en: anisotropy microstructure crystallographic fem elasticity x-ray-tomography geometrical

en:
The study aims to determine the effective elastic properties of snow, firn, and bubbly ice based on microstructural quantities. Anisotropy, one of these quantities (the other being ice volume fraction) in snow and ice, has two types: geometrical and crystallographic, resulting in snow's macroscopic anisotropic elastic behavior. The research focuses on the impact of geometrical anisotropy on potential ice volume fractions in snow and ice. 391 micro-CT images from various locations, including laboratories, the Alps, the Arctic, and Antarctica, were analyzed to achieve this.
 The analysis involved microstructure-based finite element simulations, which inherently consider microstructure and calculate the elasticity tensor. Hashin-Shtrikman bounds were utilized to predict the elastic properties of the microstructure samples. These bounds effectively captured the nonlinear interplay between geometrical anisotropy, captured by the Eshelby tensor and density. HS bounds have the advantage of the correct limiting behavior for low to high-ice volume fractions.
 We derived parameterization for five transversely isotropic elasticity tensor components, requiring only two free parameters. This parameterization was valid for ice volume fractions ranging from 0.06 to 0.93. The analysis employing the Thomsen parameter highlighted the dominance of geometrical anisotropy until an ice volume fraction of 0.7. However, to fully comprehend the elasticity of bubbly ice, a comprehensive approach is necessary to integrate coupled elastic theories that account for both geometrical and crystallographic anisotropy.
This dataset includes a Jupyter notebook with all the necessary functions required to predict the elasticity tensor of snow for the given ice volume fraction and anisotropy. Also, the code contains the least squares optimization function to compute the elasticity tensor for the six components of stress and strain. For example, we consider our dataset to calculate the samples' elasticity tensor and reproduce Fig. 7 from the paper. We take the stress and strain values obtained from load states as input for this example.
Also, a .csv file contains all the microstructural information: ice volume fraction, anisotropy, correlation functions, voxels size, and no. of voxels of the samples and the elasticity tensor obtained from finite element simulations and from present work parameterization.

anisotropy

display_name: anisotropy

crystallographic

display_name: crystallographic

elasticity

display_name: elasticity

fem

display_name: fem

geometrical

display_name: geometrical

microstructure

display_name: microstructure

x-ray-tomography

display_name: x-ray-tomography

educ

en: Education, culture and sport

en: Effective, anisotropic elasticity tensor of snow, firn, and bubbly ice


maintainer: EnviDat Support

en: snow-depth airborne-laser-scanning canopy-height snow-distribution forest-structure

state: active

type: dataset

en: Terrain elevation maps

media_type: application/zip

en: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

format: ZIP

mimetype: application/zip

en: Canopy height maps

en: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

en: Snow depth maps

en: Snow depth maps from two snow-on flights at each of the three field areas Davos (March 20th and 31st 2017), Engadien (March 20th and 31st, 2017) and Grand Mesa (February 8th and 16th, 2017)

en: Readme

media_type: text/plain

format: TXT

mimetype: text/plain

en:
This dataset includes snow depth, canopy height and terrain elevation maps of forest stands in the Grisons (CH) and at Grand Mesa (CO,USA) derived from airborne lidar. Data were acquired i) within a pilot mission of NASA's Airborne Snow Observatory in the Swiss Alps in March 2017 and ii) during NASA’s SnowEx campaign at Grand Mesa in February 2017. Snow depth maps are available for two dates separated by approx.1 week, and include an area of ca. 0.5km2 for each of the three sites Davos, Engadine and Grand Mesa.
All data were presented and analyzed in the publication 'Revisiting Snow Cover Variability and Canopy Structure within Forest Stands: Insights from Airborne Lidar Data' (Mazzotti et al., 2019, WRR, doi: 10.1029/2019WR024898). This publication must be cited when using this dataset.

Paper Citation:
 > _Giulia Mazzotti; William Ryan Currier; Jeffrey S. Deems; Justin M. Pflug; Jessica D. Lundquist; Tobias Jonas (2019). Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resources Research, 55, 6198– 6216, [doi: 10.1029/2019WR024898](https://doi.org/10.1029/2019WR024898)._

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: ALS-based snow depth and canopy height maps from flights in 2017 (Grisons, CH and Grand Mesa, CO)


en: phytosociology typoch diagnostic-species vegetation-type vegetation-classification character-species

en: TypoCH_modified list.csv

media_type: text/csv

en:
The file contains the vegetation types and the modified list of diagnostic species (based on Delarze et al. (2015). The numbers indicate the weight of a species in the particular vegetation type for the calculation of the TypoCH score:
1) accompanying species -> 1 point
2) dominant accompanying species (if >10% cover in the plot) -> 2 points
3) character species -> 4 points
4) dominant character species (if >10% cover in the plot) -> 8 points

format: CSV

en: How the TypoCH list was modified.pdf

media_type: application/pdf

en: Describes details on the modification procedure to improve the TypoCH reference list.

format: PDF

en: The TypoCH scoring system (Eggenberg & Bornand 2023), which is widely used in Switzerland, provides good results as classification method for vegetation types based on Delarze et al. (2015). However, the reference list contained species with no diagnostic value and important character species were missing. We therefore made a first attempt to modify the list based on numerical methods and expert knowledge to improve the classification success, at least for vegetation types of the open land (i.e. grasslands, fens, bogs).

character-species

display_name: character-species

diagnostic-species

display_name: diagnostic-species

phytosociology

display_name: phytosociology

typoch

display_name: typoch

vegetation-classification

display_name: vegetation-classification

vegetation-type

display_name: vegetation-type

en: Modified TypoCH reference list of diagnostic species for the classification of vegetation types in Switzerland


maintainer: Franziska Gerber

en: topography cryowrf wrf cosmo-wrf static-data landuse

en: Static data for WRF - Topography

format: SERVICE

en:
Example GEOGRID.TBL to use with the 1s static data;
Note about naming:
* 121 -> 1-2-1 topography smoothing applied to dataset
* 1 -> one smoothing cycle applied to the data (needs to be changed depending on the chosen resolution to avoid too steep slope angles)

en: Documentation

en: Documentation of the dataset

en: Static data for WRF - Landuse

en: Example namelist.wps to use with the 1s static data

en: Static data for WRF - Soiltype bottom

en: Static data for WRF - Soiltype top

en: Static input data (topography, landuse and soiltype) for the WRF preprocessing system WPS is provided for Switzerland and its neighboring countries between 45-49 N and 4-12 E. The data is provided at a resolution of 1 s. Topography is based on the Aster dataset, while landuse is extracted from the Corine landuse dataset. Soil type is set to silty clay loam for the entire domain. This static input data is valid for WRF and CRYOWRF.

cosmo-wrf

display_name: cosmo-wrf

cryowrf

display_name: cryowrf

landuse

display_name: landuse

static-data

display_name: static-data

topography

display_name: topography

wrf

display_name: wrf

educ

en: Education, culture and sport

en: High resolution static data for WRF over Switzerland


restoring-grassland-multifunctionality

title_for_slug: restoring-grassland-multifunctionality

en: mineralization ecosystem-multifunctionality nematodes grassland plants biodiversity bacteria soil-biodiversity fungi restoration

en: Please note that C.sto and Corg have been corrected.

format: XLS

en: Functional diversity above_belowground fauna

en: Please note that EMF, MF.below, MF.abio and Soil.hetero have been corrected.

en:
Please cite this paper together with the citation for the datafile.

Resch, M. C., Schütz, M., Buchmann, N., Frey, B., Graf, U., van der Putten, W. H., Zimmermann, S., Risch, A. C. 2021. Evaluating long-term success in grassland restoration – an ecosystem multifunctionality approach. Ecological Applications 31, e02271.

 Study area

The study was conducted in the Canton of Zurich, Switzerland, in and around two nature reserves Eigental and Altläufe der Glatt (47°27’ to 47°29’ N, 8°37’ to 8°32’ E, 417 to 572 m a.s.l.). All studied grasslands were located with a radius of approximately 4 km. Average monthly temperatures range from 0.7 ± 2.0 °C (January) to 19.0 ± 1.5 °C (July), and monthly precipitation range from 60 ± 42 mm (January) to 118 ± 46 mm (July [maxima]; 1989-2017; MeteoSchweiz 2018). In our study, we focused on semi-dry and semi-wet oligo- to mesotrophic grasslands characterized by high plant species richness and groundwater fluctuations throughout the year (Delarze et al. 2015, see also Resch et al. 2019).

 Experimental design and sampling

A large-scale restoration experiment to expand and reconnect isolated remnants of species-rich grasslands was initiated in the nature reserve Eigental in 1990. Twenty hectares of adjacent intensive grasslands were chosen for restoration. In 1995, three restoration methods of increasing intervention intensities were implemented. The goal of all three methods was to lower the availability of soil nutrients and hence, facilitate ecosystem development towards the targeted nutrient-poor grasslands. These methods were: Harvest only (hay harvest twice a year), Topsoil (removal of the nutrient-rich topsoil), and Topsoil+Propagules (topsoil removal combined with the application of hay from target vegetation). Plant biomass harvest (once a year in late summer/early autumn) commenced in Topsoil and Topsoil+Propagules five years after the soils were removed and is still ongoing today. We measured restoration success by comparing the three restoration methods with intensively managed (Initial) and semi-natural grasslands (Target) 22 years after restoration. Initial grassland sites share the same agricultural history as the restored sites: mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes (Resch et al. 2019). Target sites were the sites from which hay for seeding the Topsoil+Propagules sites was collected. Soil conditions (i.e., soil types, soil texture) were comparable to those found in the restored grasslands (Resch et al. 2019). Additionally, Target sites were selected to represent a variety of semi-natural grasslands, including semi-dry to semi-wet conditions. In Target grasslands, biomass is harvested once a year in late summer or early autumn. Eleven 5 m x 5 m (25 m2) plots were randomly established in each of the five treatments (in total 55 plots; for a detailed map see Neff et al. 2020). An additional 2 m x 2 m (4 m2) subplot was randomly established at least 2 m away from each 25 m2 plot for destructive sampling. Data sampling took place between June and September 2017.

Vegetation properties

All plant species were identified within the 25 m2 plots (nomenclature: Lauber and Wagner 1996) in mid-June 2017 (in total 250 species). Vegetation structure and plant biomass were assessed diagonally on a transect of 2 m x 10 cm within the 25 m2 plot in early July 2017. We measured the maximum and mean height of the vegetation at the start, middle and end of the transect and calculated the standard deviation of these measures to describe vegetation structural heterogeneity (Schuldt et al. 2019). Thereafter, biomass was clipped on the entire transect to 1 cm height, sorted into five functional groups (graminoids, forbs, legumes, litter, and woody species), dried at 60 °C for 48 h, and weighed (Meyer et al. 2015).

 Aboveground arthropods

Aboveground arthropods were sampled at two locations in each 25 m2 plot in early July 2017 (see also Neff et al. 2020). Briefly, two cylindrical baskets (50 cm diameter, 67 cm height; woven fabric) were thrown simultaneously from outside the plot into two opposite corners. A closable mosquito mesh sleeve was mounted to the top of the baskets and an integrated metal ring at the bottom was fixed to the ground with metal stakes to assure that insects could not escape. A suction sampler (Vortis, Burkhard Manufacturing Co. Ltd., Hertfordshire, England) was then inserted into one of the baskets through the opening of the sleeve and the plot was “vacuumed" twice for 105 seconds with a 30 seconds break. The collected animals were immediately transferred into 70% ethanol. Arthropods were sorted and assigned to 23 taxonomic groups. Holometabolic larvae were lumped into one category while hemimetabolic larvae were grouped separately from adults in the respective taxonomic rank. We used mean values of individuals per plot for total abundance. Aboveground arthropod richness was defined by the number of different taxa to lowest taxonomic level (in total 23 taxa). All taxa were assigned to one of five trophic levels: 1) primary producers, 2) primary consumers, 3) secondary consumers, 4) tertiary consumers, and 5) quaternary consumers.

 Belowground fauna

Sampling of all belowground fauna took place in mid-July 2017. Earthworms were sampled in two 30 cm x 30 cm x 20 cm soil monoliths at two opposite corners of the 25 m2 plot (opposite to aboveground arthropod sampling). The excavated soil monolith was broken by hand, all earthworms collected and immediately transferred in a 4% formaldehyde solution. Thereafter, earthworm individuals were identified to species level (in total 10 taxa; Christian and Zicsi 1999) and species assigned to three functional groups (Bouché 1977).
To assess soil arthropod communities, we randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) in each 4 m2 subplot with a slide hammer corer lined with a plastic sleeve (AMS Samplers, American Falls, Idaho, USA). Soil arthropods were extracted using Berlese-Tullgren funnels (3 mm mesh), starting the day of sampling and lasting 14 days. Individuals were stored in 70% ethanol. Soil arthropods were assigned to 41 taxonomic groups and 4 feeding types. Holometabolic and hemimetabolic larvae were treated as previously described for aboveground arthropods. Belowground arthropod richness refers to the 41 taxonomic groups.

For soil nematode sampling, we randomly collected eight soil cores of 2.2 cm diameter (Giddings Machine Company, Windsor, CO, USA) within each 4 m2 subplot to a depth of 12 cm. The eight cores were combined, gently homogenized, placed in coolers, kept at 4 °C and transported to the laboratory at NIOO in Wageningen (NL) within one week after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink 1960) and prepared for morphological identification and quantification as described by Resch et al. (2019). Nematodes were identified to family level (39 taxa) according to Bongers (1988), assigned to 17 functional groups, 5 feeding types and 5 colonizer-persister (C-P) classes (Yeates et al. 1993, Bongers 1990, Resch et al. 2019).

We randomly collected two more soil cores (2.2 cm diameter x 12 cm depth) within each 4 m2 subplot to determine soil microbial communities. Again, the soil cores were combined, homogenized, placed in coolers and transported to the laboratory at WSL in Birmensdorf (Switzerland) where the metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNeasy PowerMax Soil Kit (Quiagen, Hilden, NRW, GER) according to the manufacturer`s instructions. PCR amplification of the V3-V4 region of the prokaryotic small-subunit (16S) and the ribosomal internal transcribed spacer region (ITS2) of eukaryotes was performed with 1 ng of template DNA utilizing PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates and pooled. The pooled amplicons were sent to the Genome Quebec Innovation Centre (Montreal, QC, Canada) for barcoding using the Fluidigm Access Array technology (Fluidigm) and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA). Quality filtering, clustering into operational taxonomic units (OTUs) and taxonomic assignment were performed as described by Frey et al. (2016) and Adamczyk et al. (2019). We used a customised pipeline largely based on UPARSE (Edgar 2013) implemented in USEARCH v. 9.2 (Edgar 2010). After discarding singletons of dereplicated sequences, clustering into OTUs with 97% sequence similarity was performed (Edgar 2013). Quality-filtered reads were mapped on the filtered set of centroid sequences. Taxonomic classification of prokaryotic and fungal sequences was conducted querying against most recent versions of SILVA (v.132, Quast et al. 2013) and UNITE (v.8, Nilsson et al. 2018). Only taxonomic assignments with confidence rankings equal or higher than 0.8 were accepted (assignments below 0.8 set to unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as eukaryotic OTUs assigned other than fungi were removed prior to data analysis. In addition, prokaryotic and fungal datasets were filtered to discard singletons and doubletons. Thereafter, OTU abundance matrices were rarefied to the lowest number of sequences per community, to normalize the total number of reads and achieve parity between samples (Prokaryota: 29,843 reads; Fungi: 26,690 reads). Finally, prokaryotic and fungal observed richness (number of OTUs) were estimated (Prokaryota: 14,010 OTUs; Fungi: 5,813 OTUs). For prokaryotes, we distinguished five and for fungi six functional types based on lowest taxonomic resolution (Nguyen et al. 2016, Tedersoo et al. 2014). Belowground taxon richness was defined by the total number of earthworm, arthropod, nematode, fungi, and prokaryote taxa assigned to lowest taxonomic level. Finally, all belowground taxa were assigned to the same five trophic levels as the aboveground arthropods.

 Soil chemical and physical properties, soil nitrogen mineralization

We randomly collected three 5 cm diameter x 12 cm depth soil samples in each 4 m2 subplot with a slide hammer corer (AMS Samplers, American Falls, Idaho, USA), pooled them and then made two subsamples. One was field-fresh and stored at 3 °C until analysis, the other was dried for 48 h at 60 °C and passed through a 4 mm mesh. From the dried sample, we measured soil pH potentiometrically in 0.01 M CaCl2 (soil:solution ratio=1:2; 30 minutes equilibration time). Total and organic carbon content were measured on fine-ground samples (≤ 0.5 mm) by dry combustion using a CN analyzer NC 2500 (CE Instruments, Wigan, United Kingdom). Inorganic carbon of samples with a pH > 6.5 was removed with acid vapor prior to analysis of organic carbon (Walthert et al. 2010). We calculated total soil carbon (C) storage after correcting its content for soil depth, stone content and density of fine earth (see below). Exchangeable cations were determined on another 5 g dry soil sample with 50 mL unbuffered 1 M NH4Cl solution (soil:solution ratio=1:10, end-over-end shaker for 1.5 hours) and measured by an ICP-OES (Optima 7300 DV, Perkin-Elmer, Waltham, Massachusetts, USA). Thereafter, cation exchange capacity (CEC) was calculated as the sum of exchangeable cations and protons (and expressed as mmolc per 1 kg soil) and used to describe nutrient retention capacity in our plots. Concentrations of exchangeable protons were calculated as the difference between total and Al-induced exchangeable acidity as determined by the KCl-method (Thomas 1982).

Ammonium (NH4+) and nitrate (NO3−) were extracted from a 20 g fresh subsample with 80 mL 1M KCl for 1.5 hours on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnemühle FineArt GmbH, Dassel, Germany). NH4+ concentrations were determined colorimetrically by automated flow injection analysis (FIAS 300, Perkin-Elmer, Waltham, Massachusetts, USA). NO3− concentrations were measured colorimetrically according to Norman and Stucki (1981). Potential soil net nitrogen (N) mineralization was assessed during an 8-week incubation period under controlled moisture (60% of field capacity), temperature (20 °C) and light conditions (dark) in the laboratory. We weighed duplicate samples of fresh soil equivalent to 8 g dry soil (24 h at 104 °C) into 50 mL Falcon tubes. Soil samples were extracted for NH4+ and NO3− at the beginning and after eight weeks as described above. Soil net N mineralization was calculated as the difference between the inorganic nitrogen (NH4+ and NO3−) before and after the incubation (Hart et al. 1994), corrected for the total incubation time and represented per day values expressed as mg N kg-1 soil d-1.

To assess soil physical properties, we randomly collected one undisturbed soil core per 4 m2 subplot (5 cm diameter, 12 cm depth) in a steel cylinder that fit into the slide hammer (AMS Samplers, American Falls, Idaho, USA). The cylinder was capped in the field to avoid disturbance. We then measured field capacity in the laboratory. For this purpose, the cylinder and soil therein were saturated in a water bath and drained on a sand/silt-bed with a suction corresponding to 60 cm hydrostatic head. The moist soil was dried at 105 °C to constant weight. Field capacity was calculated by dividing the mass of water by the total mass of wet soil contained at 60 cm hydrostatic head and used to describe water holding capacity. Thereafter, samples were passed through a 4 mm mesh. Fine-earth and skeleton fractions were weighed separately to assess bulk soil density (fine-earth plus skeleton), density of fine earth, and proportion of skeleton. Particle density was determined with the pycnometer method (Blake and Hartge 1986), and total porosity and proportion of fine pores were calculated (Danielson and Sutherland 1986). Clay, silt, and sand contents were quantified with the sediment method (Gee and Bauder 1986).

Surface and soil temperature (12 cm depth, water-resistant digital pocket thermometer; IP65, H-B Instrument, Trappe, Pennsylvania, USA) as well as volumetric soil moisture content (12 cm depth, time domain reflectometry; Field-Scout TDR 300, Spectrum Technologies, Aurora, Illinois, USA) were measured at five random locations within the 4 m2 subplots every month from June to September. We calculated the standard deviation of each temperature and moisture measure over four months to describe seasonal variations. Slope inclination was determined at plot-level via GPS measurements (GPS 1200, Leica Geosystem, Heerbrugg, Switzerland) and categorized into slope gradient classes according to FAO standards (1990). Thickness of the topsoil horizon (equivalent to Ah or Aa horizon) was determined at one soil monolith (30 x 30 x 30 cm3) per 4 m2 subplot in cm and rounded to next integer.

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Resch, M. C., M. Schütz, U. Graf, R. Wagenaar, W.H. van der Putten, and A. C. Risch. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56:1782-1793.

Schuldt, A., A. Ebeling, M. Kunz, M. Staab, C. Guimarães-Steinicke, D. Bachmann, N. Buchmann, W. Durka, A. Fichtner, F. Fornoff, W. Härdtle, L. R. Hertzog, A-N. Klein, C. Roscher, J. Schaller, von G. Oheimb, A. Weigelt, W. Weisser, C.Wirth, J. Zhang, H. Bruelheide, and N. Eisenhauer. 2019. Multiple plant diversity components drive consumer communities across ecosystems. Nature Communications 10:1460.

Tedersoo, L., M. Bahram, S. Põlme, U. Kõljalg, N. S. Yorou, R. Wijesundera, L. Villarreal Ruiz, A. M. Vasco-Palacios, P. Q. Thu, A. Suija, M. E. Smith, C. Sharp, E. Saluveer, A. Saitta, M. Rosas, T. Riit, D. Ratkowsky, K. Pritsch, K. Põldmaa, M. Piepenbring, C. Phosri, M. Peterson, K. Parts, K. Pärtel, E. Otsing, E. Nouhra, A. L. Njouonkou, R. H. Nilsson, L. N. Morgado, J. Mayor, T. W. May, L. Majuakim, D. J. Lodge, S. See Lee, K.-H. Larsson, P. Kohout, K. Hosaka, I. Hiiesalu, T. W. Henkel, H. Harend, L.-D. Guo, A. Greslebin, G. Grelet, J. Geml, G. Gates, W. Dunstan, C. Dunk, R. Frenkhan, L. Dearnaley, A. De Kesel, T. Dang, X. Chen, F. Buegger, F. Q. Brearley, G. Bonito, S. Anslan, S. Abell, and K. Abarenkov. 2014. Global diversity and geography of soil fungi. Science 346:1256688.

Thomas, G.W. 1982. Exchangeable cations. Pages 159-165 in A. L. Page, R. H. Miller, and D. R. Keeney, editors. Methods of Soil Analysis: Part 2—Chemical and microbiological properties. Soil Science Society of America (SSSA) Inc., Madison.

Walthert, L., U. Graf, A. Kammer, J. Luster, D. Pezzotta, S. Zimmermann, and F. Hagedorn. 2010. Determination of organic and inorganic carbon, δ13C, and nitrogen in soils containing carbonates after acid fumigation with HCl. Journal of Plant Nutrition and Soil Sciences 173:207-216.

Yeates, G. W., T. Bongers, R. G. M. de Goede, D. W. Freckman, and S. S. Georgieva. 1993. Feeding habits in soil nematode families and genera – an outline for soil ecologists. Journal of Nematology 25:315-331.

bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

ecosystem-multifunctionality

display_name: ecosystem-multifunctionality

fungi

display_name: fungi

grassland

display_name: grassland

mineralization

display_name: mineralization

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil-biodiversity

display_name: soil-biodiversity

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Restoring grassland multifunctionality


maintainer: Stephanie Mayer

en: snow-instability snow-profiles snowpack-simulation failure-layer snowpack snow-stratigraphy rutschblock

en: SWISS data set: Properties of observed snow profiles and simulated failure layers

en: For each profile pair from the SWISS data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. Please note that only those profile pairs which fulfilled the similarity criteria (column similarity_obs_sim = 1, 121 profiles) were used to validate the RF model. The content of the columns is explained in Table 1 of the ReadMe file.

en: Observed snow profiles

en: Observed snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding simulated profile in the "simulated_profiles" folder. One row corresponds to one observed snow layer. The content of the columns is described in Table 2 of the ReadMe file.

en: ReadMe

en: ReadMe file explaining data structure and content

en: DAV data set: Properties of observed snow profiles and simulated failure layers

en:
For each profile pair from the DAV data set, this file contains one row with information on the observed snow stability and all extracted features describing the simulated failure layers. The content of the columns is explained in Table 1 of the ReadMe file. Only those profile pairs which fulfilled predefined similarity criteria (column
"similarity_obs_sim" = 1) and which belonged to the stability classes "stable" and "unstable" (column "stability_class"
= 0 or 1) were used to train the RF model. Please note that for each of the two snow profiles with RB score 7 (profile
IDs 7228 and 9526), three additional layers were included in this data set to obtain a balanced set of training data (73
unstable and 73 stable profiles).

en: Simulated snow profiles

en: Simulated snow stratigraphy in form of one *.csv-file per snow profile from the DAV and SWISS data sets (in respective subfolders). Each file is named after the profile ID which allows identifying the corresponding observed profile in the "observed_profiles" folder. One row corresponds to one simulated snow layer. The content of the columns 1-7 is described in Table 3 of the ReadMe file. The remaining columns (8-31) contain all features that were used in the development of the RF model and are described in Table 1 of the ReadMe file.

en:
This data set includes information on all observed and simulated snow profiles that were used to train and validate the
random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified.

The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model.

failure-layer

display_name: failure-layer

rutschblock

display_name: rutschblock

snow-instability

display_name: snow-instability

snow-profiles

display_name: snow-profiles

snow-stratigraphy

display_name: snow-stratigraphy

snowpack

display_name: snowpack

snowpack-simulation

display_name: snowpack-simulation

en: Observed and simulated snow profile data


maintainer: Yaquan Chang

en: relief plant-biodiversity climate-history endemism tectonic-faults

en:
This dataset includes geomorphic predictors and plant biodiversity patterns in the Hengduan Mountains, published in the Geological Society of London special volume: Asian Geodynamics, Climate and Biodiversity (https://doi.org/10.1144/SP549-2024-17).
The geomorphic predictors include catchment-restricted relief and chi maps, while the climate predictors comprise site water balance, growing degree days, and climate change velocity from the Last Glacial Maximum (LGM) to the present.
The plant biodiversity patterns are represented by a plant richness map for 13,321 species in the Hengduan Mountains. Species-level plant range maps are available in the dataset, previously published under DOI: 10.16904/envidat.424.

climate-history

display_name: climate-history

endemism

display_name: endemism

plant-biodiversity

display_name: plant-biodiversity

relief

display_name: relief

tectonic-faults

display_name: tectonic-faults

educ

en: Education, culture and sport

en: Tectonic and climatic controls on plant biodiversity in the Hengduan Mountains China


en: ecological-indicator-values switzerland ecological-maps plants soil-moisture soil-ph soil-mapping landolt

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en: Description

en: Description of the predictors provided in this dataset

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.


finanzausgleich-kanton-luzern

title_for_slug: finanzausgleich-kanton-luzern

de: offentliche-finanzen volkswirtschaft statistische-grundlagen ressourcenausgleich verwaltung lastenausgleich gemeinden gemeindefinanzen finanzausgleich

fr: Compensation des charges de l'éducation

de: Bildungslastenausgleich

en: Equalisation of educational burdens

it: Perequazione degli oneri educativi

de: Die Datensätze enthalten alle Kennzahlen seit 2020, die für die Berechnung der fünf Ausgleichsgefässe des kantonalen Finanzausgleichs des Kantons Luzern gemäss Finanzausgleichsgesetz und -verordnung erforderlich sind. Die Verrechnung der Kennzahlen zu Indikatoren und die Verteilung der Mittel wird in den Anhängen der Finanzausgleichsverordnung detailliert beschrieben. Die Kennzahlen stammen aus verschiedenen Datenquellen, die zum Teil in der Verordnung explizit genannt werden.

identifier: lustat-fa-lu-bla

fr: Compensation des charges dues à des facteurs géo-topographiques

de: Topografischer Lastenausgleich

en: Topographic cost compensation

identifier: lustat-fa-lu-tla

fr: Péréquation des ressources

de: Ressourcenausgleich

en: Equalisation of resources

it: Perequazione delle risorse

identifier: lustat-fa-lu-ra

fr: Compensation des charges d'infrastructure

en: Infrastructure load compensation

de: Infrastrukturlastenausgleich

identifier: lustat-fa-lu-ila

fr: Compensation des charges dues à des facteurs socio-démographiques

de: Soziallastenausgleich

en: Socio-demographic cost compensation

fr: Les jeux de données contiennent tous les indicateurs depuis 2020 nécessaires au calcul des cinq enveloppes de péréquation de la péréquation financière cantonale du canton de Lucerne, conformément à la loi et à l'ordonnance sur la péréquation financière. L'imputation des chiffres clés aux indicateurs et la répartition des moyens sont décrites en détail dans les annexes de l'ordonnance sur la péréquation financière. Les indicateurs proviennent de différentes sources de données, dont certaines sont explicitement mentionnées dans l'ordonnance.

en: The data sets contain all key figures since 2020 that are required for the calculation of the fiscal equalization and cost compensation of the Canton of Lucerne in accordance with the Financial Equalization Act and Ordinance. The calculation of the indicators based on the key figures and the distribution of the funds is described in detail in the annexes to the Fiscal Equalization Ordinance. The key figures come from various data sources, some of which are explicitly mentioned in the ordinance.

finanzausgleich

display_name: finanzausgleich

gemeindefinanzen

display_name: gemeindefinanzen

gemeinden

display_name: gemeinden

lastenausgleich

display_name: lastenausgleich

offentliche-finanzen

display_name: offentliche-finanzen

ressourcenausgleich

display_name: ressourcenausgleich

statistische-grundlagen

display_name: statistische-grundlagen

verwaltung

display_name: verwaltung

volkswirtschaft

display_name: volkswirtschaft

spatial: Kanton Luzern

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

fr: LUSTAT Statistik Luzern

lustat

fr:
LUSTAT statistique Lucerne est le centre de compétences et de services pour la statistique publique du canton de Lucerne. Avec ses informations statistiques objectives, LUSTAT accompagne les processus de formation d'opinion et de prise de décision dans la politique, l'administration, la société et les affaires.
LUSTAT statistique Lucerne publie ici progressivement des jeux de données appropriées de la statistique cantonale sous forme de données OGD.

en:
LUSTAT Statistics Lucerne is the competence and service center for public statistics in the Canton of Lucerne. With its objective statistical information, LUSTAT accompanies opinion-forming and decision-making processes in politics, administration, society and business.
LUSTAT Statistics Lucerne is gradually publishing here suitable datasets from the cantonal statistics as OGD data.

de:
LUSTAT Statistik Luzern ist das Kompetenz- und Dienstleistungszentrum der öffentlichen Statistik im Kanton Luzern. Mit ihren objektiven statistischen Informationen begleitet LUSTAT Meinungsbildungs- und Entscheidungsprozesse in Politik, Verwaltung, Gesellschaft und Wirtschaft.
LUSTAT Statistik Luzern veröffentlicht hier schrittweise geeignete Datensammlungen der kantonalen Statistik als OGD-Daten.

it:
LUSTAT statistica Lucerna è il centro di competenza e servizi per la statistica pubblica nel cantone di Lucerna. Con le sue informazioni statistiche oggettive, LUSTAT accompagna i processi di formazione delle opinioni e decisionali in politica, amministrazione, società e affari.
LUSTAT statistica Lucerna sta gradualmente pubblicando qui oportuni set di dati della statistica cantonale come dati OGD.

fr: Péréquation financière canton de Lucerne

en: Financial equalization canton of Lucerne

it: Perequazione comunale del cantone di Lucerna


maintainer: LUSTAT Statistik Luzern

de: wahlen politik gewahlte gemeinderatswahlen kommunale-wahlen kandidierende

fr: Élections communales canton de Lucerne de 2020

de: Gemeinderatswahlen Kanton Luzern seit 2020

en: Municipal council elections Canton Lucerne since 2020

it: Elezioni del consiglio comunale cantone di Lucerna dal 2020

de: Kandidierende und Gewählte bei den Gemeinderatswahlen seit 2020 im Kanton Luzern

identifier: lustat-grwahlen-lu

gemeinderatswahlen

display_name: gemeinderatswahlen

gewahlte

display_name: gewahlte

kandidierende

display_name: kandidierende

kommunale-wahlen

display_name: kommunale-wahlen

politik

display_name: politik

wahlen

display_name: wahlen

de: LUSTAT Statistik Luzern

en: LUSTAT Statistik Luzern

it: LUSTAT Statistik Luzern

lustat

fr: LUSTAT statistique Lucerne

en: LUSTAT Statistics Lucerne

it: LUSTAT statistica Lucerna

political_level: canton

value: I14Y DCAT Harvester LUSTAT


de: offentliche-finanzen gemeindefinanzen gemeinderechnungen verwaltung sachkonto gemeinden statistische-grundlagen volkswirtschaft artenkonto finanzkennzahlen funktion

de: Jahresrechnungen Erfolgsrechnung: Aufwand und Ertrag (Artengliederung)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Art
- Ertrag nach einstufiger Art
- Aufwand nach zweistufiger Art
- Ertrag nach zweistufiger Art
- Aufwand nach dreistufiger Art
- Ertrag nach dreistufiger Art
- Aufwand nach vierstufiger Art
- Ertrag nach vierstufiger Art

identifier: gefis-lu-jr-er-art

de: Jahresrechnungen: Bilanz, Erfolgsrechnung und Investitionsrechnung (Kontofunktion und Kontoart)

de: Daten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern im höchsten Detaillierungsgrad der Kontofunktion und Kontoart (aggregiert auf Minimalvorgabe vom Kanton: Stufen 3 oder 4 bei Kontofunktion und Stufen 4, 5 oder 6 bei Kontoart)

identifier: lustat-gefis-lu-jr

de: Jahresrechnungen Erfolgsrechnung: Aufwand, Ertrag und Nettoaufwand (funktionelle Gliederung)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Kontofunktion
- Ertrag nach einstufiger Kontofunktion
- Nettoaufwand nach einstufiger Kontofunktion
- Aufwand nach zweistufiger Kontofunktion
- Ertrag nach zweistufiger Kontofunktion
- Nettoaufwand nach zweistufiger Kontofunktion
- Aufwand nach dreistufiger Kontofunktion
- Ertrag nach dreistufiger Kontofunktion
- Nettoaufwand nach dreistufiger Kontofunktion

identifier: gefis-lu-jr-er-fkt

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben und Investitionseinnahmen (Kontofuntktion und Kontoart)

de:
Investitionsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion kombiniert mit zwei- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach einstufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach einstufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach einstufiger Kontofunktion und vierstufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Investitionsausgaben nach dreistufiger Kontofunktion und vierstufiger Kontoart
- Investitionseinnahmen nach dreistufiger Kontofunktion und vierstufiger Kontoart

identifier: gefis-lu-jr-ir-fkt-art

de: Jahresrechnungen Bilanz: Aktiven und Passiven (Artengliederung)

de:
Bilanzdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aktiven nach einstufiger Art
- Passiven nach einstufiger Art
- Aktiven nach zweistufiger Art
- Passiven nach zweistufiger Art
- Aktiven nach dreistufiger Art
- Passiven nach dreistufiger Art
- Aktiven nach vierstufiger Art
- Passiven nach vierstufiger Art

identifier: lustat-gefis-lu-jr-bl-art

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben, Investitionseinnahmen und Nettoinvestitionen (funktionelle Gliederung)

de:
Investitionsrechnungsdaten  der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Kontofunktion
- Investitionseinnahmen nach einstufiger Kontofunktion
- Nettoinvestitionen nach einstufiger Kontofunktion
- Investitionsausgaben nach zweistufiger Kontofunktion
- Investitionseinnahmen nach zweistufiger Kontofunktion
- Nettoinvestitionen nach zweistufiger Kontofunktion
- Investitionsausgaben nach dreistufiger Kontofunktion
- Investitionseinnahmen nach dreistufiger Kontofunktion
- Nettoinvestitionen nach dreistufiger Kontofunktion

identifier: gefis-lu-jr-ir-fkt

de: Jahresrechnungen Erfolgsrechnung: Aufwand und Ertrag (Kontofuntktion und Kontoart)

de:
Erfolgsrechnungsdaten der Jahresrechnungen der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis dreistufiger Kontofunktion kombiniert mit zwei- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Aufwand nach einstufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach einstufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach einstufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach einstufiger Kontofunktion und vierstufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach zweistufiger Kontofunktion und vierstufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und zweistufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und dreistufiger Kontoart
- Aufwand nach dreistufiger Kontofunktion und vierstufiger Kontoart
- Ertrag nach dreistufiger Kontofunktion und vierstufiger Kontoart

identifier: gefis-lu-jr-er-fkt-art

de: Jahresrechnungen Investitionsrechnung: Investitionsausgaben und Investitionseinnahmen (Artengliederung)

de:
Investitionsrechnungsdaten der Gemeindefinanzstatistik vom Kanton Luzern nach ein- bis vierstufiger Kontoart. Datensammlung umfasst folgende Arbeitsblätter:
- Investitionsausgaben nach einstufiger Art
- Investitionseinnahmen nach einstufiger Art
- Investitionsausgaben nach zweistufiger Art
- Investitionseinnahmen nach zweistufiger Art
- Investitionsausgaben nach dreistufiger Art
- Investitionseinnahmen nach dreistufiger Art
- Investitionsausgaben nach vierstufiger Art
- Investitionseinnahmen nach vierstufiger Art

identifier: gefis-lu-jr-ir-art

de: Das Datenset beinhaltet die Jahresrechnungen der  Gemeindefinanzstatistik des Kantons Luzern seit 2019 gemäss dem HRM2-Standard. Es werden für jede Gemeinde die Funktionen, die Kontoarten und die entsprechenden Saldi ausgewiesen. Es ist der Gebietsstand des jeweiligen Jahres aufgeführt. Die Daten wurden direkt bei den Gemeinden erhoben und bilden einen Auszug aus deren Buchhaltungssystem ab. Statistische Korrekturen zwecks Gewährleistung der Konformität mit dem kantonalen Kontenrahmen wurden in Einzelfällen vorgenommen.

en: The dataset contains the annual accounts of the Municipal Finance Statistics of the Canton Lucerne since 2019 in accordance with the HRM2 standard. The table shows the cost centers or the cost units, the account types and the corresponding account balances for each municipality. The territorial status of the respective year is disclosed. The data was collected directly from the municipalities and represents an extract of their accounting system. Statistical corrections were made in exceptional cases to ensure conformity with the cantonal chart of accounts.

artenkonto

display_name: artenkonto

finanzkennzahlen

display_name: finanzkennzahlen

funktion

display_name: funktion

gemeinderechnungen

display_name: gemeinderechnungen

sachkonto

display_name: sachkonto

fr: Statistique des finances communales canton de Lucerne: comptes annuels

en: Municipal Finance Statistics Canton Lucerne: annual accounts

de: Gemeindefinanzstatistik Kanton Luzern: Jahresrechnungen

it: Statistica finanziaria comunale cantone di Lucerna: conti annuali


de: funktion gemeindefinanzen sachkonto gemeinden offentliche-finanzen verwaltung artenkonto statistische-grundlagen volkswirtschaft gemeindebudgets

fr: Statistique des finances communales canton de Lucerne: budgets annuels

en: Municipal Finance Statistics Canton Lucerne: annual budgets

de: Gemeindefinanzstatistik Kanton Luzern: Budgets

it: Statistica finanziaria comunale cantone di Lucerna: bilanci annuali

de: Das Datenset beinhaltet die Budgetdaten der  Gemeindefinanzstatistik des Kantons Luzern seit 2020 gemäss dem HRM2-Standard. Es werden für jede Gemeinde die Funktionen, die Kontoarten und die entsprechenden Saldi ausgewiesen. Es ist der Gebietsstand des jeweiligen Jahres aufgeführt. Die Daten wurden direkt bei den Gemeinden erhoben und bilden einen Auszug aus deren Buchhaltungssystem ab. Statistische Korrekturen zwecks Gewährleistung der Konformität mit dem kantonalen Kontenrahmen wurden in Einzelfällen vorgenommen.

en: The dataset contains the budget data of the Municipal Finance Statistics of the Canton Lucerne since 2020 in accordance with the HRM2 standard. The table shows the cost centers or the cost units, the account types and the corresponding account balances for each municipality. The territorial status of the respective year is disclosed. The data was collected directly from the municipalities and represents an extract of their accounting system. Statistical corrections were made in exceptional cases to ensure conformity with the cantonal chart of accounts.

gemeindebudgets

display_name: gemeindebudgets

gemeindefinanzen

display_name: gemeindefinanzen

gemeinden

display_name: gemeinden

gove

de: Regierung und öffentlicher Sektor

econ

de: Wirtschaft und Finanzen

de: LUSTAT Statistik Luzern

lustat

de:
LUSTAT Statistik Luzern ist das Kompetenz- und Dienstleistungszentrum der öffentlichen Statistik im Kanton Luzern. Mit ihren objektiven statistischen Informationen begleitet LUSTAT Meinungsbildungs- und Entscheidungsprozesse in Politik, Verwaltung, Gesellschaft und Wirtschaft.
LUSTAT Statistik Luzern veröffentlicht hier schrittweise geeignete Datensammlungen der kantonalen Statistik als OGD-Daten.


de: subjektive-lebensbedingungen bevolkerung befragung lebensqualitat lebensbedingungen

en: subjective-living-conditions quality-of-life survey population living-conditions

de: Antworten zu den Fragen

en: Answers to the questions

identifier: bbf-lu-antworten

de: Grundgesamtheit

en: Universe

identifier: bbf-lu-grundgesamtheit

de:
Die Datensammlung zur Bevölkerungsbefragung Kanton Luzern 2023 besteht aus zwei Distributionen/Ressourcen:
- Individualdaten mit den Antworten zu den Fragen (bbf-lu-antworten.csv)
- Angaben zur Grundgesamtheit der gewichtungsrelevanten Variablen für die Endlichkeitskorrektur (bbf-lu-grundgesamtheit.csv)

en:
The data set for the population survey Canton of Lucerne 2023 consists of two distributions/resources:
- Individual data with the answers to the questions (bbf-lu-antworten.csv)
- Information on the population of the weighting-relevant variables for the finiteness correction (bbf-lu-grundgesamtheit.csv)

befragung

display_name: befragung

bevolkerung

display_name: bevolkerung

lebensbedingungen

display_name: lebensbedingungen

lebensqualitat

display_name: lebensqualitat

living-conditions

display_name: living-conditions

population

display_name: population

quality-of-life

display_name: quality-of-life

subjective-living-conditions

display_name: subjective-living-conditions

subjektive-lebensbedingungen

display_name: subjektive-lebensbedingungen

survey

display_name: survey

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

en: Population survey Canton of Lucerne 2023


de: bevolkerungsentwicklung gemeinden bevolkerungswachstum bevolkerungsszenarien bevolkerung wachstum

fr: Scénario moyen (référence) 2023 - 2050

de: Mittleres Szenario (Referenz) 2023 - 2050

en: Medium scenario (reference) 2023 - 2050

it: Scenario medio (riferimento) 2023 - 2050

fr: Le scénario moyen (scénario de référence) tient compte des hypothèses du modèle qui extrapolent les évolutions démographiques des dernières décennies. Dans la perspective actuelle, il représente un cours probable.

de: Das mittlere Szenario (Referenzszenario) berücksichtigt Modellannahmen, welche die demografischen Entwicklungen der letzten Jahrzehnte fortschreiben. Es stellt dabei einen – aus gegenwärtiger Sicht – wahrscheinlichen Verlauf dar.

en: The medium scenario (reference scenario) takes into account model assumptions that extrapolate the demographic developments of the last decades. It represents a probable course – from the current perspective.

it: Lo scenario medio (scenario di riferimento) tiene conto delle ipotesi del modello che estrapolano gli sviluppi demografici degli ultimi decenni. Dal punto di vista attuale, rappresenta un corso probabile.

fr: Scénario bas 2023 - 2050

de: Tiefes Szenario 2023 - 2050

en: Low scenario 2023 - 2050

it: Scenario basso 2023 - 2050

fr: Le scénario bas repose sur des hypothèses qui orientent moins le niveau d'instruction et la croissance économique, réduisant ainsi la croissance démographique par rapport au scénario de référence.

en: The low scenario is based on hypotheses that drive educational attainment and economic growth less, thus reducing population growth compared to the reference scenario.

de: Das tiefe Szenario basiert auf Hypothesen, welche das Bildungsniveau und das Wirtschaftswachstum weniger vorantreiben und somit das Bevölkerungswachstum im Vergleich zum Referenzszenario mindern.

it: Lo scenario basso si basa su ipotesi che spingono meno il livello di istruzione e la crescita economica, riducendo così la crescita della popolazione rispetto allo scenario di riferimento.

fr: Scénario haut 2023 - 2050

de: Hohes Szenario 2023 - 2050

en: High scenario 2023 - 2050

it: Scenario alto 2023 - 2050

fr: Le scénario haut combine des hypothèses favorables à la croissance démographique et économique. La croissance démographique est donc estimée plus élevée que dans le scénario de référence.

en: The high scenario combines hypotheses that favor population and economic growth. Population growth is therefore estimated to be higher than in the reference scenario.

de: Beim hohen Szenario werden Hypothesen kombiniert, die das Bevölkerungs- und Wirtschaftswachstum begünstigen.

it: Lo scenario alto combina ipotesi che favoriscono la popolazione e la crescita economica. La crescita della popolazione è quindi stimata superiore a quella dello scenario di riferimento.

fr: Les scénarios de population LUSTAT pour le canton de Lucerne sont des modèles de calcul qui extrapolent l'évolution de la population résidente permanente au niveau communal. Trois variantes ont été calculées pour chaque scénario, qui diffèrent par les hypothèses sous-jacentes. Ils tiennent compte des hypothèses des modèles qui sont basées sur les tendances démographiques et socio-économiques des dernières décennies. L'année de calcul des chiffres clés sur lesquels se basent les calculs correspond à l'année 2023. Les scénarios partent de la population résidente permanente au 31 décembre 2022 et, en outre, aux personnes bénéficiant d'un statut de protection S.

de: Die LUSTAT-Bevölkerungsszenarien für den Kanton Luzern sind Modellberechnungen, welche die Entwicklung der ständigen Wohnbevölkerung auf kommunaler Ebene fortschreiben. Für die Szenarien wurden jeweils drei Varianten berechnet, welche sich in den zugrundeliegenden Hypothesen unterscheiden. Sie berücksichtigen Modellannahmen, welche auf demografischen und sozioökonomischen Trends der letzten Jahrzehnte beruhen. Das Berechnungsjahr der, bei den Berechnungen zugrundeliegenden, Kennziffern entspricht dem Jahr 2023. Als Anfangsbestand dient den Szenarien die ständige Wohnbevölkerung per 31.12.2022 plus die Personen mit Schutzstatus S.

en: The LUSTAT population scenarios for the canton of Lucerne are model calculations that extrapolate the development of the permanent resident population at the municipal level. Three variants were calculated for each scenario, which differ in the underlying hypotheses. They take into account model assumptions based on demographic and socioeconomic trends of recent decades. The year of calculation of the key figures on which the calculations are based on corresponds to the year 2023. The permanent resident population as of 31.12.2022 and additionally persons with protection status S is used as the initial stock for the scenarios.

it: Gli scenari demografici LUSTAT per il Cantone di Lucerna sono modelli di calcolo che estrapolano l'evoluzione della popolazione residente permanente a livello comunale. Per ogni scenario sono state calcolate tre varianti, che si differenziano per le ipotesi sottostanti. Prendono in considerazione le ipotesi del modello che si basano sulle tendenze demografiche e socioeconomiche degli ultimi decenni. L'anno di calcolo per le cifre chiave su cui si basano i calcoli corrisponde all'anno 2023. Gli scenari iniziano con la popolazione residente permanente al 31 dicembre 2022 e inoltre le persone con status di protezione S.

bevolkerungsentwicklung

display_name: bevolkerungsentwicklung

bevolkerungsszenarien

display_name: bevolkerungsszenarien

bevolkerungswachstum

display_name: bevolkerungswachstum

wachstum

display_name: wachstum

fr: Scénarios d’évolution démographique des communes du canton de lucerne

de: Szenarien zur Bevölkerungsentwicklung der Luzerner Gemeinden

en: Scenarios for population development of the communes of Canton Lucerne

it: Scenari per l'evoluzione demografica per comune di cantone di Lucerna


maintainer: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: BAG-OFSP-UFSP-FOPH Website

de: BAG-OFSP-UFSP-FOPH Website

en: BAG-OFSP-UFSP-FOPH Website

it: BAG-OFSP-UFSP-FOPH Website

fr: FSME - Système de déclaration obligatoire

de: FSME - Obligatorisches Meldesystem

en: TBE - mandatory reporting system

it: FSME - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle des cas de FSME en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of TBE cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von FSME Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di FSME in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

fsme-bag

display_name: fsme-bag

fsme-meningo-encephalite-a-tiques-ofsp

display_name: fsme-meningo-encephalite-a-tiques-ofsp

tbe-foph

display_name: tbe-foph

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.

political_level: confederation

value: DCAT-BAG-IDD Harvester

fr: FSME

de: FSME

en: TBE

it: FSME


name: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Shigellose - système de déclaration obligatoire

de: Shigellose - Obligatorisches Meldesystem

en: Shigellosis - mandatory reporting system

it: Shigellosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas de shigellose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Shigellose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of shigellosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di shigellosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

shigellose-bag

display_name: shigellose-bag

shigellose-ofsp

display_name: shigellose-ofsp

shigellosi-ufsp

display_name: shigellosi-ufsp

shigellosis-foph

display_name: shigellosis-foph

fr: Shigellose

de: Shigellose

en: Shigellosis

it: Shigellosi


chlamydiose

title_for_slug: chlamydiose

fr: Chlamydiose - système de déclaration obligatoire

en: Chlamydia - mandatory reporting system

de: Chlamydiose - Obligatorisches Meldesystem

it: Clamidiosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas de chlamydiose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Chlamydiose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of chlamydia infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di clamidiosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

chlamydia-foph

display_name: chlamydia-foph

chlamydiose-bag

display_name: chlamydiose-bag

chlamydiose-ofsp

display_name: chlamydiose-ofsp

clamidiosi-ufsp

display_name: clamidiosi-ufsp

de: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Chlamydiose

de: Chlamydiose

en: Chlamydia

it: Clamidiosi


fr: Borréliose - Sentinella

en: Lyme disease - sentinella

de: Borreliose - Sentinella

it: Borreliosi - Sentinella

fr: Les données se fondent sur les informations recueillies par le système Sentinella. Depuis 2008, les médecins transmettent des informations sur les premières consultations de patients présentant une maladie de Lyme dans leur cabinet ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Seit 2008 übermitteln ambulante Ärztinnen und Ärzte Informationen über Erstkonsultationen in Arztpraxen bei Patientinnen und Patienten mit Lyme Borreliose.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Since 2008, outpatient doctors have been submitting information on initial consultations in medical practices for patients with Lyme Disease.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Dal 2008, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano una malattia di Lyme.

fr: Données concernant la propagation et l’évolution temporelle des cas de borréliose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés provenant du système de déclaration Sentinella.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Borreliose Virusinfektionen und Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten aus dem Sentinella-Meldesystem.

en: Data on the spread and development of lyme disease infections and cases in Switzerland and the Principality of Liechtenstein. You will find data from the Sentinella reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di borreliosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati basate sul sistema di dichiarazione Sentinella.

borreliose-bag

display_name: borreliose-bag

borreliosemaladie-de-lyme-ofsp

display_name: borreliosemaladie-de-lyme-ofsp

borreliosi-malattia-di-lyme-ufsp

display_name: borreliosi-malattia-di-lyme-ufsp

lyme-disease-foph

display_name: lyme-disease-foph

fr: Borréliose

de: Borreliose

en: Lyme disease

it: Borreliose


fr: BAG-OFSP-UFSP-FOPH Website

de: BAG-OFSP-UFSP-FOPH Website

en: BAG-OFSP-UFSP-FOPH Website

it: BAG-OFSP-UFSP-FOPH Website

fr: Salmonellose - système de déclaration obligatoire

de: Salmonellose - Obligatorisches Meldesystem

en: Salmonellosis - mandatory reporting system

it: Salmonellosi - sistema di dichiarazione obbligatoria

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

fr: Données concernant la propagation et l’évolution temporelle des cas de salmonellose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Salmonellose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of salmonellosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di salmonellosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

salmonellose-bag

display_name: salmonellose-bag

salmonellose-ofsp

display_name: salmonellose-ofsp

salmonellosi-ufsp

display_name: salmonellosi-ufsp

salmonellosis-foph

display_name: salmonellosis-foph

fr: Salmonellose

de: Salmonellose

en: Salmonellosis

it: Salmonellosi


fr: Tularémie - Système de déclaration obligatoire

de: Tularämie - Obligatorisches Meldesystem

en: Tularaemia - mandatory reporting system

it: Tularemia - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle des cas de tularémie en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Tularämie Infektionen Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu laborbestätigten Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of tularemia infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on  cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di tularemia in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

tularaemia-foph

display_name: tularaemia-foph

tularamie-bag

display_name: tularamie-bag

tularemia-ufsp

display_name: tularemia-ufsp

tularemie-ofsp

display_name: tularemie-ofsp

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

fr: Tularémie

de: Tularämie

en: Tularemia

it: Tularämie


fr: Campylobactériose - système de déclaration obligatoire

de: Campylobacteriose - Obligatorisches Meldesystem

en: Campylobacteriosis - mandatory reporting system

it: Campilobatteriosi - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas de campylobactériose en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of campylobacteriosis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Campylobacteriose Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di campilobatteriosi in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

campilobatteriosi-ufsp

display_name: campilobatteriosi-ufsp

campylobacteriose-bag

display_name: campylobacteriose-bag

campylobacteriose-ofsp

display_name: campylobacteriose-ofsp

campylobacteriosis-foph

display_name: campylobacteriosis-foph

de: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.

fr: Campylobactériose

de: Campylobacteriose

en: Campylobacteriosis

it: Campilobatteriosi


hepatitis-b

title_for_slug: hepatitis-b

fr: Hépatite B - système de déclaration obligatoire

de: Hepatitis B - Obligatorisches Meldesystem

en: Hepatitis B - mandatory reporting system

it: Epatite B - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas d'hépatite B en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Hepatitis B Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of hepatitis B infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di epatite B in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

epatite-b-ufsp

display_name: epatite-b-ufsp

hepatite-b-ofsp

display_name: hepatite-b-ofsp

hepatitis-b-bag

display_name: hepatitis-b-bag

hepatitis-b-foph

display_name: hepatitis-b-foph

fr: Hépatite B

en: Hepatitis B

de: Hepatitis B

it: Epatite B


fr: BAG-OFSP-UFSP-FOPH Website

de: BAG-OFSP-UFSP-FOPH Website

en: BAG-OFSP-UFSP-FOPH Website

it: BAG-OFSP-UFSP-FOPH Website

fr: Virus respiratoire - Monitorage des eaux usées

en: Respiratory viruses - wastewater monitoring

de: Respiratorische Viren - Abwassermonitoring

it: Virus respiratori - Monitoraggio delle acque reflue

fr: Les données se fondent sur les informations issues du monitorage national des eaux usées de la Suisse et de la Principauté de Liechtenstein. Ce monitorage enregistre la charge virale de certains virus dans des échantillons des stations d’épuration des eaux usées (STEP) participantes ; il enregistre celle du SARS-CoV-2 depuis janvier 2022, celle de l’influenzavirus et du VRS depuis juillet 2023.

de: Die Daten basieren auf Informationen aus dem nationalen Abwassermonitoring der Schweiz und des Fürstentums Liechtenstein. Dieses Monitoring erfasst seit Januar 2022 die Viruslast von SARS-CoV-2 und seit Juli 2023 die Viruslast von Influenza und RSV in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

en: The data are based on information from the national wastewater monitoring programme of Switzerland and the Principality of Liechtenstein. This monitoring programme has been recording the viral load of SARS-CoV-2 since January 2022 and since July 2023, the viral load of influenza and RSV in wastewater samples from participating wastewater treatment plants (WWTPs).

it: I dati pubblicati di seguito si basano sulle informazioni ricavate dal monitoraggio nazionale delle acque reflue della Svizzera e del Principato del Liechtenstein. Questo monitoraggio registra la carica virale del SARS-CoV-2 dal gennaio 2022 e quella dell’influenza e del VRS dal luglio 2023 nei campioni di acque reflue degli impianti di depurazione delle acque reflue (IDA) partecipanti.

fr: Virus respiratoire - Sentinella

de: Respiratorische Viren - Sentinella

en: Respiratory viruses - sentinella

it: Virus respiratori - Sentinella

fr: Les données se fondent sur les informations recueillies par le système de déclaration Sentinella. Dans le cadre de ce système, les médecins transmettent des informations sur les premières consultations en raison d’une infection respiratoire aiguë (ARI) ou d’une affection grippale (ILI) dans leurs cabinets ou lors de visites à domicile.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Within the framework of this reporting system, outpatient doctors send information on initial consultations due to acute respiratory infection (ARI) or influenza-like illness (ILI) in medical practices and during home visits.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte Informationen zu Erstkonsultationen aufgrund akuter respiratorischer Infektion (ARI) oder grippeähnlicher Erkrankung (ILI) in Arztpraxen und bei Hausbesuchen.

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI) o una sindrome simil-influenzale (influenza-like illness, ILI).

fr: Influenza - Sentinella

de: Influenza - Sentinella

en: Influenza - sentinella

it: Influenza - Sentinella

fr: Les données se fondent sur les informations recueillies dans le cadre du système Sentinella. Depuis 1987, les médecins transmettent des informations concernant les premières consultations de patients présentant une affection grippale dans leur cabinet ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella Erhebungssystem. Ambulant tätige Ärztinnen und Ärzte übermitteln seit 1987 Informationen zu Erstkonsultationen von Patientinnen und Patienten mit einer grippeähnlichen Erkrankung (influenza-like illness, ILI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (Sentinella, SSSN) monitoring system. Since 1987, outpatient doctors have been submitting information on initial consultations in medical practices and during home visits for patients with influenza-like illness (ILI).

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Dal 1987 i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano una sindrome simil-influenzale (influenza-like illness, ILI).

fr: Influenza - Système de déclaration obligatoire

de: Influenza - Obligatorisches Meldesystem

en: Influenza - mandatory reporting system

it: Influenza - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires en Suisse et dans la Principauté de Liechtenstein ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori in Svizzera e nel Principato del Liechtenstein all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle des infections grippales et des cas de grippe en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les cas confirmés en laboratoire provenant du système de déclaration obligatoire et sur la charge virale dans les eaux usées provenant du monitorage des eaux usées.

en: Data on the spread and development of influenza infections and cases in Switzerland and the Principality of Liechtenstein. You will find data of outpatient consultations from the Sentinella reporting system and of cases from the obligatory reporting systemand of the viral load in wastewater from the wastewater monitoring system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Influenza Infektionen und Grippe Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu laborbestätigten Fällen aus dem obligatorischen Meldesystem und zur Viruslast im Abwasser aus dem Abwassermonitoring.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni e dei casi di influenza in Svizzera e nel Principato del Liechtenstein. Qui trovate dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati dei casi confermati in laboratorio basate sul sistema di dichiarazione obbligatoria e dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue.

bag-grippe-influenza

display_name: bag-grippe-influenza

foph-seasonal-flu-influenza

display_name: foph-seasonal-flu-influenza

ofsp-grippe-saisonniere-influenza

display_name: ofsp-grippe-saisonniere-influenza

ufsp-influenza-stagionale-influenza

display_name: ufsp-influenza-stagionale-influenza

fr: Influenza

de: Influenza

en: Influenza

it: Influenza


fr: Covid-19 - Sentinella

de: Covid-19 - Sentinella

en: Covid-19 - sentinella

it: Covid-19 - Sentinella

fr: Les données se fondent sur les informations recueillies par le système Sentinella. Dans le cadre de ce système de déclaration, les médecins transmettent depuis mars 2020 des informations sur les premières consultations de patients présentant une infection respiratoire aiguë dans leur cabinet ou lors de visites à domicile.

de: Die Daten basieren auf Informationen aus dem Sentinella-Meldesystem. Im Rahmen dieses Meldesystems übermitteln ambulant tätige Ärztinnen und Ärzte seit März 2020 Informationen zu Erstkonsultationen von Patientinnen und Patienten mit akuter respiratorischer Infektion (ARI) in Arztpraxen und bei Hausbesuchen.

en: The data are based on information from the Swiss Sentinel Surveillance Network (SSSN, Sentinella) monitoring system. Since March 2020, the system has been used by doctors working on an outpatient basis to submit information on initial consultations in medical practices and during home visits for patients with acute respiratory infections (ARIs).

it: I dati si basano sulle informazioni ricavate dal sistema di dichiarazione Sentinella. Nel quadro di questo sistema di dichiarazione, dal marzo 2020 i medici che esercitano nel settore ambulatoriale trasmettono informazioni relative alle prime consultazioni svolte negli studi medici o durante le visite domiciliari in cui i pazienti presentano un’infezione respiratoria acuta (acute respiratory infection, ARI).

fr: SARS-CoV-2 (Covid-19) - monitorage des variants dans les eaux usées

de: SARS-CoV-2 (Covid-19) - Virusvarianten im Abwasser

en: SARS-CoV-2 (Covid-19) -  monitoring of variants in wastewater

it: SARS-CoV-2 (Covid-19) - monitoraggio delle varianti nelle acque reflue

fr: Les données se fondent sur les informations issues du monitorage des variants dans les eaux usées de la Suisse. Ce monitorage enregistre la répartition des variants celle du SARS-CoV-2 dans des échantillons des stations d’épuration des eaux usées (STEP) participantes depuis février 2021.

de: Die Daten basieren auf Informationen aus dem Variantenmonitoring im Abwasser der Schweiz . Dieses Monitoring erfasst seit Februar 2021 die Verteilung der Virusvarianten von SARS-CoV-2 in Abwasserproben der teilnehmenden Abwasserreinigungsanlagen (ARA).

en: The data are based on information from the monitoring programme of variants in wastewater of Switzerland. This monitoring programme has been recording the distribution of variants of SARS-CoV-2 since February 2021 in wastewater samples from participating wastewater treatment plants (WWTPs).

it: I dati pubblicati di seguito si basano sulle informazioni ricavate dalmonitoraggio delle varianti nelle acque reflue della Svizzera. Questo monitoraggio registra la distribuzione delle varianti del SARS-CoV-2 dal febbraio 2021 nei campioni di acque reflue degli impianti di depurazione delle acque reflue (IDA) partecipanti.

fr: Covid-19 - surveillance génomique

de: Covid-19 - Genomische Überwachung

en: Covid-19 - genomic surveillance

it: Covid-19 - monitoraggio genomico

fr: Les données se fondent sur les informations tirées du Programme national de surveillance génomique du SARS-CoV-2, auquel participent, à l’heure actuelle, des laboratoires des hôpitaux universitaires et de grands hôpitaux régionaux de Suisse, ainsi qu’une plateforme de séquençage.

de: Die Daten basieren auf Informationen aus dem nationalen genomischen SARS-CoV-2 Überwachungsprogramm. An diesem beteiligen sich aktuell Laboratorien der Universitätsspitäler und grösserer Regionalspitäler der Schweiz sowie eine Sequenzierungsplattform.

en: The data are based on information from the national genomic SARS-CoV-2 surveillance programme. Currently participating in the programme are laboratories of the university hospitals and larger regional hospitals in Switzerland, as well as a sequencing platform.

it: I dati si basano sulle informazioni ricavate dal programma nazionale di sorveglianza genomica del SARS-CoV-2, al quale attualmente aderiscono i laboratori degli ospedali universitari e dei maggiori ospedali regionali della Svizzera, nonché una piattaforma di sequenziamento.

fr: Covid-19 - Système de déclaration obligatoire

de: Covid-19 - Obligatorisches Meldesystem

en: Covid-19 - mandatory reporting system

it: Covid-19 - Sistema di dichiarazione obbligatoria

fr: Les données se fondent sur les informations que les laboratoires, les médecins et les hôpitaux ont transmises à l’OFSP dans le cadre de la déclaration obligatoire.

de: Die Daten basieren auf Informationen, die Laboratorien, Ärztinnen und Ärzte sowie Spitäler dem BAG im Rahmen der Meldepflicht übermittelt haben.

en: The data are based on information that laboratories, doctors and hospitals have submitted to the FOPH under the mandatory reporting requirement.

it: I dati si basano su informazioni comunicate dai laboratori, dai medici e dagli ospedali all’Ufficio federale della sanità pubblica (UFSP) nel quadro della dichiarazione obbligatoria.

fr: Données concernant la propagation et l’évolution temporelle des infections au SARS-CoV-2 et des cas de COVID-19 en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur la charge virale dans les eaux usées provenant du monitorage correspondant, sur les consultations ambulatoires provenant du système de déclaration Sentinella, sur les variantes de virus provenant de la surveillance génomique et sur sur les cas, hospitalisations, décès et tests provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von SARS-CoV-2 Infektionen und Covid-19 Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zur Viruslast im Abwasser aus dem Abwassermonitoring, zu ambulanten Konsultationen aus dem Sentinella-Meldesystem, zu Virusvarianten aus der genomischen Überwachung und zu Fällen, Hospitalisationen, Todesfällen und Tests aus dem obligatorischen Meldesystem.

en: Data on the spread and development of SARS-CoV-2 infections and Covid-19 cases in Switzerland and the Principality of Liechtenstein. You will find data of the viral load in wastewater from the wastewater monitoring system, of outpatient consultations from the Sentinella reporting system, of virus variants from the genomic surveillance system and of cases, hospitalisations, deaths and tests from the obligatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale delle infezioni da SARS-CoV-2 e dei casi di COVID-19 in Svizzera e nel Principato del Liechtenstein. Qui trovate dati della carica virale nelle acque reflue basate sul sistema di monitoraggio delle acque reflue, dati delle consultazioni ambulatoriali basate sul sistema di dichiarazione Sentinella, dati delle varianti del virus basate sul sistema di sorveglianza genomica e dati di casi, ospedalizzazioni, decessi e test basate sul sistema di dichiarazione obbligatoria.

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

abteilung-uebertragbare-krankheiten

fr: Division Maladies transmissibles

de: Abteilung Übertragbare Krankheiten

en: Communicable Diseases Division

it: Divisione Malattie trasmissibili

de: Übertragbare Krankheiten gefährden die öffentliche Gesundheit. Die Abteilung überwacht diese Krankheiten, publiziert regelmässig Berichte zur epidemiologischen Situation, legt Präventions- und Kontrollstrategien fest und setzt sie um.

fr: SARS-CoV-2 (Covid-19)

de: SARS-CoV-2 (Covid-19)

en: SARS-CoV-2 (Covid-19)

it: SARS-CoV-2 (Covid-19)


hepatitis-e

title_for_slug: hepatitis-e

fr: BAG-OFSP-UFSP-FOPH Website

de: BAG-OFSP-UFSP-FOPH Website

en: BAG-OFSP-UFSP-FOPH Website

it: BAG-OFSP-UFSP-FOPH Website

fr: Hépatite E - système de déclaration obligatoire

de: Hepatitis E - Obligatorisches Meldesystem

en: Hepatitis E - mandatory reporting system

it: Epatite E - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas d'hépatite E en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Hepatitis E Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

en: Data on the spread and development of hepatitis E infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

it: Dati della diffusione e dell’evoluzione temporale dei casi di epatite E in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

epatite-e-ufsp

display_name: epatite-e-ufsp

hepatite-e-ofsp

display_name: hepatite-e-ofsp

hepatitis-e-bag

display_name: hepatitis-e-bag

hepatitis-e-foph

display_name: hepatitis-e-foph

de: Bundesamt für Gesundheit, Abteilung Übertragbare Krankheiten

fr: Les maladies transmissibles constituent une menace pour la santé publique. La division les surveille, publie régulièrement des rapports sur la situation épidémiologique, définit des stratégies de prévention et de contrôle, et les met en œuvre.

en: Communicable diseases pose a risk to public health. The division monitors these diseases, publishing regular reports on the epidemiological situation, laying down and implementing prevention and control strategies.

it: Le malattie trasmissibili mettono in pericolo la salute pubblica. La divisione Malattie trasmissibili le monitora, pubblica regolarmente rapporti sulla situazione epidemiologica, stabilisce strategie di prevenzione e di controllo e le attua.

fr: Hépatite E

en: Hepatitis E

de: Hepatitis E

it: Epatite E


syphilis

title_for_slug: syphilis

fr: Syphilis - système de déclaration obligatoire

en: Syphilis - mandatory reporting system

de: Syphilis - Obligatorisches Meldesystem

it: Sifilide - sistema di dichiarazione obbligatoria

fr: Données concernant la propagation et l’évolution temporelle des cas du syphilis en Suisse et dans la Principauté de Liechtenstein. Vous trouverez des donnés sur les cas provenant du système de déclaration obligatoire.

en: Data on the spread and development of syphilis infections and cases in Switzerland and the Principality of Liechtenstein. You will find data on cases from the mandatory reporting system.

de: Daten zur Verbreitung und zeitlichen Entwicklung von Syphilis Erkrankungsfällen in der Schweiz und im Fürstentum Liechtenstein. Sie finden Daten zu Fällen aus dem obligatorischen Meldesystem.

it: Dati della diffusione e dell’evoluzione temporale dei casi di sifilide in Svizzera e nel Principato del Liechtenstein. Qui trovate dati dei casi basate sul sistema di dichiarazione obbligatoria.

sifilide-ufsp

display_name: sifilide-ufsp

syphilis-bag

display_name: syphilis-bag

syphilis-foph

display_name: syphilis-foph

syphilis-ofsp

display_name: syphilis-ofsp

fr: Syphilis

de: Syphilis

en: Syphilis

it: Sifilide