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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsNeubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia; Tegen, Ina; Wieners, Karl-Hermann; Mauritsen, Thorsten; Stemmler, Irene; Barthel, Stefan; Bey, Isabelle; Daskalakis, Nikos; Heinold, Bernd; Kokkola, Harri; Partridge, Daniel; Rast, Sebastian; Schmidt, Hauke; Schutgens, Nick; Stanelle, Tanja; Stier, Philip; Watson-Parris, Duncan; Lohmann, Ulrike;Project: 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.
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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: SOMPAAna Maria Roxana Petrescu; Chunjing Qiu; Philippe Ciais; Rona L. Thompson; Philippe Peylin; Matthew J. McGrath; Efisio Solazzo; Greet Janssens‐Maenhout; Francesco N. Tubiello; P. Bergamaschi; D. Brunner; Glen P. Peters; L. Höglund-Isaksson; Pierre Regnier; Ronny Lauerwald; David Bastviken; Aki Tsuruta; Wilfried Winiwarter; Prabir K. Patra; Matthias Kuhnert; Gabriel D. Orregioni; Monica Crippa; Marielle Saunois; Lucia Perugini; Tiina Markkanen; Tuula Aalto; Christine Groot Zwaaftink; Yuanzhi Yao; Chris Wilson; Giulia Conchedda; Dirk Günther; Adrian Leip; Pete Smith; Jean‐Matthieu Haussaire; Antti Leppänen; Alistair J. Manning; Joe McNorton; Patrick Brockmann; A.J. Dolman;Abstract. 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.
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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 Frédéric Chevallier; Pierre Regnier; Julia Pongratz; Atul K. Jain; Roxana Petrescu; Robert J. Scholes; Pep Canadell; Masayuki Kondo; Hui Yang; Marielle Saunois; Bo Zheng; Wouter Peters; Wouter Peters; Benjamin Poulter; Benjamin Poulter; Benjamin Poulter; Matthew W. Jones; Hanqin Tian; Xuhui Wang; Shilong Piao; Shilong Piao; Ronny Lauerwald; Ronny Lauerwald; Ingrid T. Luijkx; Anatoli Shvidenko; Anatoli Shvidenko; Gustaf Hugelius; Celso von Randow; Chunjing Qiu; Robert B. Jackson; Robert B. Jackson; Prabir K. Patra; Philippe Ciais; Ana Bastos;Abstract. 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; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsNeubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia; Tegen, Ina; Wieners, Karl-Hermann; Mauritsen, Thorsten; Stemmler, Irene; Barthel, Stefan; Bey, Isabelle; Daskalakis, Nikos; Heinold, Bernd; Kokkola, Harri; Partridge, Daniel; Rast, Sebastian; Schmidt, Hauke; Schutgens, Nick; Stanelle, Tanja; Stier, Philip; Watson-Parris, Duncan; Lohmann, Ulrike;Project: 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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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.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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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=10.26050/wdcc/ar6.c6cmhcme1hi&type=result"></script>'); --> </script>
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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visibility 8visibility views 8 download downloads 2 Powered bymore_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=10.5061/dryad.bt6616g&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019 United KingdomPublisher:IOP Publishing Funded by:UKRI | Comparative assessment an..., UKRI | Integrated assessment of ..., UKRI | Euro-China GE: Dynamics o...UKRI| Comparative assessment and region-specific optimisation of GGR ,UKRI| Integrated assessment of the emission-health-socioeconomics nexus and air pollution mitigation solutions and interventions in Beijing (INHANCE) ,UKRI| Euro-China GE: Dynamics of Green Growth in European and Chinese Cities (DRAGON)Jing Meng; Zongyong Zhang; Zongyong Zhang; Yuli Shan; Lili Yang; Lili Yang; Dabo Guan; Dabo Guan; Xian Li; Xian Li;China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.
University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Environmental Research LettersArticle . 2019Data sources: DANS (Data Archiving and Networked Services)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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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 download downloads 8 Powered bymore_vert University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Environmental Research LettersArticle . 2019Data sources: DANS (Data Archiving and Networked Services)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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2002 United KingdomPublisher:Informa UK Limited Authors: Boyd, Emily;handle: 10546/131479
A focus on land-use and forests as a means to reduce carbon dioxide levels in the global atmosphere has been at the heart of the international climate change debate since the United Nations Kyoto Protocol was agreed in 1997. This environmental management practice is a process technically referred to as mitigation. These largely technical projects have aimed to provide sustainable development benefits to forest-dependent people, as well as to reduce greenhouse gas emissions. However, these projects have had limited success in achieving these local development objectives. This article argues that this is due in part to the patriarchal underpinnings of the sustainable development and climate-change policy agendas. The author explores this theory by considering how a climate mitigation project in Bolivia has resulted in different outcomes for women and men, and makes links between the global decision-making process and local effects.
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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.
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For further information contact us at helpdesk@openaire.euAccess Routesbronze 49 citations 49 popularity Top 10% influence Top 10% impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2007 United KingdomPublisher:Elsevier BV Authors: Hubacek, Klaus; Guan, Dabo; Barua, Anamika;China and India are the world's largest developing economies and also two of the most populous countries. China, which now has more than 1.3 billion people, is expected to grow to more than 1.4 billion by 2050, and India with a population of I billion will overtake China to be the most populous country with about 1.6 billion population. These two countries are home to 37% of the world's population today. In addition, China and India have achieved notable success in their economic development characterised by a high rate of gross domestic product (GDP) growth in the last two decades. Together the two countries account already for almost a fifth of world GDP. The most direct and significant result of economic growth in India and China is the amazing improvement in quality of life (or at least spending power) for an increasing share of the population. The populations of both the countries have experienced a transition from 'poverty' to 'adequate food and clothing',- today growing parts of the population are getting closer to 'well to do lifestyles'. These seLyments of the society are not satisfied any more with enough food and clothes, but are also eager to obtain a quality life of high nutrient food, comfortable living, health care and other quality services. The theme of this paper is to analyse how the major drivers contributed to the environmental consequences in the past, and to take a forward look at the environmental impacts of these driving forces in China and India. The paper identifies population, affluence and technology to be the major drivina forces in environmental pollution for these two countries then applies the simple equation of Impact = Population x Affluence x Technology, or I = PAT to evaluate the effects of changes in these drivers on CO, emissions. (C) 2007 Elsevier Ltd. All rights reserved.
CORE arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2007Data sources: Bielefeld Academic Search Engine (BASE)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.euAccess RoutesGreen bronze 179 citations 179 popularity Top 1% influence Top 1% impulse Top 10% Powered by BIP!
visibility 37visibility views 37 download downloads 5,816 Powered bymore_vert CORE arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2007Data sources: Bielefeld Academic Search Engine (BASE)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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2017 United KingdomPublisher:SAGE Publications Authors: Jakobsson, N.; Muttarak, R.; Schoyen, M.A.;Recent theoretical literature in social policy argued that climate change posed a new risk to the states and called for transformation from a traditional welfare state to an ‘eco’ state. From a theoretical point of view, different welfare regimes may manage environmental/climate change risks in a similar way to social risks. However, not much has been done to explore the issue empirically. To this end, this paper aims to investigate public attitudes towards environmental and traditional welfare policies given that environmental change is a new social risk the welfare states have to address. Do individuals that care for one area also care for the other? That is, do the preferences in these two policy spheres complement or substitute one another? We test these hypotheses both at the individual- and country-level, using data from 14 countries included in all three waves (1993, 2000, and 2010) of the environmental module in the International Social Survey Programme. Specifically, we investigate the relationship between attitudes towards income redistribution (indicator of support for welfare policy) and willingness to pay for environmental protection (indicator of support for environmental policy). Our findings suggest that attitudes in the two areas are substitutes in the total sample, but that the relationship is very small and only statistically significant in some specifications. When we explore country differentials, we observe clear heterogeneity in the relationship, which can be explained by differences in political and historical contexts across countries.
University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)Social Science Open Access RepositoryArticle . 2018Data sources: Social Science Open Access Repositoryadd 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.euAccess RoutesGreen hybrid 33 citations 33 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
visibility 9visibility views 9 download downloads 18 Powered bymore_vert University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)Social Science Open Access RepositoryArticle . 2018Data sources: Social Science Open Access Repositoryadd 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=10.1177/2399654417711448&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019 Germany, France, Spain, United Kingdom, France, Spain, United States, Australia, AustraliaPublisher:Proceedings of the National Academy of Sciences Funded by:EC | BIGSEA, NSERC, EC | MERCES +1 projectsEC| BIGSEA ,NSERC ,EC| MERCES ,EC| CERESDavid A. Carozza; Steve Mackinson; Jeroen Steenbeek; Villy Christensen; Philippe Verley; Susa Niiranen; Andrea Bryndum-Buchholz; Matthias Büchner; Derek P. Tittensor; Derek P. Tittensor; Jan Volkholz; John P. Dunne; Elizabeth A. Fulton; Julia L. Blanchard; Ricardo Oliveros-Ramos; Jacob Schewe; Simon Jennings; Simon Jennings; Manuel Barange; Charles A. Stock; Boris Worm; Miranda C. Jones; Nicola D. Walker; Laurent Bopp; Olivier Maury; Olivier Maury; William W. L. Cheung; Tiago H. Silva; Daniele Bianchi; Heike K. Lotze; Tilla Roy; Catherine M. Bulman; Tyler D. Eddy; Tyler D. Eddy; Nicolas Barrier; Marta Coll; Eric D. Galbraith; Eric D. Galbraith; Jose A. Fernandes; Yunne-Jai Shin; Yunne-Jai Shin;While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.
CIRAD: HAL (Agricult... arrow_drop_down CIRAD: HAL (Agricultural Research for Development)Article . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Publication Database PIK (Potsdam Institute for Climate Impact Research)Article . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Proceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: CrossrefRecolector de Ciencia Abierta, RECOLECTAArticle . 2019Data sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BY NC NDData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2019License: CC BY NC NDData sources: Diposit Digital de Documents de la UABProceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Tasmania: UTas ePrintsArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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=10.1073/pnas.1900194116&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 397 citations 397 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 30visibility views 30 download downloads 97 Powered bymore_vert CIRAD: HAL (Agricult... arrow_drop_down CIRAD: HAL (Agricultural Research for Development)Article . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Publication Database PIK (Potsdam Institute for Climate Impact Research)Article . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Proceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: CrossrefRecolector de Ciencia Abierta, RECOLECTAArticle . 2019Data sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BY NC NDData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2019License: CC BY NC NDData sources: Diposit Digital de Documents de la UABProceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Tasmania: UTas ePrintsArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsNeubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia; Tegen, Ina; Wieners, Karl-Hermann; Mauritsen, Thorsten; Stemmler, Irene; Barthel, Stefan; Bey, Isabelle; Daskalakis, Nikos; Heinold, Bernd; Kokkola, Harri; Partridge, Daniel; Rast, Sebastian; Schmidt, Hauke; Schutgens, Nick; Stanelle, Tanja; Stier, Philip; Watson-Parris, Duncan; Lohmann, Ulrike;Project: 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.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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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: SOMPAAna Maria Roxana Petrescu; Chunjing Qiu; Philippe Ciais; Rona L. Thompson; Philippe Peylin; Matthew J. McGrath; Efisio Solazzo; Greet Janssens‐Maenhout; Francesco N. Tubiello; P. Bergamaschi; D. Brunner; Glen P. Peters; L. Höglund-Isaksson; Pierre Regnier; Ronny Lauerwald; David Bastviken; Aki Tsuruta; Wilfried Winiwarter; Prabir K. Patra; Matthias Kuhnert; Gabriel D. Orregioni; Monica Crippa; Marielle Saunois; Lucia Perugini; Tiina Markkanen; Tuula Aalto; Christine Groot Zwaaftink; Yuanzhi Yao; Chris Wilson; Giulia Conchedda; Dirk Günther; Adrian Leip; Pete Smith; Jean‐Matthieu Haussaire; Antti Leppänen; Alistair J. Manning; Joe McNorton; Patrick Brockmann; A.J. Dolman;Abstract. 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.
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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.
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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 Frédéric Chevallier; Pierre Regnier; Julia Pongratz; Atul K. Jain; Roxana Petrescu; Robert J. Scholes; Pep Canadell; Masayuki Kondo; Hui Yang; Marielle Saunois; Bo Zheng; Wouter Peters; Wouter Peters; Benjamin Poulter; Benjamin Poulter; Benjamin Poulter; Matthew W. Jones; Hanqin Tian; Xuhui Wang; Shilong Piao; Shilong Piao; Ronny Lauerwald; Ronny Lauerwald; Ingrid T. Luijkx; Anatoli Shvidenko; Anatoli Shvidenko; Gustaf Hugelius; Celso von Randow; Chunjing Qiu; Robert B. Jackson; Robert B. Jackson; Prabir K. Patra; Philippe Ciais; Ana Bastos;Abstract. 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.
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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=10.5194/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; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsNeubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia; Tegen, Ina; Wieners, Karl-Hermann; Mauritsen, Thorsten; Stemmler, Irene; Barthel, Stefan; Bey, Isabelle; Daskalakis, Nikos; Heinold, Bernd; Kokkola, Harri; Partridge, Daniel; Rast, Sebastian; Schmidt, Hauke; Schutgens, Nick; Stanelle, Tanja; Stier, Philip; Watson-Parris, Duncan; Lohmann, Ulrike;Project: 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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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.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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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.
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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
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=10.5061/dryad.bt6616g&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 8visibility views 8 download downloads 2 Powered bymore_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=10.5061/dryad.bt6616g&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019 United KingdomPublisher:IOP Publishing Funded by:UKRI | Comparative assessment an..., UKRI | Integrated assessment of ..., UKRI | Euro-China GE: Dynamics o...UKRI| Comparative assessment and region-specific optimisation of GGR ,UKRI| Integrated assessment of the emission-health-socioeconomics nexus and air pollution mitigation solutions and interventions in Beijing (INHANCE) ,UKRI| Euro-China GE: Dynamics of Green Growth in European and Chinese Cities (DRAGON)Jing Meng; Zongyong Zhang; Zongyong Zhang; Yuli Shan; Lili Yang; Lili Yang; Dabo Guan; Dabo Guan; Xian Li; Xian Li;China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.
University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Environmental Research LettersArticle . 2019Data sources: DANS (Data Archiving and Networked Services)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=10.1088/1748-9326/ab4e54&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 download downloads 8 Powered bymore_vert University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Environmental Research LettersArticle . 2019Data sources: DANS (Data Archiving and Networked Services)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=10.1088/1748-9326/ab4e54&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2002 United KingdomPublisher:Informa UK Limited Authors: Boyd, Emily;handle: 10546/131479
A focus on land-use and forests as a means to reduce carbon dioxide levels in the global atmosphere has been at the heart of the international climate change debate since the United Nations Kyoto Protocol was agreed in 1997. This environmental management practice is a process technically referred to as mitigation. These largely technical projects have aimed to provide sustainable development benefits to forest-dependent people, as well as to reduce greenhouse gas emissions. However, these projects have had limited success in achieving these local development objectives. This article argues that this is due in part to the patriarchal underpinnings of the sustainable development and climate-change policy agendas. The author explores this theory by considering how a climate mitigation project in Bolivia has resulted in different outcomes for women and men, and makes links between the global decision-making process and local effects.
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=10.1080/13552070215905&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 49 citations 49 popularity Top 10% influence Top 10% 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.
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=10.1080/13552070215905&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2007 United KingdomPublisher:Elsevier BV Authors: Hubacek, Klaus; Guan, Dabo; Barua, Anamika;China and India are the world's largest developing economies and also two of the most populous countries. China, which now has more than 1.3 billion people, is expected to grow to more than 1.4 billion by 2050, and India with a population of I billion will overtake China to be the most populous country with about 1.6 billion population. These two countries are home to 37% of the world's population today. In addition, China and India have achieved notable success in their economic development characterised by a high rate of gross domestic product (GDP) growth in the last two decades. Together the two countries account already for almost a fifth of world GDP. The most direct and significant result of economic growth in India and China is the amazing improvement in quality of life (or at least spending power) for an increasing share of the population. The populations of both the countries have experienced a transition from 'poverty' to 'adequate food and clothing',- today growing parts of the population are getting closer to 'well to do lifestyles'. These seLyments of the society are not satisfied any more with enough food and clothes, but are also eager to obtain a quality life of high nutrient food, comfortable living, health care and other quality services. The theme of this paper is to analyse how the major drivers contributed to the environmental consequences in the past, and to take a forward look at the environmental impacts of these driving forces in China and India. The paper identifies population, affluence and technology to be the major drivina forces in environmental pollution for these two countries then applies the simple equation of Impact = Population x Affluence x Technology, or I = PAT to evaluate the effects of changes in these drivers on CO, emissions. (C) 2007 Elsevier Ltd. All rights reserved.
CORE arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2007Data sources: Bielefeld Academic Search Engine (BASE)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=10.1016/j.futures.2007.03.010&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 179 citations 179 popularity Top 1% influence Top 1% impulse Top 10% Powered by BIP!
visibility 37visibility views 37 download downloads 5,816 Powered bymore_vert CORE arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2007Data sources: Bielefeld Academic Search Engine (BASE)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=10.1016/j.futures.2007.03.010&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2017 United KingdomPublisher:SAGE Publications Authors: Jakobsson, N.; Muttarak, R.; Schoyen, M.A.;Recent theoretical literature in social policy argued that climate change posed a new risk to the states and called for transformation from a traditional welfare state to an ‘eco’ state. From a theoretical point of view, different welfare regimes may manage environmental/climate change risks in a similar way to social risks. However, not much has been done to explore the issue empirically. To this end, this paper aims to investigate public attitudes towards environmental and traditional welfare policies given that environmental change is a new social risk the welfare states have to address. Do individuals that care for one area also care for the other? That is, do the preferences in these two policy spheres complement or substitute one another? We test these hypotheses both at the individual- and country-level, using data from 14 countries included in all three waves (1993, 2000, and 2010) of the environmental module in the International Social Survey Programme. Specifically, we investigate the relationship between attitudes towards income redistribution (indicator of support for welfare policy) and willingness to pay for environmental protection (indicator of support for environmental policy). Our findings suggest that attitudes in the two areas are substitutes in the total sample, but that the relationship is very small and only statistically significant in some specifications. When we explore country differentials, we observe clear heterogeneity in the relationship, which can be explained by differences in political and historical contexts across countries.
University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)Social Science Open Access RepositoryArticle . 2018Data sources: Social Science Open Access Repositoryadd 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=10.1177/2399654417711448&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 33 citations 33 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
visibility 9visibility views 9 download downloads 18 Powered bymore_vert University of East A... arrow_drop_down University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BY NCData sources: Bielefeld Academic Search Engine (BASE)Social Science Open Access RepositoryArticle . 2018Data sources: Social Science Open Access Repositoryadd 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=10.1177/2399654417711448&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019 Germany, France, Spain, United Kingdom, France, Spain, United States, Australia, AustraliaPublisher:Proceedings of the National Academy of Sciences Funded by:EC | BIGSEA, NSERC, EC | MERCES +1 projectsEC| BIGSEA ,NSERC ,EC| MERCES ,EC| CERESDavid A. Carozza; Steve Mackinson; Jeroen Steenbeek; Villy Christensen; Philippe Verley; Susa Niiranen; Andrea Bryndum-Buchholz; Matthias Büchner; Derek P. Tittensor; Derek P. Tittensor; Jan Volkholz; John P. Dunne; Elizabeth A. Fulton; Julia L. Blanchard; Ricardo Oliveros-Ramos; Jacob Schewe; Simon Jennings; Simon Jennings; Manuel Barange; Charles A. Stock; Boris Worm; Miranda C. Jones; Nicola D. Walker; Laurent Bopp; Olivier Maury; Olivier Maury; William W. L. Cheung; Tiago H. Silva; Daniele Bianchi; Heike K. Lotze; Tilla Roy; Catherine M. Bulman; Tyler D. Eddy; Tyler D. Eddy; Nicolas Barrier; Marta Coll; Eric D. Galbraith; Eric D. Galbraith; Jose A. Fernandes; Yunne-Jai Shin; Yunne-Jai Shin;While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.
CIRAD: HAL (Agricult... arrow_drop_down CIRAD: HAL (Agricultural Research for Development)Article . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Publication Database PIK (Potsdam Institute for Climate Impact Research)Article . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Proceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: CrossrefRecolector de Ciencia Abierta, RECOLECTAArticle . 2019Data sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BY NC NDData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2019License: CC BY NC NDData sources: Diposit Digital de Documents de la UABProceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Tasmania: UTas ePrintsArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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=10.1073/pnas.1900194116&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 397 citations 397 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 30visibility views 30 download downloads 97 Powered bymore_vert CIRAD: HAL (Agricult... arrow_drop_down CIRAD: HAL (Agricultural Research for Development)Article . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2019License: CC BY NC NDFull-Text: https://hal.umontpellier.fr/hal-02272161Data sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Publication Database PIK (Potsdam Institute for Climate Impact Research)Article . 2019License: CC BY NC NDData sources: Bielefeld Academic Search Engine (BASE)Proceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedLicense: CC BY NC NDData sources: CrossrefRecolector de Ciencia Abierta, RECOLECTAArticle . 2019Data sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTARecolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BY NC NDData sources: Recolector de Ciencia Abierta, RECOLECTADiposit Digital de Documents de la UABArticle . 2019License: CC BY NC NDData sources: Diposit Digital de Documents de la UABProceedings of the National Academy of SciencesArticle . 2019 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Tasmania: UTas ePrintsArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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=10.1073/pnas.1900194116&type=result"></script>'); --> </script>
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