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Research data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Authors: Diana Stralberg;Velocity-based macrorefugia for boreal passerine birds Citation for dataset -------------------- Stralberg, D. Velocity-based macrorefugia for boreal passerine birds. Boreal Avian Modelling Project. Edmonton, Alberta, Canada. DOI: 10.5281/zenodo.1299880 https://doi.org/10.5281/zenodo.1299880 Data layers ----------------- Refugia layers represent mid-century (2041-2070) and end-of-century (2071-2100) conditions for the SRES A2 emissions scenario at 4-km resolution ----------------- Combined index for 53 species (clipped to Brandt's boreal region): _refbrandt53_YYYYZZZZ Species-specific indices: XXXX_refYYYY where: YYYY = Time period (2050s or 2080s) ZZZZ = weighted or unweighted XXXX = Songbird Species Code (see Birdlookup.csv) Percentile values of refugia indices for mapping purposes 0.01 0.1 0.25 0.5 0.75 0.9 0.99 "2050s, weighted " 0.032 0.243 0.317 0.399 0.484 0.589 0.779 "2080s, weighted" 0.002 0.09 0.137 0.2 0.281 0.386 0.675 "2050s, unweighted" 0.006 0.108 0.159 0.218 0.292 0.358 0.421 "2080s, unweighted" 0.001 0.055 0.083 0.123 0.185 0.241 0.297 Projection information ------------------- """+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs""" ------------------- Projection LAMBERT Spheroid GRS80 Units METERS Zunits NO Xshift 0.0 Yshift 0.0 Parameters 49 0 0.0 /* 1st standard parallel 77 0 0.0 /* 2nd standard parallel -95 0 0.0 /* central meridian 0 0 0.0 /* latitude of projection's origin 0.0 /* false easting (meters) 0.0 /* false northing (meters)
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | HELIXEC| HELIXThiery, Wim; Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; Gudmundsson, Lukas; Seneviratne, Sonia I.; Andrijevic, Marina; Frieler, Katja; Emanuel, Kerry; Geiger, Tobias; Bresch, David N.; Zhao, Fang; Willner, Sven N.; Büchner, Matthias; Volkholz, Jan; Bauer, Nico; Chang, Jinfeng; Ciais, Philippe; Dury, Marie; François, Louis; Grillakis, Manolis; Gosling, Simon N.; Hanasaki, Naota; Hickler, Thomas; Huber, Veronika; Ito, Akihiko; Jägermeyr, Jonas; Khabarov, Nikolay; Koutroulis, Aristeidis; Liu, Wenfeng; Lutz, Wolfgang; Mengel, Matthias; Müller, Christoph; Ostberg, Sebastian; Reyer, Christopher P. O.; Stacke, Tobias; Wada, Yoshihide;This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.
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visibility 317visibility views 317 download downloads 197 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 2020Embargo end date: 01 Jul 2020 United StatesPublisher:Mountain Scholar Authors: Post, Alison; Knapp, Alan;handle: 10217/208775
Climate change is intensifying the hydrologic cycle globally, increasing both the size and frequency of extreme precipitation events, or deluges. Arid and semi-arid ecosystems are expected to be particularly responsive to this change because their ecological processes are largely driven by distinct soil moisture pulses. However, since soil moisture, air temperature, and plant phenology vary throughout the growing season, deluges will likely have differing impacts on these systems depending on when they occur. We conducted a field experiment to assess how the seasonal timing (early, middle, or late growing season) of a single deluge (70 mm precipitation event) altered key ecological processes in the semi-arid shortgrass steppe of North America. Regardless of timing, a single deluge stimulated most ecosystem processes, but a deluge at mid-season caused the greatest increase in soil respiration, canopy greenness, aboveground net primary production (ANPP), and growth and flowering of the dominant plant species (Bouteloua gracilis). In contrast, belowground net primary production (BNPP) was insensitive to deluge timing, with a consistent BNPP increase in all the deluge treatments that was almost twice as large as the ANPP response. This BNPP response was largely driven by enhanced root production at 10-20 cm, rather than 0-10 cm, soil depths. In a semi-arid ecosystem, a single deluge can have season-long impacts on many ecosystem processes, but responses can be mediated by event timing. Therefore, predicting responses of semi-arid ecosystems to more dynamic precipitation regimes, and subsequent impacts on the global carbon budget, will require knowledge of how deluge magnitude, frequency, and timing are being altered by climate change. These data are from an experimental field study that assessed the impact of deluge events and their timing on various ecological processes in the shortgrass steppe of Northeastern Colorado. The experiment period was the 2017 growing season (May - Sept). Included are the following datasets: Precipitation, air temperature, soil moisture, soil respiration, ANPP, BNPP, canopy greenness, plot species composition, B. gracilis leaf length, B. gracilis flowering, B. gracilis water potential.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Asner, Gregory P.; Sousan, Sinan; Knapp, David E.; Selmants, Paul C.; Martin, Roberta E.; Hughes, R. Flint; Giardina, Christian P.;Forest aboveground carbon density (ACD) for the main eight Hawaiian Islands in 2015-2016. The data are in 30 meter resolution format with the units of Mg C per hectare. The file is a standard GeoTIFF. Use of these data requires citation of this dataset plus citation of the source study as follows: Asner, G.P., S. Sousan, D.E. Knapp, P.C. Selmants, R.E. Martin, R.F. Hughes, and C.P. Giardina. 2016. Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago. Carbon Balance and Management 11, doi:10.1186/s13021-015-0043-4
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visibility 465visibility views 465 download downloads 36 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 2016Embargo end date: 03 Dec 2016Publisher:Dryad Petersen, John E.; Frantz, Cynthia M.; Shammin, M. Rumi; Yanisch, Tess M.; Tincknell, Evan; Myers, Noel;doi: 10.5061/dryad.82nc3
DataForAssessingSeasonalEffectsOnElectricityAndWaterForRepositoryThis Excel file contains data used to conduct a seasonal analysis to assess whether seasonal patterns exist in electricity use in dorms and whether these patterns differ by latitude. The first worksheet contains metadata.Fall 2010 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Fall 2010 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_F10_survey.pdfSpring 2012 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Spring 2012 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_Spring12_survey.pdfFall 10 Campus Conservation Nationals electricity, water, webhit, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Fall 2010 CCN competition. The first sheet contains metadata defining all variable names.Fall10_CCN_elec_water_webhits_commitments.xlsxSpring 2012 Campus Conservation Nationals electricity, water, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Spring 2012 CCN competition. The first sheet contains metadata defining all variable names.Spring12_CCN_elec_water_commitments_no.xlsxFall 10 CCN data aggregated at dorm level with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Fall10_CCN_dormagg_with_psych_variables.xlsxSpring 2012 CCN data with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Spring12__CCN_dormagg_with_psych_variables.xlsx “Campus Conservation Nationals” (CCN) is a recurring, nation-wide electricity and water-use reduction competition among dormitories on college campuses. We conducted a two year empirical study of the competition’s effects on resource consumption and the relationship between conservation, use of web technology and various psychological measures. Significant reductions in electricity and water use occurred during the two CCN competitions examined (n = 105,000 and 197,000 participating dorm residents respectively). In 2010, overall reductions during the competition were 4% for electricity and 6% for water. The top 10% of dorms achieved 28% and 36% reductions in electricity and water respectively. Participation was larger in 2012 and reductions were slightly smaller (i.e. 3% electricity). The fact that no seasonal pattern in electricity use was evident during non-competition periods suggests that results are attributable to the competition. Post competition resource use data collected in 2012 indicates that conservation behavior was sustained beyond the competition. Surveys were used to assess psychological and behavioral responses (n = 2,900 and 2,600 in 2010 and 2012 respectively). Electricity reductions were significantly correlated with: web visitation, specific conservation behaviors, awareness of the competition, motivation and sense of empowerment. However, participants were significantly more motivated than empowered. Perceived benefits of conservation were skewed towards global and future concerns while perceived barriers tended to be local. Results also suggest that competitions may be useful for “preaching beyond the choir” – engaging those who might lack prior intrinsic or political motivation. Although college life is distinct, certain conclusions related to competitions, self-efficacy, and motivation and social norms likely extend to other residential settings.
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visibility 48visibility views 48 download downloads 27 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 2022Publisher:SCAR - Microbial Antarctic Resource System Barret, Maialen; Thalasso, Frederic; Gandois, Laure; Cruz, Klara Martinez; Jaureguy, Armando Sepulveda; Lavergne, Céline; Teisserenc, Roman; Polette Aguilar; Gerardo-Nieto, Oscar; Etchebehere, Claudia; Martins, Bruna; Fochesatto, Javier; Tananaev, Nikita; Svenning, Mette; Seppey, Christophe; Tveit, Alexander; Chamy, Rolando; Astorga-España, Maria Soledad; Mansilla, Andres; Van De Putte, Anton; Sweetlove, Maxime; Murray, Alison; Cabrol, Léa;doi: 10.15468/hhkhz2
Methane emissions from aquatic and terrestrial ecosystems play a crucial role in global warming, which is particularly affecting high-latitude ecosystems. As major contributors to methane emissions in natural environments, the microbial communities involved in methane production and oxidation deserve a special attention. Microbial diversity and activity are expected to be strongly affected by the already observed (and further predicted) temperature increase in high-latitude ecosystems, eventually resulting in disrupted feedback methane emissions. The METHANOBASE project has been designed to investigate the intricate relations between microbial diversity and methane emissions in Arctic, Subarctic and Subantarctic ecosystems, under natural (baseline) conditions and in response to simulated temperature increments. We report here a small subunit ribosomal RNA (16S rRNA) analysis of lake, peatland and mineral soil ecosystems.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 Kazakhstan, United States, United Statesadd 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 2022Embargo end date: 08 Mar 2022Publisher:Dryad Authors: Campbell, Christina; Maro, Aleksey; Weaver, Victoria; Dudley, Robert;doi: 10.6078/d1m420
Ethanol within ripe and over-ripe fruit is produced naturally through the metabolic activity of fermentative yeasts. As a consequence, frugivorous animals may chronically consume ethanol as part of their routine diet, although direct measurements of such exposure are lacking. Here, we present data on ethanol concentrations within fruits of the Neotropical tree Spondias mombin (Anacardiaceae) that are eaten by Geoffroy's spider monkeys (Ateles geoffroyi) on Barro Colorado Island, Panama. Of collected fruits that were partially consumed and then dropped by foraging monkeys, pulp-ethanol content was typically in the range of 1–2%; the percentage of pulp for consumed fruits was not significantly correlated with ethanol concentration of the pulp remaining within each fruit. Urine samples from foraging spider monkeys were also evaluated for the ethanol metabolites ethyl glucuronide (EtG) and ethyl sulfate (EtS); five of six samples tested positive for both compounds. In aggregate, these data indicate natural exposure to fruit-associated ethanol in a wild primate species. The data provided here is for analysis of the Spondias mombin fruit ethanol data collected on the infrared spectrometer. See the README.txt file for further instructions. See the published literature associated with this data.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Figgener, Jan; Haberschusz, David; Wessels, Oliver; Kairies, Kai-Philipp; Bors, Jakob; van Ouwerkerk, Jonas; Sauer, Dirk Uwe;The dataset accompanies the Nature Energy publication by Figgener et al. (2024), Multi-year field measurements of home storage systems and their use in capacity estimation, DOI 10.1038/s41560-024-01620-9. In addition, we use the dataset in Figgener et al. (2024), Degradation mode estimation using reconstructed open circuit voltage curves from multi-year home storage field data, DOI 10.48550/arXiv.2411.08025 The ISEA / CARL of RWTH Aachen University measured 21 private home storage systems in Germany over up to eight years from 2015 to 2022. All these storage systems are combined with residential photovoltaic systems to increase self-consumption. The measured quantities published are system-level battery current, voltage, power, battery pack housing temperature, and room temperature. The sample rate is one second. The dataset consists of 106 system years, 14 billion data points, and 1,270 monthly files stored in 21 system folders. Use the data as follows:1. Download the data (Data_ID_01.zip to Data_ID_21.zip) and the belonging repository (Metadata_and_Code.zip) 2. Uncompress the files so that the uncompressed folders have the same name as the .zip files. 3. Copy all data folders in folder "Metadata_and_Code/00_Data/01_Operational_Data". Read and execute the file "StartUp_Read_and_Execute.m" and stay in this folder for any script you execute. In addition, a detailed description of the dataset and how to use it can be found in the supplementary information of the publication.
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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 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Horowitz, Larry W.; John, Jasmin G.; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; Rand, Kristopher; Vahlenkamp, Hans; Zadeh, Niki T.; Wilson, Chandin; Dunne, John P.; Ploshay, Jeffrey; Winton, Michael; Zeng, Yujin;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.DAMIP.NOAA-GFDL.GFDL-ESM4' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 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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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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Research data keyboard_double_arrow_right Dataset 2018Publisher:Zenodo Authors: Diana Stralberg;Velocity-based macrorefugia for boreal passerine birds Citation for dataset -------------------- Stralberg, D. Velocity-based macrorefugia for boreal passerine birds. Boreal Avian Modelling Project. Edmonton, Alberta, Canada. DOI: 10.5281/zenodo.1299880 https://doi.org/10.5281/zenodo.1299880 Data layers ----------------- Refugia layers represent mid-century (2041-2070) and end-of-century (2071-2100) conditions for the SRES A2 emissions scenario at 4-km resolution ----------------- Combined index for 53 species (clipped to Brandt's boreal region): _refbrandt53_YYYYZZZZ Species-specific indices: XXXX_refYYYY where: YYYY = Time period (2050s or 2080s) ZZZZ = weighted or unweighted XXXX = Songbird Species Code (see Birdlookup.csv) Percentile values of refugia indices for mapping purposes 0.01 0.1 0.25 0.5 0.75 0.9 0.99 "2050s, weighted " 0.032 0.243 0.317 0.399 0.484 0.589 0.779 "2080s, weighted" 0.002 0.09 0.137 0.2 0.281 0.386 0.675 "2050s, unweighted" 0.006 0.108 0.159 0.218 0.292 0.358 0.421 "2080s, unweighted" 0.001 0.055 0.083 0.123 0.185 0.241 0.297 Projection information ------------------- """+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs""" ------------------- Projection LAMBERT Spheroid GRS80 Units METERS Zunits NO Xshift 0.0 Yshift 0.0 Parameters 49 0 0.0 /* 1st standard parallel 77 0 0.0 /* 2nd standard parallel -95 0 0.0 /* central meridian 0 0 0.0 /* latitude of projection's origin 0.0 /* false easting (meters) 0.0 /* false northing (meters)
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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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visibility 485visibility views 485 download downloads 76 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 2021Publisher:Zenodo Funded by:EC | HELIXEC| HELIXThiery, Wim; Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; Gudmundsson, Lukas; Seneviratne, Sonia I.; Andrijevic, Marina; Frieler, Katja; Emanuel, Kerry; Geiger, Tobias; Bresch, David N.; Zhao, Fang; Willner, Sven N.; Büchner, Matthias; Volkholz, Jan; Bauer, Nico; Chang, Jinfeng; Ciais, Philippe; Dury, Marie; François, Louis; Grillakis, Manolis; Gosling, Simon N.; Hanasaki, Naota; Hickler, Thomas; Huber, Veronika; Ito, Akihiko; Jägermeyr, Jonas; Khabarov, Nikolay; Koutroulis, Aristeidis; Liu, Wenfeng; Lutz, Wolfgang; Mengel, Matthias; Müller, Christoph; Ostberg, Sebastian; Reyer, Christopher P. O.; Stacke, Tobias; Wada, Yoshihide;This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.
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visibility 317visibility views 317 download downloads 197 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 2020Embargo end date: 01 Jul 2020 United StatesPublisher:Mountain Scholar Authors: Post, Alison; Knapp, Alan;handle: 10217/208775
Climate change is intensifying the hydrologic cycle globally, increasing both the size and frequency of extreme precipitation events, or deluges. Arid and semi-arid ecosystems are expected to be particularly responsive to this change because their ecological processes are largely driven by distinct soil moisture pulses. However, since soil moisture, air temperature, and plant phenology vary throughout the growing season, deluges will likely have differing impacts on these systems depending on when they occur. We conducted a field experiment to assess how the seasonal timing (early, middle, or late growing season) of a single deluge (70 mm precipitation event) altered key ecological processes in the semi-arid shortgrass steppe of North America. Regardless of timing, a single deluge stimulated most ecosystem processes, but a deluge at mid-season caused the greatest increase in soil respiration, canopy greenness, aboveground net primary production (ANPP), and growth and flowering of the dominant plant species (Bouteloua gracilis). In contrast, belowground net primary production (BNPP) was insensitive to deluge timing, with a consistent BNPP increase in all the deluge treatments that was almost twice as large as the ANPP response. This BNPP response was largely driven by enhanced root production at 10-20 cm, rather than 0-10 cm, soil depths. In a semi-arid ecosystem, a single deluge can have season-long impacts on many ecosystem processes, but responses can be mediated by event timing. Therefore, predicting responses of semi-arid ecosystems to more dynamic precipitation regimes, and subsequent impacts on the global carbon budget, will require knowledge of how deluge magnitude, frequency, and timing are being altered by climate change. These data are from an experimental field study that assessed the impact of deluge events and their timing on various ecological processes in the shortgrass steppe of Northeastern Colorado. The experiment period was the 2017 growing season (May - Sept). Included are the following datasets: Precipitation, air temperature, soil moisture, soil respiration, ANPP, BNPP, canopy greenness, plot species composition, B. gracilis leaf length, B. gracilis flowering, B. gracilis water potential.
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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.
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=10.25675/10217/208775&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Asner, Gregory P.; Sousan, Sinan; Knapp, David E.; Selmants, Paul C.; Martin, Roberta E.; Hughes, R. Flint; Giardina, Christian P.;Forest aboveground carbon density (ACD) for the main eight Hawaiian Islands in 2015-2016. The data are in 30 meter resolution format with the units of Mg C per hectare. The file is a standard GeoTIFF. Use of these data requires citation of this dataset plus citation of the source study as follows: Asner, G.P., S. Sousan, D.E. Knapp, P.C. Selmants, R.E. Martin, R.F. Hughes, and C.P. Giardina. 2016. Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago. Carbon Balance and Management 11, doi:10.1186/s13021-015-0043-4
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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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visibility 465visibility views 465 download downloads 36 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 2016Embargo end date: 03 Dec 2016Publisher:Dryad Petersen, John E.; Frantz, Cynthia M.; Shammin, M. Rumi; Yanisch, Tess M.; Tincknell, Evan; Myers, Noel;doi: 10.5061/dryad.82nc3
DataForAssessingSeasonalEffectsOnElectricityAndWaterForRepositoryThis Excel file contains data used to conduct a seasonal analysis to assess whether seasonal patterns exist in electricity use in dorms and whether these patterns differ by latitude. The first worksheet contains metadata.Fall 2010 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Fall 2010 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_F10_survey.pdfSpring 2012 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Spring 2012 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_Spring12_survey.pdfFall 10 Campus Conservation Nationals electricity, water, webhit, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Fall 2010 CCN competition. The first sheet contains metadata defining all variable names.Fall10_CCN_elec_water_webhits_commitments.xlsxSpring 2012 Campus Conservation Nationals electricity, water, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Spring 2012 CCN competition. The first sheet contains metadata defining all variable names.Spring12_CCN_elec_water_commitments_no.xlsxFall 10 CCN data aggregated at dorm level with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Fall10_CCN_dormagg_with_psych_variables.xlsxSpring 2012 CCN data with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Spring12__CCN_dormagg_with_psych_variables.xlsx “Campus Conservation Nationals” (CCN) is a recurring, nation-wide electricity and water-use reduction competition among dormitories on college campuses. We conducted a two year empirical study of the competition’s effects on resource consumption and the relationship between conservation, use of web technology and various psychological measures. Significant reductions in electricity and water use occurred during the two CCN competitions examined (n = 105,000 and 197,000 participating dorm residents respectively). In 2010, overall reductions during the competition were 4% for electricity and 6% for water. The top 10% of dorms achieved 28% and 36% reductions in electricity and water respectively. Participation was larger in 2012 and reductions were slightly smaller (i.e. 3% electricity). The fact that no seasonal pattern in electricity use was evident during non-competition periods suggests that results are attributable to the competition. Post competition resource use data collected in 2012 indicates that conservation behavior was sustained beyond the competition. Surveys were used to assess psychological and behavioral responses (n = 2,900 and 2,600 in 2010 and 2012 respectively). Electricity reductions were significantly correlated with: web visitation, specific conservation behaviors, awareness of the competition, motivation and sense of empowerment. However, participants were significantly more motivated than empowered. Perceived benefits of conservation were skewed towards global and future concerns while perceived barriers tended to be local. Results also suggest that competitions may be useful for “preaching beyond the choir” – engaging those who might lack prior intrinsic or political motivation. Although college life is distinct, certain conclusions related to competitions, self-efficacy, and motivation and social norms likely extend to other residential settings.
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visibility 48visibility views 48 download downloads 27 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:SCAR - Microbial Antarctic Resource System Barret, Maialen; Thalasso, Frederic; Gandois, Laure; Cruz, Klara Martinez; Jaureguy, Armando Sepulveda; Lavergne, Céline; Teisserenc, Roman; Polette Aguilar; Gerardo-Nieto, Oscar; Etchebehere, Claudia; Martins, Bruna; Fochesatto, Javier; Tananaev, Nikita; Svenning, Mette; Seppey, Christophe; Tveit, Alexander; Chamy, Rolando; Astorga-España, Maria Soledad; Mansilla, Andres; Van De Putte, Anton; Sweetlove, Maxime; Murray, Alison; Cabrol, Léa;doi: 10.15468/hhkhz2
Methane emissions from aquatic and terrestrial ecosystems play a crucial role in global warming, which is particularly affecting high-latitude ecosystems. As major contributors to methane emissions in natural environments, the microbial communities involved in methane production and oxidation deserve a special attention. Microbial diversity and activity are expected to be strongly affected by the already observed (and further predicted) temperature increase in high-latitude ecosystems, eventually resulting in disrupted feedback methane emissions. The METHANOBASE project has been designed to investigate the intricate relations between microbial diversity and methane emissions in Arctic, Subarctic and Subantarctic ecosystems, under natural (baseline) conditions and in response to simulated temperature increments. We report here a small subunit ribosomal RNA (16S rRNA) analysis of lake, peatland and mineral soil ecosystems.
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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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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023 Kazakhstan, United States, United Statesadd 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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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: 08 Mar 2022Publisher:Dryad Authors: Campbell, Christina; Maro, Aleksey; Weaver, Victoria; Dudley, Robert;doi: 10.6078/d1m420
Ethanol within ripe and over-ripe fruit is produced naturally through the metabolic activity of fermentative yeasts. As a consequence, frugivorous animals may chronically consume ethanol as part of their routine diet, although direct measurements of such exposure are lacking. Here, we present data on ethanol concentrations within fruits of the Neotropical tree Spondias mombin (Anacardiaceae) that are eaten by Geoffroy's spider monkeys (Ateles geoffroyi) on Barro Colorado Island, Panama. Of collected fruits that were partially consumed and then dropped by foraging monkeys, pulp-ethanol content was typically in the range of 1–2%; the percentage of pulp for consumed fruits was not significantly correlated with ethanol concentration of the pulp remaining within each fruit. Urine samples from foraging spider monkeys were also evaluated for the ethanol metabolites ethyl glucuronide (EtG) and ethyl sulfate (EtS); five of six samples tested positive for both compounds. In aggregate, these data indicate natural exposure to fruit-associated ethanol in a wild primate species. The data provided here is for analysis of the Spondias mombin fruit ethanol data collected on the infrared spectrometer. See the README.txt file for further instructions. See the published literature associated with this data.
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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 2024Publisher:Zenodo Figgener, Jan; Haberschusz, David; Wessels, Oliver; Kairies, Kai-Philipp; Bors, Jakob; van Ouwerkerk, Jonas; Sauer, Dirk Uwe;The dataset accompanies the Nature Energy publication by Figgener et al. (2024), Multi-year field measurements of home storage systems and their use in capacity estimation, DOI 10.1038/s41560-024-01620-9. In addition, we use the dataset in Figgener et al. (2024), Degradation mode estimation using reconstructed open circuit voltage curves from multi-year home storage field data, DOI 10.48550/arXiv.2411.08025 The ISEA / CARL of RWTH Aachen University measured 21 private home storage systems in Germany over up to eight years from 2015 to 2022. All these storage systems are combined with residential photovoltaic systems to increase self-consumption. The measured quantities published are system-level battery current, voltage, power, battery pack housing temperature, and room temperature. The sample rate is one second. The dataset consists of 106 system years, 14 billion data points, and 1,270 monthly files stored in 21 system folders. Use the data as follows:1. Download the data (Data_ID_01.zip to Data_ID_21.zip) and the belonging repository (Metadata_and_Code.zip) 2. Uncompress the files so that the uncompressed folders have the same name as the .zip files. 3. Copy all data folders in folder "Metadata_and_Code/00_Data/01_Operational_Data". Read and execute the file "StartUp_Read_and_Execute.m" and stay in this folder for any script you execute. In addition, a detailed description of the dataset and how to use it can be found in the supplementary information of the publication.
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=10.5281/zenodo.12091223&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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=10.5281/zenodo.12091223&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 Horowitz, Larry W.; John, Jasmin G.; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; Rand, Kristopher; Vahlenkamp, Hans; Zadeh, Niki T.; Wilson, Chandin; Dunne, John P.; Ploshay, Jeffrey; Winton, Michael; Zeng, Yujin;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.DAMIP.NOAA-GFDL.GFDL-ESM4' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.
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=10.26050/wdcc/ar6.c6danggfd&type=result"></script>'); --> </script>
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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.
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.c6danggfd&type=result"></script>'); --> </script>
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