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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Yukimoto, Seiji;Koshiro, Tsuyoshi;
Kawai, Hideaki;Koshiro, Tsuyoshi
Koshiro, Tsuyoshi in OpenAIREOshima, Naga;
+12 AuthorsOshima, Naga
Oshima, Naga in OpenAIREYukimoto, Seiji;Koshiro, Tsuyoshi;
Kawai, Hideaki;Koshiro, Tsuyoshi
Koshiro, Tsuyoshi in OpenAIREOshima, Naga;
Yoshida, Kohei; Urakawa, Shogo;Oshima, Naga
Oshima, Naga in OpenAIRETsujino, Hiroyuki;
Tsujino, Hiroyuki
Tsujino, Hiroyuki in OpenAIREDeushi, Makoto;
Tanaka, Taichu; Hosaka, Masahiro; Yoshimura, Hiromasa; Shindo, Eiki; Mizuta, Ryo; Ishii, Masayoshi; Obata, Atsushi; Adachi, Yukimasa;Deushi, Makoto
Deushi, Makoto 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.C4MIP.MRI.MRI-ESM2-0.hist-bgc' 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 MRI-ESM2.0 climate model, released in 2017, includes the following components: aerosol: MASINGAR mk2r4 (TL95; 192 x 96 longitude/latitude; 80 levels; top level 0.01 hPa), atmos: MRI-AGCM3.5 (TL159; 320 x 160 longitude/latitude; 80 levels; top level 0.01 hPa), atmosChem: MRI-CCM2.1 (T42; 128 x 64 longitude/latitude; 80 levels; top level 0.01 hPa), land: HAL 1.0, ocean: MRI.COM4.4 (tripolar primarily 0.5 deg latitude/1 deg longitude with meridional refinement down to 0.3 deg within 10 degrees north and south of the equator; 360 x 364 longitude/latitude; 61 levels; top grid cell 0-2 m), ocnBgchem: MRI.COM4.4, seaIce: MRI.COM4.4. The model was run by the Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan (MRI) in native nominal resolutions: aerosol: 250 km, atmos: 100 km, atmosChem: 250 km, land: 100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Embargo end date: 13 Jul 2018Publisher:Mendeley Authors: Speakman, J;This experiment was to assess the impact of dietary macro-nutrient composition on body weight of the mouse. In total we used 30 different diets and 5 different strains of mice. This file contains the individual data of the food intake averaged over the last 10 days and food intake of entire 3 months, body composition and metabolic responses of male C57BL/6 mice to 3 months feeding on one of 6 different diets. Ten mice were exposed to each diet. The diets had variable sucrose from 5 to 30% and fixed protein content at 25% and fat content at 41.7% (diets 22, diet 25 to 29). Full details of the dietary compositions can be found in the paper supplementary table 1. Complete meta-data are in the meta-data tab of the file. Means for each diet derived from these individual values are presented in Figure S5 of Hu et al (2018) Cell metabolism.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:PANGAEA Authors:Zweifel, Roman;
Sterck, Frank J;Zweifel, Roman
Zweifel, Roman in OpenAIREBraun, Sabine;
Braun, Sabine
Braun, Sabine in OpenAIREBuchmann, Nina;
+8 AuthorsBuchmann, Nina
Buchmann, Nina in OpenAIREZweifel, Roman;
Sterck, Frank J;Zweifel, Roman
Zweifel, Roman in OpenAIREBraun, Sabine;
Braun, Sabine
Braun, Sabine in OpenAIREBuchmann, Nina;
Buchmann, Nina
Buchmann, Nina in OpenAIREEugster, Werner;
Eugster, Werner
Eugster, Werner in OpenAIREGessler, Arthur;
Gessler, Arthur
Gessler, Arthur in OpenAIREHaeni, Matthias;
Haeni, Matthias
Haeni, Matthias in OpenAIREPeters, Richard L;
Peters, Richard L
Peters, Richard L in OpenAIREWalthert, Lorenz;
Walthert, Lorenz
Walthert, Lorenz in OpenAIREWilhelm, Micah;
Ziemínska, Kasia;Wilhelm, Micah
Wilhelm, Micah in OpenAIREEtzold, Sophia;
Etzold, Sophia
Etzold, Sophia in OpenAIREThe timing of diel stem growth of mature forest trees is still largely unknown, as empirical data with high temporal resolution have not been available so far. Consequently, the effects of day-night conditions on tree growth remained uncertain. Here we present the first comprehensive field study of hourly-resolved radial stem growth of seven temperate tree species, based on 57 million underlying data points over a period of up to 8 years. We show that trees grow mainly at night, with a peak after midnight, when the vapour pressure deficit (VPD) is among the lowest. A high VPD strictly limits radial stem growth and allows little growth during daylight hours, except in the early morning. Surprisingly, trees also grow in moderately dry soil when the VPD is low. Species-specific differences in diel growth dynamics show that species able to grow earlier during the night are associated with the highest number of hours with growth per year and the largest annual growth increment. We conclude that species with the ability to overcome daily water deficits faster have greater growth potential. Furthermore, we conclude that growth is more sensitive than carbon uptake to dry air, as growth stops before stomata are known to close.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 28 Apr 2023Publisher:Dryad The ecological impacts of multiple stressors are hard to predict but important to understand. When multiple stressors influence foundation species, the effects can cascade throughout the ecosystem. Gulf of Mexico seagrass ecosystems are currently experiencing a suite of novel stressors, including warmer water temperatures and increased herbivory due to tropicalization and conservation efforts. We investigated the impact of warming temperatures and grazing history on plant performance, morphology, and palatability by integrating a mesocosm study using the seagrass Thalassia testudinum with feeding trials using the sea urchin Lytechinus variegatus. Warming temperatures negatively impacted T. testudinum tolerance traits, reducing belowground biomass by 34%, productivity by 74%, shoot density by 10%, and the number of leaves per plant by 24%, and negatively impacted resistance traits through 13% lower toughness of young leaves and a trend for reduced leaf carbon:nitrogen. Lytechinus variegatus individuals preferred to consume plants grown under heated conditions, which supports findings of enhanced palatability. Simulated turtle grazing impacted more plant traits than grazing by other herbivores, potentially diminishing plant resilience to future disturbances through reduced rhizome non-structural carbohydrate concentrations and increasing palatability through reduced fiber content and 23% lower leaf carbon:phosphorus. Simulated turtle, simulated parrotfish, and urchin grazing reduced leaf carbon:nitrogen by 11%, also potentially increasing nutritive value. Interactions between warming temperatures and grazers on plant traits were additive for 16 out of 19 response variables. However, the stressors non-additively impacted the number of leaves per plant, fiber content, and epiphyte load. We suggest that the impacts of grazers on leaf turnover rate and leaf age may vary based on water temperature, potentially driving these interactions. Overall, increased temperatures and grazing pressure will likely reduce seagrass resilience, structure, and biomass, potentially impacting feedback systems and producing negative consequences for seagrass cover, associated species, and ecosystem services.
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visibility 2visibility views 2 download downloads 39 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:Science Data Bank Authors: Shuai ZHANG;Climate trends during maize growing period and their impacts on spring maize yield in North China was investigated. This dataset contains: 1) information of stations in cultivation region for spring maize in North China; 2) Trend in temperature and its effect on yield in cultivation region for spring maize in North China; 3) Trend in radiation and its effect on yield in cultivation region for spring maize in North China; 4) Trend in precipitation and its effect on yield in cultivation region for spring maize in North China. Climate trends during maize growing period and their impacts on spring maize yield in North China was investigated. This dataset contains: 1) information of stations in cultivation region for spring maize in North China; 2) Trend in temperature and its effect on yield in cultivation region for spring maize in North China; 3) Trend in radiation and its effect on yield in cultivation region for spring maize in North China; 4) Trend in precipitation and its effect on yield in cultivation region for spring maize in North China.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Authors:Minx, Jan C.;
Minx, Jan C.
Minx, Jan C. in OpenAIRELamb, William F.;
Lamb, William F.
Lamb, William F. in OpenAIREAndrew, Robbie M.;
Andrew, Robbie M.
Andrew, Robbie M. in OpenAIRECanadell, Josep G.;
+13 AuthorsCanadell, Josep G.
Canadell, Josep G. in OpenAIREMinx, Jan C.;
Minx, Jan C.
Minx, Jan C. in OpenAIRELamb, William F.;
Lamb, William F.
Lamb, William F. in OpenAIREAndrew, Robbie M.;
Andrew, Robbie M.
Andrew, Robbie M. in OpenAIRECanadell, Josep G.;
Crippa, Monica;Canadell, Josep G.
Canadell, Josep G. in OpenAIREDöbbeling, Niklas;
Döbbeling, Niklas
Döbbeling, Niklas in OpenAIREForster, Piers;
Guizzardi, Diego;Forster, Piers
Forster, Piers in OpenAIREOlivier, Jos;
Olivier, Jos
Olivier, Jos in OpenAIREPongratz, Julia;
Pongratz, Julia
Pongratz, Julia in OpenAIREReisinger, Andy;
Reisinger, Andy
Reisinger, Andy in OpenAIRERigby, Matthew;
Rigby, Matthew
Rigby, Matthew in OpenAIREPeters, Glen;
Peters, Glen
Peters, Glen in OpenAIRESaunois, Marielle;
Saunois, Marielle
Saunois, Marielle in OpenAIRESmith, Steven J.;
Smith, Steven J.
Smith, Steven J. in OpenAIRESolazzo, Efisio;
Solazzo, Efisio
Solazzo, Efisio in OpenAIRETian, Hanqin;
Tian, Hanqin
Tian, Hanqin in OpenAIREComprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.
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visibility 3Kvisibility views 3,130 download downloads 1,221 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare Authors:Pati, Pranab Kumar;
Kaushik, Priya; Khan, M.L.; Khare, P.K.;Pati, Pranab Kumar
Pati, Pranab Kumar in OpenAIREWood specific gravity (WSG) is an important component in biomass estimation through non-destructive allometric approach. However, a number of factors like climatic condition, soil, disturbance, management practice, geographic location etc. have huge impact on WSG variation. The present data set provides a collective WSG data for different species (333) consisting of 711 individuals procured from already published research paper for 11 forest groups of India occurring in different climatic and edaphic conditions. It also includes WSG data of a number of juvenile tree species for tropical dry deciduous forest. A number of studies in India have not considered WSG value in biomass estimation of juvenile trees. However, previous reports of Chaturvedi et al. (2012) suggested that the use of WSG in biomass estimation provide better result than using only the diameter and height as variables. It also includes samples/ species column for getting information about the number of samples considered for WSG determination. Especially this data set will be helpful to get WSG data on the basis of similar climatic condition, forest group according to the need of the future studies and this may minimize the source of WSG variation which would ultimately minimize variation in biomass and carbon estimation. It will also help to provide WSG data for allometric model development. Also it will be help to study the physical property (strength) of wood. Further, use of this database will save the time of workers as it is easily assessable and it provides WSG value of a number of species at one place.
figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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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more_vert figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 07 Dec 2022Publisher:Dryad Authors:Shao, Junjiong;
Zhou, Xuhui; van Groenigen, Kees; Zhou, Guiyao; +9 AuthorsShao, Junjiong
Shao, Junjiong in OpenAIREShao, Junjiong;
Zhou, Xuhui; van Groenigen, Kees; Zhou, Guiyao; Zhou, Huimin; Zhou, Lingyan; Lu, Meng; Xia, Jianyang; Jiang, Lin; Hungate, Bruce; Luo, Yiqi; He, Fangliang; Thakur, Madhav;Shao, Junjiong
Shao, Junjiong in OpenAIREAim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.
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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=10.5061/dryad.gtht76hms&type=result"></script>'); --> </script>
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visibility 14visibility views 14 download downloads 1 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:figshare This repository contains spatial data and metadata for the research article: Thieme M.L. et al. (2021). Navigating trade-offs between dams and river conservation. Global Sustainability 4, e17, 1–7. https://doi.org/10.1017/sus.2021.15
figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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=10.6084/m9.figshare.14977305&type=result"></script>'); --> </script>
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more_vert figshare arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData 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.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: Voldoire, Aurore;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.HighResMIP.CNRM-CERFACS.CNRM-CM6-1-HR' 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 CNRM-CM6-1-HR climate model, released in 2017, includes the following components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T359; Gaussian Reduced with 181724 grid points in total distributed over 360 latitude circles (with 720 grid points per latitude circle between 32.2degN and 32.2degS reducing to 18 grid points per latitude circle at 89.6degN and 89.6degS); 91 levels; top level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA025, tripolar primarily 1/4deg; 1442 x 1050 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 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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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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