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Public acceptance (PA) is nowadays essential for the sustainable development of nuclear energy and becomes animportant issue for research community. Although some studies had investigated the factors influencing PA ofnuclear energy, few researches were founded to verify the impact of cultural values. This research proposed atheoretical model to explore how individualism and collectivism, as an important dimension of culture, moderated the relevance between perceived risk/benefit and PA. A questionnaire survey was conducted nationwidein China whose number of under-construction nuclear power plants ranks first in the world, and received 887valid responses. The analysis of moderating effect showed individualism weakened the relevance betweenperceived benefit and PA, whereas collectivism had no significant moderating role on the relevance betweenperceived benefit and PA. Collectivism strengthened the relevance between perceived risk and PA, whereasindividualism had no significant moderating role on the relevance between perceived risk and PA. Moreover,perceived benefit was confirmed to be a more important predictor for PA than perceived risk. The abovementioned findings could not only provide new insights that help to understand the difference in energy policiesbetween China and the developed countries, but also provide new reference and guidance for the future policymaking. Public acceptance (PA) is nowadays essential for the sustainable development of nuclear energy and becomes animportant issue for research community. Although some studies had investigated the factors influencing PA ofnuclear energy, few researches were founded to verify the impact of cultural values. This research proposed atheoretical model to explore how individualism and collectivism, as an important dimension of culture, moderated the relevance between perceived risk/benefit and PA. A questionnaire survey was conducted nationwidein China whose number of under-construction nuclear power plants ranks first in the world, and received 887valid responses. The analysis of moderating effect showed individualism weakened the relevance betweenperceived benefit and PA, whereas collectivism had no significant moderating role on the relevance betweenperceived benefit and PA. Collectivism strengthened the relevance between perceived risk and PA, whereasindividualism had no significant moderating role on the relevance between perceived risk and PA. Moreover,perceived benefit was confirmed to be a more important predictor for PA than perceived risk. The abovementioned findings could not only provide new insights that help to understand the difference in energy policiesbetween China and the developed countries, but also provide new reference and guidance for the future policymaking.

Permafrost regions contain approximately half of the carbon stored in land ecosystems and have warmed at least twice as much as any other biome. This warming has influenced vegetation activity, leading to changes in plant composition, physiology, and biomass storage in aboveground and belowground components, ultimately impacting ecosystem carbon balance. Yet, little is known about the causes and magnitude of long-term changes in the above- to belowground biomass ratio of plants (η). Here, we analyzed η values based on 3,013 plots and 26,337 plant-specific measurements representing eight sites across the Tibetan Plateau from 1995 to 2021. Our analysis revealed distinct temporal trends in η for three vegetation types: a 17% increase in alpine wetlands, and a decrease of 26% and 48% in alpine meadows and alpine steppes, respectively. These trends were primarily driven by temperature-induced growth preferences rather than shifts in plant species composition. Our findings indicate that in wetter ecosystems climate warming promotes aboveground plant growth, while in drier ecosystems, such as alpine meadows and alpine steppes, plants allocate more biomass belowground. Four process-based biogeochemical models failed to simulate the observed changes in η, which highlights the importance of improved process understanding of the processes driving the response of biomass distribution to climate warming, which is crucial for predicting the future carbon trajectory of permafrost ecosystems.

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.ScenarioMIP.CAS.FGOALS-g3' 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 FGOALS-g3 climate model, released in 2017, includes the following components: atmos: GAMIL3 (180 x 80 longitude/latitude; 26 levels; top level 2.19hPa), land: CAS-LSM, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run by the Chinese Academy of Sciences, Beijing 100029, China (CAS) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.

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.ScenarioMIP.CAS.FGOALS-g3.ssp370' 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 FGOALS-g3 climate model, released in 2017, includes the following components: atmos: GAMIL3 (180 x 80 longitude/latitude; 26 levels; top level 2.19hPa), land: CAS-LSM, ocean: LICOM3.0 (LICOM3.0, tripolar primarily 1deg; 360 x 218 longitude/latitude; 30 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run by the Chinese Academy of Sciences, Beijing 100029, China (CAS) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.

We inferred patterns of biogeographic diversification and trait evolution in Vitaceae based on a robust phylogeny with dense sampling. We inferred patterns of biogeographic diversification and trait evolution in Vitaceae based on a robust phylogeny with dense sampling.

Although many studies have tested the direct effects of drought on alien plant invasion, less is known about whether drought affects alien plant invasion indirectly via interactions of plants with other groups of organisms such as soil mesofauna. To test for such indirect effects, we grew single plants of nine naturalized alien target species in pot-mesocosms with a community of five native grassland species under four combinations of two drought (well-watered vs drought) and two soil-mesofauna-inoculation (with vs without) treatments. We found that drought decreased the absolute and the relative biomass production of the alien plants, and thus reduced their competitive strength in the native community. Drought also decreased the abundance of soil mesofauna, particularly soil mites, but did not affect the abundance and richness of soil herbivores. Soil-fauna inoculation did not affect biomass of the alien plants but increased biomass of the native plant community, and thereby decreased the relative biomass production of the alien plants. This increased invasion resistance due to soil fauna, however, tended (p = 0.09) to be stronger for plants growing under well-watered conditions than under drought. Synthesis. Our multispecies experiment thus shows that soil fauna might help native communities to resist alien plant invasions, but that this effect might be weakened under drought. In other words, soil mesofauna may buffer the negative effects of drought on alien plant invasions. The file archives 'SoilFauna_Drought_PlantInvasion_Date_YJL.tar' include three dataset, one named 'SoilFauna_Drought_PlantInvasion.csv' (Biomass data), one named 'SoilFaunaData.csv' (Soil Fauna data), and one named 'SoilNitrogenData.csv' (soil nitrogen data). The file 'SoilFauna_Drought_PlantInvasion.Rmd' is the R script, and its output is 'SoilFauna_Drought_PlantInvasion.html'. All data were collected from a greenhouse expeirment at the Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences.

Climate trends during rice growing period and their impacts on rice yield in South China was investigated. This dataset contains: 1) information of stations in cultivation region for double-season rice in South China; 2) Trend in temperature and its effect on yield in cultivation region for double-season rice in South China; 3) Trend in radiation and its effect on yield in cultivation region for double-season rice in South China; 4) Trend in precipitation and its effect on yield in cultivation region for double-season rice in South China. Climate trends during rice growing period and their impacts on rice yield in South China was investigated. This dataset contains: 1) information of stations in cultivation region for double-season rice in South China; 2) Trend in temperature and its effect on yield in cultivation region for double-season rice in South China; 3) Trend in radiation and its effect on yield in cultivation region for double-season rice in South China; 4) Trend in precipitation and its effect on yield in cultivation region for double-season rice in South China.

(1) Seed mass: we collected the seeds from maternal plants and air-dried them, selected 100 seeds from five mesocosms per maternal environment, and determined their air-dried mass (mg); the thousand-seed mass (mg) was calculated as follows: hundred-seed mass × 10. (2) Seed germination: seed germination was checked daily; the seed germination rate (%) was calculated as follows: (the number of germinated seeds/the initial number of seeds) × 100%. (3) Chlorophyll content: we selected three leaves from each individual and recorded three readings with a portable chlorophyll meter (SPAD-502, Konica Minolta, Japan) per leaf, and then all readings per individual were averaged. (4) Leaf dry matter content (LDMC): we determined the mass of a water-saturated fresh leaf after rehydrating it at room temperature for 24 h, and then determined its dry mass after oven-drying at 85 °C for 24 h; LDMC (mg g-1) was calculated as the ratio of leaf oven-dry mass to leaf water-saturated fresh mass. (5) Flowering and seed-setting date: the onset of the first flowering and seed-setting was observed every 1–3 days; from the observations, we could determine the number of days from 1 April (i.e., day of year, DOY) for flowering and seed-setting phases. (6) Whole-plant biomass: at the end of the experiment, we harvested all plants and separated them into shoots and roots; all harvested plants were oven-dried at 65 °C for 48 h and then weighed; the whole-plant biomass (g) was defined as the sum of dry shoot biomass and dry root biomass. (7) Shoot/root ratio: we calculated a shoot/root ratio based on shoot biomass and root biomass. Maternal effects allow offspring to cope with changing environments. While the immediate effects of climate warming and nitrogen (N) deposition are well documented, their maternal effects have been little studied. We conducted a 6-year maternal experiment with Solidago canadensis, native to North America and invasive in China, and two offspring experiments to address how maternal warming, maternal N-addition and population source interacted to influence offspring performance. Maternal effects of warming and N-addition on seed traits, leaf dry matter content, and whole-plant biomass were stronger in S. canadensis offspring from China than in offspring from North America. Matched maternal-offspring environments allowed offspring to perform better compared to mismatched environments; offspring grown under warming flowered and produced seeds within a growing season only when their maternal plants were previously exposed to warming. Offspring environments influenced its performance and also modulated maternal effects. We suggest that the maternal effects of simulated climate warming and N deposition could vary ranges, and our findings imply that maternal warming could advance the reproductive phenology of offspring. README_ZhouFunctEcol2021.xlsx contains metadata for each of the following datasheets: Zhou_FE2021_biomass.csv file contains the shoot biomass, root biomass, and whole-plant biomass of offspring individuals grown under different conditions. Zhou_FE2021_chlorophyll.csv file contains the leaf chlorophyll content of offspring individuals grown under different conditions. Zhou_FE2021_flowering date.csv file contains the flowering date of offspring individuals grown under different conditions. Zhou_FE2021_leaf dry matter content.csv file contains the leaf dry matter content of offspring individuals grown under different conditions. Zhou_FE2021_seed germination.csv file contains the seed germination rate of maternal individuals grown under different conditions. Zhou_FE2021_seed mass.csv file contains the seed mass of maternal individuals grown under different conditions. Zhou_FE2021_seed-setting date.csv file contains the seed-setting date of offspring individuals grown under different conditions. Zhou_FE2021_shoot root ratio.csv file contains the shoot/root ratio of offspring individuals grown under different conditions.

XES and HERFD data was obtained by the spectrometer in E-line of Shanghai synchrotron radiation facility. XES data is firstly deduced by subtracting background and tails, and then is normilized. HERFD-XAFS data was deduced by Athena software. XES and HERFD data was obtained by the spectrometer in E-line of Shanghai synchrotron radiation facility. XES data is firstly deduced by subtracting background and tails, and then is normilized. HERFD-XAFS data was deduced by Athena software.