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Research data keyboard_double_arrow_right Collection , Dataset 2023Publisher:PANGAEA Ausems, Anne; Kuepper, Nadja; Archuby, Diego; Braun, Christina; Gębczyński, Andrzej; Gladbach, Anja; Hahn, Steffen; Jadwiszczak, Piotr; Krämer, Philipp; Libertelli, Marcela; Lorenz, Stefan; Richter, Benjamin; Ruß, Anja; Schmoll, Tim; Thorn, Simon; Turner, John; Wojczulanis-Jakubas, Katarzyna; Jakubas, Dariusz; Quillfeldt, Petra;This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)
PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Lin, Yu-Shih; Elvert, Marcus; Heuer, Verena B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:PANGAEA Authors: Bussmann, Ingeborg; Anselm, Norbert; Fischer, Philipp; von der Esch, Elisabeth;The main objective of this Sternfahrt-8, from 10th to 16th September 2021, was to assess the temporal variance of oceanographic real time data in the Elbe influence area of the German Bight (North Sea). Therefore, the participating Ships should repeat the same tracks for four days (see map). One ship (RV Uthörn) covered the western part between Cuxhaven and Heligoland, the second ship (RV Littorina) went to the northern part between Heligoland and Büsum and the third vessel (RV Ludwig Prandtl) should have covered the middle part of the study area, but due to vandalism damage it could not participate on the cruise. During the whole cruise chemical and physical data were recorded continuously along the tracks. Additionally, discrete water samples were taken on six stations along the way for further analysis in the laboratory. The latter data is not included in the present dataset, and can be accessed via https://doi.pangaea.de/10.1594/PANGAEA.963455. For more information about the MOSES campaign and the "Sternfahrten" cruises see article cited in references.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:PANGAEA Schild, Laura; Kruse, Stefan; Heim, Birgit; Stieg, Amelie; von Hippel, Barbara; Gloy, Josias; Smirnikov, Viktor; Töpfer, Nils; Troeva, Elena I; Pestryakova, Luidmila A; Herzschuh, Ulrike;Vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021.Ground vegetation was surveyed for different vegetation types within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were chosen for the survey. The assignment of a vegetation type is always unique to a site. Their cover on the circular forest plot was recorded in percent.In total, 84 vegetation types at 58 forest plots were assessed. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:PANGAEA Authors: Sánchez, Nicolás; Brüggemann, Daniel; Goldenberg, Silvan Urs;This data was collected as a part of a mesocosm study to investigate the ecosystem impacts of ocean alkalinity enhancement, within the EU H2020 OceanNETs project. Nine mesocosms were deployed in Taliarte Harbour (Gran Canaria, Spain) and were regularly sampled using integrated water samplers between 10th September-25th October 2021. A gradient design was used in this experiment with a total of nine different alkalinity concentrations. Seawater alkalinity ranged between ambient (0 µeq kg-1 added alkalinity, OAE0) and 2400 µeq kg-1 additional alkalinity (OAE2400). The alkalinity levels increased in equal intervals of 300 µeq kg-1 across nine mesocosms (OAE0, OAE300, OAE600, OAE900, OAE1200, OAE1500, OAE1800, OAE2100, OAE2400). This data set contains metazoan zooplankton biomass (µgC per L) from these nine mesocosms. Biomass was calculated based on zooplankton abundances transformed using carbon mass conversion factors. Metazoan zooplankton were sampled with apstein net (ø17cm, mesh size 55µm, 64.06285L) hauls taken every two days (except for days 5 and 9). Zooplankton were size fractioned and assessed in the correspondent size class (small: 55-200µm; medium: 200-500µm; large: 500µm-3mm). Within each size class, all organisms were counted and identified to the lowest possible taxonomic level, and developmental stages were differentiated where possible. Zooplankton abundances (individuals per L) converted to carbon biomass (µgC per L) using biomass conversion factors. Conversion factors are obtained from different sources (Sanchez et al. (in prep)). Briefly: i) metazoan zooplankton functional groups were sampled and measured for carbon biomass using an elemental analyser at specific points throughout the experiment, ii) individual zooplankton were photographed, measured, and their biovolumes and carbon masses derived using standard conversions cited in the literature, iii) zooplankton conversion factors from KOSMOS Gran Canaria 2019 (https://doi.pangaea.de/10.1594/PANGAEA.971765). The experiment, which lasted 33 days, was divided into four response phases (see Sánchez et al. (in prep)): i) pretreatment (days 1 to 4, treatment was implemented on day 4), ii) immediate (days 5-10), iii) shorter term (days 11-22), iv) longer term (days 23 to 33). This data set is associated to the submission by Paul et al. (in review) (https://doi.pangaea.de/10.1594/PANGAEA.966941), so we refer to this data set for basic parameters like water temperature, salinity, pH and carbonate chemistry, to avoid repetition.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Lin, Yu-Shih; Elvert, Marcus; Heuer, Verena B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.832453&type=result"></script>'); --> </script>
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more_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:PANGAEA Funded by:EC | ABYSSEC| ABYSSAuthors: Kiesel, Joshua; Link, Heike; Wenzhöfer, Frank;Total oxygen uptake rates were assessed by conducting sediment core incubations. After MUC retrieval and sediment core preparation on deck, three cores were taken to a dark, temperature controlled laboratory on board Polarstern that was refrigerated to 2 °C-4 °C. Incubation procedure generally followed the approach described by Link et al. (2013, https://doi.org/10.5194/bg-10-5911-2013).
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more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Heuer, Verena B; Lazar, Cassandre Sara; Goldhammer, Tobias; Wendt, Jenny; Samarkin, Vladimir A; Elvert, Marcus; Teske, Andreas P; Joye, Samantha B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2017License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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visibility 17visibility views 17 download downloads 1 Powered bymore_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2017License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021 NetherlandsPublisher:Zenodo Funded by:ARC | Linkage Projects - Grant ..., ARC | ARC Future Fellowships - ..., ARC | Linkage Projects - Grant ...ARC| Linkage Projects - Grant ID: LP180100159 ,ARC| ARC Future Fellowships - Grant ID: FT190100234 ,ARC| Linkage Projects - Grant ID: LP170101143Keith, David A.; Ferrer-Paris, José R.; Nicholson, Emily; Bishop, Melanie J.; Polidoro, Beth A.; Ramirez-Llodra, Eva; Tozer, Mark G.; Nel, Jeanne L.; Mac Nally, Ralph; Gregr, Edward J.; Watermeyer, Kate E.; Essl, Franz; Faber-Langendoen, Don; Franklin, Janet; Lehmann, Caroline E.R.; Etter, Andrés; Roux, Dirk J.; Stark, Jonathan S.; Rowland, Jessica A.; Brummitt, Neil A.; Fernandez-Arcaya, Ulla C.; Suthers, Iain M.; Wiser, Susan K.; Donohue, Ian; Jackson, Leland J.; Pennington, R.T.; Iliffe, Thomas M.; Gerovasileiou, Vasilis; Giller, Paul; Robson, Belinda J.; Pettorelli, Nathalie; Andrade, Angela; Lindgaard, Arild; Tahvanainen, Teemu; Terauds, Aleks; Chadwick, Michael A.; Murray, Nicholas J.; Moat, Justin; Pliscoff, Patricio; Zager, Irene; Kingsford, Richard T.;This dataset includes the current version of the indicative distribution maps and profiles for Ecosystem Functional Groups - Level 3 of IUCN Global Ecosystem Typology (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022). The descriptive profiles provide brief summaries of key ecological traits and processes for each functional group of ecosystems to enable any ecosystem type to be assigned to a group. Maps are indicative of global distribution patterns and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Most maps were prepared using a coarse-scale template (e.g. ecoregions), but some were compiled from higher resolution spatial data where available (see details in profiles). Higher resolution mapping is planned in future publications. We emphasise that spatial representation of Ecosystem Functional Groups does not follow higher-order groupings described in respective ecoregion classifications. Consequently, when Ecosystem Functional Groups are aggregated into functional biomes (Level 2 of the Global Ecosystem Typology), spatial patterns may differ from those of biogeographic biomes. Differences reflect the distinctions between functional and biogeographic interpretations of the term, “biome”. The PLuS Alliance supported a workshop in London to initiate development. DAK, EN, RTK, JRFP, JAR & NJM were supported by ARC Linkage Grants LP170101143 and LP180100159 and the MAVA Foundation. The IUCN Commission on Ecosystem Management supported travel for DAK to present aspects of the research to peers and stakeholders at International Congresses on Conservation Biology in 2017 and 2019, and at meetings in Africa, the middle east, and Europe. {"references": ["Keith, David et al. (Eds.) (2020) 'The IUCN Global Ecosystem Typology v2.0: Descriptive profiles for Biomes and Ecosystem Functional Groups'. The International Union for the Conservation of Nature (IUCN), Gland. DOI:10.2305/IUCN.CH.2020.13.en.", "Keith, David et al. (2022) 'A function-based typology for Earth's ecosystems'. Nature DOI:10.1038/s41586-022-05318-4"]}
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: von Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; +58 Authorsvon Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; Kirchengast, Gottfried; Adusumilli, Susheel; Straneo, Fiammetta; Allan, Richard; Barker, Paul M.; Beltrami, Hugo; Boyer, Tim; Cheng, Lijing; Church, John; Desbruyeres, Damien; Dolman, Han; Domingues, Catia M.; García-García, Almudena; Gilson, John; Gorfer, Maximilian; Haimberger, Leopold; Hendricks, Stefan; Hosoda, Shigeki; Johnson, Gregory C.; Killick, Rachel; King, Brian A.; Kolodziejczyk, Nicolas; Korosov, Anton; Krinner, Gerhard; Kuusela, Mikael; Langer, Moritz; Lavergne, Thomas; Lawrence, Isobel; Li, Yuehua; Lyman, John; Marzeion, Ben; Mayer, Michael; MacDougall, Andrew; McDougall, Trevor; Monselesan, Didier Paolo; Nitzbon, Jean; Otosaka, Inès; Peng, Jian; Purkey, Sarah; Roemmich, Dean; Sato, Kanako; Sato, Katsunari; Savita, Abhishek; Schweiger, Axel; Shepherd, Andrew; Seneviratne, Sonia I.; Slater, Donald A.; Slater, Thomas; Simons, Leon; Steiner, Andrea K.; Szekely, Tanguy; Suga, Toshio; Thiery, Wim; Timmermanns, Mary-Louise; Vanderkelen, Inne; Wijffels, Susan E.; Wu, Tonghua; Zemp, Michael;Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).
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Research data keyboard_double_arrow_right Collection , Dataset 2023Publisher:PANGAEA Ausems, Anne; Kuepper, Nadja; Archuby, Diego; Braun, Christina; Gębczyński, Andrzej; Gladbach, Anja; Hahn, Steffen; Jadwiszczak, Piotr; Krämer, Philipp; Libertelli, Marcela; Lorenz, Stefan; Richter, Benjamin; Ruß, Anja; Schmoll, Tim; Thorn, Simon; Turner, John; Wojczulanis-Jakubas, Katarzyna; Jakubas, Dariusz; Quillfeldt, Petra;This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)
PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Lin, Yu-Shih; Elvert, Marcus; Heuer, Verena B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:PANGAEA Authors: Bussmann, Ingeborg; Anselm, Norbert; Fischer, Philipp; von der Esch, Elisabeth;The main objective of this Sternfahrt-8, from 10th to 16th September 2021, was to assess the temporal variance of oceanographic real time data in the Elbe influence area of the German Bight (North Sea). Therefore, the participating Ships should repeat the same tracks for four days (see map). One ship (RV Uthörn) covered the western part between Cuxhaven and Heligoland, the second ship (RV Littorina) went to the northern part between Heligoland and Büsum and the third vessel (RV Ludwig Prandtl) should have covered the middle part of the study area, but due to vandalism damage it could not participate on the cruise. During the whole cruise chemical and physical data were recorded continuously along the tracks. Additionally, discrete water samples were taken on six stations along the way for further analysis in the laboratory. The latter data is not included in the present dataset, and can be accessed via https://doi.pangaea.de/10.1594/PANGAEA.963455. For more information about the MOSES campaign and the "Sternfahrten" cruises see article cited in references.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.971858&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:PANGAEA Schild, Laura; Kruse, Stefan; Heim, Birgit; Stieg, Amelie; von Hippel, Barbara; Gloy, Josias; Smirnikov, Viktor; Töpfer, Nils; Troeva, Elena I; Pestryakova, Luidmila A; Herzschuh, Ulrike;Vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021.Ground vegetation was surveyed for different vegetation types within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were chosen for the survey. The assignment of a vegetation type is always unique to a site. Their cover on the circular forest plot was recorded in percent.In total, 84 vegetation types at 58 forest plots were assessed. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:PANGAEA Authors: Sánchez, Nicolás; Brüggemann, Daniel; Goldenberg, Silvan Urs;This data was collected as a part of a mesocosm study to investigate the ecosystem impacts of ocean alkalinity enhancement, within the EU H2020 OceanNETs project. Nine mesocosms were deployed in Taliarte Harbour (Gran Canaria, Spain) and were regularly sampled using integrated water samplers between 10th September-25th October 2021. A gradient design was used in this experiment with a total of nine different alkalinity concentrations. Seawater alkalinity ranged between ambient (0 µeq kg-1 added alkalinity, OAE0) and 2400 µeq kg-1 additional alkalinity (OAE2400). The alkalinity levels increased in equal intervals of 300 µeq kg-1 across nine mesocosms (OAE0, OAE300, OAE600, OAE900, OAE1200, OAE1500, OAE1800, OAE2100, OAE2400). This data set contains metazoan zooplankton biomass (µgC per L) from these nine mesocosms. Biomass was calculated based on zooplankton abundances transformed using carbon mass conversion factors. Metazoan zooplankton were sampled with apstein net (ø17cm, mesh size 55µm, 64.06285L) hauls taken every two days (except for days 5 and 9). Zooplankton were size fractioned and assessed in the correspondent size class (small: 55-200µm; medium: 200-500µm; large: 500µm-3mm). Within each size class, all organisms were counted and identified to the lowest possible taxonomic level, and developmental stages were differentiated where possible. Zooplankton abundances (individuals per L) converted to carbon biomass (µgC per L) using biomass conversion factors. Conversion factors are obtained from different sources (Sanchez et al. (in prep)). Briefly: i) metazoan zooplankton functional groups were sampled and measured for carbon biomass using an elemental analyser at specific points throughout the experiment, ii) individual zooplankton were photographed, measured, and their biovolumes and carbon masses derived using standard conversions cited in the literature, iii) zooplankton conversion factors from KOSMOS Gran Canaria 2019 (https://doi.pangaea.de/10.1594/PANGAEA.971765). The experiment, which lasted 33 days, was divided into four response phases (see Sánchez et al. (in prep)): i) pretreatment (days 1 to 4, treatment was implemented on day 4), ii) immediate (days 5-10), iii) shorter term (days 11-22), iv) longer term (days 23 to 33). This data set is associated to the submission by Paul et al. (in review) (https://doi.pangaea.de/10.1594/PANGAEA.966941), so we refer to this data set for basic parameters like water temperature, salinity, pH and carbonate chemistry, to avoid repetition.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2024License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Lin, Yu-Shih; Elvert, Marcus; Heuer, Verena B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.832453&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2014License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Publisher:PANGAEA Funded by:EC | ABYSSEC| ABYSSAuthors: Kiesel, Joshua; Link, Heike; Wenzhöfer, Frank;Total oxygen uptake rates were assessed by conducting sediment core incubations. After MUC retrieval and sediment core preparation on deck, three cores were taken to a dark, temperature controlled laboratory on board Polarstern that was refrigerated to 2 °C-4 °C. Incubation procedure generally followed the approach described by Link et al. (2013, https://doi.org/10.5194/bg-10-5911-2013).
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.907888&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:PANGAEA Funded by:DFG | Modelling flow over bedfo..., DFG | The Ocean Floor – Earth’s...DFG| Modelling flow over bedform fields in tidal environments ,DFG| The Ocean Floor – Earth’s Uncharted InterfaceZhuang, Guang-Chao; Heuer, Verena B; Lazar, Cassandre Sara; Goldhammer, Tobias; Wendt, Jenny; Samarkin, Vladimir A; Elvert, Marcus; Teske, Andreas P; Joye, Samantha B; Hinrichs, Kai-Uwe;B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2017License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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visibility 17visibility views 17 download downloads 1 Powered bymore_vert B2FIND arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2017License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021 NetherlandsPublisher:Zenodo Funded by:ARC | Linkage Projects - Grant ..., ARC | ARC Future Fellowships - ..., ARC | Linkage Projects - Grant ...ARC| Linkage Projects - Grant ID: LP180100159 ,ARC| ARC Future Fellowships - Grant ID: FT190100234 ,ARC| Linkage Projects - Grant ID: LP170101143Keith, David A.; Ferrer-Paris, José R.; Nicholson, Emily; Bishop, Melanie J.; Polidoro, Beth A.; Ramirez-Llodra, Eva; Tozer, Mark G.; Nel, Jeanne L.; Mac Nally, Ralph; Gregr, Edward J.; Watermeyer, Kate E.; Essl, Franz; Faber-Langendoen, Don; Franklin, Janet; Lehmann, Caroline E.R.; Etter, Andrés; Roux, Dirk J.; Stark, Jonathan S.; Rowland, Jessica A.; Brummitt, Neil A.; Fernandez-Arcaya, Ulla C.; Suthers, Iain M.; Wiser, Susan K.; Donohue, Ian; Jackson, Leland J.; Pennington, R.T.; Iliffe, Thomas M.; Gerovasileiou, Vasilis; Giller, Paul; Robson, Belinda J.; Pettorelli, Nathalie; Andrade, Angela; Lindgaard, Arild; Tahvanainen, Teemu; Terauds, Aleks; Chadwick, Michael A.; Murray, Nicholas J.; Moat, Justin; Pliscoff, Patricio; Zager, Irene; Kingsford, Richard T.;This dataset includes the current version of the indicative distribution maps and profiles for Ecosystem Functional Groups - Level 3 of IUCN Global Ecosystem Typology (v2.1). Please refer to Keith et al. (2020) and Keith et al. (2022). The descriptive profiles provide brief summaries of key ecological traits and processes for each functional group of ecosystems to enable any ecosystem type to be assigned to a group. Maps are indicative of global distribution patterns and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Most maps were prepared using a coarse-scale template (e.g. ecoregions), but some were compiled from higher resolution spatial data where available (see details in profiles). Higher resolution mapping is planned in future publications. We emphasise that spatial representation of Ecosystem Functional Groups does not follow higher-order groupings described in respective ecoregion classifications. Consequently, when Ecosystem Functional Groups are aggregated into functional biomes (Level 2 of the Global Ecosystem Typology), spatial patterns may differ from those of biogeographic biomes. Differences reflect the distinctions between functional and biogeographic interpretations of the term, “biome”. The PLuS Alliance supported a workshop in London to initiate development. DAK, EN, RTK, JRFP, JAR & NJM were supported by ARC Linkage Grants LP170101143 and LP180100159 and the MAVA Foundation. The IUCN Commission on Ecosystem Management supported travel for DAK to present aspects of the research to peers and stakeholders at International Congresses on Conservation Biology in 2017 and 2019, and at meetings in Africa, the middle east, and Europe. {"references": ["Keith, David et al. (Eds.) (2020) 'The IUCN Global Ecosystem Typology v2.0: Descriptive profiles for Biomes and Ecosystem Functional Groups'. The International Union for the Conservation of Nature (IUCN), Gland. DOI:10.2305/IUCN.CH.2020.13.en.", "Keith, David et al. (2022) 'A function-based typology for Earth's ecosystems'. Nature DOI:10.1038/s41586-022-05318-4"]}
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: von Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; +58 Authorsvon Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; Kirchengast, Gottfried; Adusumilli, Susheel; Straneo, Fiammetta; Allan, Richard; Barker, Paul M.; Beltrami, Hugo; Boyer, Tim; Cheng, Lijing; Church, John; Desbruyeres, Damien; Dolman, Han; Domingues, Catia M.; García-García, Almudena; Gilson, John; Gorfer, Maximilian; Haimberger, Leopold; Hendricks, Stefan; Hosoda, Shigeki; Johnson, Gregory C.; Killick, Rachel; King, Brian A.; Kolodziejczyk, Nicolas; Korosov, Anton; Krinner, Gerhard; Kuusela, Mikael; Langer, Moritz; Lavergne, Thomas; Lawrence, Isobel; Li, Yuehua; Lyman, John; Marzeion, Ben; Mayer, Michael; MacDougall, Andrew; McDougall, Trevor; Monselesan, Didier Paolo; Nitzbon, Jean; Otosaka, Inès; Peng, Jian; Purkey, Sarah; Roemmich, Dean; Sato, Kanako; Sato, Katsunari; Savita, Abhishek; Schweiger, Axel; Shepherd, Andrew; Seneviratne, Sonia I.; Slater, Donald A.; Slater, Thomas; Simons, Leon; Steiner, Andrea K.; Szekely, Tanguy; Suga, Toshio; Thiery, Wim; Timmermanns, Mary-Louise; Vanderkelen, Inne; Wijffels, Susan E.; Wu, Tonghua; Zemp, Michael;Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).
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