cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18739/a2bk16q5t
title: Ice microstructure (optical measurements) from Jarvis Glacier, Alaska, 2017-2020

description: Ice sheets and alpine glaciers discharge primarily though streaming flow, so the dynamics of that flow is central to the overall mass balance of the cryosphere. In glaciers and ice streams, the resistance to flow at the bed is important, but equally important is the internal viscous strength of the ice near the margins. In many cases, the lateral margins support greater than 50% of the resisting stress. At present, there is moderate to high uncertainty of the factors controlling the viscous strength of streaming ice under natural conditions. Although experiments suggest that variations in the intensity and orientation of the crystallographic fabric can result in up to a ten-fold difference in flow strength, in-situ observational studies of the microstructural architecture of streaming ice number in the low single digits. Most microstructural and in-situ rheological studies come from ice divides, near sites of paleoclimate coring. To complement that work and provide insight into the dynamic influence of streaming ice margins, our study documented both temperature and microstructure across a strain gradient at the lateral margin of Jarvis (Creek) Glacier and related those observations to modeled and observed 3D velocity structure.
 The dataset included here is one component of the larger project described above: crossed-polarized light images of thin-sections from three ice cores collected in spring 2017. Holes were drilled along a transect from less to more sheared ice, with the goal being to reach bed in at least two locations within the time constraints of the drilling season. We attempted six holes. Three were studied: JA, 63.4750˚N, 145.6753˚W, 1621 m elevation, 80 m long; JB, 63.4749˚N, 145.6759˚W, 1625 m, 30 m long; JE, 63.4743˚N, 145.6766˚W, 1625 m, 18 m long. JA and JE appear to have reached bed; other cores were limited by debris. We selected 12 samples from JA, 8 from JB, and 6 from JE to represent each ice core. For background, we also include a location map and core log.
DOI: 10.18739/a2tb0xw4t
title: Arctic surface Urban Heat Island (UHI), MODIS Land Surface Temperature (LST) data, 2000-2016.

description: This data set is comprised of two image maps and one data file. The data file contains Land Surface Temperature (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, and surface Urban Heat Island (UHI) data calculated based on LST data for 118 arctic and sub-arctic urban areas, 2000-2016. Seasonally and temporally averaged urban LST and surface UHI time series are provided in the data archive. These data were analyzed for cities in northern West Siberia (Miles and Esau, 2017) and 57 cities in northern Fennoscandia (Miles and Esau, 2020). This data set was produced in the project 'Collaborative Research: HIARC: Anthropogenic Heat Islands in the Arctic: Windows to the Future of the Regional Climates, Ecosystems, and Societies'. The international HIARC project was performed within the Belmont Forum Collaboration Research Action (CRA) on 'Arctic Observing and Research for Sustainability', with funding from the Research Council of Norway, NSF, and the Russian Foundation for Basic Research.
DOI: 10.15468/dl.dxsqtp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((37.28417 0.2491667, 37.28417 0.2391667, 37.285 0.2391667, 37.285 0.2375, 37.28583 0.2375, 37.28583 0.2358333, 37.2875 0.2358333, 37.2875 0.2375, 37.28833 0.2375, 37.28833 0.24, 37.2875 0.24, 37.2875 0.2408333, 37.28667 0.2408333, 37.28667 0.2441667, 37.2875 0.2441667, 37.2875 0.245, 37.28667 0.245, 37.28667 0.2466667, 37.28583 0.2466667, 37.28583 0.2491667, 37.28417 0.2491667))",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027827-241107131044228/datasets/export for details.
DOI: 10.15468/dl.5qjf7v
title: Occurrence Download

description: A dataset containing 66800 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Rhododendron ponticum L."
 ]
}

 The dataset includes 66800 records from 209 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027823-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18739/a2f18sg1v
title: Evaluating the Competing Impacts of Global Emissions Reductions and Climate Change on the Distribution and Retention of selected persistent organic pollutants (POPs) in the Arctic Ocean, 1979-2050

description: The goal of the proposed research is to better understand how changes in global emissions and climate are affecting the distribution, lifetime, and bioavailability of selected persistent organic pollutants (POPs) in the Arctic Ocean. POPs travel globally in air and water, are often highly bioaccumulative, and have the ability to cycle among environmental media enabling long-range transport to remote regions such as the Arctic. The investigators will use a modeling approach to provide insight into the relative importance of changing primary anthropogenic emissions and oceanic biogeochemical processes in controlling the fate and lifetime of POPs in the Arctic Ocean. The research will focus on two classes of compounds (polyfluorinated compounds - PFCs - and polychlorinated biphenyls - PCBs) with contrasting physical and chemical properties affecting behavior and reactivity in the atmosphere and ocean. The investigators will also collect new data on depth profiles of PCBs and two PFCs - perfluorooctane sulfonate (PFOS) and perfluorooctanate (PFOA) - in the Arctic Ocean. Three main objectives will be addressed in the proposed research:
 1) Quantify the global and regional atmospheric budget of PCBs and PFCs, including relevant spatially-varying uncertainties 
 2) Quantify the budget of PCBs and PFCs in the Arctic Ocean, including inputs from atmospheric deposition, riverine inflows, and ocean cycling 
 3) Quantify the relative importance of atmospheric, oceanic, and riverine inputs of PFOA, PFOS and PCBs to the Arctic, including the influence of climate and emissions.
 Ultimately this project will improve knowledge of how these compounds reach the Arctic and inform environmental management. The broader impacts component of the project will have three main goals: (1) Provide policy-relevant information to the Stockholm Convention and other international agreements on POPs to support monitoring and evaluation efforts for its controls on PCBs and PFOS and related compounds; (2) Inform sustainability education, by developing a case study on emerging POPs in the Arctic for courses relevant to environmental sustainability; and (3) train the next generation of interdisciplinary scientists (one graduate student will be trained at each of the three collaborating institutions).
DOI: 10.18739/a2nk36594
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L520

description: Data from Lake 520. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a2ht2gc50
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L280

description: Data from Lake 280. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a28911r88
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L129

description: Data from Lake 129. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a24m91b6t
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L80

description: Data from Lake 80. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.15468/dl.6d52gu
title: Occurrence Download

description: A dataset containing 455616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "OccurrenceStatus is Present",
 "TaxonKey is Ciconiiformes",
 "Year 2010-2024"
 ]
}

 The dataset includes 455616 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027814-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18739/a20v89j2p
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L56

description: Data from Lake 56. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a2w37kw70
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: North Head 1

description: Data from lakes in North Head. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a2rb6w338
title: 2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: Manta Lake

description: Data from Manta Lake. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
DOI: 10.18739/a2mk6589w
title: Collaborative Research: Year-round autonomous sampling of methane in Arctic lakes, Northwest Territories, Canada, 2011-2017

description: The investigators propose to measure methane concentrations in frozen lakes continuously throughout the Arctic winter using autonomous sampling devices, to more thoroughly address the variability in the methane flux from Arctic lakes to the atmosphere. Methane is a potent greenhouse gas, the release of which from Arctic sources is poised to increase with climate warming. This project will expand upon a successful pilot study that included the initial testing of autonomous continuous fluid sampler and sensor systems. The proposed expansion will involve additional capabilities and the deployment of a sampling unit in each of six small lakes along a north-south gradient in the Mackenzie River delta in the Canadian Arctic for a nine-month period, spanning the winter season. With these data the investigators aim to characterize the physical, chemical, and microbial conditions in the water column to elucidate hydrologic, microbial, and weathering processes during the winter season, when methane builds in lake water under the ice cover. The investigators hypothesize that sudden (week, days, or even hours) releases of methane, following spring flooding and ice cover breakup, produce a distinct atmospheric flux from Arctic lakes that would otherwise be missed, since most logistically reasonable sampling occurs in the summer months when methane concentrations in these lakes are low or below detection.
 The majority of methane flux to the Arctic atmosphere is estimated to come from soils and small lakes, although these estimates are based on few direct observations with large uncertainties. This proposed study, using in situ samplers and sensors, will allow an extensive microbial, gas and ion analytical program coupled with a network of physical and chemical sensor data to assess temporal conditions during winter months; to confirm fundamental processes and rates; to determine the interplay among microbial, geochemical and physical processes; and to develop a plan for a more inclusive study that takes advantage of low cost proxies for significant processes that best characterize temporal aspects of lake conditions. The project will enhance infrastructure for future research in the Arctic through the development of novel in situ sampling. The project will support several undergraduate and graduate students, providing valuable lab-based experience for students from non-research-intensive institutions. The investigators also will conduct two informal outreach activities to communicate the importance of Arctic climate change to primary school students while also teaching them about design and engineering. They also intend to work closely with Aurora College and Aurora Research Institute based in Inuvik, Canada, to engage First Nations youth.
DOI: 10.15156/bio/sh0201556.10fu
title: SH0201556.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201557.10fu
title: SH0201557.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201558.10fu
title: SH0201558.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201559.10fu
title: SH0201559.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201560.10fu
title: SH0201560.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201561.10fu
title: SH0201561.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.