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Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022). This version includes an update of continental heat content uncertainty, where the standard deviation has been corrected from the precedent version to consider properly the value from permafrost heat storage uncertainty.

This dataset includes annual soil conservation capacities and their impact factors in China from 1992 to 2019. These data are developed based on an improved RUSLE model to estimate potential and controlled soil erosion in China from 1992 to 2019. As important input factors, the vegetation cover and management (C) factor and rainfall erosivity (R) factor are optimized for different regions. The C-factor is optimized according to each province's farmland and non-farmland conditions. The R-factor is calculated for karst and non-karst areas separately using daily precipitation. The dataset contains nine zip files (“.rar”), which can be divided into comprehensive data and detailed data. Comprehensive data include mean values and changing rates of soil conservation capacity (SC1992-2019), the C-factor (C1992-2019), and the R-factor (R1992-2019) in China from 1992 to 2019. Detailed data include the water and soil conservation measure factor data (P_300), the soil erodibility factor data (K_300), the topographic factor data (LS_300), the R-factor data in two-year increments (R_year), the C-factor data in two-year increments (C_year), and the SC data in two-year increments (SC_year). Most data have a spatial resolution of 300 m (the resolution of the R-factor is 1 km). All the data in the zip files are raster data (“.tif”), which can be opened by GIS software like ArcMap. This dataset can support large-scale and long-term assessment of soil and water conservation potential in China. It also can serve as a basis for identifying the impacts of climate change and human activities on soil conservation services. This dataset includes annual soil conservation capacities and their impact factors in China from 1992 to 2019. These data are developed based on an improved RUSLE model to estimate potential and controlled soil erosion in China from 1992 to 2019. As important input factors, the vegetation cover and management (C) factor and rainfall erosivity (R) factor are optimized for different regions. The C-factor is optimized according to each province's farmland and non-farmland conditions. The R-factor is calculated for karst and non-karst areas separately using daily precipitation. The dataset contains nine zip files (“.rar”), which can be divided into comprehensive data and detailed data. Comprehensive data include mean values and changing rates of soil conservation capacity (SC1992-2019), the C-factor (C1992-2019), and the R-factor (R1992-2019) in China from 1992 to 2019. Detailed data include the water and soil conservation measure factor data (P_300), the soil erodibility factor data (K_300), the topographic factor data (LS_300), the R-factor data in two-year increments (R_year), the C-factor data in two-year increments (C_year), and the SC data in two-year increments (SC_year). Most data have a spatial resolution of 300 m (the resolution of the R-factor is 1 km). All the data in the zip files are raster data (“.tif”), which can be opened by GIS software like ArcMap. This dataset can support large-scale and long-term assessment of soil and water conservation potential in China. It also can serve as a basis for identifying the impacts of climate change and human activities on soil conservation services.

Plant secondary metabolites (SMs) play crucial roles in plant-environment interactions and contribute greatly to human health. Global climate changes are expected to dramatically affect plant secondary metabolism, yet a systematic understanding of such influences is still lacking. Here, we employed medicinal and aromatic plants (MAAPs) as model plant taxa and performed a meta-analysis from 360 publications using 1828 paired observations to assess the responses of different SMs levels and the accompanying plant traits to elevated carbon dioxide (eCO2), elevated temperature (eT), elevated nitrogen deposition (eN), and decreased precipitation (dP). The overall results showed that phenolic and terpenoid levels generally respond positively to eCO2 but negatively to eN, while the total alkaloid concentration was increased remarkably by eN. By contrast, dP promotes the levels of all SMs, while eT exclusively exerts a positive influence on the levels of phenolic compounds. Further analysis highlighted the dependence of SM responses on different moderators such as plant functional types, climate change levels or exposure durations, mean annual temperature and mean annual precipitation. Moreover, plant phenolic and terpenoid responses to climate changes could be attributed to the variations in C/N ratio and total soluble sugar levels, while the trade-off supposition contributed to SM responses to climate changes other than eCO2. Taken together, our results predicted the distinctive SM responses to diverse climate changes in MAAPs, and allowed us to define potential moderators responsible for these variations. Further, linking SM responses to C-N metabolism and growth-defence balance provided biological understandings in terms of plant secondary metabolic regulation. Peer-reviewed journal articles published online from January 1990 to March 2022 were searched using Web of Science (http://www.isiknowledge.com/), with the following terms: (global change OR climate change OR free-air carbon dioxide enrichment OR free-air CO2 enrichment OR elevated carbon dioxide OR elevated CO2 OR elevated atmospheric CO2 OR CO2 enrichment OR eCO2 OR atmospheric CO2 enrichment OR elevated atmospheric carbon dioxide OR carbon dioxide enrichment OR [carbon dioxide] OR nitrogen deposition OR nitrogen addition OR nitrogen application OR nitrogen fertiliz* OR nitrogen nutrition OR N deposition OR N addition OR N application OR N fertiliz* OR N nutrition OR changing precipitation OR increased precipitation OR decreased precipitation OR drought OR water stress OR water addition OR warming OR elevated temperature OR climate warming OR elevated temperature OR increased temperature) AND (medicinal plant OR aromatic plants). 

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022).

Vapor pressure deficit (VPD) is related to rice evapotranspiration, and it has major impact on rice yield. This dataset includes the information of stations in cultivation region for single season rice and double season rice in Southwest Plateau and trend in VPD and its effect on rice yield during 1980-2008. It is useful for the analysis of the spatiotemporal variations of VPD in Southwest Plateau. Vapor pressure deficit (VPD) is related to rice evapotranspiration, and it has major impact on rice yield. This dataset includes the information of stations in cultivation region for single season rice and double season rice in Southwest Plateau and trend in VPD and its effect on rice yield during 1980-2008. It is useful for the analysis of the spatiotemporal variations of VPD in Southwest Plateau.

Urban land use change has the potential to affect local to global biogeochemical carbon (C) and nitrogen (N) cycles and associated greenhouse gas (GHG) fluxes. We conducted a meta-analysis to 1) assess the effects of urbanization-induced land-use conversion on soil nitrous oxide (N2O) and methane (CH4) fluxes, 2) quantify direct N2O emission factors (EFd) of fertilized urban soils used e.g., as lawns or forests, and 3) identify the key drivers leading to flux changes associated with urbanization. On average, urbanization increases soil N2O emissions by 153%, to 3.0 kg N ha-1 yr-1, while rates of soil CH4 uptake are reduced by 50%, to 2.0 kg C ha-1 yr-1. The mean annual N2O EFd of fertilized lawns and urban forests is 1.4%, suggesting that urban soils can be regional hotspots of N2O emissions. On a global basis, conversion of land to urban greenspaces has increased soil N2O emission by 0.46 Tg N2O-N yr-1 and decreased soil CH4 uptake by 0.58 Tg CH4-C yr-1. Urbanization-driven changes in soil N2O emission and CH4 uptake are associated with changes in soil properties (bulk density, pH, total N content and C/N ratio), increased temperature, and management practices, especially fertilizer use. Overall, our meta-analysis shows that urbanization increases soil N2O emissions and reduces the role of soils as a sink for atmospheric CH4. These effects can be mitigated by avoiding soil compaction, reducing fertilization of lawns, and restoring native ecosystems in urban landscapes.

This dataset records the Spatiotemporal Variation of early rice phenology, contains the details of early rice agrometeorological experiment stations and mean date of early rice phenology date and trend in phenology date during the period of 1981–2009. This dataset is helpful to study the response of early rice to climate change. This dataset records the Spatiotemporal Variation of early rice phenology, contains the details of early rice agrometeorological experiment stations and mean date of early rice phenology date and trend in phenology date during the period of 1981–2009. This dataset is helpful to study the response of early rice to climate change.

A series of Ho and Pr doped LuYSGG laser crystals were successfully grown by Czochralski method. X-ray rocking curves indicate their high crystalline quality. Crystal structure and basic parameters are provided by XRD and Rietveld refinement. Combining density functional theory, the bandgaps of YSGG and LuYSGG are calculated to be 3.497 and 3.483 eV, respectively. Particularly, the J-O parameters and emission spectra suggest the LuYSGG is more suitable as host for Ho3+ ions and could achieve better 2.9 μm emission than YSGG. Meanwhile, the luminescent decay curves show the deactivated Pr3+ ion can greatly narrow the lifetime gap between the 5I6 and 5I7 energy levels, which can eventually attenuate effect of self-termination phenomenon on the 2.9 μm emission. A series of Ho and Pr doped LuYSGG laser crystals were successfully grown by Czochralski method. X-ray rocking curves indicate their high crystalline quality. Crystal structure and basic parameters are provided by XRD and Rietveld refinement. Combining density functional theory, the bandgaps of YSGG and LuYSGG are calculated to be 3.497 and 3.483 eV, respectively. Particularly, the J-O parameters and emission spectra suggest the LuYSGG is more suitable as host for Ho3+ ions and could achieve better 2.9 μm emission than YSGG. Meanwhile, the luminescent decay curves show the deactivated Pr3+ ion can greatly narrow the lifetime gap between the 5I6 and 5I7 energy levels, which can eventually attenuate effect of self-termination phenomenon on the 2.9 μm emission.

Satisfying China’s food demand without harming the environment is one of the greatest sustainability challenges for the coming decades. Here we provide a comprehensive forward-looking assessment of the environmental impacts of China’s growing demand on the country itself and on its trading partners. We find that the increasing food demand, especially for livestock products (~16%–30% across all scenarios), would domestically require ~3–12 Mha of dditional pasture between 2020 and 2050, resulting in ~-2% to +16% growth in agricultural greenhouse gas (GHG) emissions. The projected ~15%–24% reliance on agricultural imports in 2050 would result in ~90–175 Mha of agricultural land area and ~88–226 MtCO2-equivalent yr-1of GHG emissions virtually imported to China, which account for ~26%–46% and ~13%–32% of China’s global environmental impacts, respectively. The distribution of the environmental impacts between China and the rest of the world would substantially depend on development of trade openness. Thus, to limit the negative environmental impacts of its growing food consumption, besides domestic policies, China needs to also take responsibility in the development of sustainable international trade. Satisfying China’s food demand without harming the environment is one of the greatest sustainability challenges for the coming decades. Here we provide a comprehensive forward-looking assessment of the environmental impacts of China’s growing demand on the country itself and on its trading partners. We find that the increasing food demand, especially for livestock products (~16%–30% across all scenarios), would domestically require ~3–12 Mha of dditional pasture between 2020 and 2050, resulting in ~-2% to +16% growth in agricultural greenhouse gas (GHG) emissions. The projected ~15%–24% reliance on agricultural imports in 2050 would result in ~90–175 Mha of agricultural land area and ~88–226 MtCO2-equivalent yr-1of GHG emissions virtually imported to China, which account for ~26%–46% and ~13%–32% of China’s global environmental impacts, respectively. The distribution of the environmental impacts between China and the rest of the world would substantially depend on development of trade openness. Thus, to limit the negative environmental impacts of its growing food consumption, besides domestic policies, China needs to also take responsibility in the development of sustainable international trade.