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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/
    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: Stoyanovich, Sawyer; Zeyu Yang; Hanson, Mark; Hollebone, Bruce P; +7 Authors

    The main petroleum product transported through pipelines in Canada is diluted bitumen (dilbit), a semi-liquid form of heavy crude oil mixed with natural gas condensates to facilitate transport. The weathering, fate, behaviour, and environmental effects of dilbit are crucial to consider when responding to a spill, however few environmental studies on dilbit have been completed. Here we report on 11-day long experimental spills of dilbit (Cold Lake Winter Blend) in outdoor micro-cosms meant to simulate a low-energy aquatic system containing natural lake water and sedi-ments treated with a low (1:8,000 oil:water) and high (1:800 oil:water) volume of dilbit. In the first 24 hours of the experiment, volatile hydrocarbons quickly evaporated from the dilbit, result-ing in increased dilbit density and viscosity. These changes in dilbit’s physical and chemical properties ultimately led to its submergence after 8 days. We also detected rapid accumulation of polycyclic aromatic compounds in the water column of the treated-microcosms following the spills. Our study provides new information on the environmental fate and behaviour of dilbit in a freshwater environment that will be critical to environmental risk assessments of proposed pipe-line projects. In particular, our study demonstrates the propensity for dilbit to sink under ambient environmental conditions in fresh waters typical of many boreal lakes.

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    figshare
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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    figshare
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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      figshare
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
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      figshare
      Dataset . 2019
      License: CC 0
      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
      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/
      PANGAEA - Data Publisher for Earth and Environmental Science
      Other dataset type . 2017
      License: CC BY
      Data sources: Datacite
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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/
    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
  • Presence of Common Scales: country: name of the country or the territory; geodi: two-letters country code; iso: three-letters country code; d: date of the observation; cases: number of cases reported on the given day by the European Centre for Disease Prevention and Control; deaths: number of deaths reported on the given day by the European Centre for Disease Prevention and Control; school: binary variable equal to1 if schools were closed and 0 otherwise; school_local: binary flag to distinguish localized school closures from other cases. 1 denotes that school closures were implemented at the local level and 0 denotes that school closures were not implemented at the local level (either at the national level or no school closures). The data on the scale of school closures is imported from the UNESCO. The interaction of school and school_local allows researchers to create three levels of measures: no school closures (school=0 and school_local=0), localized school closures (school=1 and school_local==1) or national school closures (school=1 and school_local=0); domestic: binary variable equal to 1 if there was a domestic lockdown and 0 otherwise; domestic_local: binary variable to distinguish localized domestic lockdowns from other cases. 1 denotes that domestic lockdowns were implemented at the local level and 0 means that domestic lockdowns were not implemented at the local-level (either at the national level or not implemented). The nature of the domestic lockdown is based on our reading of the measures reported by the ACAPS. The interaction of domestic and domestic_local allows researchers to create three levels of measures: no domestic lockdown (domestic=0 and domestic_local=0), localized domestic lockdowns (domestic=1 and domestic_local=1) or national domestic lockdowns (domestic=1 and domestic_local=0); travel: binary variable equal to1 if travel restrictions were implemented and 0 otherwise; travel_partial: binary flag to differentiate partial travel restrictions from other cases. 1 denotes that travel restrictions were partial and 0 denotes that travel restrictions were not partial (either strict or not implemented). The nature of the travel restrictions is based on our reading of the measures reported by the ACAPS. The interaction of travel and travel_partial allows researchers to create three levels of measures: no travel restrictions (travel=0 and travel_partial=0), partial travel restrictions (travel=1 and travel_partial=1) or strict travel restrictions (travel=1 and travel_partial=0); travel_dom: binary variable equal to1 if travel restrictions within the country (e.g. inter-region travels) were implemented and 0 otherwise; travel_dom_partial: binary flag to differentiate partial domestic travel restrictions from other cases. 1 denotes that travel restrictions were partial and 0 denotes that travel restrictions were not partial (either strict or not implemented). The nature of the travel restrictions is based on our reading of the measures reported by the ACAPS. The interaction of travel and travel_partial allows researchers to create three levels of measures: no domestic travel restrictions (travel_dom=0 and travel_dom_partial=0), partial domestic travel restrictions (travel_dom=1 and travel_dom_partial=1) or strict domestic travel restrictions (travel_dom=1 and travel_dom_partial=0); curf: binary variable equal to1 if a curfew was implemented and 0 otherwise; curf_partial: binary flag to differentiate partial curfews from other cases. 1 denotes that the curfew was partial and 0 denotes that the curfew was not partial (either strict or not implemented). The nature of the curfew is based on our reading of the measures reported by the ACAPS. The interaction of curf and curf_partial allows researchers to create three levels of measures: no curfew (curf=0 and curf_partial=0), partial curfew (curf=1 and curf_partial=1) or strict curfew (curf=1 and curf_partial=0); mass: binary variable equal to1 if bans on mass gatherings were implemented and 0 otherwise; mass_partial: binary flag to distinguish localized bans on mass gatherings from other cases. 1 denotes that bans on mass gatherings were partial and 0 denotes that bans on mass gatherings were not partial (either strict or not implemented). The nature of the bans on mass gatherings is based on our reading of the measures reported by the ACAPS. The interaction of mass and mass_partial allows researchers to create three levels of measures: no bans on mass gatherings (mass=0 and mass_partial=0), localized or partial bans (mass=1 and mass_partial=1) or national or strict bans (mass=1 and mass_partial=0); elect: binary variable equal to1 if some elections were postponed and 0 otherwise; elect_partial: binary flag to differentiate countries which postponed only some of the elections from the others. 1 denotes that countries both maintained and postponed elections and 0 denotes that elections were either postponed, maintained or were not scheduled. IDEA lists all maintained and postponed elections since the beginning of 2020. The interaction of elect and elect_partial allows researchers to differentiate three settings: all elections were maintained despite COVID-19 (elect=0 and elect_partial=0), some elections were maintained and others were postponed (elect=1 and elect_partial=1) or all elections were postponed (elect=1 and elect_partial=0); sport: binary variable equal to1 if bans on sporting and large events were implemented and 0 otherwise; sport_partial: binary flag to distinguish partial bans and cancellations of sporting and large events. 1 denotes that bans on sporting and large events were localized, strict or with no spectators, 0 that bans on sporting and large events are not localized or partial (either national or no measures implemented). The nature of the bans on sporting and large events is based on our reading of the measures reported by the ACAPS. The interaction of sport and sport_partial allows researchers to create three levels of measures: no bans (sport=0 and sport_partial=0), partial bans (sport=1 and sport_partial=1) or national bans on mass gatherings (sport=1 and sport_partial=0); rest: binary variable equal to1 if restaurants were closed and 0 otherwise; rest_local: binary flag to distinguish localized and/or partial restaurant and bar closures from other cases. The variable is coded 1 in the three following situations: localized closures, limitations on the number of customers in bars and restaurants, and closures of either bars or restaurants. 0 indicates national closures or no closures at all. The coding is based on our reading of the measures reported by the ACAPS. The interaction of rest and rest_local allows researchers to create three levels of measures: no closures (rest=0 and rest_local=0), localized closures (rest=1 and rest_local=1) or national closures (rest=1 and rest_local=0); testing: binary variable equal to1 if there was a public testing policy and 0 otherwise; testing_narrow: binary flag to distinguish narrow testing policies from large testing policies. 1 denotes that testing policies were targeted to some individuals, 0 that testing policies were not targeted (either large or not implemented). The nature of the testing policy is based on the information reported in the measures ���mass population testing��� and ���testing policy��� in the ACAPS. When the measure was targeted, testing_narrow was coded 1. On the contrary, when the measure was not targeted, testing_narrow was coded 0. The interaction of testing and testing_narrow allows researchers to create three levels of measures: no testing policy (testing=0 and testing_narrow =0), narrow testing policy (testing=1 and testing_narrow =1) or large testing policy (testing=1 and testing_narrow =0); surveillance: binary variable equal to1 if mobile app or bracelet surveillance was implemented and 0 otherwise; surveillance_partial: binary variable equal to1 if the enhanced surveillance is optional or reserved for a category of person (e.g. certain professions or foreigners) and 0 otherwise, based on information in the ACAPS. When the measure was partial, surveillance_partial was coded 1. On the contrary, when the measure was strict (anybody suspected of having COVID-19), surveillance_partial was coded 0. The interaction of surveillance and surveillance_partial allows researchers to create three levels of measures: no surveillance (surveillance=0 and surveillance_partial =0), partial surveillance (surveillance=1 and surveillance_partial=1) or strict surveillance (surveillance=1 and surveillance_partial =0); masks : binary variable equal to1 if mandates to wear masks in public spaces were implemented and 0 otherwise; masks_partial: binary variable equal to1 if the obligation to wear masks is regional, based on information in the ACAPS. When the measure was regional, masks_partial was coded 1. On the contrary, when the measure was national, masks_partial was coded 0. The interaction of masks and masks_partial allows researchers to create three levels of measures: no obligations to wear masks (masks=0 and masks_partial =0), regional obligations to wear masks (masks=1 and masks_partial=1) or national obligations to wear masks (masks=1 and masks_partial =0); state: binary variable equal to1 if the state of emergency is declared and 0 otherwise; state_partial: binary variable equal to1 if the state of emergency is declared on a local basis and 0 otherwise, based on information in the ACAPS. When the measure was local, state_partial was coded 1. On the contrary, when the measure was not localized, state_partial was coded 0. The interaction of state and state_partial allows researchers to create three levels of measures: no state of emergency (state=0 and state_partial =0), partial state of emergency (state=1 and state_partial=1) or national state of emergency (state=1 and state_partial =0); cash: binary variable equal to1 if cash transfers are implemented and 0 otherwise; wage: binary variable equal to1 if wage support is implemented and 0 otherwise; credit: binary variable equal to1 if credit schemes are implemented and 0 otherwise; taxc: binary variable equal to1 if tax credits are implemented and 0 otherwise; taxd: binary variable equal to1 if tax delays are implemented and 0 otherwise; export: binary variable equal to1 if supports to importers or exporters are implemented and 0 otherwise; rate: binary variable equal to1 if the Central Bank lowered the interest rates and 0 otherwise; Rigidity_Public_Health: average of the ten coded public health measures. Public health measures are valued 0.5 if they are localized or partial and 1 if they are national or strict. 0 indicates no measures; Economic_Measures: average of the coded economic measures. The Response2covid19 dataset tracks governments��� responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures ��� 13 public health measures and 7 economic measures ��� taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset (���Governments��� Responses to COVID-19 (Response2covid19)���) and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. Public health measures include international and domestic travel restrictions, bans on mass gatherings, school closing and domestic lockdown among others. Economic measures include wage support, cash transfers, interest rates cuts, tax cuts and delays, and support to exporters or importers. . Smallest Geographic Unit: Country-level other; Cite data as Porcher, Simon "A novel dataset of governments��� responses to COVID-19 all around the world", chaire EPPP discussions paper 2020-03. Link: https://www.chaire-eppp.org/wp-content/uploads/2020/05/WP202003.pdf All countries with available information (228 countries). Response Rates: 62,700 observations; 228 countries.

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    Authors: Faria, Larissa; Cuthbert, Ross N.; Dickey, James W. E.; Jeschke, Jonathan M.; +3 Authors

    List of publications included in the systematic review

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    ZENODO
    Dataset . 2023
    License: CC 0
    Data sources: ZENODO
    0
    citations0
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
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    Authors: Thomas, Helmuth; Schlundt, Michael;

    Underway temperature and salinity data was collected along the cruise track with two autonomous measurement systems. Usually, the systems are changed after 6 hours. While temperature is taken at the water inlet in about 6.5 m depth, salinity is estimated within the interior measurement container from conductivity and interior temperature. No temperature and salinity calibration were performed. For details to all processing steps see Data Processing Report.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
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    Authors: Waelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; +59 Authors

    Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.

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    PANGAEA
    Dataset . 2019
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      Data sources: B2FIND
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    Authors: Espinasse, Boris; St John Glew, Katie;

    We produced carbon and nitrogen isoscapes across the entire Southern Ocean (>40°S) using surface particulate organic matter isotope data, collected over the past 50 years. We used Integrated Nested Laplace Approximation -based approaches to predict mean annual isoscapes and four seasonal isoscapes using a suite of environmental data as predictor variables.

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    PANGAEA
    Dataset . 2021
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      Data sources: B2FIND
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    Authors: Dickey, James W.E.; Cuthbert, Ross N.; Rea, Michael; Laverty, Ciaran; +10 Authors

    Table S2. Summary of the GB online survey outlining which of the four species of turtle was being sold :

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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
    0
    citations0
    popularityAverage
    influenceAverage
    impulseAverage
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
30 Research products
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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: Stoyanovich, Sawyer; Zeyu Yang; Hanson, Mark; Hollebone, Bruce P; +7 Authors

    The main petroleum product transported through pipelines in Canada is diluted bitumen (dilbit), a semi-liquid form of heavy crude oil mixed with natural gas condensates to facilitate transport. The weathering, fate, behaviour, and environmental effects of dilbit are crucial to consider when responding to a spill, however few environmental studies on dilbit have been completed. Here we report on 11-day long experimental spills of dilbit (Cold Lake Winter Blend) in outdoor micro-cosms meant to simulate a low-energy aquatic system containing natural lake water and sedi-ments treated with a low (1:8,000 oil:water) and high (1:800 oil:water) volume of dilbit. In the first 24 hours of the experiment, volatile hydrocarbons quickly evaporated from the dilbit, result-ing in increased dilbit density and viscosity. These changes in dilbit’s physical and chemical properties ultimately led to its submergence after 8 days. We also detected rapid accumulation of polycyclic aromatic compounds in the water column of the treated-microcosms following the spills. Our study provides new information on the environmental fate and behaviour of dilbit in a freshwater environment that will be critical to environmental risk assessments of proposed pipe-line projects. In particular, our study demonstrates the propensity for dilbit to sink under ambient environmental conditions in fresh waters typical of many boreal lakes.

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    figshare
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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    figshare
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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      figshare
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
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      figshare
      Dataset . 2019
      License: CC 0
      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
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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
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      ZENODO
      Dataset . 2018
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  • Presence of Common Scales: country: name of the country or the territory; geodi: two-letters country code; iso: three-letters country code; d: date of the observation; cases: number of cases reported on the given day by the European Centre for Disease Prevention and Control; deaths: number of deaths reported on the given day by the European Centre for Disease Prevention and Control; school: binary variable equal to1 if schools were closed and 0 otherwise; school_local: binary flag to distinguish localized school closures from other cases. 1 denotes that school closures were implemented at the local level and 0 denotes that school closures were not implemented at the local level (either at the national level or no school closures). The data on the scale of school closures is imported from the UNESCO. The interaction of school and school_local allows researchers to create three levels of measures: no school closures (school=0 and school_local=0), localized school closures (school=1 and school_local==1) or national school closures (school=1 and school_local=0); domestic: binary variable equal to 1 if there was a domestic lockdown and 0 otherwise; domestic_local: binary variable to distinguish localized domestic lockdowns from other cases. 1 denotes that domestic lockdowns were implemented at the local level and 0 means that domestic lockdowns were not implemented at the local-level (either at the national level or not implemented). The nature of the domestic lockdown is based on our reading of the measures reported by the ACAPS. The interaction of domestic and domestic_local allows researchers to create three levels of measures: no domestic lockdown (domestic=0 and domestic_local=0), localized domestic lockdowns (domestic=1 and domestic_local=1) or national domestic lockdowns (domestic=1 and domestic_local=0); travel: binary variable equal to1 if travel restrictions were implemented and 0 otherwise; travel_partial: binary flag to differentiate partial travel restrictions from other cases. 1 denotes that travel restrictions were partial and 0 denotes that travel restrictions were not partial (either strict or not implemented). The nature of the travel restrictions is based on our reading of the measures reported by the ACAPS. The interaction of travel and travel_partial allows researchers to create three levels of measures: no travel restrictions (travel=0 and travel_partial=0), partial travel restrictions (travel=1 and travel_partial=1) or strict travel restrictions (travel=1 and travel_partial=0); travel_dom: binary variable equal to1 if travel restrictions within the country (e.g. inter-region travels) were implemented and 0 otherwise; travel_dom_partial: binary flag to differentiate partial domestic travel restrictions from other cases. 1 denotes that travel restrictions were partial and 0 denotes that travel restrictions were not partial (either strict or not implemented). The nature of the travel restrictions is based on our reading of the measures reported by the ACAPS. The interaction of travel and travel_partial allows researchers to create three levels of measures: no domestic travel restrictions (travel_dom=0 and travel_dom_partial=0), partial domestic travel restrictions (travel_dom=1 and travel_dom_partial=1) or strict domestic travel restrictions (travel_dom=1 and travel_dom_partial=0); curf: binary variable equal to1 if a curfew was implemented and 0 otherwise; curf_partial: binary flag to differentiate partial curfews from other cases. 1 denotes that the curfew was partial and 0 denotes that the curfew was not partial (either strict or not implemented). The nature of the curfew is based on our reading of the measures reported by the ACAPS. The interaction of curf and curf_partial allows researchers to create three levels of measures: no curfew (curf=0 and curf_partial=0), partial curfew (curf=1 and curf_partial=1) or strict curfew (curf=1 and curf_partial=0); mass: binary variable equal to1 if bans on mass gatherings were implemented and 0 otherwise; mass_partial: binary flag to distinguish localized bans on mass gatherings from other cases. 1 denotes that bans on mass gatherings were partial and 0 denotes that bans on mass gatherings were not partial (either strict or not implemented). The nature of the bans on mass gatherings is based on our reading of the measures reported by the ACAPS. The interaction of mass and mass_partial allows researchers to create three levels of measures: no bans on mass gatherings (mass=0 and mass_partial=0), localized or partial bans (mass=1 and mass_partial=1) or national or strict bans (mass=1 and mass_partial=0); elect: binary variable equal to1 if some elections were postponed and 0 otherwise; elect_partial: binary flag to differentiate countries which postponed only some of the elections from the others. 1 denotes that countries both maintained and postponed elections and 0 denotes that elections were either postponed, maintained or were not scheduled. IDEA lists all maintained and postponed elections since the beginning of 2020. The interaction of elect and elect_partial allows researchers to differentiate three settings: all elections were maintained despite COVID-19 (elect=0 and elect_partial=0), some elections were maintained and others were postponed (elect=1 and elect_partial=1) or all elections were postponed (elect=1 and elect_partial=0); sport: binary variable equal to1 if bans on sporting and large events were implemented and 0 otherwise; sport_partial: binary flag to distinguish partial bans and cancellations of sporting and large events. 1 denotes that bans on sporting and large events were localized, strict or with no spectators, 0 that bans on sporting and large events are not localized or partial (either national or no measures implemented). The nature of the bans on sporting and large events is based on our reading of the measures reported by the ACAPS. The interaction of sport and sport_partial allows researchers to create three levels of measures: no bans (sport=0 and sport_partial=0), partial bans (sport=1 and sport_partial=1) or national bans on mass gatherings (sport=1 and sport_partial=0); rest: binary variable equal to1 if restaurants were closed and 0 otherwise; rest_local: binary flag to distinguish localized and/or partial restaurant and bar closures from other cases. The variable is coded 1 in the three following situations: localized closures, limitations on the number of customers in bars and restaurants, and closures of either bars or restaurants. 0 indicates national closures or no closures at all. The coding is based on our reading of the measures reported by the ACAPS. The interaction of rest and rest_local allows researchers to create three levels of measures: no closures (rest=0 and rest_local=0), localized closures (rest=1 and rest_local=1) or national closures (rest=1 and rest_local=0); testing: binary variable equal to1 if there was a public testing policy and 0 otherwise; testing_narrow: binary flag to distinguish narrow testing policies from large testing policies. 1 denotes that testing policies were targeted to some individuals, 0 that testing policies were not targeted (either large or not implemented). The nature of the testing policy is based on the information reported in the measures ���mass population testing��� and ���testing policy��� in the ACAPS. When the measure was targeted, testing_narrow was coded 1. On the contrary, when the measure was not targeted, testing_narrow was coded 0. The interaction of testing and testing_narrow allows researchers to create three levels of measures: no testing policy (testing=0 and testing_narrow =0), narrow testing policy (testing=1 and testing_narrow =1) or large testing policy (testing=1 and testing_narrow =0); surveillance: binary variable equal to1 if mobile app or bracelet surveillance was implemented and 0 otherwise; surveillance_partial: binary variable equal to1 if the enhanced surveillance is optional or reserved for a category of person (e.g. certain professions or foreigners) and 0 otherwise, based on information in the ACAPS. When the measure was partial, surveillance_partial was coded 1. On the contrary, when the measure was strict (anybody suspected of having COVID-19), surveillance_partial was coded 0. The interaction of surveillance and surveillance_partial allows researchers to create three levels of measures: no surveillance (surveillance=0 and surveillance_partial =0), partial surveillance (surveillance=1 and surveillance_partial=1) or strict surveillance (surveillance=1 and surveillance_partial =0); masks : binary variable equal to1 if mandates to wear masks in public spaces were implemented and 0 otherwise; masks_partial: binary variable equal to1 if the obligation to wear masks is regional, based on information in the ACAPS. When the measure was regional, masks_partial was coded 1. On the contrary, when the measure was national, masks_partial was coded 0. The interaction of masks and masks_partial allows researchers to create three levels of measures: no obligations to wear masks (masks=0 and masks_partial =0), regional obligations to wear masks (masks=1 and masks_partial=1) or national obligations to wear masks (masks=1 and masks_partial =0); state: binary variable equal to1 if the state of emergency is declared and 0 otherwise; state_partial: binary variable equal to1 if the state of emergency is declared on a local basis and 0 otherwise, based on information in the ACAPS. When the measure was local, state_partial was coded 1. On the contrary, when the measure was not localized, state_partial was coded 0. The interaction of state and state_partial allows researchers to create three levels of measures: no state of emergency (state=0 and state_partial =0), partial state of emergency (state=1 and state_partial=1) or national state of emergency (state=1 and state_partial =0); cash: binary variable equal to1 if cash transfers are implemented and 0 otherwise; wage: binary variable equal to1 if wage support is implemented and 0 otherwise; credit: binary variable equal to1 if credit schemes are implemented and 0 otherwise; taxc: binary variable equal to1 if tax credits are implemented and 0 otherwise; taxd: binary variable equal to1 if tax delays are implemented and 0 otherwise; export: binary variable equal to1 if supports to importers or exporters are implemented and 0 otherwise; rate: binary variable equal to1 if the Central Bank lowered the interest rates and 0 otherwise; Rigidity_Public_Health: average of the ten coded public health measures. Public health measures are valued 0.5 if they are localized or partial and 1 if they are national or strict. 0 indicates no measures; Economic_Measures: average of the coded economic measures. The Response2covid19 dataset tracks governments��� responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures ��� 13 public health measures and 7 economic measures ��� taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset (���Governments��� Responses to COVID-19 (Response2covid19)���) and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. Public health measures include international and domestic travel restrictions, bans on mass gatherings, school closing and domestic lockdown among others. Economic measures include wage support, cash transfers, interest rates cuts, tax cuts and delays, and support to exporters or importers. . Smallest Geographic Unit: Country-level other; Cite data as Porcher, Simon "A novel dataset of governments��� responses to COVID-19 all around the world", chaire EPPP discussions paper 2020-03. Link: https://www.chaire-eppp.org/wp-content/uploads/2020/05/WP202003.pdf All countries with available information (228 countries). Response Rates: 62,700 observations; 228 countries.