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Research data keyboard_double_arrow_right Dataset 2021Publisher:NERC EDS Environmental Information Data Centre Authors:O’Gorman, E.J.;
O’Gorman, E.J.
O’Gorman, E.J. in OpenAIREWarner, E.;
Warner, E.
Warner, E. in OpenAIREMarteinsdóttir, B.;
Helmutsdóttir, V.F.; +2 AuthorsMarteinsdóttir, B.
Marteinsdóttir, B. in OpenAIREO’Gorman, E.J.;
O’Gorman, E.J.
O’Gorman, E.J. in OpenAIREWarner, E.;
Warner, E.
Warner, E. in OpenAIREMarteinsdóttir, B.;
Helmutsdóttir, V.F.;Marteinsdóttir, B.
Marteinsdóttir, B. in OpenAIREEhrlén, J.;
Ehrlén, J.
Ehrlén, J. in OpenAIRERobinson, S.I.;
Robinson, S.I.
Robinson, S.I. in OpenAIREHerbivory assessments were made at the plant community and species levels. We focused on three plant species with a widespread occurrence across the temperature gradient: cuckooflower (Cardamine pratensis, Linnaeus), common mouse-ear (Cerastium fontanum, Baumgerten), and marsh violet (Viola palustris, Linnaeus). For assessments of invertebrate herbivory at the species level, thirty individuals per species of C. pratensis, C. fontanum, and V. palustris were marked in each of ten plots, using a stratified random sampling method where individuals were randomly selected, but the full range of within-plot soil temperatures was represented. For assessments of invertebrate herbivory at the community level, five 50 × 50 cm quadrats were marked at random points in eight of the plots that best captured the full temperature gradient. The community-level herbivory assessment was conducted on 19th June. The number of damaged plants was recorded out of 100 random individuals, selected using a 10 × 10 grid within each 50 × 50 cm quadrat. For the species-level herbivory assessment, individual marked plants were surveyed for signs of invertebrate herbivory every two weeks from 30th May to 2nd July, generating three time-points per species. At each survey, all marked individuals for each species were assessed within a 48-hour period. Plants were recorded as damaged or not damaged by invertebrate herbivores at each time-point. Further details of how phenological stage of development, vegetation community composition, soil temperature, moisture, pH, nitrate, ammonium, and phosphate were recorded are provided in the supporting documentation. This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate.
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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:Neubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsFerrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRENeubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia;Ferrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRETegen, Ina;
Tegen, Ina
Tegen, Ina in OpenAIREWieners, Karl-Hermann;
Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIREMauritsen, Thorsten;
Stemmler, Irene; Barthel, Stefan; Bey, Isabelle;Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREDaskalakis, Nikos;
Heinold, Bernd;Daskalakis, Nikos
Daskalakis, Nikos in OpenAIREKokkola, Harri;
Kokkola, Harri
Kokkola, Harri in OpenAIREPartridge, Daniel;
Rast, Sebastian; Schmidt, Hauke;Partridge, Daniel
Partridge, Daniel in OpenAIRESchutgens, Nick;
Stanelle, Tanja;Schutgens, Nick
Schutgens, Nick in OpenAIREStier, Philip;
Stier, Philip
Stier, Philip in OpenAIREWatson-Parris, Duncan;
Watson-Parris, Duncan
Watson-Parris, Duncan in OpenAIRELohmann, Ulrike;
Lohmann, Ulrike
Lohmann, Ulrike in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
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.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2020Publisher:Copernicus GmbH Funded by:EC | METLAKE, EC | VERIFY, EC | IMBALANCE-P +4 projectsEC| METLAKE ,EC| VERIFY ,EC| IMBALANCE-P ,EC| CHE ,RCN| Integrated Carbon Observation System (ICOS)-Norway and Ocean Thematic Centre (OTC) ,EC| VISUALMEDIA ,AKA| Novel soil management practices - key for sustainable bioeconomy and climate change mitigation -SOMPA / Consortium: SOMPAAuthors:Ana Maria Roxana Petrescu;
Ana Maria Roxana Petrescu
Ana Maria Roxana Petrescu in OpenAIREChunjing Qiu;
Philippe Ciais;Chunjing Qiu
Chunjing Qiu in OpenAIRERona L. Thompson;
+35 AuthorsRona L. Thompson
Rona L. Thompson in OpenAIREAna Maria Roxana Petrescu;
Ana Maria Roxana Petrescu
Ana Maria Roxana Petrescu in OpenAIREChunjing Qiu;
Philippe Ciais;Chunjing Qiu
Chunjing Qiu in OpenAIRERona L. Thompson;
Philippe Peylin;Rona L. Thompson
Rona L. Thompson in OpenAIREMatthew J. McGrath;
Matthew J. McGrath
Matthew J. McGrath in OpenAIREEfisio Solazzo;
Greet Janssens‐Maenhout;Efisio Solazzo
Efisio Solazzo in OpenAIREFrancesco N. Tubiello;
Francesco N. Tubiello
Francesco N. Tubiello in OpenAIREP. Bergamaschi;
D. Brunner; Glen P. Peters; L. Höglund-Isaksson;P. Bergamaschi
P. Bergamaschi in OpenAIREPierre Regnier;
Pierre Regnier
Pierre Regnier in OpenAIRERonny Lauerwald;
Ronny Lauerwald
Ronny Lauerwald in OpenAIREDavid Bastviken;
David Bastviken
David Bastviken in OpenAIREAki Tsuruta;
Aki Tsuruta
Aki Tsuruta in OpenAIREWilfried Winiwarter;
Wilfried Winiwarter
Wilfried Winiwarter in OpenAIREPrabir K. Patra;
Prabir K. Patra
Prabir K. Patra in OpenAIREMatthias Kuhnert;
Gabriel D. Orregioni;Matthias Kuhnert
Matthias Kuhnert in OpenAIREMonica Crippa;
Monica Crippa
Monica Crippa in OpenAIREMarielle Saunois;
Lucia Perugini;Marielle Saunois
Marielle Saunois in OpenAIRETiina Markkanen;
Tiina Markkanen
Tiina Markkanen in OpenAIRETuula Aalto;
Tuula Aalto
Tuula Aalto in OpenAIREChristine Groot Zwaaftink;
Christine Groot Zwaaftink
Christine Groot Zwaaftink in OpenAIREYuanzhi Yao;
Yuanzhi Yao
Yuanzhi Yao in OpenAIREChris Wilson;
Chris Wilson
Chris Wilson in OpenAIREGiulia Conchedda;
Dirk Günther;Giulia Conchedda
Giulia Conchedda in OpenAIREAdrian Leip;
Adrian Leip
Adrian Leip in OpenAIREPete Smith;
Jean‐Matthieu Haussaire;Pete Smith
Pete Smith in OpenAIREAntti Leppänen;
Alistair J. Manning;Antti Leppänen
Antti Leppänen in OpenAIREJoe McNorton;
Patrick Brockmann; A.J. Dolman;Joe McNorton
Joe McNorton in OpenAIREAbstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).
https://doi.org/10.5... arrow_drop_down https://doi.org/10.5194/essd-2...Article . 2020 . Peer-reviewedLicense: CC BYData sources: Crossrefadd 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=10.5194/essd-2020-367&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert https://doi.org/10.5... arrow_drop_down https://doi.org/10.5194/essd-2...Article . 2020 . Peer-reviewedLicense: CC BYData sources: Crossrefadd 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.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type , Journal 2020 Belgium, Netherlands, France, United KingdomPublisher:Copernicus GmbH Authors:Frédéric Chevallier;
Pierre Regnier; Julia Pongratz;Frédéric Chevallier
Frédéric Chevallier in OpenAIREAtul K. Jain;
+30 AuthorsAtul K. Jain
Atul K. Jain in OpenAIREFrédéric Chevallier;
Pierre Regnier; Julia Pongratz;Frédéric Chevallier
Frédéric Chevallier in OpenAIREAtul K. Jain;
Atul K. Jain
Atul K. Jain in OpenAIRERoxana Petrescu;
Roxana Petrescu
Roxana Petrescu in OpenAIRERobert J. Scholes;
Robert J. Scholes
Robert J. Scholes in OpenAIREPep Canadell;
Pep Canadell
Pep Canadell in OpenAIREMasayuki Kondo;
Hui Yang;Masayuki Kondo
Masayuki Kondo in OpenAIREMarielle Saunois;
Marielle Saunois
Marielle Saunois in OpenAIREBo Zheng;
Wouter Peters; Wouter Peters;Bo Zheng
Bo Zheng in OpenAIREBenjamin Poulter;
Benjamin Poulter; Benjamin Poulter;Benjamin Poulter
Benjamin Poulter in OpenAIREMatthew W. Jones;
Matthew W. Jones
Matthew W. Jones in OpenAIREHanqin Tian;
Hanqin Tian
Hanqin Tian in OpenAIREXuhui Wang;
Shilong Piao; Shilong Piao; Ronny Lauerwald; Ronny Lauerwald;Xuhui Wang
Xuhui Wang in OpenAIREIngrid T. Luijkx;
Anatoli Shvidenko; Anatoli Shvidenko; Gustaf Hugelius; Celso von Randow;Ingrid T. Luijkx
Ingrid T. Luijkx in OpenAIREChunjing Qiu;
Robert B. Jackson; Robert B. Jackson; Prabir K. Patra; Philippe Ciais;Chunjing Qiu
Chunjing Qiu in OpenAIREAna Bastos;
Ana Bastos
Ana Bastos in OpenAIREAbstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.
Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2022Full-Text: https://hal.science/hal-03604087Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2022License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2022Full-Text: https://hal.science/hal-03604087Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmd-20...Article . 2020 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2022 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2022License: CC BYData sources: Wageningen Staff Publicationsadd 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=10.5194/gmd-2020-259&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 46 citations 46 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!
visibility 7visibility views 7 download downloads 13 Powered bymore_vert Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2022Full-Text: https://hal.science/hal-03604087Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2022License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2022Full-Text: https://hal.science/hal-03604087Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmd-20...Article . 2020 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2022 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2022License: CC BYData sources: Wageningen Staff Publicationsadd 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=10.5194/gmd-2020-259&type=result"></script>'); --> </script>
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:Neubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsFerrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRENeubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia;Ferrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRETegen, Ina;
Tegen, Ina
Tegen, Ina in OpenAIREWieners, Karl-Hermann;
Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIREMauritsen, Thorsten;
Stemmler, Irene; Barthel, Stefan; Bey, Isabelle;Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREDaskalakis, Nikos;
Heinold, Bernd;Daskalakis, Nikos
Daskalakis, Nikos in OpenAIREKokkola, Harri;
Kokkola, Harri
Kokkola, Harri in OpenAIREPartridge, Daniel;
Rast, Sebastian; Schmidt, Hauke;Partridge, Daniel
Partridge, Daniel in OpenAIRESchutgens, Nick;
Stanelle, Tanja;Schutgens, Nick
Schutgens, Nick in OpenAIREStier, Philip;
Stier, Philip
Stier, Philip in OpenAIREWatson-Parris, Duncan;
Watson-Parris, Duncan
Watson-Parris, Duncan in OpenAIRELohmann, Ulrike;
Lohmann, Ulrike
Lohmann, Ulrike in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Embargo end date: 29 Jun 2018Publisher:Dryad Murray, David; Kainz, Martin; Hebberecht, Laura; Sales, Kris; Hindar, Kjetil; Gage, Matthew;Triploidy could prevent escaped farm salmon breeding in the wild, while also improving nutrient quality within farmed fillets. Despite these potential advantages, triploid Atlantic salmon have not been widely used in aquaculture, and their reproductive function has yet to be fully evaluated. Here, we compare reproductive function and fillet composition between triploid and diploid farm salmon under standard aquaculture rearing conditions. We show that female triploids are sterile and do not develop gonads. In contrast, males produce large numbers of motile spermatozoa capable of fertilising wild salmon eggs. However, compared with diploids, reproductive development and survival rates of eggs fertilised by triploid males were significantly reduced, with less than 1% of eggs sired by triploid males reaching late eyed stages of development. Analyses of fillets showed that total lipid and fatty acid quantities were significantly lower in triploid compared to diploid Atlantic salmon fillets. However, when fatty acids were normalized to total lipid content, triploid fillets had significantly higher relative levels of important omega-3 Long Chain Polyunsaturated Fatty Acids. Our results show that: (1) escaped triploid farm salmon are very unlikely to reproduce in the wild; and (2) if able to match diploid fillet lipid content, triploid farm salmon could achieve better fillet quality in terms of essential fatty acids. Comparisons between diploid and triploid Atlantic salmonExcel file containing all the data collected during the investigation into the reproductive maturation of triploid Atlantic salmon, their fatty acid biochemistry and how they compare to diploid conspecifics
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Embargo end date: 13 Nov 2019Publisher:Dryad Authors:Warren-Thomas, Eleanor;
Nelson, Luke; Juthong, Watinee; Bumrungsri, Sara; +7 AuthorsWarren-Thomas, Eleanor
Warren-Thomas, Eleanor in OpenAIREWarren-Thomas, Eleanor;
Nelson, Luke; Juthong, Watinee; Bumrungsri, Sara; Brattström, Oskar; Stroesser, Laetitia; Chambon, Bénédicte; Penot, Éric; Tongkaemkew, Uraiwan; Edwards, David P.; Dolman, Paul M.;Warren-Thomas, Eleanor
Warren-Thomas, Eleanor in OpenAIREMonocultural rubber plantations have replaced tropical forest, causing biodiversity loss. While protecting intact or semi-intact biodiverse forest is paramount, improving biodiversity value within the 11.4 million hectares of existing rubber plantations could offer important conservation benefits, if yields are also maintained. Some farmers practice agroforestry with high-yielding clonal rubber varieties to increase and diversify incomes. Here, we ask whether such rubber agroforestry improves biodiversity value or affects rubber yields relative to monoculture. We surveyed birds, fruit-feeding butterflies and reptiles in 25 monocultural and 39 agroforest smallholder rubber plots in Thailand, the world’s biggest rubber producer. Management and vegetation structure data were collected from each plot, and landscape composition around plots was quantified. Rubber yield data were collected for a separate set of 34 monocultural and 47 agroforest rubber plots in the same region. Reported rubber yields did not differ between agroforests and monocultures, meaning adoption of agroforestry in this context should not increase land demand for natural rubber. Butterfly richness was greater in agroforests, where richness increased with greater natural forest extent in the landscape. Bird and reptile richness were similar between agroforests and monocultures, but bird richness increased with the height of herbaceous vegetation inside rubber plots. Species composition of butterflies differed between agroforests and monocultures, and in response to natural forest extent, while bird composition was influenced by herbaceous vegetation height within plots, the density of non-rubber trees within plots (representing agroforestry complexity), and natural forest extent in the landscape. Reptile composition was influenced by canopy cover and open habitat extent in the landscape. Conservation priority and forest-dependent birds were not supported within rubber. Synthesis and applications. Rubber agroforestry using clonal varieties provides modest biodiversity benefits relative to monocultures, without compromising yields. Agroforests may also generate ecosystem service and livelihood benefits. Management of monocultural rubber production to increase inter-row vegetation height and complexity may further benefit biodiversity. However, biodiversity losses from encroachment of rubber onto forests will not be offset by rubber agroforestry or rubber plot management. This evidence is important for developing guidelines around biodiversity-friendly rubber and sustainable supply chains, and for farmers interested in diversifying rubber production. The accompanying ReadMe.txt file explains the contents of each .csv file, including definitions of each column. Sampling protocols are outlined in the paper in Journal of Applied Ecology.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2016 United Kingdom, Netherlands, Spain, AustraliaPublisher:Copernicus GmbH Funded by:EC | SIP-VOL+, ARC | ARC Centres of Excellence..., RSF | Scientific basis of the n... +2 projectsEC| SIP-VOL+ ,ARC| ARC Centres of Excellences - Grant ID: CE140100008 ,RSF| Scientific basis of the national biobank - depository of the living systems ,UKRI| Process-Based Emergent Constraints on Global Physical and Biogeochemical Feedbacks ,EC| IMBALANCE-PAuthors:Anna B. Harper;
Anna B. Harper
Anna B. Harper in OpenAIREPeter M. Cox;
Peter M. Cox
Peter M. Cox in OpenAIREPierre Friedlingstein;
Andy J. Wiltshire; +17 AuthorsPierre Friedlingstein
Pierre Friedlingstein in OpenAIREAnna B. Harper;
Anna B. Harper
Anna B. Harper in OpenAIREPeter M. Cox;
Peter M. Cox
Peter M. Cox in OpenAIREPierre Friedlingstein;
Andy J. Wiltshire;Pierre Friedlingstein
Pierre Friedlingstein in OpenAIREChris D. Jones;
Chris D. Jones
Chris D. Jones in OpenAIREStephen Sitch;
Stephen Sitch
Stephen Sitch in OpenAIRELina M. Mercado;
Margriet Groenendijk; Eddy Robertson;Lina M. Mercado
Lina M. Mercado in OpenAIREJens Kattge;
Gerhard Bönisch;Jens Kattge
Jens Kattge in OpenAIREOwen K. Atkin;
Owen K. Atkin
Owen K. Atkin in OpenAIREMichael Bahn;
Johannes Cornelissen;Michael Bahn
Michael Bahn in OpenAIREÜlo Niinemets;
Vladimir Onipchenko;Ülo Niinemets
Ülo Niinemets in OpenAIREJosep Peñuelas;
Josep Peñuelas
Josep Peñuelas in OpenAIRELourens Poorter;
Lourens Poorter
Lourens Poorter in OpenAIREPeter B. Reich;
Nadjeda A. Soudzilovskaia;Peter B. Reich
Peter B. Reich in OpenAIREPeter van Bodegom;
Peter van Bodegom
Peter van Bodegom in OpenAIREAbstract. Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year−1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage.
University of Wester... arrow_drop_down University of Western Sydney (UWS): Research DirectArticle . 2016License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2016License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Australian National University: ANU Digital CollectionsArticleLicense: CC BYData sources: Bielefeld Academic Search Engine (BASE)Geoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2021License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2016License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2016License: CC BYData sources: Diposit Digital de Documents de la UABWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff Publicationsadd 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=10.5194/gmd-9-2415-2016&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 109 citations 109 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 7visibility views 7 download downloads 26 Powered bymore_vert University of Wester... arrow_drop_down University of Western Sydney (UWS): Research DirectArticle . 2016License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2016License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Australian National University: ANU Digital CollectionsArticleLicense: CC BYData sources: Bielefeld Academic Search Engine (BASE)Geoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2021License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2016License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2016License: CC BYData sources: Diposit Digital de Documents de la UABWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff Publicationsadd 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=10.5194/gmd-9-2415-2016&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 United KingdomPublisher:Informa UK Limited Authors:Ingmar von Homeyer;
Ingmar von Homeyer
Ingmar von Homeyer in OpenAIRESebastian Oberthür;
Sebastian Oberthür
Sebastian Oberthür in OpenAIREAndrew J. Jordan;
Andrew J. Jordan
Andrew J. Jordan in OpenAIREThe EU has long pursued relatively ambitious climate and energy policies, often against the backdrop of what has been termed the EU ‘polycrisis’. This paper introduces a special issue which seeks t...
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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=10.1080/13501763.2021.1918221&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 48 citations 48 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
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.
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=10.1080/13501763.2021.1918221&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Authors:Mauro Luberti;
Mauro Luberti
Mauro Luberti in OpenAIREAlexander Brown;
Marco Balsamo;Alexander Brown
Alexander Brown in OpenAIREMauro Capocelli;
Mauro Capocelli
Mauro Capocelli in OpenAIREdoi: 10.3390/en15031091
The increasing demand for energy and commodities has led to escalating greenhouse gas emissions, the chief of which is represented by carbon dioxide (CO2). Blue hydrogen (H2), a low-carbon hydrogen produced from natural gas with carbon capture technologies applied, has been suggested as a possible alternative to fossil fuels in processes with hard-to-abate emission sources, including refining, chemical, petrochemical and transport sectors. Due to the recent international directives aimed to combat climate change, even existing hydrogen plants should be retrofitted with carbon capture units. To optimize the process economics of such retrofit, it has been proposed to remove CO2 from the pressure swing adsorption (PSA) tail gas to exploit the relatively high CO2 concentration. This study aimed to design and numerically investigate a vacuum pressure swing adsorption (VPSA) process capable of capturing CO2 from the PSA tail gas of an industrial steam methane reforming (SMR)-based hydrogen plant using NaX zeolite adsorbent. The effect of operating conditions, such as purge-to-feed ratio and desorption pressure, were evaluated in relation to CO2 purity, CO2 recovery, bed productivity and specific energy consumption. We found that conventional cycle configurations, namely a 2-bed, 4-step Skarstrom cycle and a 2-bed, 6-step modified Skarstrom cycle with pressure equalization, were able to concentrate CO2 to a purity greater than 95% with a CO2 recovery of around 77% and 90%, respectively. Therefore, the latter configuration could serve as an efficient process to decarbonize existing hydrogen plants and produce blue H2.
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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=10.3390/en15031091&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
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.
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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