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Research data keyboard_double_arrow_right Dataset 2020Publisher:Zenodo Funded by:EC | TotalControlEC| TotalControlAuthors:Sood, Ishaan;
Sood, Ishaan
Sood, Ishaan in OpenAIREMeyers, Johan;
Meyers, Johan
Meyers, Johan in OpenAIREDataset for TotalControl reference windfarm database simulation of a pressure-driven high Reynolds number boundary layer flow with 0 degree inflow wind direction angle (Casename PDk 0) Included Python files for loading and visualizing the data. Use the plot_*.py files. Further information, including description of the case and dataset can be found in the deliverable report at: https://cordis.europa.eu/project/id/727680/results "Database for reference wind farms part 2: windfarm simulations"
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2015Embargo end date: 19 Nov 2015Publisher:Dryad Dinh, Khuong Van; Janssens, Lizanne; Therry, Lieven; Gyulavári, Hajnalka Anna; Bervoets, Lieven; Stoks, Robby;doi: 10.5061/dryad.cb978
Many species are too slow to track their poleward moving climate niche under global warming. Pesticide exposure may contribute to this by reducing population growth and impairing flight ability. Moreover, edge populations at the moving range front may be more vulnerable to pesticides because of the rapid evolution of traits to enhance their rate of spread that shunt energy away from detoxification and repair. We exposed replicated edge and core populations of the poleward moving damselfly Coenagrion scitulum to the pesticide esfenvalerate at low and high densities. Exposure to esfenvalerate had strong negative effects on survival, growth rate and development time in the larval stage and negatively affected flight-related adult traits (mass at emergence, flight muscle mass and fat content) across metamorphosis. Pesticide effects did not differ between edge and core populations, except that at the high concentration the pesticide-induced mortality was 17% stronger in edge populations. Pesticide exposure may therefore slow down the range expansion by lowering population growth rates, especially because edge populations suffered a higher mortality, and by negatively affecting dispersal ability by impairing flight-related traits. These results emphasize the need for direct conservation efforts toward leading-edge populations for facilitating future range shifts under global warming. MAIN DATAEVA-2015-167-OA DATA.xlsSUPPLEMENTARY DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS)EVA-2015-167-OA DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS).xls
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visibility 13visibility views 13 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:Zenodo Funded by:EC | MPC-. GTEC| MPC-. GTAuthors:Bastero, Josué Borrajo;
Figueroa, Iago Cupeiro; Picard, Damien; Helsen, Lieve; +1 AuthorsBastero, Josué Borrajo
Bastero, Josué Borrajo in OpenAIREBastero, Josué Borrajo;
Figueroa, Iago Cupeiro; Picard, Damien; Helsen, Lieve; Laverge, Jelle;Bastero, Josué Borrajo
Bastero, Josué Borrajo in OpenAIREThe dataset consists of the building energy simulation data for three case-study buildings (Infrax office building (BE); Ter Potterie elderly home (BE) and Haus M multi-family building (CH)). For these buildings, HVAC-concepts were simulated: the hybridGEOTABS-MPC concept (not for Haus M), hybridGEOTABS-RBC baseline concept and nonGEOTABS-RBC concept. The dataset includes the hourly time series for a one year simulation for the major outputs of the BES-model. The results are reported in hybridGEOTABS deliverable D4.9. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 723649
ZENODO 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 ZENODO 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 2020Embargo end date: 12 Nov 2020Publisher:Dryad Funded by:NSF | BE/CNH: Complex Ecosystem..., NSF | Webs on the Web: Internet..., NSF | CNH: Socio-Ecosystem Dyna... +2 projectsNSF| BE/CNH: Complex Ecosystem Interactions Over Multiple Spatial and Temporal Scales: The Biocomplexity of Sanak Island ,NSF| Webs on the Web: Internet Database, Analysis, and Visualization of Ecological Networks ,NSF| CNH: Socio-Ecosystem Dynamics of Human-Natural Networks on Model Islands ,CO| MAINTENANCE AND RESILIENCE OF FOUNDATIONAL SPECIES TO CLIMATE FLUCTUATIONS: ROLE OF "SUPPORTING" SPECIES INTERACTIONS ,NSF| Semantic Web Informatics for Species in Space and TimeAuthors:Shaw, Jack;
Coco, Emily;Shaw, Jack
Shaw, Jack in OpenAIREWootton, Kate;
Wootton, Kate
Wootton, Kate in OpenAIREDaems, Dries;
+3 AuthorsDaems, Dries
Daems, Dries in OpenAIREShaw, Jack;
Coco, Emily;Shaw, Jack
Shaw, Jack in OpenAIREWootton, Kate;
Wootton, Kate
Wootton, Kate in OpenAIREDaems, Dries;
Daems, Dries
Daems, Dries in OpenAIREGillreath-Brown, Andrew;
Swain, Anshuman;Gillreath-Brown, Andrew
Gillreath-Brown, Andrew in OpenAIREDunne, Jennifer;
Dunne, Jennifer
Dunne, Jennifer in OpenAIREAnalyses of ancient food webs reveal important paleoecological processes and responses to a range of perturbations throughout Earth’s history, such as climate change. These responses can inform our forecasts of future biotic responses to similar perturbations. However, previous analyses of ancient food webs rarely accounted for key differences between modern and ancient community data, particularly selective loss of soft-bodied taxa during fossilization. To consider how fossilization impacts inferences of ancient community structure we (1) analyzed node-level attributes to identify correlations between ecological roles and fossilization potential and (2) applied selective information loss procedures to food web data for extant systems. We found that selective loss of soft-bodied organisms has predictable effects on the trophic structure of “artificially fossilized” food webs, because these organisms occupy unique, consistent food web positions. Fossilized food webs misleadingly appear less stable (i.e., more prone to trophic cascades), with less predation and an overrepresentation of generalist consumers. We also found that ecological differences between soft- and hard-bodied taxa—indicated by distinct positions in modern food webs—are recorded in an Early Eocene web, but not in Cambrian webs. This suggests that ecological differences between the groups have existed for ≥ 48 million years. Our results indicate that accounting for soft-bodied taxa is vital for accurate depictions of ancient food webs. However, the consistency of information loss trends across the analyzed food webs means it is possible to predict how the selective loss of soft-bodied taxa affects food web metrics, which can permit better modeling of ancient communities. Repository Contents: Supplementary Information: Containing Supplementary Text, Figures, Tables, and Data descriptions. Supplementary Data 1: Food web data (adjacency matrices and metadata; see publication; see Related Works). Supplementary Data 2: Additional references consulted for preservation group assignments. Supplementary Data 3: Data and R scripts to recreate analyses from this study. S3_AllWebTaxonomy_updated_200903.csv: Taxonomy data for all food web nodes. S3_AnalysisOfTaxonomicRanks.csv: Lowest taxonomic rank for each node. S3_MainFigures_CaimanComparison.R: Compare the three food webs contained in (Roopnarine and Hertog 2013). S3_MainFigures_ComparisonFunctions.R: Functions for calculating metrics and generating trophic species webs. S3_MainFigures_FossilizationFunctions.R: Functions for artificially fossilizing networks. S3_MainFigures_Setup_200826.R: Setup to import food webs. S3_MainFigures_Code.R: Code to apply functions. S3_pbdb_data_200504.csv: Data from the Paleobiology Database, excluding Lagerstätten (see publication). S3_PresGrAssignments_updated_200902.csv: Preservation group assignments for all nodes. Fossil faunal lists were downloaded from the PBDB on 17th January 2020. Any data processing steps are shown in R Scripts and described in publication. Paleobiology Database is licensed under a CC BY 4.0 International License. https://creativecommons.org/licenses/by/4.0/. We analyzed food webs for four modern marine systems, one modern freshwater system, two ancient marine systems, and one ancient lake system from previous publications. All webs have similar, broad higher-rank taxonomic compositions and contain at least 85 nodes (the size of the smallest ancient network considered). For comparisons with ancient diversity, we downloaded fossil occurrences from the Paleobiology Database (PBDB) on 17th January 2020.
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visibility 30visibility views 30 download downloads 175 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 | SmartCulTourEC| SmartCulTourThe datasets present collected data through resident surveys on the perceptions on tourism development and the state of cultural heritage, as part of the Horizon 2020 funded project SmartCulTour (www.smartcultour.eu). The data is collected on individual respondent level for Local Administrative Units (LAUs) for the following municipalities/cities: Spain: Huesca, Graus, Benasque, Barbastro, Ainsa, Jaca, Sariñena the Netherlands: Rotterdam, Dordrecht, Molenlanden, Ridderkerk, Zwijndrecht, Barendrecht, Delft Belgium: Dendermonde, Puurs-Sint-Amands, Bornem, Berlare, Aalst, Denderleeuw, Willebroek Croatia: Split, Trogir, Kaštela, Solin, Sinj, Dugopolje, Klis Finland: Utsjoki Italy: Vicenza, Caldogno, Grumolo, Pojana Maggiore, Lonigo, Montagnana The data is presented as cross-sectional data and available for the following year: 2020. Please consult the metadata on each dataset for an overview of collected indicators and units of measurement.
ZENODO 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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visibility 83visibility views 83 download downloads 74 Powered bymore_vert ZENODO 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 2019Publisher:Zenodo Funded by:EC | AWESCOEC| AWESCOAuthors:Haas, Thomas;
Haas, Thomas
Haas, Thomas in OpenAIREMeyers, Johan;
Meyers, Johan
Meyers, Johan in OpenAIREAWESCO Wind Field Datasets The present datasets contain time-resolved three-dimensional wind field data computed by means of large-eddy simulations. The atmospheric boundary layer is modelled as pressure driven boundary layer (PDBL) and the computations are performed using the software SPWind developed at KU Leuven. Wind field data is provided for three different roughness classes corresponding to offshore and onshore conditions. For each roughness class, 45 minutes of wind data, sampled every second, is available and stored in HDF5 format for time series of 15 minutes. The file size is approximately 10GB. The data can be accessed using processing scripts provided for both Python and MATLAB. For more information, please read the provided documentation.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:Zenodo Funded by:EC | MPC-. GTEC| MPC-. GTAuthors: Anne Caminade; Marc Stöckli; Jan Hoogmartens; Damien Picard;A set of hydraulic schemes for hybridGEOTABS concepts suitable for various EU climates and system operation modes. These schemes provide additional guidance for HVAC designers during feasibility and mostly pre-design stage. They enable the HVAC engineer to consider the hydraulic connection between the basic hybridGEOTABS concept modules and auxiliary equipment required to implement the concept. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 723649
ZENODO arrow_drop_down Smithsonian figshareDataset . 2020License: 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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more_vert ZENODO arrow_drop_down Smithsonian figshareDataset . 2020License: 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 2020Publisher:Zenodo Funded by:EC | RIBuildEC| RIBuildAuthors:Morelli, M.;
Morelli, M.
Morelli, M. in OpenAIREBlumberga, A.;
Veidenbergs, I.;Blumberga, A.
Blumberga, A. in OpenAIREBlumberga, D.;
+13 AuthorsBlumberga, D.
Blumberga, D. in OpenAIREMorelli, M.;
Morelli, M.
Morelli, M. in OpenAIREBlumberga, A.;
Veidenbergs, I.;Blumberga, A.
Blumberga, A. in OpenAIREBlumberga, D.;
Blumberga, D.
Blumberga, D. in OpenAIREGrāvelsiņš, A.;
Conrad, C.; Sönchen, A.;Grāvelsiņš, A.
Grāvelsiņš, A. in OpenAIREFreudenberg, P.;
Deurinck, M.;Freudenberg, P.
Freudenberg, P. in OpenAIRED'Orazio, M.;
D'Orazio, M.
D'Orazio, M. in OpenAIREQuagliarini, E.;
Quagliarini, E.
Quagliarini, E. in OpenAIREDi Perna, C.;
Di Perna, C.
Di Perna, C. in OpenAIREDi Giuseppe, E.;
Di Giuseppe, E.
Di Giuseppe, E. in OpenAIREHansen, T.K.;
Ståhl, F.;Hansen, T.K.
Hansen, T.K. in OpenAIRELasvaux, S.;
Lasvaux, S.
Lasvaux, S. in OpenAIREPadey, P.;
Padey, P.
Padey, P. in OpenAIREDatabase prepared in Excel including four elements, as background information for RIBuild Deliverable D1.1 about the historic building stock: Historic buildings stock energy consumption (1) Historic building stock description (2) Building construction elements (3) Case studies (4) Element (1)-(3) are referring to the historic building stock in RIBuild partner countries in general, while element (4) contains examples of carried out renovation projects, involving internal insulation of a historic building. If available, the case study sheets contain information about the floor area, present use, the building envelope (thickness, materials), renovation history, pre- and post-energy usage and renovation cost. Further, information about typical defects and the main driving forces for the renovation project, planning or design tools used, whether the goal with the renovation was achieved and the satisfaction of the users. Overview of data files to be found in 'RIBuild data WP1' as part of this dataset.
ZENODO arrow_drop_down Smithsonian figshareDataset . 2020License: 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 ZENODO arrow_drop_down Smithsonian figshareDataset . 2020License: 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.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2015Publisher:Elsevier BV Authors:Guido Pepermans;
Guido Pepermans
Guido Pepermans in OpenAIREFrank Verboven;
Frank Verboven;Frank Verboven
Frank Verboven in OpenAIREOlivier De Groote;
+1 AuthorsOlivier De Groote
Olivier De Groote in OpenAIREGuido Pepermans;
Guido Pepermans
Guido Pepermans in OpenAIREFrank Verboven;
Frank Verboven;Frank Verboven
Frank Verboven in OpenAIREOlivier De Groote;
Olivier De Groote;Olivier De Groote
Olivier De Groote in OpenAIREWe study the determinants of PV adoption in the region of Flanders (Belgium), where PV adoption reached high levels during 2006-2012, because of active government intervention. Based on a unique dataset at a very detailed spatial level, we estimate a Poisson model to explain the heterogeneity in adoption rates. We obtain the following findings. First, local policies have a robust and significant impact on PV adoption, providing indirect evidence that the larger regional incentives formed the basis for the strong development of PV adoption in the region. Second, there is a strong unconditional income effect, implying a Matthew effect in the subsidization of PVs. Our third finding is however that this income effect is largely driven by the fact that wealthier households are more likely to adopt because they tend to be larger (and hence higher users), are more frequent house owners (who capture more of the benefits), or own houses that are better suited for PV. We can thus identify the channels through which wealthier households are more likely to benefit from the PV support. Finally, we identify the importance of several housing characteristics: PV adoption tends to be more likely in larger and in more recently built houses. In several extensions, we consider the determinants of the average size of installed PVs, and the differential impact of certain variables over time.
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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 RoutesGreen bronze 121 citations 121 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2024Publisher:American Association for the Advancement of Science (AAAS) Authors:Madalina Vlasceanu;
Madalina Vlasceanu
Madalina Vlasceanu in OpenAIREKimberly C. Doell;
Kimberly C. Doell
Kimberly C. Doell in OpenAIREJoseph B. Bak-Coleman;
Joseph B. Bak-Coleman
Joseph B. Bak-Coleman in OpenAIREBoryana Todorova;
+196 AuthorsBoryana Todorova
Boryana Todorova in OpenAIREMadalina Vlasceanu;
Madalina Vlasceanu
Madalina Vlasceanu in OpenAIREKimberly C. Doell;
Kimberly C. Doell
Kimberly C. Doell in OpenAIREJoseph B. Bak-Coleman;
Joseph B. Bak-Coleman
Joseph B. Bak-Coleman in OpenAIREBoryana Todorova;
Michael M. Berkebile-Weinberg;Boryana Todorova
Boryana Todorova in OpenAIRESamantha J. Grayson;
Samantha J. Grayson
Samantha J. Grayson in OpenAIREYash Patel;
Yash Patel
Yash Patel in OpenAIREDanielle Goldwert;
Yifei Pei; Alek Chakroff;Danielle Goldwert
Danielle Goldwert in OpenAIREEkaterina Pronizius;
Karlijn L. van den Broek;Ekaterina Pronizius
Ekaterina Pronizius in OpenAIREDenisa Vlasceanu;
Denisa Vlasceanu
Denisa Vlasceanu in OpenAIRESara Constantino;
Sara Constantino
Sara Constantino in OpenAIREMichael J. Morais;
Michael J. Morais
Michael J. Morais in OpenAIREPhilipp Schumann;
Steve Rathje;Philipp Schumann
Philipp Schumann in OpenAIREKe Fang;
Salvatore Maria Aglioti;
Salvatore Maria Aglioti
Salvatore Maria Aglioti in OpenAIREMark Alfano;
Mark Alfano
Mark Alfano in OpenAIREAndy J. Alvarado-Yepez;
Andy J. Alvarado-Yepez
Andy J. Alvarado-Yepez in OpenAIREAngélica Andersen;
Angélica Andersen
Angélica Andersen in OpenAIREFrederik Anseel;
Frederik Anseel
Frederik Anseel in OpenAIREMatthew A. J. Apps;
Matthew A. J. Apps
Matthew A. J. Apps in OpenAIREChillar Asadli;
Fonda Jane Awuor;Chillar Asadli
Chillar Asadli in OpenAIREFlavio Azevedo;
Piero Basaglia;Flavio Azevedo
Flavio Azevedo in OpenAIREJocelyn J. Bélanger;
Jocelyn J. Bélanger
Jocelyn J. Bélanger in OpenAIRESebastian Berger;
Sebastian Berger
Sebastian Berger in OpenAIREPaul Bertin;
Paul Bertin
Paul Bertin in OpenAIREMichał Białek;
Michał Białek
Michał Białek in OpenAIREOlga Bialobrzeska;
Olga Bialobrzeska
Olga Bialobrzeska in OpenAIREMichelle Blaya-Burgo;
Michelle Blaya-Burgo
Michelle Blaya-Burgo in OpenAIREDaniëlle N. M. Bleize;
Daniëlle N. M. Bleize
Daniëlle N. M. Bleize in OpenAIRESimen Bø;
Simen Bø
Simen Bø in OpenAIRELea Boecker;
Lea Boecker
Lea Boecker in OpenAIREPaulo S. Boggio;
Paulo S. Boggio
Paulo S. Boggio in OpenAIRESylvie Borau;
Sylvie Borau
Sylvie Borau in OpenAIREBjörn Bos;
Björn Bos
Björn Bos in OpenAIREAyoub Bouguettaya;
Ayoub Bouguettaya
Ayoub Bouguettaya in OpenAIREMarkus Brauer;
Markus Brauer
Markus Brauer in OpenAIRECameron Brick;
Cameron Brick
Cameron Brick in OpenAIRETymofii Brik;
Tymofii Brik
Tymofii Brik in OpenAIRERoman Briker;
Roman Briker
Roman Briker in OpenAIRETobias Brosch;
Tobias Brosch
Tobias Brosch in OpenAIREOndrej Buchel;
Ondrej Buchel
Ondrej Buchel in OpenAIREDaniel Buonauro;
Daniel Buonauro
Daniel Buonauro in OpenAIRERadhika Butalia;
Radhika Butalia
Radhika Butalia in OpenAIREHéctor Carvacho;
Héctor Carvacho
Héctor Carvacho in OpenAIRESarah A. E. Chamberlain;
Sarah A. E. Chamberlain
Sarah A. E. Chamberlain in OpenAIREHang-Yee Chan;
Hang-Yee Chan
Hang-Yee Chan in OpenAIREDawn Chow;
Dawn Chow
Dawn Chow in OpenAIREDongil Chung;
Dongil Chung
Dongil Chung in OpenAIRELuca Cian;
Luca Cian
Luca Cian in OpenAIRENoa Cohen-Eick;
Noa Cohen-Eick
Noa Cohen-Eick in OpenAIRELuis Sebastian Contreras-Huerta;
Luis Sebastian Contreras-Huerta
Luis Sebastian Contreras-Huerta in OpenAIREDavide Contu;
Davide Contu
Davide Contu in OpenAIREVladimir Cristea;
Vladimir Cristea
Vladimir Cristea in OpenAIREJo Cutler;
Silvana D'Ottone;Jo Cutler
Jo Cutler in OpenAIREJonas De Keersmaecker;
Jonas De Keersmaecker
Jonas De Keersmaecker in OpenAIRESarah Delcourt;
Sarah Delcourt
Sarah Delcourt in OpenAIRESylvain Delouvée;
Sylvain Delouvée
Sylvain Delouvée in OpenAIREKathi Diel;
Benjamin D. Douglas;Kathi Diel
Kathi Diel in OpenAIREMoritz A. Drupp;
Moritz A. Drupp
Moritz A. Drupp in OpenAIREShreya Dubey;
Shreya Dubey
Shreya Dubey in OpenAIREJānis Ekmanis;
Jānis Ekmanis
Jānis Ekmanis in OpenAIREChristian T. Elbaek;
Christian T. Elbaek
Christian T. Elbaek in OpenAIREMahmoud Elsherif;
Iris M. Engelhard;Mahmoud Elsherif
Mahmoud Elsherif in OpenAIREYannik A. Escher;
Yannik A. Escher
Yannik A. Escher in OpenAIRETom W. Etienne;
Tom W. Etienne
Tom W. Etienne in OpenAIRELaura Farage;
Laura Farage
Laura Farage in OpenAIREAna Rita Farias;
Ana Rita Farias
Ana Rita Farias in OpenAIREStefan Feuerriegel;
Stefan Feuerriegel
Stefan Feuerriegel in OpenAIREAndrej Findor;
Andrej Findor
Andrej Findor in OpenAIRELucia Freira;
Lucia Freira
Lucia Freira in OpenAIREMalte Friese;
Malte Friese
Malte Friese in OpenAIRENeil Philip Gains;
Neil Philip Gains
Neil Philip Gains in OpenAIREAlbina Gallyamova;
Albina Gallyamova
Albina Gallyamova in OpenAIRESandra J. Geiger;
Sandra J. Geiger
Sandra J. Geiger in OpenAIREOliver Genschow;
Oliver Genschow
Oliver Genschow in OpenAIREBiljana Gjoneska;
Theofilos Gkinopoulos;Biljana Gjoneska
Biljana Gjoneska in OpenAIREBeth Goldberg;
Beth Goldberg
Beth Goldberg in OpenAIREAmit Goldenberg;
Amit Goldenberg
Amit Goldenberg in OpenAIRESarah Gradidge;
Sarah Gradidge
Sarah Gradidge in OpenAIRESimone Grassini;
Kurt Gray; Sonja Grelle;Simone Grassini
Simone Grassini in OpenAIRESiobhán M. Griffin;
Siobhán M. Griffin
Siobhán M. Griffin in OpenAIRELusine Grigoryan;
Lusine Grigoryan
Lusine Grigoryan in OpenAIREAni Grigoryan;
Ani Grigoryan
Ani Grigoryan in OpenAIREDmitry Grigoryev;
Dmitry Grigoryev
Dmitry Grigoryev in OpenAIREJune Gruber;
June Gruber
June Gruber in OpenAIREJohnrev Guilaran;
Johnrev Guilaran
Johnrev Guilaran in OpenAIREBritt Hadar;
Britt Hadar
Britt Hadar in OpenAIREUlf J.J. Hahnel;
Ulf J.J. Hahnel
Ulf J.J. Hahnel in OpenAIREEran Halperin;
Eran Halperin
Eran Halperin in OpenAIREAnnelie J. Harvey;
Annelie J. Harvey
Annelie J. Harvey in OpenAIREChristian A. P. Haugestad;
Christian A. P. Haugestad
Christian A. P. Haugestad in OpenAIREAleksandra M. Herman;
Aleksandra M. Herman
Aleksandra M. Herman in OpenAIREHal E. Hershfield;
Hal E. Hershfield
Hal E. Hershfield in OpenAIREToshiyuki Himichi;
Toshiyuki Himichi
Toshiyuki Himichi in OpenAIREDonald W. Hine;
Wilhelm Hofmann;Donald W. Hine
Donald W. Hine in OpenAIRELauren Howe;
Lauren Howe
Lauren Howe in OpenAIREEnma T. Huaman-Chulluncuy;
Enma T. Huaman-Chulluncuy
Enma T. Huaman-Chulluncuy in OpenAIREGuanxiong Huang;
Guanxiong Huang
Guanxiong Huang in OpenAIRETatsunori Ishii;
Tatsunori Ishii
Tatsunori Ishii in OpenAIREAyahito Ito;
Ayahito Ito
Ayahito Ito in OpenAIREFanli Jia;
Fanli Jia
Fanli Jia in OpenAIREJohn T. Jost;
John T. Jost
John T. Jost in OpenAIREVeljko Jovanović;
Veljko Jovanović
Veljko Jovanović in OpenAIREDominika Jurgiel;
Ondřej Kácha;Dominika Jurgiel
Dominika Jurgiel in OpenAIREReeta Kankaanpää;
Reeta Kankaanpää
Reeta Kankaanpää in OpenAIREJaroslaw Kantorowicz;
Jaroslaw Kantorowicz
Jaroslaw Kantorowicz in OpenAIREElena Kantorowicz-Reznichenko;
Keren Kaplan Mintz;Elena Kantorowicz-Reznichenko
Elena Kantorowicz-Reznichenko in OpenAIREIlker Kaya;
Ilker Kaya
Ilker Kaya in OpenAIREOzgur Kaya;
Ozgur Kaya
Ozgur Kaya in OpenAIRENarine Khachatryan;
Narine Khachatryan
Narine Khachatryan in OpenAIREAnna Klas;
Anna Klas
Anna Klas in OpenAIREColin Klein;
Colin Klein
Colin Klein in OpenAIREChristian A. Klöckner;
Lina Koppel;Christian A. Klöckner
Christian A. Klöckner in OpenAIREAlexandra I. Kosachenko;
Alexandra I. Kosachenko
Alexandra I. Kosachenko in OpenAIREEmily J. Kothe;
Ruth Krebs;Emily J. Kothe
Emily J. Kothe in OpenAIREAmy R. Krosch;
Amy R. Krosch
Amy R. Krosch in OpenAIREAndre P.M. Krouwel;
Andre P.M. Krouwel
Andre P.M. Krouwel in OpenAIREYara Kyrychenko;
Yara Kyrychenko
Yara Kyrychenko in OpenAIREMaria Lagomarsino;
Maria Lagomarsino
Maria Lagomarsino in OpenAIREClaus Lamm;
Claus Lamm
Claus Lamm in OpenAIREFlorian Lange;
Florian Lange
Florian Lange in OpenAIREJulia Lee Cunningham;
Julia Lee Cunningham
Julia Lee Cunningham in OpenAIREJeffrey Lees;
Jeffrey Lees
Jeffrey Lees in OpenAIRETak Yan Leung;
Tak Yan Leung
Tak Yan Leung in OpenAIRENeil Levy;
Neil Levy
Neil Levy in OpenAIREPatricia L. Lockwood;
Patricia L. Lockwood
Patricia L. Lockwood in OpenAIREChiara Longoni;
Chiara Longoni
Chiara Longoni in OpenAIREAlberto López Ortega;
Alberto López Ortega
Alberto López Ortega in OpenAIREDavid D. Loschelder;
David D. Loschelder
David D. Loschelder in OpenAIREJackson G. Lu;
Jackson G. Lu
Jackson G. Lu in OpenAIREYu Luo;
Joseph Luomba;Annika E. Lutz;
Annika E. Lutz
Annika E. Lutz in OpenAIREJohann M. Majer;
Johann M. Majer
Johann M. Majer in OpenAIREEzra Markowitz;
Ezra Markowitz
Ezra Markowitz in OpenAIREAbigail A. Marsh;
Abigail A. Marsh
Abigail A. Marsh in OpenAIREKaren Louise Mascarenhas;
Karen Louise Mascarenhas
Karen Louise Mascarenhas in OpenAIREBwambale Mbilingi;
Bwambale Mbilingi
Bwambale Mbilingi in OpenAIREWinfred Mbungu;
Winfred Mbungu
Winfred Mbungu in OpenAIRECillian McHugh;
Cillian McHugh
Cillian McHugh in OpenAIREMarijn H.C. Meijers;
Marijn H.C. Meijers
Marijn H.C. Meijers in OpenAIREHugo Mercier;
Hugo Mercier
Hugo Mercier in OpenAIREFenant Laurent Mhagama;
Fenant Laurent Mhagama
Fenant Laurent Mhagama in OpenAIREKaterina Michalakis;
Katerina Michalakis
Katerina Michalakis in OpenAIRENace Mikus;
Nace Mikus
Nace Mikus in OpenAIRESarah Milliron;
Sarah Milliron
Sarah Milliron in OpenAIREPanagiotis Mitkidis;
Panagiotis Mitkidis
Panagiotis Mitkidis in OpenAIREFredy S. Monge-Rodríguez;
Fredy S. Monge-Rodríguez
Fredy S. Monge-Rodríguez in OpenAIREYouri L. Mora;
Youri L. Mora
Youri L. Mora in OpenAIREDavid Moreau;
David Moreau
David Moreau in OpenAIREKosuke Motoki;
Kosuke Motoki
Kosuke Motoki in OpenAIREManuel Moyano;
Mathilde Mus;Manuel Moyano
Manuel Moyano in OpenAIREJoaquin Navajas;
Joaquin Navajas
Joaquin Navajas in OpenAIRETam Luong Nguyen;
Tam Luong Nguyen
Tam Luong Nguyen in OpenAIREDung Minh Nguyen;
Dung Minh Nguyen
Dung Minh Nguyen in OpenAIRETrieu Nguyen;
Laura Niemi;Trieu Nguyen
Trieu Nguyen in OpenAIRESari R. R. Nijssen;
Sari R. R. Nijssen
Sari R. R. Nijssen in OpenAIREGustav Nilsonne;
Gustav Nilsonne
Gustav Nilsonne in OpenAIREJonas P. Nitschke;
Jonas P. Nitschke
Jonas P. Nitschke in OpenAIRELaila Nockur;
Ritah Okura;Laila Nockur
Laila Nockur in OpenAIRESezin Öner;
Sezin Öner
Sezin Öner in OpenAIREAsil Ali Özdoğru;
Asil Ali Özdoğru
Asil Ali Özdoğru in OpenAIREHelena Palumbo;
Helena Palumbo
Helena Palumbo in OpenAIRECostas Panagopoulos;
Costas Panagopoulos
Costas Panagopoulos in OpenAIREMaria Serena Panasiti;
Maria Serena Panasiti
Maria Serena Panasiti in OpenAIREPhilip Pärnamets;
Philip Pärnamets
Philip Pärnamets in OpenAIREMariola Paruzel-Czachura;
Mariola Paruzel-Czachura
Mariola Paruzel-Czachura in OpenAIREYuri G. Pavlov;
Yuri G. Pavlov
Yuri G. Pavlov in OpenAIRECésar Payán-Gómez;
César Payán-Gómez
César Payán-Gómez in OpenAIREAdam R. Pearson;
Adam R. Pearson
Adam R. Pearson in OpenAIRELeonor Pereira da Costa;
Leonor Pereira da Costa
Leonor Pereira da Costa in OpenAIREHannes M. Petrowsky;
Hannes M. Petrowsky
Hannes M. Petrowsky in OpenAIREStefan Pfattheicher;
Stefan Pfattheicher
Stefan Pfattheicher in OpenAIRENhat Tan Pham;
Nhat Tan Pham
Nhat Tan Pham in OpenAIREVladimir Ponizovskiy;
Clara Pretus;Vladimir Ponizovskiy
Vladimir Ponizovskiy in OpenAIREGabriel G. Rêgo;
Gabriel G. Rêgo
Gabriel G. Rêgo in OpenAIRERitsaart Reimann;
Ritsaart Reimann
Ritsaart Reimann in OpenAIREShawn A. Rhoads;
Shawn A. Rhoads
Shawn A. Rhoads in OpenAIREJulian Riano-Moreno;
Julian Riano-Moreno
Julian Riano-Moreno in OpenAIREdoi: 10.1126/sciadv.adj5778 , 10.17615/j71a-aj22 , 10.48350/192662 , 10.26181/27048496.v1 , 10.26181/27048496
pmid: 38324680
pmc: PMC10849597
doi: 10.1126/sciadv.adj5778 , 10.17615/j71a-aj22 , 10.48350/192662 , 10.26181/27048496.v1 , 10.26181/27048496
pmid: 38324680
pmc: PMC10849597
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.
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