosomal setae, and coxal apodemes (ap1, ap2, ap; pra, prosternal apodeme). Other arrows elsewhere indicate characteristic ridges on coxal plates (a,b,c); genital flange (fl), and underlying postgenital plate (pp), which bears setae 3a and extends anterolaterally into lateral flaps (f) that flank the genital coverflap; and ventral ridges on femur, genu, and coxal fields (E).
Figure 8 in A gall mite, Aceria rhodiolae (Acari: Eriophyidae), altering the phytochemistry of a medicinal plant, Rhodiola rosea (Crassulaceae), in the Canadian Arctic
Figure 8. (A) Healthy infructescence of a Rhodiola rosea plant from Nunavik (Canada) versus (B) a mite-infested inflorescence (mostly pale green or yellowish) that partly (centrally) developed into fruits (yellow to red). (C) Dried inflorescences from Labrador (Canada) with a few (upper right) to most (lower left) flowers galled, and a galled leaf (isolated, in the middle). (D) Dried inflorescences from western Russia that were preserved in an herbarium for over 100 years. (E,F) Enlargement of a galled flower and galled leaf from Labrador (same scale). Arrows point at some of the galled flowers (B‒D) or leaves (C). The scale on (C) also applies to (D), and is approximate for (A,B).
Figure 1 in A gall mite, Aceria rhodiolae (Acari: Eriophyidae), altering the phytochemistry of a medicinal plant, Rhodiola rosea (Crassulaceae), in the Canadian Arctic
Figure 1. (A) Map of Canada, showing the area surveyed for Rhodiola rosea in Nunavik, Québec (in white). The small arrow indicates a site where additional samples were taken in Labrador, Newfoundland. (B) Region along the coast of Ungava Bay where populations of R. rosea were surveyed (geographic extremes of study sites: northwest 61.078°N, 69.632°W; northeast 60.422°N, 64.839°W; south 58.023°N). Open circles indicate sites with at least a few galled plants, whereas solid circles indicate sites with no galled plants.
Data on transit history and anti-fouling practices for ships arriving to the Canadian Arctic
<p>Ship biofouling is a major vector for the introduction and spread of harmful marine species globally, however, its importance in Arctic coastal ecosystems is understudied. The objective of this study was to provide insight regarding the extent of biofouling (i.e., percent cover, abundance, and species richness) on commercial ships operating in the Canadian Arctic. A questionnaire was used to collect information on transit history, anti-fouling practices, and self-reported estimates of biofouling extent from a sample of ships operating in the region during 2015 – 2016.</p>
Canadian Arctic killer whale genomic variants
<p>This dataset contains resequencing data used in our killer whale genomics research exaiming population structure and demographic history, including unfiltered genomic variants and filtered SNPs. Source code for genomic analyses is available at <a href="http://github.com/edegreef/NBW-resequencing">github.com/edegreef/killerwhale-resequencing</a>. Data uploaded here contain:</p> <ul> <li><strong>orca_sample_info.csv</strong> - metadata for the killer whale samples</li> <li><strong>orca_unfiltered_diploid.vcf.gz</strong> - all variant calls, including indels and SNPs (n = 29)</li> <li><strong>orca_snps_q30_biallelic.vcf.gz </strong>- SNPs filtered for quality and bi-allelic sites (n = 29)</li> <li><strong>orca_snps_q30_biallelic_HWE0.005_miss0.4.vcf.gz</strong> - SNPs filtered for quality, bi-allelic sites, out of HWE, and missingness > 0.4 (n = 29).</li> <li><strong>orca_snps_q30_biallelic_HWE0.005_miss0.4_maf0.05_LDprunedr08_n24.vcf.gz</strong> - SNPs further filtered for MAF, LD-pruned, and removal of kin & duplicates (n = 24).</li> </ul>
DeltaCAN: A new data set of Canadian Arctic and subarctic coastal deltas
<p>Arctic coasts constitute the critical interface between land and sea, and are subject to rapid changes caused by a warming climate. Current trends throughout the Arctic show increasing erosion trends, while other parts of the coast are experiencing prograding trends. Until now, a vast majority of our knowledge of Arctic coastal evolution is confined to site-specific studies with limited geospatial representation. Here, we present DeltaCAN, a novel data set on the locations of Canadian deltas larger than 500 m in width derived by visual interpretation of freely available satellite imagery. DeltaCAN is Canada's first nationwide coastal detection covering 250.000 km of coastline in the Arctic, identifying 2712 deltas. The inventory is based on inspection of remotely-sensed satellite imageries, developed through an expert-based mapping approach where we implemented a quality control mechanism to assess the completeness of the data set. The DeltaCAN data set allows for assessing changes at an unprecedented spatial extent, improving our understanding of delta morphodynamics.</p>
Fig. 2 in Morphological and morphometric differentiation of dorsal-spined first stage larvae of lungworms (Nematoda: Protostrongylidae) infecting muskoxen (Ovibos moschatus) in the central Canadian Arctic
Fig. 2. Laboratory guide for the differentiation of L1 of U. pallikuukensis and V. eleguneniensis. The guide is based on key morphological features supported by morphometric data of heat killed L1. These features were characteristic of each of the species as visible under 400 × magnification.
Fig. 1 in Morphological and morphometric differentiation of dorsal-spined first stage larvae of lungworms (Nematoda: Protostrongylidae) infecting muskoxen (Ovibos moschatus) in the central Canadian Arctic
Fig. 1. Morphology of first stage larva (L1) of Umingmakstrongylus pallikuukensis. Photomicrograph of U. pallikuukensis L1 taken at 400 × magnification in differential interference contrast indicating the location of relevant important anatomical structures.
Fig. 3 in Morphological and morphometric differentiation of dorsal-spined first stage larvae of lungworms (Nematoda: Protostrongylidae) infecting muskoxen (Ovibos moschatus) in the central Canadian Arctic
Fig. 3. Morphology of Cystocaulus ocreatus first stage larva (L1). Photomicrograph of C. ocreatus L1 collected from Uzbekistan (US National Parasite Collection No. 95144) taken at 400 × magnification in differential interference contrast showing ventral post-anal cuticular striations and overall elongated structure of the tail spike similar to U. pallikuukensis.
Supplemental data for "Widespread and rapid dynamics of subglacial water in the Canadian Arctic"
<h2>What's inside</h2> <p>This data set contains:</p> <ol> <li><strong>Inventory:</strong> The inventory of the active subglacial water bodies in the Canadian Arctic.</li> <li><strong>Workflows:</strong> Data analysis code that produces the study results. </li> <li><strong>Results:</strong> The derived ArcticDEM strip data and visualizations generated by this study.</li> </ol> <p>See "README.md" for more information.</p>
Linked collectors and determiners for: Rhamphomyia Meigen of the Canadian Arctic Archipelago, Greenland and Iceland (Diptera: Empididae).
Natural history specimen data linked to collectors and determiners held within, "Rhamphomyia Meigen of the Canadian Arctic Archipelago, Greenland and Iceland (Diptera: Empididae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8e19d5d0-be5e-4022-a16c-b3ce0e554c54">https://bionomia.net/dataset/8e19d5d0-be5e-4022-a16c-b3ce0e554c54</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8e19d5d0-be5e-4022-a16c-b3ce0e554c54">https://gbif.org/dataset/8e19d5d0-be5e-4022-a16c-b3ce0e554c54</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Natural history museum data on Canadian Arctic marine benthos.
Natural history specimen data linked to collectors and determiners held within, "Natural history museum data on Canadian Arctic marine benthos". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/eaf9401e-a5e3-4a27-89ad-2d6ac6559167">https://bionomia.net/dataset/eaf9401e-a5e3-4a27-89ad-2d6ac6559167</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/eaf9401e-a5e3-4a27-89ad-2d6ac6559167">https://gbif.org/dataset/eaf9401e-a5e3-4a27-89ad-2d6ac6559167</a>. Formatted as a Frictionless Data package.
FIG. 6. — A in Archaeofaunal signatures of specialized bowhead whaling in the Western Canadian Arctic: a regional study
FIG. 6. — A, Faunal frequencies (%NISP) for sites on the East Channel of the Mackenzie River; B., faunal frequencies (%NISP) for sites
FIG. 7 in Archaeofaunal signatures of specialized bowhead whaling in the Western Canadian Arctic: a regional study
FIG. 7. — Artefact frequencies of whale bone artefacts as a percentage of total organic artefacts from coastal contexts in the Mackenzie Delta Region. Black bars represent presumptive whaling sites, while grey bars represent non-whaling sites.
FIG. 8 in Archaeofaunal signatures of specialized bowhead whaling in the Western Canadian Arctic: a regional study
FIG. 8. — Relative meat contribution of taxa in the presumptive bowhead whaling assemblages based on % weight of total edible tissue, using techniques applied in Friesen & Arnold (1995).
FIG. 3 in Archaeofaunal signatures of specialized bowhead whaling in the Western Canadian Arctic: a regional study
FIG. 3. — Locations of bowhead whale aggregation areas (after Martell et al.1984; Fraker et al. 1978, and Hardwood & Smith 2002).
PAH concentrations in the Fram Strait, the Canadian Arctic Archipelago and the lower Great Lakes
<p>The PEs were deployed at different water depths of deep moorings deployed in the Fram Strait during 2014-2015 (9 samples) and 2018-2019 (22 samples), as well as in surface seawater of the Canadian Arctic Archipelago (6 samples), and in the air (6 samples) and surface water (3 samples) of the lower Great Lakes during 2018-2019. For atmospheric sampling, PEs have deployed at ~1-2 m height and fixed inside two inverted bowls to prevent rainfall and direct solar radiation. For water sampling, PEs were strung on stainless steel wires and attached to stainless steel cages. The surface-water cages were fixed to subsurface floats at ~4-5 m depth, while the deep-water cages were fastened to deep moorings at different depths for ~1 year. PAH concentration data were collected.</p> <p>Supporting information for "Zhang, L., Ma, Y., Vojta, S., Morales-McDevitt, M., Hoppmann, M., Soltwedel, T., et al. (2023). Presence, Sources and Transport of Polycyclic Aromatic Hydrocarbons in the Arctic Ocean. <em>Geophysical Research Letters</em>, 50, e2022GL101496". <a href="https://doi.org/10.1029/2022GL101496">https://doi.org/10.1029/2022GL101496</a></p>
Ground-penetrating radar and shallow firn cores from Devon Ice Cap, Canadian Arctic
<p>GPR data and firn cores were collected over Devon Ice Cap, Canadian Arctic in May 2015.</p> <p>-----------------------------------------------------------------</p> <p><strong>Firn cores</strong></p> <p>Six ~11 m long firn cores were drilled using a Kovacs drill (9 cm diameter) along the GPR profiles. Pictures were taken of the firn cores, which were subsequently used to log the firn facies. From each core, three sections at different depths that did not include ice layers were weighted with a digital scale and used to calculate the firn density. At each firn core location, the snow depth was recorded, as well as at an additional location where a snow pit was dug (SPB1).</p> <p><em>DIC_firn_cores_2015_density.xlsx</em>: Firn core density measurements. Three measurements were taken from each core, using ice-free sections. </p> <p><em>DIC_firn_cores_2015_stratigraphy.xlsx</em>: Firn stratigraphy for each core location, derived from the firn core pictures. F stands for firn, I for ice layer, and P for percolation pipe/feature (ice in the firn core that does not present as an ice layer throughout the core diameter).</p> <p><em>DIC_snowdepth_2015.xlsx</em>: Snow depth measurements at each core location.</p> <p><em>Firn_core_pictures.zip</em>: Pictures of the firn cores taken with infrared and visible light cameras.</p> <p>-----------------------------------------------------------------</p> <p><strong>GPR data</strong></p> <p>GPR data were collected with a PulseEKKO Noggin radar (Sensors & Software Inc.) with 500 MHz center frequency antennae (i.e., 0.6 m wavelength). The antennae were mounted on a plastic sled towed by snowmobile, generating a data set sampled every ~0.4 m along track. Positioning was obtained with a Leica Geosystems GPS system providing a 25 cm RMS accuracy.</p> <p>Processing of the GPR data was performed in Matlab and included dewow filtering, time-zero shift, background removal, Butterworth band-pass filtering and the application of a gain function.</p> <p><em>PulseEkko_RawData</em>: Folder containing the raw PulseEKKO GPR and GPS files.</p> <p><em>PulseEkko_ProcessedData</em>: Contains the processed GPR data as .mat files. Description of the data files can be found in <em>ProcessedData_readme.txt</em>.</p> <p> </p>
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