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66 results for “Arctic Water”
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>
Arctic LTER 1988: del 13C and del 15N ratios measurement for Eriophorum, Carex and lichen species in water tracks at Toolik and Imnavait Creek
del 13C and del 15N ratios were measured for plant and lichen in watertracks in the Toolik Lake drainage and the east facing slope of the Imnavait Creek area. Sampling locations for each species for a specific date were chosen across an elevation gradient starting from the lakeside and leading to ridge crest. The vegetation was dried and analyzed for stable isotopes.
ICON-Coast model output for a study on the impact of Arctic coastal erosion on sea water carbonate saturation.
<p>Primary output of the ocean-biogeochemistry model ICON-Coast that has been used to create the figures in a manuscript on the impact of Arctic coastal erosion on sea water carbonate saturation.</p>
Genomic basis of deep‐water adaptation in Arctic Charr (Salvelinus alpinus) morphs
<p>Colonization of extreme habitats requires extensive adaptation to novel environmental challenges. Deep-water environments (>50 m) have high hydrostatic pressure, low temperature, and low light, requiring physiological and visual system adaptation, but genomic mechanisms underlying evolution in these environments are rarely known. Post-glacial colonization of Gander Lake in Newfoundland, Canada, by Arctic Charr (Salvelinus alpinus) provides the opportunity to study the genomic basis of adaptation to extreme deep-water environments. Here, we compare genomic and morphometric divergence between a phenotypically divergent deep-water, demersal morph adapted to depths of up to 288m and a larger, piscivorous morph occupying shallower depths. Using a SNP array and resequencing of nuclear and mitochondrial genomes, we find moderate genetic divergence (FST = 0.15 - 0.11) between morphs, consistent with divergence in body shape and size, despite absence of mitochondrial genome divergence. Outlier analyses identified three key genes with very high divergence against a genome-wide distribution of diverged genomic islands containing genes with functions related to deep-water adaptation such as sensory processes, ligand binding and regulation of transcription. Quantification of SNP array signal intensity variation associated with complex polymorphisms (e.g. copy number variants), similarly uncovered genetic separation of morphs and coincided with several islands of genomic divergence, but also revealed additional genomic regions and molecular mechanisms associated with depth adaptation. Together, these results show that adaptation to an extreme deep-water environment has been facilitated by multiple polymorphism types with roles in cellular and physiological processes, providing insight into the genomic basis of adaptation in extreme environments.</p>
Tracking freshwater browning and coastal water darkening from boreal forests to the Arctic Ocean
<p></p> <p class="MsoNormal"><span>The forest cover of Northern Europe has been steadily expanding during the last 120 years. More terrestrial vegetation and carbon fixation leads to more export to surface waters. This may cause freshwater browning, as more degraded plant-litter ends up as chromophoric (coloured) dissolved organic matter. Although most freshwater ultimately drains to coastal waters, the link between freshwater browning and coastal water darkening is poorly understood. Here, we explore this relationship through a combination of centennial records of forest and coastal water clarity, contemporary optical measurements in lakes and coastal waters, as well as an ocean drift model. We suggest a link between forest cover in Northern Europe and coastal water clarity in the Baltic, Kattegat and Skagerrak Sea and show how brown coloured freshwater from Northern European catchments can dictate coastal water clarity across thousands of kilometres, from the Baltic lakes to the Barents Sea.</span></p>
FESOM model data and particle tracking data used in publication 'Cross-shelf transport of Barents Sea dense water as a sink for CO2 in the Arctic Ocean'
<p>FESOM model data and particle tracking data used in the paper 'Cross-shelf transport of Barents Sea dense water as a sink for CO2 in the Arctic Ocean" by Andreas Rogge at al.</p> <p>1) FESOM velocity fields averaged over the top 200 m water depth, averaged over the time period 2015-2018.</p> <p>2) FESOM transect at 95°E in the Arctic Ocean (temperature, salinity and velocity), averaged over the time period 2015-2018.</p> <p>3a) Particle back-tracking data based on daily FESOM velocity fields in netcdf format. Particles were released at 95°E every 14 days during the year 2018 and tracked until they reached the surface. Three different constant sinking velocities were used, representative for small and large non-ballasted particles and small ballasted particles.</p> <p>3b) Distribution of particles at the surface for the experiments with three different sinking velocities as mat files. </p>
In-situ parameters, nutrients and dissolved carbon distribution in the water column and pore waters of Arctic Fjords (Western Spitsbergen) during a melting season
<p>A nutrient distribution such as phosphate (PO₄³⁻), ammonium (NH₄⁺), nitrate (NO₃⁻), dissolved silica (Si), total dissolved nitrogen (TN), dissolved organic nitrogen (DON) together with dissolved organic carbon (DOC) and inorganic carbon (DIC), was investigated during a high melting season in 2021 in the western Spitsbergen fjords (Hornsund, Isfjorden, Kongsfjorden, and Krossfjorden). Both the water column and the pore water were investigated for nutrients and dissolved carbon distribution and gradients. The water column concentrations of most measured parameters such as PO₄³⁻, NH₄⁺, NO₃⁻, Si, and DIC showed significant changes among fjords and water masses. In addition, pore water gradients of PO₄³⁻, NH₄⁺, NO₃⁻, Si, DIC and DOC revealed significant variability between fjords and are likely substantial sources of the investigated elements for the water column. The obtained dataset reflects differences in hydrography and biogeochemical ecosystem function of the western Spitsbergen fjords and may form the base for further modelling of physical oceanographic and biogeochemical processes within the investigated fjord systems.</p> <p> </p>
Data from: Dietary plasticity and broad North Atlantic origins inferred from bulk and amino acid-specific δ15N and δ13C favor killer whale range expansions into Arctic waters
<p>Killer whales (<em>Orcinus orca</em>) occur seasonally in the eastern Canadian Arctic (ECA), where their range expansion associated with declining sea ice have raised questions about the impacts of increasing killer whale predation pressure on Arctic-endemic prey. We assessed diet and distribution of ECA killer whales using bulk and compound specific stable isotope analysis (CSIA) of amino acids (AA) of 54 skin biopsies collected from 2009-2020 around Baffin Island, Canada. Bulk ECA killer whale skin δ15N and δ13C values did not overlap with potential Arctic prey after adjustment for trophic discrimination, and instead reflected foraging history in the North Atlantic prior to their arrival in the ECA. Adjusted killer whale stable isotope (SI) values primarily overlapped with several species of North Atlantic baleen whales or tuna. Amino acid (AA)-specific δ15N values indicated the ECA killer whales fed primarily on marine mammals, having similar glutamic acid δ15N – phenylalanine δ15N (δ15NGlx-Phe) and threonine δ15N (δ15NThr) as mammal-eating killer whales from the eastern North Pacific (ENP) that served as a comparative framework. However, one ECA whale grouped with the fish-eating ENP ecotype based δ15NThr. Distinctive essential AA δ13C of ECA killer whale groups, along with bulk SI similarity to killer whales from different regions of the North Atlantic, indicate different populations converge in Arctic waters from a broad source area. Generalist diet and long-distance dispersal capacity favor range expansions, and integration of these insights will be critical for assessing ecological impacts of increasing killer whale predation pressure on Arctic-endemic species.</p>
Figure 3 in Untangling the Derogenes varicus species complex in Scandinavian waters and the Arctic: description of Derogenes abba n. sp. (Trematoda, Derogenidae) from Hippoglossoides platessoides and new host records for D. varicus (Müller, 1784) sensu stricto
Figure 3. "Derogenes limula" ex Parablennius tentacularis. Unpublished line drawing by A. Looss.
Figure 1 in Unusual shallow-water boreal gastropod species associations at the Northern part of Arctic archipelago Novaya Zemlya
Figure 1. Map of studied areas off Novaya Zemlya.
Tracing the imprint of river runoff on Arctic water mass transformation [dataset]
<p>This dataset contains the underlying data for the manuscript Lambert et al., Tracing the imprint of river runoff<br> variability on Arctic water mass transformation, submitted to JGR-Oceans</p> <p>-----------------------------------<br> Both files contain variables with the general notation:<br> S..., which are the cumulative salt fluxes;<br> S..2, which are the salinity-transformation fluxes;<br> T..., which are the cumulative heat fluxes; and<br> T..2, which are the temperature-transformation fluxes.</p> <p>-----------------------------------<br> In the file crfdata.nc, the variable names contain:<br> slrx: surface salinity restoring term<br> emp: evaporation-precipitation, small en neglected in the manuscript<br> rnf: river runoff<br> ice: ice melt<br> brnx: brine rejection including the penetration into subsurface layers<br> qns: nonsolar surface heat flux<br> qswx: heat flux due to shortwave radiation including the penetration into subsurface layers<br> fsiso/ftiso: isopycnal diffusion of salt/heat<br> fsdia/ftdia: diapycnal diffusion of salt/heat<br> sec: advection across the collective Arctic gateways</p> <p>Each variable is of size [4,12,nS] or [4,12,nT] where nS is the number of salinity bins, equal to the length of variable S<br> and nT is the number of temperature bins, equal to the length of variable T</p> <p>The first dimension is ordered as follows:<br> 0: delta_s, the equilibrium response to a 30% increase in total Arctic river runoff<br> 1: tau_s, the e-folding time scale of this response in months<br> 2: std, the standard deviation of the control value<br> 3: ctrl, the average control value</p> <p>The second dimension indicates the calendar month</p> <p>-----------------------------------------<br> In the file pp2.nc, the variable names contain:<br> slrx: surface salinity restoring term<br> rnf: river runoff<br> ice: ice melt<br> brnx: brine rejection including the penetration into subsurface layers<br> qns: nonsolar surface heat flux<br> qswx: heat flux due to shortwave radiation including the penetration into subsurface layers<br> adv: advection across the collective Arctic gateways<br> dif: total isopycnal + diapyncal diffusion</p> <p>Each variable is of size [2,nS] or [2,nT]</p> <p>The first dimension is:<br> 0: explained model variance between 0 and 1<br> 1: explained model variance where correlations with p>.05 equal NaN</p>
Data from: Dietary plasticity and broad North Atlantic origins inferred from bulk and amino acid-specific δ15N and δ13C favor killer whale range expansions into Arctic waters
Open the record for dataset details and reuse information.
Genomic basis of deep‐water adaptation in Arctic Charr (Salvelinus alpinus) morphs
Open the record for dataset details and reuse information.
Dataset for: Tracking freshwater browning and coastal water darkening from boreal forests to the Arctic Ocean
Open the record for dataset details and reuse information.
Arctic LTER site, station Kuparuk River, study of water temperature (mean maximum) in units of celsius on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean maximum) measurements in celsius units and were aggregated to a monthly timescale.
Arctic LTER site, station Kuparuk River, study of water temperature (mean maximum) in units of celsius on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean maximum) measurements in celsius units and were aggregated to a yearly timescale.
Arctic LTER site, station Kuparuk River, study of water temperature (mean) in units of celsius on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean) measurements in celsius units and were aggregated to a monthly timescale.
Arctic LTER site, station Kuparuk River, study of water temperature (mean) in units of celsius on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean) measurements in celsius units and were aggregated to a yearly timescale.
Arctic LTER site, station Kuparuk River, study of water temperature (mean minimum) in units of celsius on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean minimum) measurements in celsius units and were aggregated to a monthly timescale.
Arctic LTER site, station Kuparuk River, study of water temperature (mean minimum) in units of celsius on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Arctic LTER (ARC) contains water temperature (mean minimum) measurements in celsius units and were aggregated to a yearly timescale.
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