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  • Energy Research
  • 13. Climate action
  • 11. Sustainability
  • 6. Clean water
  • DE
  • IT

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Natural potentials for future cropland expansion The potential for the expansion of cropland is restricted by the availability of land resources and given local natural conditions. As a result, area that is highly suitable for agriculture according to the prevailing local biophysical conditions but is not under cultivation today has a high natural potential for expansion. Policy regulations can further restrict the availability of land for expansion by designating protected areas, although they may be suitable for agriculture. Conversely, by applying e.g. irrigation practices, land can be brought under cultivation, although it may naturally not be suitable. Here, we investigate the potentials for agricultural expansion for near future climate scenario conditions to identify the suitability of non-cropland areas for expansion according to their local natural conditions. We determine the available energy, water and nutrient supply for agricultural suitability from climate, soil and topography data, by using a fuzzy logic approach according to Zabel et al. (2014). It considers the 16 globally most important staple and energy crops. These are: barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, rye, sorghum, soy, sugarcane, sunflower, summer wheat, winter wheat. The parameterization of the membership functions that describe each of the crops’ specific natural requirements is taken from Sys et al. (1993). The considered natural conditions are: climate (temperature, precipitation, solar radiation), soil properties (texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity), and topography (elevation, slope). As a result of the fuzzy logic approach, values in a range between 0 and 1 describe the suitability of a crop for each of the prevailing natural conditions at a certain location. The smallest suitability value over all parameters finally determines the suitability of a crop. The daily climate data is provided by simulation results from the global climate model ECHAM5 (Jungclaus et al. 2006) for near future (2011-2040) SRES A1B climate scenario conditions. Soil data is taken from the Harmonized World Soil Database (HWSD) (FAO et al. 2012), and topography data is applied from the Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007). In order to gather a general crop suitability, which does not refer to one specific crop, the most suitable crop with the highest suitability value is chosen at each pixel. In addition the natural biophysical conditions, we consider today’s irrigated areas according to (Siebert et al. 2013). We assume that irrigated areas globally remain constant until 2040, since adequate data on the development of irrigated areas do not exist, although it is likely that freshwater availability for irrigation could be limited in some regions, while in other regions surplus water supply could be used to expand irrigation practices (Elliott et al. 2014). However, it is difficult to project where irrigation practices will evolve, since it is driven by economic investment costs that are required to establish irrigation infrastructure. In principle, all agriculturally suitable land that is not used as cropland today has the natural potential to be converted into cropland. We assume that only urban and built-up areas are not available for conversion, although more than 80% of global urban areas are agriculturally suitable (Avellan et al. 2012). However, it seems unlikely that urban areas will be cleared at the large scale due to high investment costs, growing cities and growing demand for settlements. Concepts of urban and vertical farming usually are discussed under the aspects of cultivating fresh vegetables and salads for urban population. They are not designed to extensively grow staple crops such as wheat or maize for feeding the world in the near future. Urban farming would require one third of the total global urban area to meet only the global vegetable consumption of urban dwellers (Martellozzo et al. 2015). Thus, urban agriculture cannot substantially contribute to global agricultural production of staple crops. Protected areas or dense forested areas are not excluded from the calculation, in order not to lose any information in the further combination with the biodiversity patterns (see chapter 2.3). We use data on current cropland distribution by Ramankutty et al. (2008) and urban and built-up area according to the ESA-CCI land use/cover dataset (ESA 2014). From this data, we calculate the ‘natural expansion potential index’ (Iexp) that expresses the natural potential for an area to be converted into cropland as follows: Iexp = S * Aav The index is determined by the quality of agricultural suitability (S) (values between 0 and 1) multiplied with the amount of available area (Aav) for conversion (in percentage of pixel area). The available area includes all suitable area that is not cultivated today, and not classified as urban or artificial area. The index ranges between 0 and 100 and indicates where the conditions for cropland expansion are more or less favorable, when taking only natural conditions into account, disregarding socio-economic factors, policies and regulations that drive or inhibit cropland expansion. The index is a helpful indicator for identifying areas where cropland expansion could take place in the near future. Further information Detailled information are available in the following publication: Delzeit, R., F. Zabel, C. Meyer and T. Václavík (2017). Addressing future trade-offs between biodiversity and cropland expansion to improve food security. Regional Environmental Change 17(5): 1429-1441. DOI: 10.1007/s10113-016-0927-1 Contact Please contact: Dr. Florian Zabel, f.zabel@lmu.de, Department für Geographie, LMU München (www.geografie.uni-muenchen.de) This research was carried out within the framework of the GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) Project, which has been supported by the German Ministry of Education and Research (BMBF) program on sustainable land management (grant number: 01LL0901E).

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    ZENODO
    Dataset . 2016
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2016
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2016
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2016
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2016
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2016
      License: CC BY
      Data sources: ZENODO
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  • Authors: Rafael Eigenmann; Thomas Foken;

    Project: Convective and Orographically-induced Precipitation Study - Weather forecast models have not been successful in improving the Quantitative Precipitation Forecast during the last 16 years. One reason for this stagnation is the lack of comprehensive, high-quality data sets usable for model validation as well as for data assimilation, thus leading to improved initial fields in numerical models. Theoretical analyses have identified the requirements measured data have to meet in order to close the gaps in process understanding. In field campaigns, it has been shown that the newest generation of remote sensing systems has the potential to yield data sets of the required quality. It is therefore time to combine the most powerful remote sensing instruments with proven ground-based and airborne measurement techniques in an Intensive Observations Period (IOP). Its goal is to serve as a backbone for the Priority Program SPP 1167 by producing the demanded data sets of unachieved accuracy and resolution. This requires a sophisticated scientific preparation and a careful coordination between the efforts of the institutions involved. For the first time, the pre-convective environment, the formation of clouds and the onset and development of precipitation as well as its intensity will be observed in four dimensions simultaneously in a region of sufficient size. This shall be achieved by combining the IOP with international programs and by collaboration between leading scientists in Europe, US, and other countries. Thus, the IOP, which we call Convective and Orographically-induced Precipitation Study (COPS), is a unique opportunity for an international field campaign featuring the newest generation of measurement systems such as scanning radar and lidar and leading to outstanding advances in atmospheric sciences. Please be aware of the common COPS/GOP/D-PHASE data policy, which you please find at http://cops.wdc-climate.de/ Summary: The energy balance stations run by University of Bayreuth continuously measured radiation and soil parameters over different land types with a sampling frequency of 1 Hz averaged to 1 min values within the data logger. After a check for plausibility the 1 min values have been averaged to 30 min intervals, which are provided in this data set. The instrumentation was different on each location. The following was measured depending on the station: - soil heat flux - soil temperature - volumetric soil water content - longwave radiation components - shortwave radiation components - tipping bucket rain gauge measurements The ground heat flux including the heat storage in the upper soil layer was determined from the measured soil heat flux, soil temperatures and volumetric soil water contents according to the 'simple measurement' (SM) method according to Liebethal and Foken (2007).

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    Authors: Srivastava, Amit Kumar;

    The yield gap for maize across the Ethiopia has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management. The yield gap of a crop grown in a certain location and cropping system is defined as the difference between the yield and biomass under optimum management and the average yield achieved by farmers. Yield under optimum management is labeled as potential yield (Yp) under irrigated conditions or water-limited potential yield (Yw) under rain-fed conditions.Yp is location specific because of the climate, and not dependent on soil properties assuming that the required water and nutrients are non-limiting and can be added through management. Thus, in areas without major soil constraints, Yp is the most relevant benchmark for irrigated systems. Whereas, for rain-fed crops, Yw, equivalent to water-limited potential yield, is the most relevant benchmark. Both Yp and Yw are calculated for optimum planting dates, planting density and region-specific crop variety which is critical in determining the feasible growth duration, particularly in tropical climatic conditions where two or even three crops are produced each year on the same field. Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Yield gaps, thus considering the spatial variation in environment and the production system. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c2bbd5ed-fd4c-4a3f-b0b1-113a5d4f3ddf}. The yield gaps plotted in the map were calculated as the average values of 7 years (the year 2004 -2010). The unit is Megagram per hectare (Mg ha-1) which is equivalent to tons ha-1. The climate data at the national scale was made available from the National Aeronautics and Space Administration (NASA), Goddard Institute of Space Studies(https://data.giss.nasa.gov/impacts/agmipcf/agmerra/), AgMERRA.The dataset is stored at 0.25°×0.25° horizontal resolution (~25km). Soil parameter values were extracted from the soil property maps of Africa at 1 km x 1 km resolution (http://www.isric.org/data/soil-property-maps-africa-1-km). Maize yields (Mg ha-1) and fertilizer application (Nitrogen and Phosphorus) rates over seven years (2004 - 2010) at administrative zone level have been collected from the Central Statistical Agency, Ethiopia.

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    https://dx.doi.org/10.60507/fk...
    Dataset . 2023
    License: CC BY SA
    Data sources: Datacite
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      https://dx.doi.org/10.60507/fk...
      Dataset . 2023
      License: CC BY SA
      Data sources: Datacite
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    Authors: Leybourne, Daniel J; Preedy, Katharine F; Valentine, Tracy A; Bos, Jorunn I B; +1 Authors

    1. Aphids are abundant in natural and managed vegetation, supporting a diverse community of organisms and causing damage to agricultural crops. Due to a changing climate, periods of drought are anticipated to increase, and the potential consequences of this for aphid-plant interactions are unclear. 2. Using a meta-analysis and synthesis approach, we aimed to advance understanding of how increased drought incidence will affect this ecologically and economically important insect group, and to characterise any potential underlying mechanisms. We used qualitative and quantitative synthesis techniques to determine whether drought stress has a negative, positive, or null effect on aphid fitness and examined these effects in relation to 1) aphid biology, 2) geographical region, 3) host plant biology. 3. Across all studies, aphid fitness is typically reduced under drought. Subgroup analysis detected no difference in relation to aphid biology, geographical region, or the aphid-plant combination, indicating the negative effect of drought on aphids is potentially universal. Furthermore, drought stress had a negative impact on plant vigour and increased plant concentrations of defensive chemicals, suggesting the observed response of aphids is associated with reduced plant vigour and increased chemical defence in drought-stressed plants. 4. We propose a conceptual model to predict drought effects on aphid fitness in relation to plant vigour and defence to stimulate further research. Please check the ReadMe for an explanation of the values included in the dataset. Please note that n/a values are included in the Global_Dataset tab for plant meta-analysis data (_Plant_Vigour, _Plant_Defence, and _Plant_Nutrition), these indicate studies that did not report these parameters. Data was collected and curated using standard systematic literature synthesis approaches. The effect size (Hedges' g) reported in the dataset was calculated from extracted means and standard deviations.

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
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    Authors: Tian, Ke (Institute of Organic Chemistry, Heidelberg University); Elbert, Sven Michael (Institute of Organic Chemistry, Heidelberg University); Hu, Xinyue (Institute of Organic Chemistry, Heidelberg University); Kirschbaum, Tobias (Institute of Organic Chemistry, Heidelberg University); +4 Authors

    Anthropogenic greenhouse gases contribute to global warming. Among those gases, perfluorocarbons (PFCs) are thousands to tens of thousands times more harmful to the environment than comparable amounts of carbon dioxide. Till date, materials that selectively adsorb perfluorocarbons in favor to other less harmful gases have not been reported. Here a series of porous organic cage compounds with alkyl-, fluoroalkyl, and partially fluorinated alkyl groups are presented. Their isomorphic crystalline states allowed us to study the property-relationship of the degree of fluorination of the alkyl chains on gas sorption properties for PFCs and their selective uptakes in comparison to other, non-fluorinated gases. By this approach, one compound was identified, having superior selectivities of PFCs vs N2 or CO2 under ambient conditions.

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    B2FIND
    Dataset . 2022
    Data sources: B2FIND
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      B2FIND
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Winchester, Benedict; Huang, Gan; Beath, Hamish; Sandwell, Philip; +3 Authors

    Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants. The updated results are from optimisations runs carried out in response to peer-review comments.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sanchez-Benítez, Antonio; Goessling, Helge; Pithan, Felix; Semmler, Tido; +1 Authors

    We provide the storyline data (in NetCDF format) used in the paper: ���The July 2019 European heatwave in a warmer climate: Storyline scenarios with a coupled model using spectral nudging��� published in Journal of Climate. The data is structured in four .tar.gz files (Preindustrial, Present, 2 and 4 K warmer climates) containing all variables used in this each climate. The data from the five ensemble members (E1 to E5) have been included separately in 3-months files. Atmospheric variables (Files are named as: {variable}_E{ensemble member}_{starting month}{year}.nc: Latent heat flux (ahfl) Sensible heat flux (ahfs) Monthly Global Mean 2m Temperature (GMTT2mMonthly) Maximum 2m Temperature (t2max) Mean 2m Temperature (t2mean) Minimum 2m Temperature (t2max) Soil Wetness (ws) Only for present climate: 850 hPa Temperature (T850) Total Cloud Cover (TCC) 500 hPa Geopotential Height (Z500) Five layers soil moisture (Only for present climate, Files are named as: From20172019in2017Climatessp370{ensemble member}_{year}{starting month}.01_jsbid.nc) Oceanic variables (from FESOM, Files are named as: {variable}_E{ensemble member}_{year}{starting month}01.nc: Sea Ice Concentration (SIC) Sea Surface Temperature (SST) Please, note that FESOM uses an unstructured mesh. This work was supported by the Helmholtz-Climate-Initiative through the HI-CAM project (Drivers cluster). Author Goessling acknowledges the financial support by the Federal Ministry of Education and Research of Germany in the framework of SSIP (Grant 01LN1701A). The simulations were performed at the German Climate Computing Center (DKRZ) using the ESM-Tools (Barbi et al. 2021). We thank Sebastian Rast (MPI-M) for support with the spectral nudging in ECHAM, and the ESM-Tools staff for their assistance during the simulation.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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  • Authors: Sampugnaro, Rossana; Santoro, Patrizia;

    The pandemic caused by Covid-19 has tested the resilience of public institutions, already burdened by a deep and complex crisis (political, economic, managerial). This crisis has revealed a discrepancy between the needs expressed by the community and the solutions adopted to satisfy them. This has been accompanied by a progressive worsening of decision-making efficiency and weak implementation capacity in a context of increasing environmental uncertainty. It is in local institutions, in particular, that the greatest problems are revealed, because of many endemic negative factors: political fragmentation, reduced economic resources, new forms of poverty. Against the background of this scenario, our study aims to analyze the reaction of local institutions to the pandemic crisis by looking at both welfare and communication services. The objective is to identify key features in understanding the resilience of municipalities. In other words, their ability to react and adapt to change, which is essential not only to deal with emergencies, such as the pandemic, but also to make the institution itself sustainable. Our interest is focused on a specific dimension of the resilience of the municipalities, related to collaboration with the third sector. The pandemic has shown that the continuous activism of non-profit organizations has allowed for the continuation of many so-called "ordinary" services, as well as the launch of several initiatives aimed at alleviating other social problems. The research has, first of all, an exploratory character that befits a new and still ongoing phenomenon. The basic questions concern the production of local welfare policies by municipalities. The data show different levels of "interventism" and different modes of communication. On this latter point, we observe the presence of significant attention-seeking among Mayors as community builders able, on the one hand, to reinforce the spirit of solidarity and, on the other, to uphold respect for the rules. On the services side, three main models of response to the pandemic emerge, two of which refer to the public-private relationship in local welfare policies. Findings suggest that these different reactions will have consequences in the immediate future for the management of the pandemic crisis (still ongoing). Specifically, the tendency is to employ a management of services based on partnership-model, which means that public-private collaboration is a pillar of local welfare. This seems to entail a greater legitimacy for individuals or associations to participate in the formulation and implementation of policies.

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    Authors: Robroek, Bjorn J.M.; Jassey, Vincent E.J.; Payne, Richard J.; Martí, Magalí; +10 Authors

    Environmental dataBioclimatic data and environmental data for all 56 European peatland site (geo referenced by longitude [long], latitude [lat] and altitude [ALT]. MAT = Mean annual temperature (°C), TS = Seasonality in temperature, MAP = Mean annual precipitation (mm), PS = Seasonality in precipitation, tot_sox = Total sulphur deposition SOx (mg m-2 yr-1), tot_noy = Total oxidized nitrogen deposition (mg m-2 yr-1), tot_nhx = Total reduced nitrogen deposition (mg m-2), PT warm = Lang’s moisture index. The four bioclimatic variables (MAT, TS, MAP, PS) were extracted from the WorldClim database (Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005)), and averaged over the 2000-2009 period. Atmospheric deposition data were produced using the EMEP (European Monitoring and Evaluation Programme)-based IDEM (Integrated Deposition Model) model (Pieterse, G., Bleeker, A., Vermeulen, A. T., Wu, Y. & Erisman, J. W. High resolution modelling of atmosphere‐canopy exchange of acidifying and eutrophying components and carbon dioxide for European forests. Tellus B 59, 412–424 (2007)) and consisted of grid cell averages of total reduced (NHx) and oxidised (NOy) nitrogen and sulphur (SOx) deposition. The moisture index (PTwarm) was calculated as the ratio between mean precipitation and mean temperature in the warmest quarter (Thornwaite, C. W. & Holzman, B. Measurement of evaporation from land and water surfaces. USDA Technical Bulletin 817, 1–143 (1942))Data 1_environmental data.txtplant community dataAbundance data (% cover) for all vascular plant and bryophyte species from five randomly chosen hummocks and lawns (0.25 m2 quadrats; ten in total) across 56 European Sphagnum-dominated peatlands were collected in two consecutive summers (2010 and 2011). Vascular plants and Sphagnum mosses were identified to the species level. Non-Sphagnum bryophytes were identified to the family level. Lichens were recorded as one group.Data 2_plant community data.txttraits vascular plantsPlant functional traits used to calculate functional indices for the vascular plant communities. Traits were extracted from LEDA (Kleyer, M. et al. The LEDA Traitbase: a database of life‐history traits of the Northwest European flora. J. Ecol. 96, 1266–1274 (2008)). Only trait data available for all species our data-set were extracted.ncomms_Data 3_traits vascular plants.txttraits SphagnumTrait values (means) for Sphagnum spp. C = tissue carbon content (mg g-1), N = tissue nitrogen content (mg g-1), P = tissue phosphorus content (mg g-1), Productivity ( St.w = stem width (mm), l.h.c. = length hyaline cells (µm), w.h.c. = width hyaline cells (µm), l.s.l. = length stem leaves (mm), w.s.l. = width stem leaves. These measured traits were complemented with traits extracted from the literature. These latter traits included plant length (Hill, M. O., Preston, C. D., Bosanquet, S. & Roy, D. B. BRYOATT: attributes of British and Irish mosses, liverworts and hornworts. Centre for Ecology & Hydrology, Huntingdon, UK (2007)), spore diameter and capsule diameter (Sundberg, S., Hansson, J. & Rydin, H. Colonization of Sphagnum on land uplift islands in the Baltic Sea: time, area, distance and life history. Journal of Biogeography 33, 1479–1491 (2006)), productivity (Gunnarsson, U. Global patterns of Sphagnum productivity. J. Bryol. 27, 269–279 (2005))ncomms_Data 4_traits Sphagnum.txt In peatland ecosystems, plant communities mediate a globally significant carbon store. The effects of global environmental change on plant assemblages are expected to be a factor in determining how ecosystem functions such as carbon uptake will respond. Using vegetation data from 56 Sphagnum-dominated peat bogs across Europe, we show that in these ecosystems plant species aggregate into two major clusters that are each defined by shared response to environmental conditions. Across environmental gradients, we find significant taxonomic turnover in both clusters. However, functional identity and functional redundancy of the community as a whole remain unchanged. This strongly suggests that in peat bogs, species turnover across environmental gradients is restricted to functionally similar species. Our results demonstrate that plant taxonomic and functional turnover are decoupled, which may allow these peat bogs to maintain ecosystem functioning when subject to future environmental change.

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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Research@WUR
    Dataset . 2017
    Data sources: Research@WUR
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    EASY
    Dataset . 2017
    Data sources: EASY
    DRYAD
    Dataset . 2018
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
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      B2FIND
      Dataset . 2017
      Data sources: B2FIND
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Research@WUR
      Dataset . 2017
      Data sources: Research@WUR
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      EASY
      Dataset . 2017
      Data sources: EASY
      DRYAD
      Dataset . 2018
      License: CC 0
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    Authors: Aman Malik; Christoph Bertram; Elmar Krigler; Gunnar Luderer;

    The file contains code to create the figures used in main text and supplementary information of the paper Climate policy accelerates structural changes in energy employment. To run the RMD file and see the resulting figures, press Knit on R studio (requires the package knitr), or else see the attached HTML file, already created through such a process. Additional funding source: University of Tokyo's "Global Commons Stewardship Framework" project.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
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      Dataset . 2021
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      Dataset . 2021
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    Natural potentials for future cropland expansion The potential for the expansion of cropland is restricted by the availability of land resources and given local natural conditions. As a result, area that is highly suitable for agriculture according to the prevailing local biophysical conditions but is not under cultivation today has a high natural potential for expansion. Policy regulations can further restrict the availability of land for expansion by designating protected areas, although they may be suitable for agriculture. Conversely, by applying e.g. irrigation practices, land can be brought under cultivation, although it may naturally not be suitable. Here, we investigate the potentials for agricultural expansion for near future climate scenario conditions to identify the suitability of non-cropland areas for expansion according to their local natural conditions. We determine the available energy, water and nutrient supply for agricultural suitability from climate, soil and topography data, by using a fuzzy logic approach according to Zabel et al. (2014). It considers the 16 globally most important staple and energy crops. These are: barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, rye, sorghum, soy, sugarcane, sunflower, summer wheat, winter wheat. The parameterization of the membership functions that describe each of the crops’ specific natural requirements is taken from Sys et al. (1993). The considered natural conditions are: climate (temperature, precipitation, solar radiation), soil properties (texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity), and topography (elevation, slope). As a result of the fuzzy logic approach, values in a range between 0 and 1 describe the suitability of a crop for each of the prevailing natural conditions at a certain location. The smallest suitability value over all parameters finally determines the suitability of a crop. The daily climate data is provided by simulation results from the global climate model ECHAM5 (Jungclaus et al. 2006) for near future (2011-2040) SRES A1B climate scenario conditions. Soil data is taken from the Harmonized World Soil Database (HWSD) (FAO et al. 2012), and topography data is applied from the Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007). In order to gather a general crop suitability, which does not refer to one specific crop, the most suitable crop with the highest suitability value is chosen at each pixel. In addition the natural biophysical conditions, we consider today’s irrigated areas according to (Siebert et al. 2013). We assume that irrigated areas globally remain constant until 2040, since adequate data on the development of irrigated areas do not exist, although it is likely that freshwater availability for irrigation could be limited in some regions, while in other regions surplus water supply could be used to expand irrigation practices (Elliott et al. 2014). However, it is difficult to project where irrigation practices will evolve, since it is driven by economic investment costs that are required to establish irrigation infrastructure. In principle, all agriculturally suitable land that is not used as cropland today has the natural potential to be converted into cropland. We assume that only urban and built-up areas are not available for conversion, although more than 80% of global urban areas are agriculturally suitable (Avellan et al. 2012). However, it seems unlikely that urban areas will be cleared at the large scale due to high investment costs, growing cities and growing demand for settlements. Concepts of urban and vertical farming usually are discussed under the aspects of cultivating fresh vegetables and salads for urban population. They are not designed to extensively grow staple crops such as wheat or maize for feeding the world in the near future. Urban farming would require one third of the total global urban area to meet only the global vegetable consumption of urban dwellers (Martellozzo et al. 2015). Thus, urban agriculture cannot substantially contribute to global agricultural production of staple crops. Protected areas or dense forested areas are not excluded from the calculation, in order not to lose any information in the further combination with the biodiversity patterns (see chapter 2.3). We use data on current cropland distribution by Ramankutty et al. (2008) and urban and built-up area according to the ESA-CCI land use/cover dataset (ESA 2014). From this data, we calculate the ‘natural expansion potential index’ (Iexp) that expresses the natural potential for an area to be converted into cropland as follows: Iexp = S * Aav The index is determined by the quality of agricultural suitability (S) (values between 0 and 1) multiplied with the amount of available area (Aav) for conversion (in percentage of pixel area). The available area includes all suitable area that is not cultivated today, and not classified as urban or artificial area. The index ranges between 0 and 100 and indicates where the conditions for cropland expansion are more or less favorable, when taking only natural conditions into account, disregarding socio-economic factors, policies and regulations that drive or inhibit cropland expansion. The index is a helpful indicator for identifying areas where cropland expansion could take place in the near future. Further information Detailled information are available in the following publication: Delzeit, R., F. Zabel, C. Meyer and T. Václavík (2017). Addressing future trade-offs between biodiversity and cropland expansion to improve food security. Regional Environmental Change 17(5): 1429-1441. DOI: 10.1007/s10113-016-0927-1 Contact Please contact: Dr. Florian Zabel, f.zabel@lmu.de, Department für Geographie, LMU München (www.geografie.uni-muenchen.de) This research was carried out within the framework of the GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) Project, which has been supported by the German Ministry of Education and Research (BMBF) program on sustainable land management (grant number: 01LL0901E).

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    ZENODO
    Dataset . 2016
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2016
    License: CC BY
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    ZENODO
    Dataset . 2016
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      ZENODO
      Dataset . 2016
      License: CC BY
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      ZENODO
      Dataset . 2016
      License: CC BY
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      ZENODO
      Dataset . 2016
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  • Authors: Rafael Eigenmann; Thomas Foken;

    Project: Convective and Orographically-induced Precipitation Study - Weather forecast models have not been successful in improving the Quantitative Precipitation Forecast during the last 16 years. One reason for this stagnation is the lack of comprehensive, high-quality data sets usable for model validation as well as for data assimilation, thus leading to improved initial fields in numerical models. Theoretical analyses have identified the requirements measured data have to meet in order to close the gaps in process understanding. In field campaigns, it has been shown that the newest generation of remote sensing systems has the potential to yield data sets of the required quality. It is therefore time to combine the most powerful remote sensing instruments with proven ground-based and airborne measurement techniques in an Intensive Observations Period (IOP). Its goal is to serve as a backbone for the Priority Program SPP 1167 by producing the demanded data sets of unachieved accuracy and resolution. This requires a sophisticated scientific preparation and a careful coordination between the efforts of the institutions involved. For the first time, the pre-convective environment, the formation of clouds and the onset and development of precipitation as well as its intensity will be observed in four dimensions simultaneously in a region of sufficient size. This shall be achieved by combining the IOP with international programs and by collaboration between leading scientists in Europe, US, and other countries. Thus, the IOP, which we call Convective and Orographically-induced Precipitation Study (COPS), is a unique opportunity for an international field campaign featuring the newest generation of measurement systems such as scanning radar and lidar and leading to outstanding advances in atmospheric sciences. Please be aware of the common COPS/GOP/D-PHASE data policy, which you please find at http://cops.wdc-climate.de/ Summary: The energy balance stations run by University of Bayreuth continuously measured radiation and soil parameters over different land types with a sampling frequency of 1 Hz averaged to 1 min values within the data logger. After a check for plausibility the 1 min values have been averaged to 30 min intervals, which are provided in this data set. The instrumentation was different on each location. The following was measured depending on the station: - soil heat flux - soil temperature - volumetric soil water content - longwave radiation components - shortwave radiation components - tipping bucket rain gauge measurements The ground heat flux including the heat storage in the upper soil layer was determined from the measured soil heat flux, soil temperatures and volumetric soil water contents according to the 'simple measurement' (SM) method according to Liebethal and Foken (2007).

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    Authors: Srivastava, Amit Kumar;

    The yield gap for maize across the Ethiopia has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management. The yield gap of a crop grown in a certain location and cropping system is defined as the difference between the yield and biomass under optimum management and the average yield achieved by farmers. Yield under optimum management is labeled as potential yield (Yp) under irrigated conditions or water-limited potential yield (Yw) under rain-fed conditions.Yp is location specific because of the climate, and not dependent on soil properties assuming that the required water and nutrients are non-limiting and can be added through management. Thus, in areas without major soil constraints, Yp is the most relevant benchmark for irrigated systems. Whereas, for rain-fed crops, Yw, equivalent to water-limited potential yield, is the most relevant benchmark. Both Yp and Yw are calculated for optimum planting dates, planting density and region-specific crop variety which is critical in determining the feasible growth duration, particularly in tropical climatic conditions where two or even three crops are produced each year on the same field. Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Yield gaps, thus considering the spatial variation in environment and the production system. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c2bbd5ed-fd4c-4a3f-b0b1-113a5d4f3ddf}. The yield gaps plotted in the map were calculated as the average values of 7 years (the year 2004 -2010). The unit is Megagram per hectare (Mg ha-1) which is equivalent to tons ha-1. The climate data at the national scale was made available from the National Aeronautics and Space Administration (NASA), Goddard Institute of Space Studies(https://data.giss.nasa.gov/impacts/agmipcf/agmerra/), AgMERRA.The dataset is stored at 0.25°×0.25° horizontal resolution (~25km). Soil parameter values were extracted from the soil property maps of Africa at 1 km x 1 km resolution (http://www.isric.org/data/soil-property-maps-africa-1-km). Maize yields (Mg ha-1) and fertilizer application (Nitrogen and Phosphorus) rates over seven years (2004 - 2010) at administrative zone level have been collected from the Central Statistical Agency, Ethiopia.

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    https://dx.doi.org/10.60507/fk...
    Dataset . 2023
    License: CC BY SA
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      https://dx.doi.org/10.60507/fk...
      Dataset . 2023
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    Authors: Leybourne, Daniel J; Preedy, Katharine F; Valentine, Tracy A; Bos, Jorunn I B; +1 Authors

    1. Aphids are abundant in natural and managed vegetation, supporting a diverse community of organisms and causing damage to agricultural crops. Due to a changing climate, periods of drought are anticipated to increase, and the potential consequences of this for aphid-plant interactions are unclear. 2. Using a meta-analysis and synthesis approach, we aimed to advance understanding of how increased drought incidence will affect this ecologically and economically important insect group, and to characterise any potential underlying mechanisms. We used qualitative and quantitative synthesis techniques to determine whether drought stress has a negative, positive, or null effect on aphid fitness and examined these effects in relation to 1) aphid biology, 2) geographical region, 3) host plant biology. 3. Across all studies, aphid fitness is typically reduced under drought. Subgroup analysis detected no difference in relation to aphid biology, geographical region, or the aphid-plant combination, indicating the negative effect of drought on aphids is potentially universal. Furthermore, drought stress had a negative impact on plant vigour and increased plant concentrations of defensive chemicals, suggesting the observed response of aphids is associated with reduced plant vigour and increased chemical defence in drought-stressed plants. 4. We propose a conceptual model to predict drought effects on aphid fitness in relation to plant vigour and defence to stimulate further research. Please check the ReadMe for an explanation of the values included in the dataset. Please note that n/a values are included in the Global_Dataset tab for plant meta-analysis data (_Plant_Vigour, _Plant_Defence, and _Plant_Nutrition), these indicate studies that did not report these parameters. Data was collected and curated using standard systematic literature synthesis approaches. The effect size (Hedges' g) reported in the dataset was calculated from extracted means and standard deviations.

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC 0
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      DRYAD
      Dataset . 2021
      License: CC 0
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    Authors: Tian, Ke (Institute of Organic Chemistry, Heidelberg University); Elbert, Sven Michael (Institute of Organic Chemistry, Heidelberg University); Hu, Xinyue (Institute of Organic Chemistry, Heidelberg University); Kirschbaum, Tobias (Institute of Organic Chemistry, Heidelberg University); +4 Authors

    Anthropogenic greenhouse gases contribute to global warming. Among those gases, perfluorocarbons (PFCs) are thousands to tens of thousands times more harmful to the environment than comparable amounts of carbon dioxide. Till date, materials that selectively adsorb perfluorocarbons in favor to other less harmful gases have not been reported. Here a series of porous organic cage compounds with alkyl-, fluoroalkyl, and partially fluorinated alkyl groups are presented. Their isomorphic crystalline states allowed us to study the property-relationship of the degree of fluorination of the alkyl chains on gas sorption properties for PFCs and their selective uptakes in comparison to other, non-fluorinated gases. By this approach, one compound was identified, having superior selectivities of PFCs vs N2 or CO2 under ambient conditions.

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    B2FIND
    Dataset . 2022
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      B2FIND
      Dataset . 2022
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    Authors: Winchester, Benedict; Huang, Gan; Beath, Hamish; Sandwell, Philip; +3 Authors

    Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants. The updated results are from optimisations runs carried out in response to peer-review comments.

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    ZENODO
    Dataset . 2023
    License: CC BY
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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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    ZENODO
    Dataset . 2023
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sanchez-Benítez, Antonio; Goessling, Helge; Pithan, Felix; Semmler, Tido; +1 Authors

    We provide the storyline data (in NetCDF format) used in the paper: ���The July 2019 European heatwave in a warmer climate: Storyline scenarios with a coupled model using spectral nudging��� published in Journal of Climate. The data is structured in four .tar.gz files (Preindustrial, Present, 2 and 4 K warmer climates) containing all variables used in this each climate. The data from the five ensemble members (E1 to E5) have been included separately in 3-months files. Atmospheric variables (Files are named as: {variable}_E{ensemble member}_{starting month}{year}.nc: Latent heat flux (ahfl) Sensible heat flux (ahfs) Monthly Global Mean 2m Temperature (GMTT2mMonthly) Maximum 2m Temperature (t2max) Mean 2m Temperature (t2mean) Minimum 2m Temperature (t2max) Soil Wetness (ws) Only for present climate: 850 hPa Temperature (T850) Total Cloud Cover (TCC) 500 hPa Geopotential Height (Z500) Five layers soil moisture (Only for present climate, Files are named as: From20172019in2017Climatessp370{ensemble member}_{year}{starting month}.01_jsbid.nc) Oceanic variables (from FESOM, Files are named as: {variable}_E{ensemble member}_{year}{starting month}01.nc: Sea Ice Concentration (SIC) Sea Surface Temperature (SST) Please, note that FESOM uses an unstructured mesh. This work was supported by the Helmholtz-Climate-Initiative through the HI-CAM project (Drivers cluster). Author Goessling acknowledges the financial support by the Federal Ministry of Education and Research of Germany in the framework of SSIP (Grant 01LN1701A). The simulations were performed at the German Climate Computing Center (DKRZ) using the ESM-Tools (Barbi et al. 2021). We thank Sebastian Rast (MPI-M) for support with the spectral nudging in ECHAM, and the ESM-Tools staff for their assistance during the simulation.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • Authors: Sampugnaro, Rossana; Santoro, Patrizia;

    The pandemic caused by Covid-19 has tested the resilience of public institutions, already burdened by a deep and complex crisis (political, economic, managerial). This crisis has revealed a discrepancy between the needs expressed by the community and the solutions adopted to satisfy them. This has been accompanied by a progressive worsening of decision-making efficiency and weak implementation capacity in a context of increasing environmental uncertainty. It is in local institutions, in particular, that the greatest problems are revealed, because of many endemic negative factors: political fragmentation, reduced economic resources, new forms of poverty. Against the background of this scenario, our study aims to analyze the reaction of local institutions to the pandemic crisis by looking at both welfare and communication services. The objective is to identify key features in understanding the resilience of municipalities. In other words, their ability to react and adapt to change, which is essential not only to deal with emergencies, such as the pandemic, but also to make the institution itself sustainable. Our interest is focused on a specific dimension of the resilience of the municipalities, related to collaboration with the third sector. The pandemic has shown that the continuous activism of non-profit organizations has allowed for the continuation of many so-called "ordinary" services, as well as the launch of several initiatives aimed at alleviating other social problems. The research has, first of all, an exploratory character that befits a new and still ongoing phenomenon. The basic questions concern the production of local welfare policies by municipalities. The data show different levels of "interventism" and different modes of communication. On this latter point, we observe the presence of significant attention-seeking among Mayors as community builders able, on the one hand, to reinforce the spirit of solidarity and, on the other, to uphold respect for the rules. On the services side, three main models of response to the pandemic emerge, two of which refer to the public-private relationship in local welfare policies. Findings suggest that these different reactions will have consequences in the immediate future for the management of the pandemic crisis (still ongoing). Specifically, the tendency is to employ a management of services based on partnership-model, which means that public-private collaboration is a pillar of local welfare. This seems to entail a greater legitimacy for individuals or associations to participate in the formulation and implementation of policies.

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    Authors: Robroek, Bjorn J.M.; Jassey, Vincent E.J.; Payne, Richard J.; Martí, Magalí; +10 Authors

    Environmental dataBioclimatic data and environmental data for all 56 European peatland site (geo referenced by longitude [long], latitude [lat] and altitude [ALT]. MAT = Mean annual temperature (°C), TS = Seasonality in temperature, MAP = Mean annual precipitation (mm), PS = Seasonality in precipitation, tot_sox = Total sulphur deposition SOx (mg m-2 yr-1), tot_noy = Total oxidized nitrogen deposition (mg m-2 yr-1), tot_nhx = Total reduced nitrogen deposition (mg m-2), PT warm = Lang’s moisture index. The four bioclimatic variables (MAT, TS, MAP, PS) were extracted from the WorldClim database (Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005)), and averaged over the 2000-2009 period. Atmospheric deposition data were produced using the EMEP (European Monitoring and Evaluation Programme)-based IDEM (Integrated Deposition Model) model (Pieterse, G., Bleeker, A., Vermeulen, A. T., Wu, Y. & Erisman, J. W. High resolution modelling of atmosphere‐canopy exchange of acidifying and eutrophying components and carbon dioxide for European forests. Tellus B 59, 412–424 (2007)) and consisted of grid cell averages of total reduced (NHx) and oxidised (NOy) nitrogen and sulphur (SOx) deposition. The moisture index (PTwarm) was calculated as the ratio between mean precipitation and mean temperature in the warmest quarter (Thornwaite, C. W. & Holzman, B. Measurement of evaporation from land and water surfaces. USDA Technical Bulletin 817, 1–143 (1942))Data 1_environmental data.txtplant community dataAbundance data (% cover) for all vascular plant and bryophyte species from five randomly chosen hummocks and lawns (0.25 m2 quadrats; ten in total) across 56 European Sphagnum-dominated peatlands were collected in two consecutive summers (2010 and 2011). Vascular plants and Sphagnum mosses were identified to the species level. Non-Sphagnum bryophytes were identified to the family level. Lichens were recorded as one group.Data 2_plant community data.txttraits vascular plantsPlant functional traits used to calculate functional indices for the vascular plant communities. Traits were extracted from LEDA (Kleyer, M. et al. The LEDA Traitbase: a database of life‐history traits of the Northwest European flora. J. Ecol. 96, 1266–1274 (2008)). Only trait data available for all species our data-set were extracted.ncomms_Data 3_traits vascular plants.txttraits SphagnumTrait values (means) for Sphagnum spp. C = tissue carbon content (mg g-1), N = tissue nitrogen content (mg g-1), P = tissue phosphorus content (mg g-1), Productivity ( St.w = stem width (mm), l.h.c. = length hyaline cells (µm), w.h.c. = width hyaline cells (µm), l.s.l. = length stem leaves (mm), w.s.l. = width stem leaves. These measured traits were complemented with traits extracted from the literature. These latter traits included plant length (Hill, M. O., Preston, C. D., Bosanquet, S. & Roy, D. B. BRYOATT: attributes of British and Irish mosses, liverworts and hornworts. Centre for Ecology & Hydrology, Huntingdon, UK (2007)), spore diameter and capsule diameter (Sundberg, S., Hansson, J. & Rydin, H. Colonization of Sphagnum on land uplift islands in the Baltic Sea: time, area, distance and life history. Journal of Biogeography 33, 1479–1491 (2006)), productivity (Gunnarsson, U. Global patterns of Sphagnum productivity. J. Bryol. 27, 269–279 (2005))ncomms_Data 4_traits Sphagnum.txt In peatland ecosystems, plant communities mediate a globally significant carbon store. The effects of global environmental change on plant assemblages are expected to be a factor in determining how ecosystem functions such as carbon uptake will respond. Using vegetation data from 56 Sphagnum-dominated peat bogs across Europe, we show that in these ecosystems plant species aggregate into two major clusters that are each defined by shared response to environmental conditions. Across environmental gradients, we find significant taxonomic turnover in both clusters. However, functional identity and functional redundancy of the community as a whole remain unchanged. This strongly suggests that in peat bogs, species turnover across environmental gradients is restricted to functionally similar species. Our results demonstrate that plant taxonomic and functional turnover are decoupled, which may allow these peat bogs to maintain ecosystem functioning when subject to future environmental change.

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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
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    Research@WUR
    Dataset . 2017
    Data sources: Research@WUR
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    EASY
    Dataset . 2017
    Data sources: EASY
    DRYAD
    Dataset . 2018
    License: CC 0
    Data sources: Datacite
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      Dataset . 2018
      License: CC 0
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      B2FIND
      Dataset . 2017
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      Research@WUR
      Dataset . 2017
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      EASY
      Dataset . 2017
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      Dataset . 2018
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    Authors: Aman Malik; Christoph Bertram; Elmar Krigler; Gunnar Luderer;

    The file contains code to create the figures used in main text and supplementary information of the paper Climate policy accelerates structural changes in energy employment. To run the RMD file and see the resulting figures, press Knit on R studio (requires the package knitr), or else see the attached HTML file, already created through such a process. Additional funding source: University of Tokyo's "Global Commons Stewardship Framework" project.

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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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    ZENODO
    Dataset . 2021
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      Dataset . 2021
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      Dataset . 2021
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