en: yellowstone soil-biodiversity wolf decomposition biogeochemical-cycling fungi carrion detritus bacteria carcass

en:
Site	ID for different carcasses across the Yellowstone Landscape
Location	Sampling location, either under carcass or control plot
Species	Indicating whether carcass was from bison or elk
Gender	Gener of carcass; F = female, M = male, ? = unknown
Lat	Latitude
Long	Longitude
DSK	Days since kill; in days
Soil.N	Soil N concentration (%)
Soil.C	Soil C concentration (%)
Veg.C	Vegetation C concentration (%); dominant grasses sampled
Veg.N	Vegetation N concentration (%); dominant grasses sampled
Veg.CtoN	Vegetation C to N ratio; dominant grasses sampled
Soil.resp	Soil respiration (g m-2 h-1)
soil.temp	Soil temperature (°C)
Soil.moist	Soil moisture (volumentric; %)
CRR	Cotton rotting rate
bacteria.richness	Bacteria richness
bacteria.diversity	Bacteria diverstiy
fungi.richness	Fungi richness
fungi.diversity	Fungi diversity
bacteria.abundance	Bacteria abundance
fungi.abundance	Fungi abundance

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:

Risch, A.C., Frossard, A., Schütz, M., Frey, B., Morris, A.W., Bump, J.K. (accepted) Effects of elk and bison carcasses on soil microbial communities and ecosystem functions in Yellowstone, USA. (accepted). Functional Ecology
doi: ...

Methods
Study area and study sites
This study was conducted in YNP’s Northern Range (NR), located in north-western Wyoming and south-western Montana, USA (~44.9163° N, 110.4169° W). The NR expands over ~1000 km2 and features long cold winters and short dry summers. Grasslands and shrublands dominate the NR that is the home of large migratory herds of bison (winter counts 2017: ~3919 individuals; Geremia, Wallen, & White, 2017) and elk (~5349 individuals) as well as their main predators, approximately five packs of wolves with a total of 33 individuals (Smith et al., 2017). As part of a long-term research program within YNP, wolf predation has been studied since their reintroduction in 1995.
For our study, we received ground-truthed coordinates of bison and elk carcasses from winter 2016/17 (November 2016 through April 2017) from the YNP Wolf Project. Between June 20 and July 1, 2017, we visited 24 carcasses in total. At five sites, we could not sample as the carcasses were no longer found. In total we located remains (hairmats, rumen content, bones, teeth) of 19 adult male and female carcasses (7 bison, 12 elk; Supplementary Table 1). Live body weights of adult bison and elk are approximately 730 kg (male bison), 450 kg (female bison), 330 kg (male elk), and 235 kg (female elk, Meagher, 1973; Quimby & Johnson, 1951).
The kills and subsequent consumption happened between 34 and 173 days prior to our sampling (hereafter “days since kill”, DSK), for which we accounted in our statistics. Note that wolves and other scavengers consumed the soft tissue of the carcasses quickly, hence, there is close to no soft tissue left for decomposition as compared to an intact body left on the soil surface. The 19 carcass sites covered the extent of YNP’s NR, with both bison and elk carcasses showing similar distributions; elevation ranged from 1703 to 2884 m a.s.l. (Supplementary Fig 1 & Supplementary Table 1). The carcasses were all located in grassland or sage-brush shrubland, with or without sparsely scattered trees, and both bison and elk carcasses showed the same distribution of DSK. At each study site, we selected a reference plot (hereafter “control”) that was of comparable size, slope aspect and vegetation to the carcass location (hereafter “carcass”). The control was at least 10 m away (Danell, Berteaux, & Brathen, 2002; Melis et al., 2007) from the carcass itself to ensure the absence of potential direct and indirect carcass effects (paired design; (Bump, Webster, et al., 2009; Bump, Peterson, et al., 2009).

Ecosystem functions and soil properties
We randomly collected 50 g of mineral soil from three locations on both control and carcass plots to a depth of 5 cm with sterile techniques and gently mixed the material to obtain a composite sample. Half the soil sample was immediately bagged in plastic bags (whirl packs), stored in a cooler with ice packs (~5 ºC), sieved (2-mm) and frozen within 4-6 hours of collection to assess soil microbial communities. For this purpose, we extracted total genomic DNA from 0.5 g soil using the PowerSoil DNA Isolation Kit (Qiagen, Hilden, Germany). DNA concentrations were measured using PicoGreen (Molecular Probes, Eugene, OR, USA). PCR amplifications of partial bacterial small-subunit ribosomal RNA genes (region V3–V4 of 16S rRNA) and fungal ribosomal internal transcribed spacers (region ITS2) were performed as described previously (Frey et al., 2016). Each sample consisting of 40 ng DNA was amplified in triplicate and pooled before purification with Agencourt AMPure XP beads (Beckman Colter, Berea, CA, USA) and quantified with the Qubit 2.0 fluorometric system (Life Technologies, Paisley, UK). Amplicons were sent to the Genome Quebec Innovation Center (Montreal, Canada) for barcoding using the Fluidigm Access Array technology and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA).
Quality control of bacterial and fungal reads was performed using a customized pipeline (Supplementary Table 2; Frey et al., 2016). Paired-ends reads were matched with USEARCH (Edgar & Flyvbjerg, 2015), substitution errors were corrected using Bayeshammer (Nikolenko, Korobeynikov, & Alekseyev, 2013) and PCR primers were trimmed (allowing for 1 mismatch, read length >300 bp for 16S and >200 bp for ITS primers) using Cutadapt (M. Martin, 2011). Sequences were dereplicated and singleton reads removed prior to clustering into operational taxonomic units (OTUs) at 97% identity using USEARCH (Edgar, 2013). The remaining centroid sequences were tested for the presence of ribosomal signatures using Metaxa2 (Bengtsson-Palme et al., 2015) or ITSx (Bengtsson-Palme et al., 2013). Taxonomic assignments of the OTUs were obtained using Bayesian classifier (Wang, Garrity, Tiedje, & Cole, 2007) with a minimum bootstrap support of 60% implemented in mothur (Schloss et al., 2009) by querying the bacterial and fungal reads against the SILVA Release 128 (Quast et al., 2013) and UNITE 8.0 (Abarenkov et al., 2010) reference databases for 16S and ITS OTUs, respectively.
Abundances of the bacterial 16S rRNA gene and fungal ITS amplicon were determined by quantitative real-time PCR (qPCR) on an ABI7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA, USA) as described previously (Frossard et al., 2018). The same primers (without barcodes) and cycling conditions as for the sequencing approach were used for the 16S and ITS qPCR. Three standard curves per target region were obtained using tenfold serial dilutions of plasmids generated from cloned targets (Frey, Niklaus, Kremer, Lüscher, & Zimmermann, 2011). Data were converted to represent mean copy number of targets per gram of soil (dry weight).
The other half of the soil sample was bagged in paper, dried to constant weight at 60°C, passed through a 2 mm sieve and analyzed for total C and N concentration with a CE Instruments NC 2100 soil analyzer (CE Elantech Inc., Lakewood NJ, USA). We also collected 20 mature and undamaged leaves of the dominant grass species growing on control and carcass sites, but taxa were not recorded. The plant material was dried at 60°C, finely ground till homogenized and also analyzed to obtain total C and N concentrations. Soil temperature (10 cm depth) was measured with a waterproof digital thermometer (Barnstead International, Dubuque IA, USA) at three locations each at the control and carcass site. Soil moisture (0 – 10 cm depth) was measured with time domain reflectometry (Field-Scout TDR-100; Spectrum Technologies, Plainfield IL, USA) at five randomly chosen points on control and carcass sites. We measured soil respiration at five randomly chosen points at both control and carcass sites with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA). For each measurement the soil chamber (15 cm high; 10 cm diameter) was tightly placed on the soil surface, after clipping plants to avoid measuring plant respiration or photosynthesis. Measurements were conducted over 120 s.
In addition, we assessed the decomposition rates of standardized OM using the cotton strip assay (Latter & Howson, 1977; Latter & Walton, 1988). Cotton cloth tensile strength loss (CTSL) is a measure of decomposition, and an index to express the combined effect of soil microclimatic, physical, chemical and biological properties on decomposition while accounting for OM quality (Latter & Walton, 1988; Risch, Jurgensen, & Frank, 2007; Withington & Sanford Jr., 2007). We placed five 20 cm wide x 13 cm long sheets of 100% unbleached cotton cloth (American Type SM 1/18’’, Warp: 34/1, Weft: 20/1, Weave plain, 29.5 picks/cm warp, 22 picks/cm weft, 237 g/m2; Daniel Jenny & Co., Switzerland;) at each carcass and control site vertically into the soil by making slits with a flat spade to a depth of 12 cm. We inserted each cloth with the spade, and then pushed the slit closed to assure tight contact with the soil. The cloths were retrieved after 18 to 27 days. After retrieval, the cloths were air-dried, remaining soil gently removed by hand, and 1.5 cm wide strips were cut at the 3.5-5.0 cm (top) and the 9-10.5 cm (bottom) soil depth. The strips were equilibrated at 50 % relative humidity and 20°C for 48 hours (climate chamber) prior to strength testing (Scanpro Awetron TH-1 tensile strength tester; AB Lorentzen and Wettre, Kista, Sweden). Cotton rotting rate (CRR) = (CTScontrol - CTSfinal/CTSfinal)1/3 * (365/t), where CTScontrol is the cotton tensile strength of a control cloth and CTSfinal the cotton tensile strength of the incubated sample, t is the incubation period in days. Control cloths were inserted into the ground and immediately retrieved to account for tensile strength loss associated with cloth insertion. We averaged the CRR of top and bottom strips for further analyses as no difference was found between the two. All sampling and cloth insertion took place between June 20 and July 1, 2017, cloths were retrieved between July 17 and 20, 2017. Soil respiration, average CRR, vegetation N concentration and vegetation C:N ratio are defined as ecosystem functions, soil C and N concentration, soil temperature and moisture as soil abiotic properties, and bacterial and fungal richness (number of taxa), diversity (Shannon) and abundance as soil biotic properties.

Statistical analyses
Univariate analyses for ecosystem functions, soil biotic and abiotic properties
We tested whether individual ecosystem functions, soil biotic and abiotic properties differed between carcass and control (“Location”), bison and elk (“Species”) and days since kill (“DSK”). For this purpose, we used linear mixed effect models (LMM, “nlme” package v 3.1 – 131.1 in R v 3.4.4; Pinheiro, Bates, DebRoy, & Sarkar, 2018; R Core Team, 2019) with Location, Species, Location x Species and DSK as fixed effects. Site was included as random effect to account for the paired design. We developed a separate model for all dependent variables. All but bacterial richness, fungal richness, fungal diversity and vegetation N concentration were natural-log transformed to meet model assumptions. For each LMM, we calculated contrasts to assess the specific comparisons we were interested in with the “lsmeans” package v 2.27-62 (Lenth & Love, 2018): 1) carcass vs control, 2) carcass bison vs control bison, and 3) carcass elk vs control elk. We also tested whether we had differences between bison and elk carcasses or the sites where bison and elk were killed and included contrasts 4) carcass bison vs carcass elk and 5) control bison vs control elk.
We calculated the log response ratio (LRR = ln[carcass/control]) to obtain carcass effects for all variables for both species separately. LRR < 0 indicates higher value at control compared to carcass, LRR > 0 indicates higher values at carcass compared control. We used LRRs for visualization and to assess spatial patterns in carcass effects across YNP. For this purpose we calculated the Moran’s I statistic for each ecosystem function, soil biotic and abiotic property based on a latitude-longitude matrix with the “moran.test” function in the “spdep” package version 1.1-3 (Bivand et al., 2019).
Multivariate analyses
Rare OTUs, defined as OTUs with a low abundance of reads, were retained in multivariate methods because they only marginally influence these analyses (Gobet, Quince, & Ramette, 2010). Bray–Curtis dissimilarity matrices were generated based on square-root-transformed matrices. We used Principal Coordinate Analyses (PCoA) to assess how soil bacterial and fungal communities differed between control and carcass of bison and elk (“vegan” package v 2.5-4, Oksanen et al., 2019). We then extracted PCoA axes scores 1 and 2 and used LMM (“nlme” package) with Location, Species, Location x Species and DSK as fixed effects. Site was, again, included as random effect. We again calculated the contrasts as described above using the “lsmeans” package. We also assessed how ecosystem functions, and soil abiotic and biotic properties were related to the soil bacteria and fungi community structure associated with bison and elk control and carcasses using the “envfit” function in the “vegan” package (Oksanen et al., 2019).
Indicator species analyses were performed using the multipatt function implemented in the “indicspecies” package version 1.7.6 with 100000 permutations (De Caceres & Jansen, 2016). This step allowed to identify OTUs that led to changes in multivariate patterns between control and carcass of both bison and elk separately (De Cáceres, Legendre, & Moretti, 2010). The multipatt function uses a point biserial correlation coefficient statistical test. Indicator OTUs were defined as bacterial and fungal OTUs with more than 50 sequences, i.e., removing rare taxa and taxa with low abundances containing little indicator information (Rime et al., 2015) and that were significantly correlated with Location (p < 0.05, correlation coefficient > 0.3). A heatmap of these OTUs were generated with the vegan and ggplot2 packages. The indicator analyses were performed in R version 3.3.3 (R Core Team, 2017).

References
Abarenkov, K., Henrik Nilsson, R., Larsson, K.-H., Alexander, I. J., Eberhardt, U., Erland, S., … Kõljalg, U. (2010). The UNITE database for molecular identification of fungi – recent updates and future perspectives. New Phytologist, 186(2), 281–285. doi:10.1111/j.1469-8137.2009.03160.x
Bengtsson-Palme, J., Hartmann, M., Eriksson, K. M., Pal, C., Thorell, K., Larsson, D. G. J., & Nilsson, R. H. (2015). metaxa2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15(6), 1403–1414. doi:10.1111/1755-0998.12399
Bengtsson-Palme, J., Ryberg, M., Hartmann, M., Branco, S., Wang, Z., Godhe, A., … Nilsson, R. H. (2013). Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods in Ecology and Evolution, 4(10), 914–919. doi:10.1111/2041-210X.12073
Bivand, R., Altman, M., Anselin, L., Assuncao, R., Berke, O., Blanchet, G., … Yu, D. (2019). spdep: Spatial dependence, weighthing schemes, statistics. R package version 1.1-3.
Bump, J. K., Peterson, R. O., & Vucetich, J. A. (2009). Wolves modulate soil nutrient heterogeneity and foliar nitrogen by configuring the distribution of ungulate carcasses. Ecology, 90(11), 3159–3167.
Bump, J. K., Webster, C. R., Vucetich, J. A., Peterson, R. O., Shields, J. M., & Powers, M. D. (2009). Ungulate carcasses perforate ecological filters and create biogeochemical hotspots in forest herbaceous layers allowing trees a competitive advantage. Ecosystems, 12(6), 996–1007. doi:10.1007/s10021-009-9274-0
Danell, K., Berteaux, D., & Brathen, K. A. (2002). Effect of muskox carcasses on nitrogen concentration in tundra vegetation. Arctic, 55(4), 389392.
De Caceres, M., & Jansen, F. (2016). indicspecies: relationship between species and groups of species. R package version 1.7.6.
De Cáceres, M., Legendre, P., & Moretti, M. (2010). Improving indicator species analysis by combining groups of sites. Oikos, 119(10), 1674–1684. doi:10.1111/j.1600-0706.2010.18334.x
Edgar, R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996.
Edgar, R. C., & Flyvbjerg, H. (2015). Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics, 31(21), 3476–3482. doi:10.1093/bioinformatics/btv401
Frey, B., Niklaus, P. A., Kremer, J., Lüscher, P., & Zimmermann, S. (2011). Heavy-machinery traffic impacts methane emissions as well as methanogen abundance and community structure in oxic forest soils. Applied and Environmental Microbiology, 77(17), 6060–6068. doi:10.1128/AEM.05206-11
Frey, B., Rime, T., Phillips, M., Stierli, B., Hajdas, I., Widmer, F., & Hartmann, M. (2016). Microbial diversity in European alpine permafrost and active layers. FEMS Microbial Ecology, 92(3), fiw018.
Frossard, A., Donhauser, J., Mestrot, A., Gygax, S., Bååth, E., & Frey, B. (2018). Long- and short-term effects of mercury pollution on the soil microbiome. Soil Biology and Biochemistry, 120, 191–199. doi:https://doi.org/10.1016/j.soilbio.2018.01.028
Geremia, C., Wallen, R., & White, P. J. (2017). Status report of the Yellowstone bison population, September 2017. Yellowstone National Park, Mammoth, WY, USA: National Park Service, Yellowstone Center for Resources.
Gobet, A., Quince, C., & Ramette, A. (2010). Multivariate cutoff level analysis (MultiCoLA) of large community data sets. Nucleic Acids Research, 38(15), e155–e155. doi:10.1093/nar/gkq545
Latter, P., & Howson, G. (1977). The use of cotton strips to indicate cellulose decomposition in the field. Pedobiologia, (17), 145–155.
Latter, P., & Walton, D. (1988). The cotton strip assay for cellulose decomposition studies in soil: history of the assay and development. In Cotton strip assay: an index for decomposition in soils (pp. 7–9). ITE Symposium, Institute of Terrestrial Ecology, Natural Environment Research Council, UK.
Lenth, R., & Love, J. (2018). lsmeans: least-squares means. R package version 2.27-62.
Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.Journal, 17(1), 10–12.
Meagher, M. M. (1973). The bison of Yellowstone National Park. NPS Scientific Monograph (Vol. 1). National Park Service, Yellowstone Center for Resources.
Melis, C., Selva, N., Teurlings, I., Skarpe, C., Linnell, J. D. C., & Andersen, R. (2007). Soil and vegetation nutrient response to bison carcasses in Białowieża Primeval Forest, Poland. Ecological Research, 22(5), 807–813. doi:10.1007/s11284-006-0321-4
Nikolenko, S. I., Korobeynikov, A. I., & Alekseyev, M. A. (2013). BayesHammer: Bayesian clustering for error correction in single-cell sequencing. BMC Genomics, 14(1), S7. doi:10.1186/1471-2164-14-S1-S7
Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., … Wagner, H. H. (2019). vegan: community ecology package. R package version 2.5-4.
Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2018). nlme: Linear and nonlinear mixed effect models. R package version 3.1-131.1.
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., … Glöckner, F. O. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research, 41(Database issue), D590–D596. doi:10.1093/nar/gks1219
Quimby, D. C., & Johnson, D. E. (1951). Weights and measurements of Rocky Mountain elk. Journal of Wildlife Management, 15, 57–62.
R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Zurich, Switzerland.
R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
Rime, T., Hartmann, M., Brunner, I., Widmer, F., Zeyer, J., & Frey, B. (2015). Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield. Molecular Ecology, 24(5), 1091–1108. doi:10.1111/mec.13051
Risch, A. C., Jurgensen, M. F., & Frank, D. A. (2007). Effects of grazing and soil micro-climate on decomposition rates in a spatio-temporally heterogeneous grassland. Plant and Soil, 298(1–2), 191–201. doi:10.1007/s11104-007-9354-x
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., … Weber, C. F. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23), 7537–7541. doi:10.1128/AEM.01541-09
Smith, D., Stahler, D., Cassidy, K., Stahler, E., Metz, M., Cassidy, B., … Cato, E. (2018). Yellowstone National Park wolf project annual report 2017. Yellowstone National Park, Mammoth, WY, USA: National Park Service, Yellowstone Center of Resources.
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16), 5261–5267. doi:10.1128/AEM.00062-07
Withington, C., & Sanford Jr., R. (2007). Decomposition rates of buried substances increase with altitude in a forest-alpine tundra ecotone. Soil Biology and Biochemistry, (39), 68–75.

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

bacteria

display_name: bacteria

biogeochemical-cycling

display_name: biogeochemical-cycling

carcass

display_name: carcass

carrion

display_name: carrion

decomposition

display_name: decomposition

detritus

display_name: detritus

fungi

display_name: fungi

soil-biodiversity

display_name: soil-biodiversity

wolf

display_name: wolf

yellowstone

display_name: yellowstone

envidat

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: Elk and bison carcasses in Yellowstone, USA


maintainer: Mountain Hydrology and Mass Movements

en: flood-fatalities earthquake-fatalities debris-flow-fatalities ice-avalanche-fatalities lightning-fatalities rockfall-fatalities natural-hazard-fatalities landslide-fatalities windstorm-fatalities

state: active

type: dataset

media_type: text/csv

en: Natural hazard fatalities per year in Swizterland since 1946.

format: CSV

mimetype: text/csv

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

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.

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: Number of natural hazard fatalities per year in Switzerland since 1946


maintainer: EnviDat Support

en: antarctica depth-of-snowfall terrestiral-laserscanning terrestrial-laser-scans gridded-data

en: Scan from 21 December 2018, 1 mm resolution

format: SERVICE

en: Deprecated: Scan from 11 January 2019, 10 cm resolution, version 1

en: This resource is deprecated. It contains erroneous data.

en: Scan from 4 January 2019, 1 mm resolution

en: Scan from 27 December 2018, 1 mm resolution

en: Scan from 11 January 2019, 1 mm resolution

en: Scan from 21 December 2018, 10 cm resolution

en: Scan from 2 January 2019, 10 cm resolution

en: Scan from 11 January 2019, 10 cm resolution, version 2

media_type: application/zip

format: ZIP

mimetype: application/zip

en: Scan from 4 January 2019, 10 cm resolution

en: Scan from 27 December 2018, 10 cm resolution

en: Scan from 2 January 2019, 1 mm resolution

en:
Surface topography maps (spatial extent: 400 m x 400 m) obtained at approximately 300 m from the top of the Hammarryggen Ice Rise in Dronning Maud Land, East Antarctica, using a Riegl VZ-6000 Terrestrial Laser Scanner (TLS). Scans were obtained on 5 days in the 2018-2019 Austral summer: on December 21 and 27, and January 2, 4 and 11. By using reflectors installed on bamboo poles, scans were registered with respect to the reflectors, such that the difference between two successive scans reveals the spatial patterns of erosion and deposition of snow. On each scan day, we used multiple scan positions to create one combined point cloud. After applying an octree filter on the point cloud, a 3D surface was obtained. For each day, the dataset contains a 1 mm and a 10 cm octree filter resolution file, only including points in a 400 m x 400 m area centered around the scan positions.

Notes:

* All files in the dataset are in the same coordinate system. However, this coordinate system is arbitrary (i.e., not related to any global coordinate system).

* From the installed reflectors, 4 reflectors could be used over the full period. The scan accuracy is generally higher within the area enclosed by the reflectors.

* The scans from January 2 were found to have exhibited small tilt during the scan and are of lesser accuracy.

* By walking along fixed corridors, disturbance of the snow was limited.

antarctica

display_name: antarctica

depth-of-snowfall

display_name: depth-of-snowfall

gridded-data

display_name: gridded-data

terrestiral-laserscanning

display_name: terrestiral-laserscanning

terrestrial-laser-scans

display_name: terrestrial-laser-scans

en: Terrestrial laser scans on Hammarryggen Ice Rise, Dronning Maud Land, East Antarctica


en: land-use-abandonment grassland-management biodiversity vascular-plant disturbance

en: Boch et al. - Vegetation records Alpengarten Schynige Platte 2010-2015.xlsx

en: Vegetation records (species lists, percentage cover of species) of a six-year experiment to test whether different land-use treatments affect species diversity and composition in alpine to subalpine graslands.

format: XLS

en: This dataset was used for the publication "Boch, Blaser, Föhr, Küchler, Fischer (2024) Haymaking complemented by moderate disturbances can sustain and restore species-rich alpine to subalpine grasslands" in Alpine Botany. It contains vegetation records (species lists, percentage cover of species) of six grassland sites with each five 2x2 m treatment plots established in the Schynige Platte Alpine Botanical Garden. In a six-year experiment, we tested the response of plant species richness and mean ecological indicator values that we calculated from this dataset, to management treatments ranging from combined haymaking and scraping, to haymaking or scraping alone, to complete abandonment. We further tested whether the treatments led to changes in species composition, i.e. shifts to different vegetation types.

biodiversity

display_name: biodiversity

disturbance

display_name: disturbance

grassland-management

display_name: grassland-management

land-use-abandonment

display_name: land-use-abandonment

vascular-plant

display_name: vascular-plant

educ

en: Education, culture and sport

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: Schynige Platte Alpine Botanical Garden land-use experiment


en: grayzone complex-terrain wrf cosmo-wrf numerical-simulation

en:
This dataset contains simulation data for *"Influence of Air Flow Features on Alpine Wind Energy Potential" (Kristianti et al., 2024).*
•	The WRF_dia2702 and WRF_dia1103 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Diablerets region on 27/02/2021 and 11/03/2021, respectively.
•	The WRF_luk2310 and WRF_luk0912 folders contain the namelist.wps, namelist.input, and output files from the simulation in the Lukmanier region on 23/10/2020 and 09/12/2020, respectively.
•	The postprocessing file contains Python codes used to create figures in Kristianti et al. (2024).
**Notes:**
•	Topography input is provided by Gerber et al. (2021).
•	Simulations are run using the COSMO-WRF model developed by Gerber et al. (2018).
•	Visualization by Python code uses wrf-python provided by Ladwig et al. (2017).
*This dataset was produced by the EDGE consortium sponsored by the Swiss Federal Office of Energy's SWEET programme, Swiss National Science Foundation (SNSF): Grant 179130, and the Swiss National Supercomputing Centre (CSCS) projects s938, s1115 and s1242.*

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

grayzone

display_name: grayzone

numerical-simulation

display_name: numerical-simulation

wrf

display_name: wrf

en: COSMO-WRF Dataset for Swiss Alps Simulations in Gray-Zone Resolution


en: engineering estimation-methods decision-making hydrology flood

media_type: application/pdf

format: PDF

en:
(English version below)
Ziel dieser Faktenblätter ist es Informationen zu den Schätzmethoden, Hinweise zur Parametrisierung und eine grobe Einschätzung der Güte der Resultate in übersichtlicher Form bereitzustellen. Ein zeitaufwändiges Zusammensuchen dieser Informationen aus unterschiedlichen Quellen entfällt daher weitgehend. Die Bearbeitenden sollen damit in der Lage sein, sich innerhalb weniger Minuten die wichtigsten Hintergrundinformationen zu jeder der vorgestellten Methoden in Erinnerung zu rufen. Der Leitfaden unterstützt bei der Plausibilisierung und bei der Mittelung der Ergebnisse der einzelnen Schätzmethoden zu einem repräsentativen Endergebnis. Vorausgesetzt wird Grundwissen und Erfahrung in der Thematik.
Der Leitfaden führt die Fachperson anhand eines Entscheidungsbaums in acht Schritten durch den Arbeitsablauf und unterstützt mit einem Fragenkatalog bei der Plausibilisierung der Ergebnisse.
Auf den Faktenblättern sind für jede Schätzmethode alle relevanten Informationen stichwortartig und grafisch übersichtlich auf einer DIN-A4 Seite zusammengefasst. Jedes Faktenblatt ist einheitlich gegliedert.
The aim of these fact sheets is to provide information on the flood estimation methods, notes on their parameterization and a rough assessment of the quality of the results in a clear form. A time-consuming research for this information from different sources is therefore largely eliminated. The users should be able to recall the most important background information on each of the methods presented within a few minutes. The guide provides support in checking plausibility and averaging the results of the individual estimation methods to produce a representative final result. Basic knowledge and experience in the subject are assumed.
The guide leads the expert through the workflow in eight steps using a decision tree and supports the plausibility check of the results with a list of questions.
On the fact sheets, all relevant information for each estimation method is summarized with key words and graphics on one DIN A4 page. Each fact sheet has a standardized structure.

decision-making

display_name: decision-making

engineering

display_name: engineering

estimation-methods

display_name: estimation-methods

flood

display_name: flood

hydrology

display_name: hydrology

en: Faktenblätter und Leitfaden für Hochwasserschätzmethoden in der Praxis


maintainer: Elisabeth Hafner

en: reliability avalanche-mapping avalanche-size-estimation remote-sensing avalanche

en: AvalancheReliabilityData

en: The .zip contains all data used to conduct the reliability study as well as the results, a detailed description of the included files is contained in the included pdf. All geospatial data is provided in the Swiss Coordinate System: CH1903+ / LV95 (EPSG 2056). For any use of the data the proper citation provided is obligatory!

mimetype: application/x-zip-compressed

en:
This dataset contains the data used and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is

 Avalanche size estimates

* the 10 pictures depicting avalanches
* the survey results from the 170 participants

 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs

 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas

The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing

en: Data reliability study: avalanche size estimates and outlines


en: forest-reserves environmental-gradients carbon-storage forest-inventory biomass-dynamics

en: R markdown document used to download the data files, reproduce the analysis and plot generation.

format: OCTET

en: Climatic space covered by the Swiss National Forest Inventory (NFI) that will be used in Figure 5.

en:
This dataset documents the analyses and the plot generation for the manuscript **Long-term biomass dynamics in temperate forests in Europe after cessation of management**.
We analyse biomass development in an extensive network of 224 plots in 37 natural forest reserves (NFR) covering a wide environmental gradient with mean annual temperatures ranging from 1 to 10.4 °C and mean annual precipitation ranging from 901 to 2317 mm. Forest inventories have been conducted approximately every 10 years during the last 60 years.
It consists of the following files:
+ **Long_term_biomass_script.Rmd**: R markdown document to reproduce the analysis and the plot generation.
+ **dat_biomass.RDS**: Biomass values for each permanent plot at each inventory. This dataset is used for data exploration and for the Biomass model, and to create Figure 2 and Figure 3.
+ **dat_biomass_change.RDS**: Biomass change values between inventories for each permanent plot. It includes the explanatory variables as well. This dataset is used for the Biomass change model and to create Figure 4 and Figure 5.
+ **NFI_climspace_netCDF.RDS**: Climatic space covered by the Swiss National Forest Inventory (NFI) that is used in Figure 5.

biomass-dynamics

display_name: biomass-dynamics

carbon-storage

display_name: carbon-storage

environmental-gradients

display_name: environmental-gradients

forest-inventory

display_name: forest-inventory

forest-reserves

display_name: forest-reserves

en: Long-term biomass dynamics of temperate forests in Europe after cessation of management


maintainer: James W. Kirchner

en: ecohydrology diurnal-cycle snowmelt diel-cycle sap-flow groundwater streamflow evapotranspiration

en: Daily time series

media_type: text/plain

en: Daily hydrometeorological and ecohydrological time series

format: TXT

mimetype: text/plain

en: Metadata

en: Column descriptions for both data files, and map coordinates for all measurement locations.

mimetype: application/pdf

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en: MODIS NDSI script

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

educ

en: Education, culture and sport

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: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


maintainer: Felix Neff

en: insects grassland functional-traits diversity restoration functional-diversity topsoil-removal long-term-experiment

en: Plot information

en:
Information on the experimental plots.

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Landuse_history**: recent agricultural use for Initial; agricultural use before restoration for all restored sites
- **Last_tilled**: Last time the site was tilled
- **Intensity**: Frequency and intensity of mowing and manuring (*intensity1*: mowing once and no manure, i*ntensity2*: 2-3 times mowing and no manure, *intensity3*: 2-3 times mowing and manuring, *intensity4*: 4-5 times mowing and manuring)
- **Slope**: slope gradient according to classes defined by FAO (1990)
- **X**: X coordinate of the plot (CH1903)
- **Y**: Y coordinate of the plot (CH1903)
- **Cluster**: Spatial cluster of the plot

en: Insect abundance

en:
Abundance of adult insects recorded in the samplings on all experimental sites

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Number_Adults**: Number of adult individuals recorded
- **Herbivore**: Logical indicating whether the species is feeding as a herbivore (*TRUE*) or not (*FALSE*)

en: Insect traits

en:
Functional traits of all herbivorous insect species sampled in the study.

- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Body volume**: Body volume determined by body length, body width and body height (in mm$^3$)
- **Body_shape**: Ratio of body length to body width
- **Hind_femur_shape**: Ratio of hind-femur length to hind-femur width
- **Hind_front_leg_ratio**: Ratio of front-leg length to hind-leg length (leg length = femur length + tibia length)
- **Wing_length_rel**: Ratio of wing length to body length
- **Leg_length_rel**: Ratio of front-leg length to body length (leg length = femur length + tibia length)
- **Antenna_length_rel**: Ratio antenna length to body length
- **Eye_width_rel**: Ratio of eye width to head width (Auchenorrhyncha, Heteroptera) / to head height (Orthoptera)
- **Feeding_specialization**: Insect specialization on food source (*m*: monophagous, *o*: oligophagous, *p*: polyphagous)
- **Feeding_tissue**: Feeding tissue used for feeding (*c*: chewers, *x*: xylem, *p*: phloem, *m*: mesophyll, *m-p/r*: mesophyll as well as phloem and/or reproductive organs, *r*: reproductive organs, *se*: ripe seeds)
- **Hibernation**: Hibernation stage (*e*: egg, *e/n*: egg and nymph, *n*: nymph, *a*: adult)
- **Generations**: Number of generations per year (*1.5* stands for *1-2* generations per year)
- **Moisture_pref_mean**: mean of preferred habitat moistures (*1*: xerophilous, *2*: moderately xerophilous, *3*: moderately mesohygrophilous, *4*: mesohygrophilous, *5*: moderately hygrophilous, *6*: hygrophilous, *7*: moderately hydrophilous, *8*: hydrophilous)
- **Moisture_pref_range**: range of preferred habitat moistures (indicating degree of specialization)

en:
This dataset contains all data, on which the following publication below is based.

**Paper Citation**:

Neff, F., Resch, M. C., Marty, A., Rolley, J. D., Schütz, M., Risch, A. C, Gossner, M. M. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands: a functional approach. Ecological Applications, 30, e02133. [10.1002/eap.2133](https://doi.org/10.1002/eap.2133)

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

 Methods

 Study site
The study area is situated within and nearby to Eigental nature reserve (47°27’36” to 47°29’06” N, 8°37’12” to 8°37’44” E, 461 to 507 m a.s.l.) in the vicinity of Zurich airport (Canton Zurich, Switzerland). Mean annual precipitation and temperature is 903 ± 136 mm and 9.14°C ± 0.50°C (mean ± SD for 2007-2017 (*MeteoSchweiz 2018*)). In 1967, the Eigental nature reserve was established to protect small and isolated remnants of species-rich, semi-natural grasslands (roughly 12 ha), which were embedded in an otherwise intensively managed landscape. It is characterized by oligo- to mesotrophic Molinion (semi-wet, matrix species *Molinia caerulea*) and Mesobromion (semi-dry, matrix species *Bromus erectus*) meadows (*Delarze et al. 2015*), reflecting small-scale habitat heterogeneity, mainly due to site-specific groundwater levels and slope inclination. As in most Central European grasslands, management is necessary to prevent shrub and tree invasions as well as to secure low levels of available soil nutrients and thus to maintain these species-rich habitats ([*Poschlod and WallisDeVries 2002*](https://doi.org/10.1016/S0006-3207(01)00201-4)).
In 1990, the government of the Canton Zurich decided to enlarge the Eigental nature reserve as a counter measure against degradation and biodiversity loss in semi-natural grasslands due to overutilization and the excessive input of nutrients (mostly nitrogen). Eleven patches of adjacent intensively managed grassland (in total roughly 20 ha) were targeted to be transformed into semi-natural grasslands. As a first restoration measure, fertilization was ceased, and biomass harvested three times to remove excessive soil nutrients from the original system and thus benefit plant species with low competitive ability on the long run. In 1995, the restoration efforts were increased and a large-scale experiment comprising three restoration measures with increasing intervention intensities was implemented:

- **Harvest only**: Initial restoration measures were continued with mowing and removing of the aboveground biomass two times a year (early summer and autumn).
- **Topsoil**: Removal of topsoil, depending on the thickness of the A horizon the upper 10 to 20 cm, in four randomly selected areas within the eleven patches in late autumn 1995. The size of the restoration area depended on individual patch size (2700 to 7000 m2).
- **Topsoil + Propagules**: Plant propagules were added on half of the area where topsoil was removed via application of fresh, seed-containing hay and hand-collected propagules of target species originating from semi-dry and semi-wet species-rich grasslands with local and regional provenance (within radius of 7 to 30 km) (1995, 1996, 1997).

Management of *Topsoil* and *Topsoil + Propagules* started five years after treatment implementation and included yearly mowing and removing of aboveground biomass (late summer or early autumn). The experiment was complemented with intensively managed grassland sites that share the same agricultural history as the restored sites (**Initial**; swards dominated by *Lolium perenne*, *L. multiflorum* and *Trifolium repens*): mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes. Finally, sites were selected in target semi-dry and semi-wet grasslands (**Target**) located within the Eigental nature reserve and another nature reserve nearby (Altläufe der Glatt; 47°28’29” to 47°27’41” N, 8°31’56” to 8°32’26” E, 418 to 420 m a.s.l.). The selected target sites are mown and aboveground biomass removed once a year in late summer or early autumn. For each of the five treatments, we selected eleven plots (5 m × 5 m) spread across the sites. Altogether, the experiment included 55 plots.

 Arthropod sampling
Aboveground arthropods were sampled using suction sampling on four consecutive days in early July 2017 before the grasslands were mown. Arthropods were sampled in two locations on each 5 m × 5 m plot, once in the south-western and once in the north-eastern corner to account for possible spatial heterogeneity within the plots. Arthropods were sorted to order or lower taxonomic levels and individuals were identified to species level. We focused on three groups (Hemiptera: Auchenorrhyncha, Hemiptera: Heteroptera, Orthoptera),

 Functional traits
We used two sets of functional traits in this study.

**Morphometric traits**:
Body volume, body shape, hind femur shape, hind/front leg ratio, wing length, leg length, antenna length and eye width. We used trait measurements from [*Simons et al. (2016)*](http://dx.doi.org/10.1890/15-0616.1) and [*Neff et al. (2019)*](https://doi.org/10.1007/s10980-019-00872-1) and complemented them with measurements on study specimens. These measurements were conducted using a high-resolution measuring stereo microscope (Leica DVM6, Leica Microsystems) including automated high-resolution photo stacking with the software Leica Application Suite X (LAS X, © 2018 Leica Microsystems CMS GmbH) and Leica Map Premium (Leica Microsystems, © 1996-2017 Digital Surf) at WSL Birmensdorf. The eight morphometric traits were calculated from direct measurements of body parts on specimens of all sampled species. From each species, we measured at least one female and one male specimen. Additionally, for species that show wing dimorphism, we included the different wing morphs and weighted them by their prevalence reported in literature. For few species, of which not all wing morphs were available for measurements (10 cases), we estimated relative wing length from congeneric species or from the literature.

**Life-history traits**
Based on an existing data set collected by [*Gossner et al. (2015)*](http://dx.doi.org/10.1890/14-2159.1). We included traits describing different life-history characteristics of herbivore insect species, namely: feeding specialization, feeding tissue, hibernation stage and number of generations per year, which are related to insect species’ vulnerability to changes in plant community composition, microhabitat use and disturbance tolerance. To represent potential changes in habitat moisture with abandonment of intensive land use (e.g., change in ground-water level), we also included two traits related to preferred habitat moisture of the study species: moisture preference, describing species’ optimum habitat moisture, and moisture range, which describes the species’ range of preferable moisture conditions.

 References

Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten. 3rd ed. Ott, Bern.

Gossner, M. M., N. K. Simons, R. Achtziger, T. Blick, W. H. O. Dorow, F. Dziock, F. Köhler, W. Rabitsch, and W. W. Weisser. 2015. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. Scientific Data 2:150013.

MeteoSchweiz. 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.

Neff, F., N. Blüthgen, M. N. Chisté, N. K. Simons, J. Steckel, W. W. Weisser, C. Westphal, L. Pellissier, and M. M. Gossner. 2019. Cross-scale effects of land use on the functional composition of herbivorous insect communities. Landscape Ecology 34:2001–2015.

Poschlod, P., and M. F. WallisDeVries. 2002. The historical and socioeconomic perspective of calcareous grasslands—lessons from the distant and recent past. Biological Conservation 104:361–376.

Simons, N. K., W. W. Weisser, and M. M. Gossner. 2016. Multi-taxa approach shows consistent shifts in arthropod functional traits along grassland land-use intensity gradient. Ecology 97:754–764.

diversity

display_name: diversity

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

grassland

display_name: grassland

insects

display_name: insects

long-term-experiment

display_name: long-term-experiment

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

en: Grassland restoration: insects and insect traits


en: snow snowpack snow-models snow-temperatures snow-cover

en: Metadata 1991

en: Dataset 1991

en:
During the development of DAISY, the snowpack model we
realised that we did not have enough accurate calibration measurements. We
needed more reliable measurements of snow temperatures and settlements
within the snow cover.

Therefore, from winter 1990/91 the thermal development of the season snow
cover in the test field with self-developed temperature harps was measured.
These temperature harps can move freely with the snow cover, in contrast to
the usually fixed temperature profiles.

With these harps, it became possible to monitor the temperatures and
settlements of the individual layers throughout the winter.

Additionally, the surface temperature, snow level and the usual
meteorological parameters such as air temperature, humidity, wind speed and
the radiation in various wavelength ranges were measured.

Furthermore, conventional snow profiles were recorded with measurements of
densities, hardness, grain sizes and grain shapes.

During three winters, this facility was intensively used for monitoring
purposes. The support and monitoring of these measurements and the
accompanying, very time-intensive manual measurements were carried out by
Peter Weilenmann and Franz Herzog.

The results of these measurements in winter 1990/91, 1991/92 and 1992/93
are given in the internal report No. 723.

The use of these measurements for the validation of DAISY and MiniDAISY are
gathered internally in report No. 724..726.

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-models

display_name: snow-models

snow-temperatures

display_name: snow-temperatures

snowpack

display_name: snowpack

en: WFJ_CAL: Calibration dataset for snow models


en: climate-change statistical-interpolation microclimate ecology forest radiation-transfer biodiversity

en: Predicted microclimate air temperatures at 100 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate air temperatures at 5 cm above ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Predicted microclimate topsoil temperatures at 5 cm below ground. 10 m spatial resolution raster files are provided for mean daily minimum (tmin), mean (tmean) and maximum (tmax) temperatures during each month from April (04) to October (10) over the period between 2012 to 2021.

en: Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate-change impacts on biodiversity and ecosystem functioning. Here we combine a national network of microclimate temperature measurements with a novel radiative transfer model to map monthly minimum, mean and maximum temperatures during the vegetation period at a 10 meter spatial resolution across Switzerland. The temperature measurements took place in 107 sampling plots distributed across different habitat types, with 62 plots in forests, 22 below trees outside forests, and 23 in open grasslands. In each plot we measured temperature in the topsoil (-5cm), as well as in the air at 5cm and 100cm height above ground. Spatial interpolation was achieved by using a hybrid approach based on linear mixed effects models with input from detailed radiation estimates that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography and vegetation height. Our data reveals strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 °C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 °C. We also found that in open grasslands, maximum temperatures at 5 cm above ground are on average 3.4 °C warmer than that of macroclimate, suggesting that in such habitats heat exposure close to the ground is often underestimated when using macroclimatic data. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by RSME’s ranging from 1.18 to 3.43 °C, with minimum temperatures generally being predicted more accurately than maximum temperatures. The microclimate maps presented here enable a more biologically relevant perspective when analysing climate-species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change.

biodiversity

display_name: biodiversity

climate-change

display_name: climate-change

ecology

display_name: ecology

forest

display_name: forest

microclimate

display_name: microclimate

radiation-transfer

display_name: radiation-transfer

statistical-interpolation

display_name: statistical-interpolation

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Monthly topsoil and near surface microclimate temperature data for Switzerland


en: tree-ring paleoclimate temperature-reconstruction mxd wood-anatomy

en: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.

en:
This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".

Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density	= Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)

en: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.

mxd

display_name: mxd

paleoclimate

display_name: paleoclimate

temperature-reconstruction

display_name: temperature-reconstruction

tree-ring

display_name: tree-ring

wood-anatomy

display_name: wood-anatomy

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: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula


en: climate-change visualization scenario landscape-change policy-action

en: Seeland subtitles FR

en:
Scenarios of landscape change under climate change in the Swiss lowlands.
Trailer in French with subtitles.

en: Entremont subtitles DE

en:
Scenarios of landscape change under climate change in the Swiss mountains.
Trailer in German with written subtitles.

en: Entremon subtitles FR

en: Scenarios of landscape change under climate change in the Swiss mountains. Trailer in French with subtitles.

en: Seeland subtitles DE

en:
Scenarios of landscape change under climate change in the Swiss lowlands.
Trailer in German with subtitles.

en:
Short videos showing scenarios of potential landscape development in a 4°C warmer climate for a Swiss mountain region and a region on the Swiss Plateau. The videos are in German or French with subtitles.
The videos' key message is: Climate change will have an impact on the Swiss landscapes. However, according to the strategy chosen to adapt to climate change, society and politics will also have a strong influence on the future landscapes and the services they will provide. If no action is taken to adapt to climate change today, then society will have to react in a hurry at a later point in time. This can often result in resource-intensive technical solutions. Conversely, if society takes action in an anticipatory way already today, nature-based solutions can be implemented more successfully and humans can benefit more from the landscape services..
These short videos are teasers that should make the viewers curious to visit the panorama pictures (https://viergrad.envidat.ch/).

landscape-change

display_name: landscape-change

policy-action

display_name: policy-action

scenario

display_name: scenario

visualization

display_name: visualization

en: Teaser videos Swiss landscapes under climate change


maintainer: Bundesamt für Energie BFE

title_for_slug: Schweizerische Elektrizitätsstatistik: Schweizerische Elektrizitätsbilanz - Monatswerte

fr: ogd35-bfe electricite production importation exportation consommation

de: ogd35-bfe elektrizitat produktion import export verbrauch

en: ogd35-bfe electricity production import export

it: ogd35-bfe elettricita produzione importazione esportazione consumo

fr: Statistique suisse de l'électricité: bilan mensuel suisse de l'électricité

it: Statistica svizzera dell'elettricità: bilancio svizzero dell'elettricità - valori mensili

author: Bundesamt für Energie BFE

fr: Cette statistique recense sur une base mensuelle la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production des centrales hydrauliques, des centrales nucléaires, des centrales thermiques classiques et renouvelables. Elle indique la consommation des installations de pompage d'accumulation et les pertes en ligne. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Schweizerische Elektrizitätsbilanz - Monatswerte gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz auf monatlicher Basis. Bei der Produktion werden Wasserkraftwerke, Kernkraftwerke, konventionell-thermische und erneuerbare Kraftwerke unterschieden. Der Verbrauch der Speicherpumpen und die Leitungsverluste werden ausgewiesen. Die monatliche Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erstellt, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

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

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

de: Bundesamt für Energie BFE

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).

political_level: confederation


eignung-erdwarmenutzung

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: eignung-erdwarmenutzung

label: geocat.ch permalink

de: AGIS Direktdownload

de: Eignung Erdwärmenutzung

format: WMS

de: Der Datensatz zeigt in welchen Gebieten die Erstellung von Erdwärmesonden und Grundwasserwärmepumpen möglich oder nicht möglich ist.

de: AGIS Service Center Kanton Aargau

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

political_level: canton

value: Aargau-Kt - Geocat Harvester


belastete-standorte-kbs

title_for_slug: belastete-standorte-kbs

de: Belastete Standorte (KBS)

de: Der Kataster der belasteten Standorte beinhaltet Standorte, welche mit grosser Wahrscheinlichkeit mit Abfällen belastet sind. Dieser Datensatz löst seit dem 19.9.2019 den Datensatz afu_kbsbelstx ab.


rebbaukataster-ur

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

title_for_slug: rebbaukataster-ur

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

format: WFS

fr: Der Rebbaukataster umfasst alle Grundstücke die mit Reben bepflanzt sind oder auf denen Reben angepflanzt werden dürfen.

spatial: Canton of Uri (UR)

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

value: Uri-Kt - Geocat Harvester

fr: Rebbaukataster (UR)

de: Rebbaukataster (UR)

en: Rebbaukataster (UR)

it: Rebbaukataster (UR)


grundwasserschutzareale-differenz-ur

title_for_slug: grundwasserschutzareale-differenz-ur

de: grundwasserschutzareal geobasisdaten

fr: Grundwasserschutzareale sind speziell ausgeschiedene Gebiete, in welchen der Schutz des unterirdischen Gewässers im Hinblick auf eine künftige Grundwasserbewirtschaftung (Nutzung oder Anreicherung) vorsorglich sichergestellt werden soll. In diesen Arealen dürfen keine Bauten und Anlagen erstellt werden, welche die künftige Bewirtschaftung beeinträchtigen können.

fr: Grundwasserschutzareale Differenz (UR)

de: Grundwasserschutzareale Differenz (UR)

en: Grundwasserschutzareale Differenz (UR)

it: Grundwasserschutzareale Differenz (UR)


grundwasserschutzzonen-ur

regi

de: Regionen und Städte

title_for_slug: grundwasserschutzzonen-ur

fr: Grundwasserschutzzonen dienen dazu, Trinkwassergewinnungsanlagen und das Grundwasser unmittelbar vor seiner Nutzung als Trinkwasser vor Beeinträchtigungen zu schützen. Sie sind um die im öffentlichen Interesse liegenden Grundwasserfassungen auszuscheiden, d.h. um alle Fassungen, deren Wasser den Anforderungen der Lebensmittelgesetzgebung entsprechen muss, sowie um Grundwasser-Anreicherungsanlagen. Die Grundwasserschutzzonen sind das wichtigste Instrument des nutzungsorientierten, planerischen Grundwasserschutzes. Grundwasserschutzzonen werden gegliedert in: Zone S1 (Fassungsbereich), Zone S2 (Engere Schutzzone), Zone S3 (Weitere Schutzzone)

fr: Grundwasserschutzzonen (UR)

de: Grundwasserschutzzonen (UR)

en: Grundwasserschutzzonen (UR)

it: Grundwasserschutzzonen (UR)


grundwasserschutzzonen-projektiert-ur

envi

de: Umwelt

title_for_slug: grundwasserschutzzonen-projektiert-ur

de: Grundwasserschutzzonen dienen dazu, Trinkwassergewinnungsanlagen und das Grundwasser unmittelbar vor seiner Nutzung als Trinkwasser vor Beeinträchtigungen zu schützen. Sie sind um die im öffentlichen Interesse liegenden Grundwasserfassungen auszuscheiden, d.h. um alle Fassungen, deren Wasser den Anforderungen der Lebensmittelgesetzgebung entsprechen muss, sowie um Grundwasser-Anreicherungsanlagen. Die Grundwasserschutzzonen sind das wichtigste Instrument des nutzungsorientierten, planerischen Grundwasserschutzes. Grundwasserschutzzonen werden gegliedert in: Zone S1 (Fassungsbereich), Zone S2 (Engere Schutzzone), Zone S3 (Weitere Schutzzone)

fr: Grundwasserschutzzonen projektiert (UR)

de: Grundwasserschutzzonen projektiert (UR)

en: Grundwasserschutzzonen projektiert (UR)

it: Grundwasserschutzzonen projektiert (UR)


grundwasserschutzzonen-differenz-ur

title_for_slug: grundwasserschutzzonen-differenz-ur

en: Grundwasserschutzzonen dienen dazu, Trinkwassergewinnungsanlagen und das Grundwasser unmittelbar vor seiner Nutzung als Trinkwasser vor Beeinträchtigungen zu schützen. Sie sind um die im öffentlichen Interesse liegenden Grundwasserfassungen auszuscheiden, d.h. um alle Fassungen, deren Wasser den Anforderungen der Lebensmittelgesetzgebung entsprechen muss, sowie um Grundwasser-Anreicherungsanlagen. Die Grundwasserschutzzonen sind das wichtigste Instrument des nutzungsorientierten, planerischen Grundwasserschutzes. Grundwasserschutzzonen werden gegliedert in: Zone S1 (Fassungsbereich), Zone S2 (Engere Schutzzone), Zone S3 (Weitere Schutzzone)

fr: Grundwasserschutzzonen Differenz (UR)

de: Grundwasserschutzzonen Differenz (UR)

en: Grundwasserschutzzonen Differenz (UR)

it: Grundwasserschutzzonen Differenz (UR)


de: baulinie eigentumsbeschrankungoreb nutzungsplanung wald zonenplan

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Zeigt die statischen Waldgrenzen aufgrund einer formellen Waldfeststellung durch die Dienststelle Landwirtschaft und Wald (lawa).

spatial: Kanton Luzern

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

value: LU-Kt - Geocat Harvester

de: Statische Waldgrenzen


zonenplane-gewasserraum

title_for_slug: zonenplane-gewasserraum

de: fliessgewasser gewasserschutz nutzungsplanung oberflachengewasser raumplanung zonenplan

de: Gewässerraum aus den Zonenplan-Überlagerungen, unterschieden nach Freihaltezone und Grünzone.

spatial: Schweiz

de: Zonenpläne: Gewässerraum


de: fliessgewasser gewasserschutz landwirtschaft landwirtschaftliche-nutzung nutzungsplanung raumplanung zonenplan

de: Der Gewässerraum ist extensiv zu gestalten und zu bewirtschaften (GSchG, Art. 36a Abs. 3). In der Landwirtschaft sind folgende Gewässerraumflächen von den Bewirtschaftungseinschränkungen ausgenommen: Flächen über eingedolten Gewässerabschnitten, Randstreifen entlang Verkehrsachen und äussere Korridore bei Gewässeräumen von grossen Fliessgewässern. Der Datensatz umfasst diese Festlegungen.


gestaltungsplane-perimeter

regi

de: Regionen und Städte

title_for_slug: gestaltungsplane-perimeter

de: eigentumsbeschrankungoreb nutzungsplanung raumplanung sondernutzungsplanung

de: Geltungsbereiche (Perimeter) von Gestaltungsplänen, welche eine siedlungsgerechte, architektonisch und erschliessungstechnisch gute Überbauung eines zusammenhängenden Gebietes sicherstellen.

de: Gestaltungspläne: Geltungsbereiche


kommunale-bebauungsplane

envi

de: Umwelt

title_for_slug: kommunale-bebauungsplane

de: baulinie eigentumsbeschrankungoreb gebaude-und-anlagen nutzungsplanung raumplanung sondernutzungsplanung wirtschaftliche-aktivitaten

de: Objekte und Perimeter der kommunalen Bebauungspläne (Naturobjekte, Baulinien, Abgrenzungen, Baubereiche, Strassen, öffentlicher Raum, usw.)

de: Kommunale Bebauungspläne


nutzungsplanung-planungszonen

title_for_slug: nutzungsplanung-planungszonen

de: bewilligungen eigentumsbeschrankungoreb nutzungsplanung raumplanung zonenplan

de: Datenshop

de: Produktansicht Geodatenshop

de: Die Planungszone bezeichnet ein Gebiet, in dem Nutzungspläne erlassen oder geändert werden müssen.

de: Nutzungsplanung: Planungszonen


soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

de: eigentumsbeschrankungoreb gebaude-und-anlagen kulturdenkmal kulturguterschutz nutzungsplanung ortsbildschutz zonenplan

de: Im Bauinventar werden schützenswerte und erhaltenswerte Baudenkmäler des Kantons erfasst. Besonders schutzwürdige Kulturobjekte werden ins Kantonale Denkmalverzeichnis eingetragen und unter Schutz gestellt.

de: Geoinformation Kanton Luzern

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

de: Kantonales Denkmalverzeichnis und Bauinventar


zonenplane

regi

fr: Régions et villes

de: Regionen und Städte

title_for_slug: zonenplane

de: baulinie eigentumsbeschrankungoreb grundeigentum nutzungsplanung raumplanung zonenplan

de: Zonenpläne sind grundeigentümerverbindlich und regeln die zulässige Art der Bodennutzung im Gebiet einer Gemeinde.

de: Nutzungsplanung: Zonenpläne


baulandangebot

envi

fr: Environnement

de: Umwelt

title_for_slug: baulandangebot

de: Durch Gemeinden angebotene Baulandparzellen. Die Angebote werden durch teilnehmenden Gemeinden selber verwaltet.

de: Baulandangebote Gemeinden


ener

fr: Énergie

de: Energie

en: Energy

it: Energia

de: gebaude-und-anlagen strahlung telekommunikation ver--und-entsorgung

de: Datenshop

de: Produktansicht Geodatenshop

de: Zeigt Antennenstandorte mit Angaben zu Betreiber und Mobilfunkstandard. Angezeigt werden Basisstationen für 2G, 3G, 4G und 5G - Mobilkommunikation.

de: Antennenstandorte Mobilfunk


de: koordinaten miv zahlstellen

de: gpx

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (gpx)

format: GPX

de: shp

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (shp)

de: turtle

media_type: text/turtle

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (turtle)

format: RDF Turtle

de: jsonl

media_type: application/json

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (jsonl)

format: JSON

de: parquet

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (parquet)

format: PARQUET

de: xls

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (xls)

de: fgb

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (fgb)

de: geojson

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (geojson)

de: csv

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (csv)

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (ov2)

de: kml

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (kml)

format: KML

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (n3)

de: json

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (json)

de: jsonld

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (jsonld)

format: JSON-LD

de: rdfxml

media_type: application/rdf+xml

de: Detailpläne und Geokoordinaten MIV Zählstellen Stadt St.Gallen (rdfxml)

format: RDF XML

de: Dieser Datensatz zeigt sämtliche Detailpläne und Geokoordinaten der Zählstellen des motorisierten Individualverkehrs (MIV) der Stadt St.Gallen. Darin enthalten sind die Pläne zur Erklärung der Richtungsnummern, die Koordinaten im schweizerischen Landeskoordinatensystem LV95, sowie im globalen Koordinatensystem WGS84 (GPS).Die LV95-Koordinaten stammen aus dem System des städtischen Tiefbauamtes, während zur Umrechnung von LV95 in WGS84 die Transformationsdienste des Bundesamt für Landestopografie swisstopo verwendet wurden: [https://www.swisstopo.admin.ch/de/karten-daten-online/calculation-services.html](https://www.swisstopo.admin.ch/de/karten-daten-online/calculation-services.html)

koordinaten

display_name: koordinaten

miv

display_name: miv

zahlstellen

display_name: zahlstellen

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

stadt-st-gallen

fr: Ville de Saint-Gall

de: Stadt St.Gallen

en: City of St.Gallen

it: Città di San Gallo

fr: Avec une population de 80 000 habitants, Saint-Gall, huitième ville de Suisse, est la métropole économique, politique, sociale et culturelle de la Suisse orientale. Ses 1400 ans d'histoire se mêlent à la créativité urbaine, à une économie innovante et à un paysage préservé.

en: With a population of 80,000, St.Gallen, Switzerland’s eighth largest city, is the economic, political, social and cultural metropolis of eastern Switzerland. Its 1400 years of history blend with urban creativity, an innovative economy and an unspoilt landscape.

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

it: Con una popolazione di 80.000 abitanti, San Gallo, l'ottava città più grande della Svizzera, è la metropoli economica, politica, sociale e culturale della Svizzera orientale. I suoi 1400 anni di storia si fondono con la creatività urbana, un'economia innovativa e un paesaggio incontaminato.

political_level: commune


de: abstimmungen partei

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (jsonld)

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (csv)

de: xls

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (xls)

de: jsonl

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (jsonl)

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (json)

de: fgb

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (fgb)

de: parquet

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (parquet)

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (n3)

de: turtle

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (turtle)

de: Wahlen Stadtrat und Stadtpräsident/in St.Gallen 22.09.2024 (rdfxml)

de: Ergebnisse der Stadtrats- und Stadtpräsidentschaftswahlen der Stadt St.Gallen vom 22. September 2024 für die Amtsdauer 2025 - 2028. Weitere Informationen und Downloads finden Sie unter: [Wahlen | stadt.sg.ch](https://www.stadt.sg.ch/home/verwaltung-politik/demokratie-politik/abstimmungen-wahlen/wahlen.html)

abstimmungen

display_name: abstimmungen

partei

display_name: partei

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

value: DCAT Harvester Stadt St. Gallen


offentliche-beleuchtung-stadt-st-gallen

title_for_slug: offentliche-beleuchtung-stadt-st-gallen

de: laternen licht beleuchtung leuchten strassen

de: Öffentliche Beleuchtung Stadt St.Gallen (jsonl)

de: Öffentliche Beleuchtung Stadt St.Gallen (fgb)

de: Öffentliche Beleuchtung Stadt St.Gallen (n3)

de: jsonld

de: Öffentliche Beleuchtung Stadt St.Gallen (jsonld)

de: kml

de: Öffentliche Beleuchtung Stadt St.Gallen (kml)

de: Öffentliche Beleuchtung Stadt St.Gallen (parquet)

de: json

de: Öffentliche Beleuchtung Stadt St.Gallen (json)

de: geojson

de: Öffentliche Beleuchtung Stadt St.Gallen (geojson)

de: Öffentliche Beleuchtung Stadt St.Gallen (ov2)

de: shp

de: Öffentliche Beleuchtung Stadt St.Gallen (shp)

de: Öffentliche Beleuchtung Stadt St.Gallen (turtle)

de: Öffentliche Beleuchtung Stadt St.Gallen (xls)

de: rdfxml

de: Öffentliche Beleuchtung Stadt St.Gallen (rdfxml)

de: gpx

de: Öffentliche Beleuchtung Stadt St.Gallen (gpx)

de: csv

de: Öffentliche Beleuchtung Stadt St.Gallen (csv)

de: Der Datensatz zeigt die verschiedenen Typen der öffentliche Beleuchtung der Stadt St.Gallen

beleuchtung

display_name: beleuchtung

laternen

display_name: laternen

leuchten

display_name: leuchten

licht

display_name: licht

strassen

display_name: strassen

ener

de: Energie

tran

de: Verkehr

stadt-st-gallen

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.


de: jsonld

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (jsonld)

de: fgb

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (fgb)

de: xls

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (xls)

de: parquet

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (parquet)

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (rdfxml)

de: turtle

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (turtle)

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (csv)

de: json

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (json)

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (n3)

de: jsonl

de: Vergaben Stadt St.Gallen grösser CHF 100.000 (jsonl)

de: Im Zusammenhang mit der Beantwortung der Interpellation «Mehr Transparenz im Vergabewesen (Open Data)», (Beschluss Nr. 4211 vom 26. Mai 2020) hat der Stadtrat die Praxis für die Publikation von Vergaben neu geregelt. Ziel ist, eine bessere Transparenz – insbesondere auch bei freihändigen Verfahren – zu ermöglichen. Ab dem 01.01.2021 werden hier daher alle Vergaben der Stadt St.Gallen ab CHF 100.000 als OGD zur Verfügung gestellt.

vergabe

display_name: vergabe

gove

de: Regierung und öffentlicher Sektor

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

stadt-st-gallen

de: Stadt St.Gallen


de: ferien feiertage schule

de: Schulferien und Feiertage Stadt St.Gallen (json)

de: csv

de: Schulferien und Feiertage Stadt St.Gallen (csv)

de: xls

de: Schulferien und Feiertage Stadt St.Gallen (xls)

de: jsonld

de: Schulferien und Feiertage Stadt St.Gallen (jsonld)

de: fgb

de: Schulferien und Feiertage Stadt St.Gallen (fgb)

de: Schulferien und Feiertage Stadt St.Gallen (jsonl)

de: Schulferien und Feiertage Stadt St.Gallen (turtle)

de: Schulferien und Feiertage Stadt St.Gallen (parquet)

de: rdfxml

de: Schulferien und Feiertage Stadt St.Gallen (rdfxml)

de: Schulferien und Feiertage Stadt St.Gallen (n3)

de: Der Datensatz zeigt die Daten der Schulferien und Feiertage in der Stadt St.Gallen.

feiertage

display_name: feiertage

ferien

display_name: ferien

schule

display_name: schule

educ

de: Bildung, Kultur und Sport

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.


de: sensor real-time fussganger passanten offene-sensordaten

de: turtle

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (turtle)

de: shp

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (shp)

de: jsonl

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (jsonl)

de: csv

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (csv)

de: gpx

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (gpx)

de: json

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (json)

de: geojson

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (geojson)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (xls)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (jsonld)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (ov2)

de: kml

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (kml)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (fgb)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (rdfxml)

de: parquet

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (parquet)

de: Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) - Archivdaten (2019 - Juni 2024) (n3)

de: Die Stadt St.Gallen verfügt an der Vadianstrasse (Höhe St.Galler Stadtwerke) über einen Sensor, der die Anzahl vorbeigehender Fussgänger misst. Dieser Datensatz zeigt die Anzahl Personen von rechts (Neumarkt) und links (Multergasse) kommend, sowie deren Summe. Der Datensatz besteht aus Archivdaten aus den Jahren 2019-2024. Die aktuellen Daten sind unter: [Passantenfrequenz Vadianstrasse, Stadt St.Gallen (Höhe St.Galler Stadtwerke) — St.Gallen (sg.ch)](https://daten.stadt.sg.ch/explore/dataset/fussganger-stgaller-innenstadt-vadianstrasse/information/?disjunctive.tag_nr&disjunctive.wochentag&disjunctive.arbeitstag)

fussganger

display_name: fussganger

offene-sensordaten

display_name: offene-sensordaten

passanten

display_name: passanten

real-time

display_name: real-time

sensor

display_name: sensor

tran

de: Verkehr

stadt-st-gallen

de: Stadt St.Gallen


legislaturziele-stadt-st-gallen

title_for_slug: legislaturziele-stadt-st-gallen

de: stadtrat vision-2030 stadtparlament dienststellen

de: turtle

de: Legislaturziele Stadt St.Gallen (turtle)

de: csv

de: Legislaturziele Stadt St.Gallen (csv)

de: jsonld

de: Legislaturziele Stadt St.Gallen (jsonld)

de: fgb

de: Legislaturziele Stadt St.Gallen (fgb)

de: rdfxml

de: Legislaturziele Stadt St.Gallen (rdfxml)

de: xls

de: Legislaturziele Stadt St.Gallen (xls)

de: Legislaturziele Stadt St.Gallen (n3)

de: json

de: Legislaturziele Stadt St.Gallen (json)

de: jsonl

de: Legislaturziele Stadt St.Gallen (jsonl)

de: Legislaturziele Stadt St.Gallen (parquet)

de:
Der
Stadtrat der Stadt St.Gallen bestimmt und veröffentlicht Legislatur- und Jahresziele, welche den Handlungsfeldern der Vision 2030 zugeordnet werden. Diese Ziele werden jeweils am Ende des Jahres, bzw. der Legislatur bewertet und im Geschäftsbericht der Stadt St.Gallen veröffentlicht. Der Datensatz zeigt die Legislaturziele und die jeweilige Bewertung bei abgeschlossenen Legislaturen.Mehr Informationen und die jeweiligen PDF-Dokumente finden Sie hier:[Stadtrat: Vision 2030 und Legislaturziele](https://www.stadt.sg.ch/home/verwaltung-politik/demokratie-politik/stadtrat.html)[Geschäftsbericht: Legislatur- und Jahresziele, inkl. Bewertung](https://www.stadt.sg.ch/home/verwaltung-politik/demokratie-politik/geschaeftsbericht.html)

dienststellen

display_name: dienststellen

stadtparlament

display_name: stadtparlament

stadtrat

display_name: stadtrat

gove

de: Regierung und öffentlicher Sektor

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

de: Legislaturziele Stadt St.Gallen


de: armut schulden rechnung betreibung

de: parquet

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (parquet)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (json)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (jsonl)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (n3)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (fgb)

de: csv

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (csv)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (xls)

de: jsonld

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (jsonld)

de: turtle

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (turtle)

de: Betreibungsfälle Stadt St.Gallen (2005-2018) (rdfxml)

de: Anzahl Betreibungsfälle in der Stadt St.Gallen (Jahre 2005-2018)

armut

display_name: armut

betreibung

display_name: betreibung

rechnung

display_name: rechnung

schulden

display_name: schulden

econ

de: Wirtschaft und Finanzen

stadt-st-gallen

de: Stadt St.Gallen


de: kapazitaten besucher freibad bader hallenbad

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (n3)

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (turtle)

de: fgb

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (fgb)

de: parquet

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (parquet)

de: json

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (json)

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (jsonld)

de: xls

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (xls)

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (csv)

de: jsonl

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (jsonl)

de: rdfxml

de: Besucherzahlen in den Frei- und Hallenbäder der Stadt St.Gallen (während Covid-19-Pandemie) (rdfxml)

de: Die Dienststelle Sport hat im Laufe der Corona-Pandemie begonnen, die Besucherinnen und Besucher der Freibäder und Hallenbäder in St.Gallen zu zählen. Dieser Datensatz zeigt diese Zählungen der Firma countee. Sie zeigen den aktuellen Besucherstand zum entsprechenden Zeitpunkt.Leider können wir aus lizenztechnischen Gründen nicht alle Besucherbewegungen hier im Portal ausweisen, weshalb wir uns auf viertelstündliche Besucherstände beschränken. Dadurch kann allerdings mit diesem Datensatz nicht auf die genaue Anzahl Besucher pro Tag geschlossen werden. Dafür stellen wir euch die Exportlinks des Zählerbetreibers Countee zur Verfügung, welche Analysen mit sämtlichen Besucherbewegungen ermöglichen. Die Exports sind nach folgendem Schema aufgebaut:Alle Bewegungen: http://countee.ch/exports/<Bad_ID>-<JAHR>.csv15min Besucherstand (dieser Datensatz): http://countee.ch/exports/<Bad_ID>-<JAHR>_15min.csvMetadaten: http://countee.ch/exports/<Bad_ID>-<JAHR>.csv.meta.txtBad_IDs:Freibad Rotmontenc5ed762037214dFamilienbad Dreilindenc5ed7621c47da1Freibad Lerchenfeldc5ed7622ecbf1fHallenbad Blumenwiesc5ed761e9a9100Hallenbad Volksbadc5ed76249da809

bader

display_name: bader

besucher

display_name: besucher

freibad

display_name: freibad

hallenbad

display_name: hallenbad

kapazitaten

display_name: kapazitaten

educ

de: Bildung, Kultur und Sport

tran

de: Verkehr

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.


de: ov offentlicher-verkehr bus linie

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (ov2)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (json)

de: kml

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (kml)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (jsonl)

de: csv

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (csv)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (n3)

de: fgb

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (fgb)

de: jsonld

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (jsonld)

de: turtle

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (turtle)

de: gpx

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (gpx)

de: geojson

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (geojson)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (xls)

de: shp

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (shp)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (parquet)

de: Liniennetz VBSG Stadt St.Gallen (grafisch) (rdfxml)

de: Darstellung der Liniennetze des öff. Verkehrs

bus

display_name: bus

linie

display_name: linie

offentlicher-verkehr

display_name: offentlicher-verkehr

ov

display_name: ov

stadt-st-gallen

de: Stadt St.Gallen


de: medienmitteilung news real-time newsfeed

de: jsonl

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (jsonl)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (jsonld)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (n3)

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (turtle)

de: json

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (json)

de: csv

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (csv)

de: fgb

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (fgb)

de: xls

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (xls)

de: rdfxml

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (rdfxml)

de: parquet

de: Newsfeed Medienmitteilungen Stadtverwaltung St.Gallen (parquet)

de: Der Datensatz bildet eine Schnittstelle zum Newsfeed der Medienmitteilungen der Stadtverwaltung. Der Link zum Newsfeed befindet sich unter "Referenzen"

medienmitteilung

display_name: medienmitteilung

news

display_name: news

newsfeed

display_name: newsfeed

real-time

display_name: real-time

educ

de: Bildung, Kultur und Sport

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.