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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.CSIRO-ARCCSS.ACCESS-CM2.ssp245' 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 Australian Community Climate and Earth System Simulator Climate Model Version 2 climate model, released in 2019, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: CABLE2.5, ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE5.1.2 (same grid as ocean). The model was run by the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science). Mailing address: CSIRO, c/o Simon J. Marsland, 107-121 Station Street, Aspendale, Victoria 3195, Australia (CSIRO-ARCCSS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version. Paper Citation: - _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

A collection of field data from four agricultural sites in the Rur catchment in Western Germany collected in the frame of the Transregional Collaborative Research Centre 32 “Patterns in Soil-Vegetation-Atmosphere-Systems: Monitoring, Modelling and Data Assimilation” (TR32). The dataset includes data on vegetation (states and fluxes), weather, soil, and agricultural management. Vegetation-related data comprises fresh and dry biomass (green and brown, predominantly per organ), plant height, green and brown leaf area index, phenological development state, nitrogen and carbon content, and carbon-, energy- and water-fluxes for a variety of agricultural plants. In addition, masses of harvest residues and regrowth of vegetation after harvest or before planting of the main crop are included. Data on agricultural management includes sowing and harvest dates, and information on cultivation, fertilization and agrochemicals. The dataset also includes gap-filled weather data and soil parameters (particle size distributions, carbon and nitrogen contents). This data can be useful for development and validation of remote sensing products. A detailed description of the dataset can be found in Reichenau et al. (2020).

Humans share an extraordinary degree of sociality with other primates, calling for comparative work into the evolutionary drivers of the variation in social engagement observed between species. Of particular interest is the contrast between the chimpanzee (Pan troglodytes) and bonobo (Pan paniscus), the latter exhibiting increased female gregariousness, more tolerant relationships, and elaborate behavioral adaptations for conflict resolution. Here we test predictions from three socio-ecological hypotheses regarding the evolution of these traits using data on wild bonobos at LuiKotale, Democratic Republic of Congo. Focusing on the behavior of co-feeding females and controlling for variation in characteristics of the feeding patch, food intake rate moderately increased while feeding effort decreased with female dominance rank, indicating that females engaged in competitive exclusion from high quality food resources. However, these rank effects did not translate into variation in energy balance, as measured from urinary C-peptide levels. Instead, energy balance varied independent of female rank with the proportion of fruit in the diet. Together with the observation that females join forces in conflicts with males, our results support the hypothesis that predicts that females trade off feeding opportunities for safety against male aggression. The key to a full understanding of variation in social structure may be an integrated view of cooperation and competition over access to the key resources food and mates, both within and between the sexes. main_pan_analysis_II_intake_poisson_script_07022017R script for analysing food intake using a GLMMMASTER_analyses_II_R_file_intake_fFile containing the variables for the GLMM on food intake, analysed in RMAIN_pan_analysis_III_movement_script_26092016R script for analysing movement probability in focal trees using GLMMMASTER_analyses_III_R_file_movement_fFile containing the variables to analyse movement probability with a GLMM in Rmain_ucp_model_script_21022018_seasonality_update_with_feedscansR script to analyse variation in urinary C-peptide in a LMMmain_ucp_model_data_r_2018_seasonality_update_with_feed_scansFile containing the variables to analyse variation in urinary C-peptide using an LMM in R

The expansion of irrigated agriculture has increased global crop production but resulted in widespread stress to freshwater resources. Ensuring that increases in irrigated production only occur in places where water is relatively abundant is a key objective of sustainable agriculture, and knowledge of how irrigated land has evolved is important for measuring progress towards water sustainability. Yet a spatially detailed understanding of the evolution of global area equipped for irrigation (AEI) is missing. Here we utilize the latest sub-national irrigation statistics (covering 17298 administrative units) from various official sources to develop a gridded (5 arc-min resolution) global product of AEI for the years 2000, 2005, 2010, and 2015. We find that AEI increased by 11% from 2000 (297 Mha) to 2015 (330 Mha) with locations of both substantial expansion (e.g., northwest India, northeast China) and decline (e.g., Russia). Combining these outputs with information on green (i.e., rainfall) and blue (i.e., surface and ground) water stress, we also examine to what extent irrigation has expanded unsustainably (i.e., in places already experiencing water stress). We find that more than half (52%) of irrigation expansion has taken place in regions that were already water stressed, with India alone accounting for 36% of global unsustainable expansion. These findings provide new insights into the evolving patterns of global irrigation with important implications for global water sustainability and food security. Recommended citation: Mehta, P., Siebert, S., Kummu, M. et al. Half of twenty-first century global irrigation expansion has been in water-stressed regions. Nat Water (2024). https://doi.org/10.1038/s44221-024-00206-9 Open-access peer reviewed publication available at https://www.nature.com/articles/s44221-024-00206-9 Files G_AEI_*.ASC were produced using the GMIA dataset[https://data.apps.fao.org/catalog/iso/f79213a0-88fd-11da-a88f-000d939bc5d8]. Files MEIER_G_AEI_*.ASC were produced using Meier et al. (2018) dataset [https://doi.pangaea.de/10.1594/PANGAEA.884744].

This data package contains data used for an model-data intercomparison originally published in: D. K. Hutchinson, H. K. Coxall, D. J. Lunt, M. Steinthorsdottir, A. M. de Boer, M. Baatsen, A. von der Heydt, M. Huber, A. T. Kennedy-Asser, L. Kunzmann, J.-B. Ladant, C. H. Lear, K. Moraweck, P. N. Pearson, E. Piga, M. J. Pound, U. Salzmann, H. D. Scher, W. P. Sijp, K. K. Śliwińska, P. A. Wilson, and Z. Zhang, 2021: The Eocene-Oligocene transition: a review of marine and terrestrial proxy data, models and model-data comparisons, Climate of the Past, 17, 269-315. https://doi.org/10.5194/cp-17-269-2021 These data are also used in a further model-data intercomparison of Antarctic temperatures: Emily Tibbett, Natalie J Burls, David K. Hutchinson, Sarah J Feakins, (2023), Proxy-Model Comparison for the Eocene-Oligocene Transition in Southern High Latitudes, Paleoceanography and Paleocliamtology, In Review. Pre-print avaiable from: https://www.authorea.com/doi/full/10.1002/essoar.10511735.2 The package contains surface air temperature and sea surface temperature from an ensemble of model simulations of the Eocene-Oligocene transition. These data are provided at annual and monthly frequency. They are also provided on the original model grid, and an interpolated common grid used for the intercomparison. (The common grid is based on the HadCM3BL model grid.) All data are provided in NETCDF format with self-describing variable names. The name and explanation of the interpolated data files are contained in: table_of_experiments.xlsx Please read that spreadsheet to interpret the filenames, and see Table 2 (p291) of Hutchinson et al (2021) for experiment descriptions. Please also be mindful to cite the original authors of the simulations when using these data, whose work made this dataset possible. The appropriate citations are listed below: Reference DOI link Baatsen et al (2020) https://doi.org/10.5194/cp-16-2573-2020 Goldner et al (2014) https://doi.org/10.1038/nature13597 Ladant et al (2014a,b) https://doi.org/10.5194/cp-10-1957-2014 https://doi.org/10.1002/2013PA002593 Hutchinson et al (2018, 2019) https://doi.org/10.5194/cp-14-789-2018 https://doi.org/10.1038/s41467-019-11828-z Kennedy et al (2015) https://doi.org/10.1098/rsta.2014.0419 Zhang et al (2012, 2014) https://doi.org/10.5194/gmd-5-523-2012 https://doi.org/10.1038/nature13705 Sijp et al (2009) https://doi.org/10.1175/2009JCLI3003.1

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

ABSTRACTA novel design for a high temperature SOFC, based on lamellar electrode-electrolyte segments obtained by solidification of an oxidic eutectic melt on an electrolyte substrate is presented. Such “composite” electrodes contain NiO or MnO - 8Y-ZrO2 lamellae, which after reduction / oxidation yield electrode-electrolyte lamellae with 1–2 μm width and a vertical dimension of> 100 μm, depending upon the amount of eutectic melt solidified on a polycrystalline substrate. The nucleation of the eutectic on a polycrystalline substrate followed by a semi-directional crystallization of the two phases yields a gradient of 3-phase boundaries over the height of such an electrode, with the number of 3-phase boundaries increasing towards the substrate.