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  • 2017-2021
  • Research data
  • Research software
  • CA
  • Transport Research

  • Authors: Bakker, Dorothee C. E.; Pfeil, Benjamin; Smith, Karl; Harasawa, Sumiko; +76 Authors

    This dataset includes Surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2013-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by Alex Kozyr of Carbon Dioxide Information Analysis Center (CDIAC), Karl Smith of NOAA Pacific Marine Environmental Laboratory (PMEL), Benjamin Pfeil of University of Bergen, Are Olsen of University of Bergen; Geophysical Institute (GFI), and Dorothee C. E. Bakker of University of East Anglia; School of Environmental Sciences as part of the SOCAT Database V3 dataset. CDIAC associated the following cruise ID(s) with this dataset: SOCA19681116

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    Authors: Natural Resources Canada | Ressources naturelles Canada;

    Cette collection fait maintenant partie du patrimoine, elle n'est plus maintenue. Elle pourrait ne pas respecter les normes actuelles du gouvernement. Les utilisateurs de l'Atlas du Canada à l'échelle nationale de 1/5 000 000 (publication du mai 2017) devraient envisager l'utilisation du nouveau produit CanVec. La série de Données de l'Atlas du Canada à l'échelle nationale de 1/5 000 000 comprend des jeux de données sur les limites, les côtes, les îles, les noms de lieux, les chemins de fer, les rivières, les routes, les traversiers et les étendues d'eau qui ont été compilés de manière à être utilisés dans des cartes à moyenne échelle (1/5 000 000 à 1/15 000 000) de l'atlas. Ces jeux de données ont été intégrés de sorte que leurs positions relatives soient correctes du point de vue cartographique. Toutes les données à l'extérieur du Canada comprises dans ces jeux de données s'y retrouvent strictement pour avoir le contexte global des données. This collection is a legacy product that is no longer maintained. It may not meet current government standards. Users of Atlas of Canada National Scale Data 1:5,000,000 (release of May 2017) should plan to make the transition towards the new CanVec product. The Atlas of Canada National Scale Data 1:5,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas medium scale (1:5,000,000 to 1:15,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

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    Lunaris
    Dataset . 2017
    Data sources: Lunaris
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Lunarisarrow_drop_down
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      Lunaris
      Dataset . 2017
      Data sources: Lunaris
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  • Authors: Bakker, Dorothee C. E.; Pfeil, Benjamin; Smith, Karl; Hankin, Steve; +69 Authors

    This dataset includes Surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2011-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by Karl Smith and Steve Hankin of US DOC; NOAA; OAR; Pacific Marine Environmental Laboratory, Benjamin Pfeil and Are Olsen of University of Bergen; Bjerknes Center for Climate Research; Geophysical Institute and Dorothee Bakker of University of East Anglia; School of Environmental Sciences as part of the SOCAT Database V2 data set. CDIAC associated the following cruise ID(s) with this data set: SOCA19681116

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    Authors: Lin, Yaping; Zhan, Aibin; Hernandez, Marco R; Paolucci, Esteban; +2 Authors

    1. Ballast water has been identified as a leading vector for introduction of non-indigenous species (NIS). Recently, the International Maritime Organization (IMO) implemented management standards – D-2 – where all large, commercial ships trading internationally are required to adopt an approved treatment system using technologies such as ultraviolet radiation or chlorination. However, current management regulations are based only on the total abundance of viable taxa transported (i.e., total propagule pressure), largely ignoring species richness (i.e., colonization pressure).2. To determine the efficacy of chlorine treatment in reducing invasion risks and changes in transported biological communities inside ballast tanks, we used DNA metabarcoding-based approaches to estimate colonization pressure (here, the number of species/Operational Taxonomic Units (OTUs) introduced) and relative propagule pressure (relative abundance of each species/OTU) of zooplankton communities in control and chlorine treated tanks during four transatlantic voyages. 3. Our study demonstrated that transport itself did not significantly reduce colonization pressure of zooplankton species, nor did chlorine treatment. Chlorine treatment altered community structure by reducing relative propagule pressure of some taxa such as Mollusca and Rotifera, while increasing relative propagule pressure of some Oligohymenophorea and Copepoda species.4. Synthesis and applications. Chlorine treatment may not reduce invasion risks as much as previously thought. Reduction in total propagule pressure does not mean reduction in abundance of all species equally. While some taxa might experience drastically reduced abundance, others might not change at all or increase due to hatching from dormant stages initiated by chlorine exposure. Therefore, management strategies should consider changes in total propagule pressure and colonization pressure when forecasting risk of new invasions. We therefore recommend adopting new approaches, such as DNA metabarcoding-based methods, to assess the whole biodiversity discharged from ballast water. As species responses to chlorine treatment are variable and affected by concentration, we also recommend a combination of different technologies to reduce introduction risks of aquatic organisms. Supplement to: Lin, Yaping; Zhan, Aibin; Hernandez, Marco R; Paolucci, Esteban; MacIsaac, Hugh J; Briski, Elizabeta (2020): Can chlorination of ballast water reduce biological invasions? Journal of Applied Ecology, 57(2), 331-343 The zip file includes:1. raw_data_clean.fasta: Raw sequence reads of zooplankton in ballast water samples2. raw_data.fasta: OTU representative sequences3. OTU_table.xlsx: OTU table

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    PANGAEA
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2019
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2019
      License: CC BY
      Data sources: Datacite
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  • Authors: Milovanoff, Alexandre; Posen, I. Daniel; MacLean, Heather L.;

    This repository contains the raw data of the inputs and results presented in the paper "Will technology save the climate? The challenge of light-duty vehicle fleet electrification" published in Nature Climate Change (2020) by Alexandre Milovanoff, I. Daniel Posen, and Heather L. MacLean (Department of Civil & Mineral Engineering, University of Toronto).

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    ZENODO
    Dataset . 2020
    Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      Data sources: ZENODO
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    Authors: Dickey, James W.E.; Cuthbert, Ross N.; Rea, Michael; Laverty, Ciaran; +10 Authors

    Table S1 The locations of the 20 pet shops surveyed across Northern Ireland :

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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
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    Authors: Statistics Canada;

    The SHS is conducted annually in the ten provinces. Starting with SHS 2015, the survey is conducted every two years in the three territorial capitals (Whitehorse, Yellowknife and Iqaluit). The SHS underwent a major redesign in 2010. The new methodology combines a questionnaire with recall periods based on the type of expenditure (last month, last 3 months, last 12 months or last payment) and a daily expenditure diary that a sub-sample of households is selected to complete for a two-week period following the interview. Also, data on income and income taxes now come mainly from the T1 (Individual Tax Return) administrative data files from the Canada Revenue Agency. Finally, collection is carried out on a continuous monthly basis from January to December from a sample of households distributed over twelve monthly collection cycles. Although the expenditure data collected since 2010 are similar to those of previous years, the changes to data collection, processing and estimation methods have created breaks in the data series. As a result, users are advised not to compare SHS data from 2010 onward with data prior to 2010, unless otherwise noted. Notes: The household income used for imputation is taken from the personal income tax data and equals the sum of the incomes of all household members aged 16 and over on December 31st of the calendar year preceding the survey.;

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    Lunaris
    Dataset . 2021
    Data sources: Lunaris
    Borealis
    Dataset . 2023
    Data sources: Datacite
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      Lunaris
      Dataset . 2021
      Data sources: Lunaris
      Borealis
      Dataset . 2023
      Data sources: Datacite
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    Authors: Cooney, Elizabeth; Okamoto, Noriko; Cho, Anna; Hehenberger, Elisabeth; +5 Authors

    <b>Abstract</b><br/><p>Dinoflagellates possess many unique cellular characteristics with unresolved evolutionary histories including nuclei with greatly expanded genomes and chromatin packaged using histone-like proteins and dinoflagellate-viral nucleoproteins instead of histones, highly reduced mitochondrial genomes with extensive RNA editing, a mix of photosynthetic and cryptic secondary plastids, and tertiary plastids. Resolving the evolutionary origin of these traits requires understanding their ancestral states and early intermediates. Several deep-branching dinoflagellate lineages are good candidates for such reconstruction, however they tend to be delicate and environmentally sparse, so such analyses are not always simple. Here, we employ transcriptome sequencing from manually-isolated and microscopically documented cells to resolve the placement of two cells of one such genus, <i>Abedinium</i>,<i> </i>collected by ROV in deep waters off the coast of Monterey Bay. One cell corresponds to the only described species, <i>A. dasypus</i>, while the second cell is distinct and formally described as<i> Abedinium folium, </i>sp. nov. <i>Abedinium</i> has classically been assigned to the deep-branching dinoflagellates subgroup Noctilucea, which is weakly supported by phylogenetic analyses of the single characterized gene from any member of the genus, small subunit ribosomal RNA (SSU rRNA). However, a phylogenetic analysis based on 221 proteins from the transcriptome places <i>Abedinium </i>in a distinct lineage, separate from and basal to the Noctilucea and the rest of the core dinoflagellates. The transcriptome also contains evidence of a cryptic plastid functioning in the biosynthesis of isoprenoids, iron-sulfur clusters, and heme, a mitochondrial genome with all three expected protein-coding genes (<i>cob</i>, <i>cox1</i>, and cox3), and the presence of some but not all dinoflagellate-specific chromatin packaging proteins.</p>

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    Borealis
    Dataset . 2021
    Data sources: Datacite
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      Borealis
      Dataset . 2021
      Data sources: Datacite
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    Authors: Callbeck, Cameron; Lavik, Gaute; Ferdelman, Timothy G; Kuypers, Marcel MM;

    Supplement to: Callbeck, Cameron; Lavik, Gaute; Ferdelman, Timothy G; Fuchs, Bernhard M; Gruber-Vodicka, Harald R; Hach, Philipp F; Littmann, Sten; Schoffelen, Niels J; Kalvelage, Tim; Thomsen, Soeren; Schunck, Harald; Löscher, Carolin R; Schmitz, Ruth A; Kuypers, Marcel MM (2018): Oxygen minimum zone cryptic sulfur cycling sustained by offshore transport of key sulfur oxidizing bacteria. The data set includes, sulfide and sulfur concentrations, SUP05 cell densities, as well as denitrification and carbon fixation rates (based on 15N- and 13C-labelled in situ incubation experiments). The transect extends from the sulfidic upper shelf into the sulfide-free offshore oxygen minimum zone.

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    PANGAEA
    Dataset . 2017
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2017
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2017
      Data sources: B2FIND
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      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2017
      License: CC BY
      Data sources: Datacite
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    Authors: Stratmann, Tanja; van Oevelen, Dick; Martínez Arbizu, Pedro; Wei, Chih-Lin; +11 Authors

    In April and May 2019, we compiled the “BenBio” part of the “BenBioDen database” following the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) Statement for systematic reviews and meta-analyses. In the first PRISMA step, the “Identification” step, we identified 1,373 articles in the Web of Science using the key words “marine meiofauna biomass”, “marine macrofauna biomass”, “marine megafauna biomass”, “marine meiobenth* biomass”, “marine macrobenth* biomass”, “marine megabenth* biomass”, “nematode biomass”, and “benthic ‘standing stock’”. We located an additional 201 publications based on expert knowledge. A search of the PANGAEA® Data Publisher (https://www.pangaea.de/) identified 1,488 datasets representing 148 publications using the key words “meiofauna biomass”, “macrofauna biomass” and “megafauna biomass”. Further 30 datasets were found in the EOL data archive (http://data.eol.ucar.edu/), through citations in review papers, and based on expert knowledge. After removing duplicates, we screened the titles and abstracts of 1,445 studies in PRISMA step 2 (“Screening”; Fig. 1A). This step excluded 951 studies because they did not report biomass values. In the Eligibility step, we assessed full texts of 494 studies for eligibility and excluded 110 studies because they did not report biomass, the publications or data were not accessible, or they did not report benthic biomass in appropriate units (g WW m-2, g DW m-2, g AFDW m-2, g or mol C m-2). Further reasons for excluding full texts included combining benthic biomass for several size classes, reporting benthic biomass for particular taxa rather than the whole size class, presenting biomass for faunal assemblages and/ or a group of sampling stations rather than for individual stations, not presenting primary research or lacking geographical details about sampling stations. We also excluded studies that estimated benthic biomass using modelling approaches, that conducted manipulative experiments, or did not report benthic biomass as single values, means or median values, but instead as ranges. The final “BenBio” part included 384 studies from which we extracted 11,792 georeferenced benthic biomass entries. The Benthos Density, i.e. “BenDen”, part of the “BenBioDen” database was established in July and August 2019 following the PRISMA Statement for systematic reviews and meta-analyses. In the Identification step, we found 2,515 articles in the Web of Science using the key words “meiofauna abundance”, “meiobenthos abundance”, “macrofauna abundance”, “macrobenthos abundance”, “megafauna abundance”, “megabenthos abundance”, “meiofauna Arctic Ocean”, “meiofauna Atlantic Ocean”, “meiofauna Black Sea”, “meiofauna Gulf of Mexico”, “meiofauna Indian Ocean”, “meiofauna Mediterranean Sea”, “meiofauna Pacific Ocean”, “meiofauna Southern Ocean”, “meiofauna Red Sea”, “meiofauna Pacific Ocean”, “megafauna Southern Ocean”, “megafauna Red Sea”, “megafauna Pacific Ocean”, “megafauna Mediterranean Sea”, “megafauna Indian Ocean”, “megafauna Black Sea”, “megafauna Gulf of Mexico”, “megafauna Atlantic Ocean”, “megafauna Arctic Ocean”, “macrofauna Arctic Ocean”, “macrofauna Atlantic Ocean”, “macrofauna Black Sea”, “macrofauna Southern Ocean”, “macrofauna Red Sea”, “macrofauna Pacific Ocean”, “macrofauna Gulf of Mexico”, “macrofauna Indian Ocean”, and “macrofauna Mediterranean Sea”. Expert knowledge identified a further 232 publications. Consulting PANGAEA® Data Publisher (https://www.pangaea.de/) identified 1,549 datasets from 172 publications using the key words “meiofauna abundance”, “macrofauna abundance” and “megafauna abundance”. Expert knowledge or unpublished datasets added a further 21 datasets. After removal of duplicates, the “Screening” step filtered 2,086 titles and abstracts and excluded 1,133 studies because they did not report benthic densities. The third PRISMA step assessed 953 studies and excluded 353 studies because they did not report metazoan meiobenthic, macrobenthic, or invertebrate megabenthic densities or they combined multiple size classes or sampling stations. We excluded other studies in the database that reported experimental studies, were inaccessible, or reported densities in a unit other than ind. m-2 or a unit that could be converted to ind. m-2, or reported densities for specific taxa instead of the entire size class. Studies were also excluded when they reported meta-studies or reviews rather than primary research, presented results of models, lacked sufficient geographical detail about sampling locations, or reported fauna associated with whale falls. The final “BenDen” part consisted of 600 studies from which we extracted 51,559 georeferenced benthic density records. For 12% (BioBen part) and 4% (BioDen part) of all data records, no exact sampling location in geographical coordinates (latitude, longitude) was indicated. For these cases, we approximated the coordinates of the sampling locations using Google Maps based on information about sampling area or based on maps presented in the original publications. We labelled these data records as ‘approximated location’. For studies that presented biomasses in several units, such as WM and DM, we report the data only once (preferred units: WM > DM > AFDM > C). The authors of this study intended to report all data records in the ‘raw’ units in which benthic fauna was measured initially. Whenever unknown conversion factors precluded calculating biomass back to ‘raw’ units, we noted this issue in the database using the label ‘converted data’ and listed references for the individual biomass conversion factors in the database. The authors of the various studies compiled in this database sometimes used different lower and upper limits (in mm) for mesh sizes of nets and/ or sieves to define the size class. Whenever an original study reported a lower and/ or upper limit mesh size, we included this information in the database as ‘sieve mesh size (mm) lower limit’ and ‘sieve mesh size (mm) upper limit’. Studies lacking this information were scored as NA. For those studies that reported data as mean or median ± error terms, we incorporated only mean or median values into the database. In all cases that did not report benthic biomasses and/ or densities in the text or in tables, but presented them in figures, we extracted biomass and/ or density values from these figures using ImageJ. Benthic fauna refers to all fauna that live in or on the seafloor, which researchers typically divide into size classes meiobenthos (32/ 64 µm – 0.5/ 1 mm), macrobenthos (250 µm – 1 cm), and megabenthos (> 1 cm). Benthic fauna play important roles in bioturbation activity, mineralization of organic matter, and in marine food webs. Evaluating their role in these ecosystem functions requires knowledge of their global distribution and biomass. We therefore established the BenBioDen database, the largest open-access database for marine benthic biomass and density data compiled so far. In total, it includes 11,792 georeferenced benthic biomass and 51,559 benthic density records from 384 and 600 studies, respectively. We selected all references following the procedure for systematic reviews and meta-analyses, and report biomass records as grams of wet mass, dry mass, or ash-free dry mass, or carbon per m2 and as abundance records as individuals per m2. This database provides a point of reference for future studies on the distribution and biomass of benthic fauna.

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    ZENODO; DRYAD
    Dataset . 2020 . 2021
    License: CC 0
    Data sources: ZENODO; Datacite
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      ZENODO; DRYAD
      Dataset . 2020 . 2021
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61 Research products
  • Authors: Bakker, Dorothee C. E.; Pfeil, Benjamin; Smith, Karl; Harasawa, Sumiko; +76 Authors

    This dataset includes Surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2013-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by Alex Kozyr of Carbon Dioxide Information Analysis Center (CDIAC), Karl Smith of NOAA Pacific Marine Environmental Laboratory (PMEL), Benjamin Pfeil of University of Bergen, Are Olsen of University of Bergen; Geophysical Institute (GFI), and Dorothee C. E. Bakker of University of East Anglia; School of Environmental Sciences as part of the SOCAT Database V3 dataset. CDIAC associated the following cruise ID(s) with this dataset: SOCA19681116

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    Authors: Natural Resources Canada | Ressources naturelles Canada;

    Cette collection fait maintenant partie du patrimoine, elle n'est plus maintenue. Elle pourrait ne pas respecter les normes actuelles du gouvernement. Les utilisateurs de l'Atlas du Canada à l'échelle nationale de 1/5 000 000 (publication du mai 2017) devraient envisager l'utilisation du nouveau produit CanVec. La série de Données de l'Atlas du Canada à l'échelle nationale de 1/5 000 000 comprend des jeux de données sur les limites, les côtes, les îles, les noms de lieux, les chemins de fer, les rivières, les routes, les traversiers et les étendues d'eau qui ont été compilés de manière à être utilisés dans des cartes à moyenne échelle (1/5 000 000 à 1/15 000 000) de l'atlas. Ces jeux de données ont été intégrés de sorte que leurs positions relatives soient correctes du point de vue cartographique. Toutes les données à l'extérieur du Canada comprises dans ces jeux de données s'y retrouvent strictement pour avoir le contexte global des données. This collection is a legacy product that is no longer maintained. It may not meet current government standards. Users of Atlas of Canada National Scale Data 1:5,000,000 (release of May 2017) should plan to make the transition towards the new CanVec product. The Atlas of Canada National Scale Data 1:5,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas medium scale (1:5,000,000 to 1:15,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

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    Lunaris
    Dataset . 2017
    Data sources: Lunaris
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      Lunaris
      Dataset . 2017
      Data sources: Lunaris
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  • Authors: Bakker, Dorothee C. E.; Pfeil, Benjamin; Smith, Karl; Hankin, Steve; +69 Authors

    This dataset includes Surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2011-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by Karl Smith and Steve Hankin of US DOC; NOAA; OAR; Pacific Marine Environmental Laboratory, Benjamin Pfeil and Are Olsen of University of Bergen; Bjerknes Center for Climate Research; Geophysical Institute and Dorothee Bakker of University of East Anglia; School of Environmental Sciences as part of the SOCAT Database V2 data set. CDIAC associated the following cruise ID(s) with this data set: SOCA19681116

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    Authors: Lin, Yaping; Zhan, Aibin; Hernandez, Marco R; Paolucci, Esteban; +2 Authors

    1. Ballast water has been identified as a leading vector for introduction of non-indigenous species (NIS). Recently, the International Maritime Organization (IMO) implemented management standards – D-2 – where all large, commercial ships trading internationally are required to adopt an approved treatment system using technologies such as ultraviolet radiation or chlorination. However, current management regulations are based only on the total abundance of viable taxa transported (i.e., total propagule pressure), largely ignoring species richness (i.e., colonization pressure).2. To determine the efficacy of chlorine treatment in reducing invasion risks and changes in transported biological communities inside ballast tanks, we used DNA metabarcoding-based approaches to estimate colonization pressure (here, the number of species/Operational Taxonomic Units (OTUs) introduced) and relative propagule pressure (relative abundance of each species/OTU) of zooplankton communities in control and chlorine treated tanks during four transatlantic voyages. 3. Our study demonstrated that transport itself did not significantly reduce colonization pressure of zooplankton species, nor did chlorine treatment. Chlorine treatment altered community structure by reducing relative propagule pressure of some taxa such as Mollusca and Rotifera, while increasing relative propagule pressure of some Oligohymenophorea and Copepoda species.4. Synthesis and applications. Chlorine treatment may not reduce invasion risks as much as previously thought. Reduction in total propagule pressure does not mean reduction in abundance of all species equally. While some taxa might experience drastically reduced abundance, others might not change at all or increase due to hatching from dormant stages initiated by chlorine exposure. Therefore, management strategies should consider changes in total propagule pressure and colonization pressure when forecasting risk of new invasions. We therefore recommend adopting new approaches, such as DNA metabarcoding-based methods, to assess the whole biodiversity discharged from ballast water. As species responses to chlorine treatment are variable and affected by concentration, we also recommend a combination of different technologies to reduce introduction risks of aquatic organisms. Supplement to: Lin, Yaping; Zhan, Aibin; Hernandez, Marco R; Paolucci, Esteban; MacIsaac, Hugh J; Briski, Elizabeta (2020): Can chlorination of ballast water reduce biological invasions? Journal of Applied Ecology, 57(2), 331-343 The zip file includes:1. raw_data_clean.fasta: Raw sequence reads of zooplankton in ballast water samples2. raw_data.fasta: OTU representative sequences3. OTU_table.xlsx: OTU table

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    PANGAEA
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA - Data Publisher for Earth and Environmental Science
    Other dataset type . 2019
    License: CC BY
    Data sources: Datacite
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      PANGAEA
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2019
      License: CC BY
      Data sources: Datacite
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  • Authors: Milovanoff, Alexandre; Posen, I. Daniel; MacLean, Heather L.;

    This repository contains the raw data of the inputs and results presented in the paper "Will technology save the climate? The challenge of light-duty vehicle fleet electrification" published in Nature Climate Change (2020) by Alexandre Milovanoff, I. Daniel Posen, and Heather L. MacLean (Department of Civil & Mineral Engineering, University of Toronto).

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    ZENODO
    Dataset . 2020
    Data sources: ZENODO
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