maintainer: Peter Bebi

en: vegetation experiment stillberg climate-change carbon-dioxide soil-temperature

en: Metadata FACE Stillberg Data File Description

en: List of descriptions for each of the .csv FACE data files.

en: Project Description FACE Stillberg

en: Link to FACE project description on the WSL website.

en: Data FACE Stillberg

en: Folder in .zip format containing the FACE datasets.

en: Metadata FACE Stillberg Experimental Design

media_type: PDF

en: Schematic illustration and tabular listing of the FACE experimental design.

en:
 Background information

High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.

 Experimental design

The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.

 Data description

Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

vegetation

display_name: vegetation

education

en: Education and science

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: FACE: Stillberg CO2 enrichment and soil warming study


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

state: active

type: dataset

en: Scan from 2 January 2019, 1 mm resolution

media_type: ascii x, y, z

format: SERVICE

en: Scan from 4 January 2019, 1 mm resolution

en: Scan from 21 December 2018, 1 mm resolution

en: Scan from 27 December 2018, 1 mm resolution

en: Scan from 2 January 2019, 10 cm resolution

en: Scan from 21 December 2018, 10 cm resolution

en: Scan from 11 January 2019, 10 cm resolution

en: Scan from 27 December 2018, 10 cm resolution

en: Scan from 4 January 2019, 10 cm resolution

en: Scan from 11 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

education

fr: Education, science

de: Bildung, Wissenschaft

it: Formazione e scienza

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

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


maintainer: Jürg Schweizer

en: avalanche-size avalanche-activity snow-avalanche danger-level avalanche-forcasting

en: Snow avalanche data

media_type: text/csv

en: This data file includes data on the avalanches mapped in the region of Davos.

format: CSV

mimetype: text/csv

en: Readme

media_type: application/pdf

en: The Readme file contains the description of the two data files.

format: PDF

mimetype: application/pdf

en: Avalanche activity data

en: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.

This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related to avalanche danger level.

The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level

snow-avalanche

display_name: snow-avalanche

education

en: Education and science

en: Snow avalanche data Davos, Switzerland, 1999-2019


maintainer: Christian G. Sommer

en: wind-packing snow kinect wind-tunnel wind-crust

en: Processing scripts

media_type: application/zip

en: Contains the Matlab- and R-scripts used to process the Kinect data

format: ZIP

mimetype: application/zip

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: Kinect data

media_type: Link

en: Links to the dataset

en:
This data sets contains the Microsoft Kinect data from 15 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winter 2016/17. The Kinect measures distributed snow depth.

The Kinect data is organized per experiment. Each experiment subfolder contains the processed Kinect depth images and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M. & Fierz C. (2018). Wind Tunnel Experiments: Influence of Erosion and Deposition on Wind-Packing of New Snow. Front. Earth Sci. 6:4. doi: 10.3389/feart.2018.00004

kinect

display_name: kinect

snow

display_name: snow

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

wind-tunnel

display_name: wind-tunnel

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: Wind crust formation: Microsoft Kinect data


en: growing-season-length precipitation growing-degree-days soil-water-balance solar-radiation temperature relative-humidity

en: CHELSA-BIOCLIM+ Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA-BIOCLIM+

media_type: geotiff

en: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.

format: GeoTIFF

en: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature

en: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution


biogas-aus-hofdunger-in-der-schweiz

maintainer: EnviDat Support

title_for_slug: biogas-aus-hofdunger-in-der-schweiz

en: biogas manure review bioenergy switzerland

en: Biogas aus Hofdünger in der Schweiz

en: Ziel dieses Whitepapers ist es, Entscheidungsträgern, Verwaltungen und Stakeholdern die aktuellsten Forschungsergebnisse zur Verfügung zu stellen, um die optimale Nutzung von Bioenergie aus Hofdünger in der Schweizer Energiewende zu fördern. Zu diesem Zweck werden die Ergebnisse des Schweizer Kompetenzzentrums für Bioenergieforschung - SCCER BIOSWEET - zusammengefasst und in einem breiteren Kontext dargestellt. Wenn nichts anderes erwähnt wird, beziehen sich die Ergebnisse auf die Schweiz und im Falle der Ressourcen auf die heimischen Biomassepotenziale.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland

education

en: Education and science


maintainer: Adam Winstral

en: snow snow-depth jules-investigation-model snow-simulation jim

en: DEM

en: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

en: Station forcing data

en: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en: HS and SWE observations

en: Automated (HS) and manual (SWE) data used to evaluate model simulations

en: File/data descriptor

en: These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

en: Meteorological data used to develop and validate the bias-detecting ensemble (BDE)


aerosol-data-weissfluhjoch

title_for_slug: aerosol-data-weissfluhjoch

en: linda aerosol raclets ice-nucleation particles inp

en: OPC-GT526S Dataset Weissfluhjoch

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

en: APS Dataset Weissfluhjoch

media_type: application/x-netcdf

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Weissfluhjoch.

mimetype: application/x-netcdf

en: SMPS Dataset Weissfluhjoch

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity) in a temporal resolution of 2 minutes, with time in UTC, measured at Weissfluhjoch.

en: LINDA Dataset Weissfluhjoch

en: The LINDA file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en: OPC-N3 Dataset Weissfluhjoch

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

linda

display_name: linda

particles

display_name: particles

raclets

display_name: raclets

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: Aerosol Data Weissfluhjoch


en: climate-change wind-speed long-term swiss-forest-lab meteo temperature precipitation meteorology relative-humidity par

en: Forest station data (LAB)

en: Data file.

en: Data plot of the field station (LAF)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the field station (LAF)

media_type: image/jpeg

en: Site photo of the field station from the side.

mimetype: image/jpeg

en: Field station data (LAF)

en: Site aerial photo (Lausanne)

en: Site aerial photo from both Lausanne stations. Source: Google. 2016. Site aerial photo from both Lausanne stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Site photo of the forest station (LAB)

en: Site photo of the fforest station from the side.

en: Data plot of the forest station (LAB)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Lausanne in Switzerland where one station is located within a natural mixed forest stand (LAB) with European beech (_Fagus sylvatica_; 160-170 yrs), European silver fir (_Abies alba_; 160-170 yrs) and Norway spruce (_Picea abies_; 160-170 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, LAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lausanne is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

education

en: Education and science

en: Lausanne, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


maintainer: Felix Neff

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

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: 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 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

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: Grassland restoration: insects and insect traits


en: topography cryowrf antarctica wrf landuse

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


maintainer: Mountain Hydrology and Mass Movements

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

media_type: CSV

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

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

education

en: Education and science

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


maintainer: Athanasios Nenes

en: raclets sigma-w cloud-droplets wolfgangpass cloud-modeling supersaturation

en: Predicted cloud droplet numbers (kappa=0.1) Davos Wolfgang

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.1 is assumed, which is the lower limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: Predicted cloud droplet numbers (kappa=0.25) Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.25 is assumed, which is the upper limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: Cloud droplet properties were predicted between February 24 and March 8 2019 for the measurement site Davos Wolfgang (1630 m a.s.l., LON: 9.853594, LAT: 46.835577). Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from a Scanning Mobility Particle Size Spectrometer (SMPS) instrument deployed at Davos Wolfgang (https://www.envidat.ch/dataset/aerosol-data-davos-wolfgang). The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at the same station and are extracted from the first bin of the instrument, being 200 m above ground level. The hygroscopic properties of the particles measured at Davos Wolfgang could not be estimated, owing to a lack of concurrent CCN measurements. As a sensitivity test, droplet calculations are performed assuming two different values of the aerosol hygroscopicity parameter, 0.1 and 0.25, based on the analysis carried out for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

wolfgangpass

display_name: wolfgangpass

envidat

en: EnviDat: the Environmental Data Portal

en: Predicted cloud droplet numbers Davos Wolfgang


maintainer: Avalanche Warning Service SLF

en: Avalanche fatalities per year in Switzerland since 1936/1937

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.
The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definition for these four categories as described in the guidelines to the avalanche accident database:
**tour**:
activities include back-country ski, snowboard or snow-shoe touring
**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances
**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

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: Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937


weissfluhjoch-dataset-for-esm-snowmip

maintainer: Nander Wever

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

en: snow-depth snow-models snow esm-snowmip weissfluhjoch

en: ini file

en: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

en: Dataset Weissfluhjoch for ESM-SnowMIP

en: Conversion script

media_type: text/x-sh

en:
Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

mimetype: text/x-sh

en: This Weissfluhjoch dataset is a processed version of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch

en: Weissfluhjoch dataset for ESM-SnowMIP


lidar-davos-wolfgang

maintainer: Patric Seifert

title_for_slug: lidar-davos-wolfgang

en: clouds tropos lidar raclets polly

en: Raman Lidar Davos

en: A portable Raman lidar system (Polly) from Leibnitz Institute for Tropospheric Research (Tropos) was deployed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Please use this [link](http://polly.tropos.de/?p=lidarzeit&Ort=39), to be directly forwarded to the Davos location and select the date of interest from the calendar (bold numbers). The data can be requested directly at the Polly team.

clouds

display_name: clouds

lidar

display_name: lidar

polly

display_name: polly

tropos

display_name: tropos

education

en: Education and science

en: LIDAR Davos Wolfgang


maintainer: Joan Casanelles Abella

en: paris dna-metabarcoding tartu poznan chelostoma-florisomne cavity-nesting-bees osmia-bicornis zurich osmia-cornuta urban-ecology hylaeus-communis plant-pollinator-interactions trap-nest antwerp

en: Larval food composition

en: Explanation data variables

en: Urbanization poses threats and opportunities for the biodiversity of wild bees. A main gap relates to the food preferences of wild bees in urban ecosystems, which usually harbour large numbers of plant species, particularly at the larval stage. This data sets describes the larval food of four wild bee species (i.e. Chelostoma florisomne, Hylaeus communis, Osmica bicornis and Osmia cornuta) and three genera (i.e. Chelostoma sp., Hylaeus sp, and Osmia sp.) common in urban areas in five different European cities (i.e. Antwerp, Paris, Poznan, Tartu and Zurich). This data results from a European-level study aimed at understanding the effects of urbanization on biodiversity across different cities and citiscapes, and a Swiss project aimed at understanding the effects of urban ecosystems in wild bee feeding behaviour. Wild bees were sampled using standardized trap-nests in 80 sites (32 in Zurich and 12 in each of the remaining cities), selected following a double gradient of available habitat at local and landscape scales. Larval pollen was obtained from the bee nests and identified using DNA metabarconding. The data provides the plant composition at the species or genus level of the different bee nests of the studied species in the studied sites of the five European cities. For Hylaeus communis, this is the first study in reporting larval food composition.

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich

envidat

en: EnviDat: the Environmental Data Portal

en: Larval food composition of four wild bee species in five European cities


maintainer: Lisa Hülsmann

en: forest-reserves empirical-mortality-models inventory-data tree-growth tree-mortality

en: Calibration data

en:
A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory.

 Meta data
Reserve: Name of the forest reserve

Plot: Permanent plot number

 Tree data
Species: Latin species name (or species group, cf. _Quercus_ spp.)

y: Status of the tree with 0 = alive and 1 = dead

dt: Length of the mortality period (years)

DBH: Diameter at breast height (mm) of the second inventory

relBAI: Annual relative basal area increment (-) calculated based on the first and the second DBH measurement as the compound annual growth rate of the trees basal area

 Stand data
_All stand variables were calculated for the second inventory._

mDBH: Mean diameter at breast height (mm)

iqrDBH: Interquartile range of diameter at breast height (mm)

BA: Basal area per hectare (m2 ha-1)

N: Number of trees per hectare (ha-1)

 Climate data
_Both climate variables were calculated for the period between the second and the third inventory._

P: Mean annual precipitation sum (mm)

mT: Mean annual air temperature (°C)

en:
The dataset comprises > 90 000 records from inventories in 54 strict forest reserves in [Switzerland](https://www.wsl.ch/de/wald/biodiversitaet-naturschutz-urwald/naturwaldreservate.html) and [Lower Saxony / Germany](http://naturwaelder.de/) along a considerable environmental gradient. It was used to develop parsimonious, species-specific mortality models for 18 European tree species based on tree size and growth as well as additional covariates on stand structure and climate.

 Inventory data
Measurements had been conducted repeatedly on up to 14 permanent plots per reserve for up to 60 years with re-measurement intervals of 4 - 27 years. The permanent plots vary in size between 0.03 and 3.47 ha. The inventories provide diameter measurements at breast height (DBH) and information on the species and status (alive or dead) of trees with DBH ≥ 4 cm for Switzerland and ≥ 7 cm for Germany.

 Data selection
We excluded three permanent plots where at least 80 % of the trees died during an interval of 10 years, and mortality could be clearly assigned to a disturbance agent. Mortality in the remaining stands was rather low, with a mean annual mortality rate of 1.5 % and strong variation between plots from 0 to 6.5 % (assessed for trees of all species with DBH ≥ 7 cm).
We only used data from permanent plots with at least 20 trees per species to obtain reliable plot-level mortality rates even for species with low mortality rates (about 5 % during 10 years), and selected tree species occurring on at least 10 plots to cover sufficient ecological gradients. This led to a dataset of 197 permanent plots and 18 tree or shrub species: _Abies alba_ Mill., _Acer campestre_ L., _Acer pseudoplatanus_ L., _Alnus incana_ Moench., _Betula pendula_ Roth, _Carpinus betulus_ L., _Cornus mas_ L., _Corylus avellana_ L., _Fagus sylvatica_ L., _Fraxinus excelsior_ L., _Picea abies_ (L.) Karst, _Pinus mugo_ Turra, _Pinus sylvestris_ L., _Quercus pubescens_ Willd., _Quercus_ spp. (_Q. petraea_ Liebl. and _Q. robur_ L.; not properly differentiated in the Swiss inventories), _Sorbus aria_ Crantz, _Tilia cordata_ Mill. and _Ulmus glabra_ Huds..

 Predictors of tree mortality
We considered tree size and growth as key indicators for mortality risk. Radial stem growth between the first and second inventory and DBH at the second inventory were used to predict tree status (alive or dead) at the third inventory. To this end, the annual relative basal area increment (relBAI) was calculated as the compound annual growth rate of the trees basal area. Additional covariates on stand structure and climate comprise mean annual precipitation sum (P), mean annual air temperature (mT), the mean and the interquartile range of DBH (mDBH, iqrDBH), basal area (BA) and the number of trees (N) per hectare.

 Further information
For further information, refer to Hülsmann _et al_. (in press) How to kill a tree – Empirical mortality models for eighteen species and their performance in a dynamic forest model. _Ecological Applications_.

empirical-mortality-models

display_name: empirical-mortality-models

forest-reserves

display_name: forest-reserves

inventory-data

display_name: inventory-data

tree-growth

display_name: tree-growth

tree-mortality

display_name: tree-mortality

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: Calibration data for empirical mortality models of 18 European tree species


en: phenology chilling budburst hatch spongy-month

en: Phenology and performance/preference tests Data

media_type: ZIP

en:
-"Synchronex_Cuttings_Pheno.txt" provides the budburst date ('Stage 2') of each twig of the six studies species in the four different temperature treatments ("ambient", "a+5"=Ambient +5°C, 'Greenhouse-5'= Greenhouse at temperature >5°C, 'Greenhouse_10' = Greenhouse at temperature >10°C); 'Success' give the percentage of buds within the twig that succeeded to reach at least stage 2 during the experiment.

'Synchronex-Gypsy.txt' provides the number of eggs that have hatched at each monitoring date (Day of the year in columns); "DOY_hatch_1" corresponds to the first DOY when at least one egg has hatched; "Replicate_egg_mass" correspond to the egg mass replicate (1 to 5)

'PerformanceTest_GypsyMoth.txt' provides the biomass in mg of the caterpillars fed with fresh leaves of each tested tree species during one week. "Fresh_alive" is the biomass of only the living caterpillars after 1 week and "Freshpermoth" corresponds the weight per living caterpillar (Fresh alive/Nalive)

'PreferenceTest_All_species.txt' provides the total surface of leaf disc of each tested tree species remaining after exposing 5 caterpillars to these leaves during 24H. "Total_area" is the surface of the disc of each species measured after 24h exposed to the spongy moth first instars. For each species 'control' means the surface of the disc after 24H without any exposure to the larvae. 'EatenPercent correspond to the percentage surface loss compared to the control.

en: 3 R-Scripts used for the analyses of the temperature, phenology and performance/preference tests

en: Temperature data Spongy moth experiment

en:
4 files with hourly temperature recorded at the height of buds in each of the four temperature treatments:
- Winter6: greenhouse where temperature was kept >6°C over winter
- Winter10: greenhouse where temperature was kept >10°C over winter
- OTC_Ambient: Open Top Chamber at Ambient temperature
- OTC_Warm: Open Top Chamber at +3.5°C warmer temperature

en:
The files correspond to the data and R-script used for the analyses of the following paper "Feasting on the ordinary or starving for the exceptional: phenological synchrony between spongy moth and budburst of European trees in a warmer climate" published in Ecology and Evolution by Vitasse et al. 2023.
There are three zip files corresponding to the Temperature data, phenology/preference/performance tests and R-Scripts for the analyses.

Input data:
'Synchrony_Cuttings_Pheno.txt':

budburst

display_name: budburst

chilling

display_name: chilling

hatch

display_name: hatch

phenology

display_name: phenology

spongy-month

display_name: spongy-month

en: Synchrony between spongy moth hatching and leaf phenology of temperate trees


en: meteoswiss cosmo-wrf numerical-simulation high-resolution complex-terrain

en: COSMO-WRF documentation v1.0

en:
Gerber, Franziska; Sharma, Varun (2018). Running COSMO-WRF on very-high resolution over complex terrain. EnviDat. doi:10.16904/envidat.35

Documentation about the procedure to run COSMO-WRF

en: StaticData

en:
Scripts to process geographical/static data (see Section 3 in COSMOWRFdocumentation.pdf).
- ascii_to_bin_landuse.f90
- ascii_to_bin_soiltype.f90
- ascii_to_bin_topo_wgs84_ws2sf1.f90
- see_slopes.ncl
- soiltype_writing.py
- toposmooth_wgs84_cosmobound.ncl
- write_geogrid.o

en: WPSrun

en: Scripts to run the WRF pre-processing (WPS) for COSMO-WRF simulation (see Section 5 in COSMOWRFdocumentation.pdf)

en: Postprocessing

en: Postprocessing scripts to map WRF output on swiss coordinates (see Section 7 in COSMOWRFdocumentation.pdf)

en: WRFrun

en: Scripts to run COSMO-WRF simulation (see Section 6 in COSMOWRFdocumentation.pdf)

en: WPSSetup

en: Scripts that need to be changed to compile WPS (see COSMOWRFdocumentation.pdf, Section 4)

en: MeteorologicalData

en: Scripts to process meteorological data (see Section 2 in COSMOWRFdocumentation.pdf).

en: This is a technical documentation of the procedure to run the Weather Research and Forecasting (WRF) model over complex alpine terrain using Consortium for Small-Scale Modeling (COSMO) reanalysis by the Federal Office of Meteorology and Climatology (MeteoSwiss) as initial and boundary conditions (COMSO-WRF). The setup is adapted for very high resolution simulations based on COSMO-2 (2.2 km resolution) reanalysis. This document gives an overview over steps to setup COSMO-WRF and adaptations needed to run COSMO-WRF. Additionally, the calculation of precipitation rate at a horizontal plane and remapping COSMO-WRF output on Swiss coordinates are documented.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

high-resolution

display_name: high-resolution

meteoswiss

display_name: meteoswiss

numerical-simulation

display_name: numerical-simulation

education

en: Education and science


maintainer: Sebastian Schlögl

en: turbulent-sensible-heat-fluxes stable-boundary-layer snow atmospheric-turbulence atmosphere

en: Turbulence data AA00

en: sensor in 0.2 m height

en: Turbulence data GR00

en: sensor in 2 m height

en: Turbulence data WFJ11

en: Turbulence data WFJ07

en: upper sensor

en: sensor in 1 m height

en: sensor in 25 m height

en: Turbulence data PM07

en: SEE

en: NWW

en: lower sensor

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

snow

display_name: snow

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

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: How do stability corrections perform in the stable boundary layer over snow?


maintainer: Rebecca Mott

en: patchy-snow-covers tls riegl-vz6000 snow-ablation-rates terrestrial-laser-scanning

en: Digital Elevation Modell 2016

en: Snowmask 2016

en: Digital Elevation Modell 2014

en: Snowmask 2014

en: Digital Elevation Modell 2015

en: Gletschboden test site

en: Snowmask 2015

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

education

en: Education and science

en: EnviDat: the Environmental Data Portal

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


maintainer: Matthias Haeni

en: par precipitation meteorology temperature meteo relative-humidity long-term swiss-forest-lab climate-change wind-speed

en: Site photo of the field station (CIF)

en: Site photo of the field station from the side.

en: Site photo of the forest station (CIB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Data plot of the forest station (CIB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Forest station data (CIB)

en: Data file.

en: Data plot of the field station (CIF)

en: Site aerial photo (Chironico)

en: Site aerial photo from both Chironico stations. Source: Google. 2016. Site aerial photo from both Chironico stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Chironico in Switzerland where one station is located within a natural coniferous forest stand (CIB) with Norway spruce (_Picea abies_; 160-180 yrs) and European silver fir (_Abies alba_; 140-160 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CIF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Chironico is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Chironico, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 2000 onwards


unuberbaute-bauzonen-in-kraft-genehmigt

geography

fr: Géographie

de: Geographie

en: Geography

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

en: Territory and environment

it: Territorio e ambiente

title_for_slug: unuberbaute-bauzonen-in-kraft-genehmigt

de: gebaude-und-anlagen nutzungsplanung raumplanung wirtschaftliche-aktivitaten zonenplan

label: geocat.ch permalink

spatial: Kanton Luzern

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Überbauungsgrad der unüberbauten Bauzonen des genehmigten Zonenplans, laufend aktualisiert

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.

political_level: canton

value: LU-Kt - Geocat Harvester

de: Unüberbaute Bauzonen, in Kraft (genehmigt)


quartiere

title_for_slug: quartiere

fr: vecteur ville

de: vektor grossstadt

en: vector city

it: vettore citta-grandi-dimensioni

spatial: Biel/Bienne

protocol: WWW:DOWNLOAD:Geopackage (ogc)

fr: Télécharger les données (Datastore)

de: Daten herunterladen (Datastore)

media_type: Geopackage (ogc)

format: GPKG

protocol: WWW:DOWNLOAD:MS Excel

media_type: MS Excel

format: XLS

media_type: GeoJSON

format: GeoJSON

media_type: DXF

format: DXF

fr: Les données indiquent les limites des quartiers de Bienne. Elles ont été définies par le Département de l’urbanisme.

de: Die Daten stellen die Quartiergrenzen in Biel dar. Sie wurden von der Stadtplanung definiert.

name: Ville de Bienne - Département de l'urbanisme

basisdaten-biel-bienne

fr: Données de base Ville de Bienne

de: Basisdaten Stadt Biel

it: Città di Biel/Bienne

fr: Bienne est la plus grande ville bilingue de Suisse et la métropole mondiale de l’horlogerie. Elle compte environ 56 000 habitantes et habitants. Grâce à son ouverture sur le monde et à sa situation centrale entre la Suisse alémanique et la Suisse romande, elle ne cesse de se développer de manière dynamique. Située au bord du lac de Bienne et au pied du Jura, elle jouit d’une qualité de vie remarquable.

de: Biel ist die grösste zweisprachige Stadt der Schweiz und Uhren-Weltmetropole. Sie zählt rund 56 000 Einwohnerinnen und Einwohner. Mit ihrer Weltoffenheit und dank ihrer zentralen Lage zwischen der deutschen und französischen Schweiz entwickelt sie sich stets dynamisch weiter. Am Bielersee und Jurasüdfuss gelegen bietet sie eine hohe Lebensqualität.

it: Bienne è la più grande città bilingue della Svizzera e la capitale mondiale dell’orologeria. Conta circa 56 000 abitanti. Grazie al suo cosmopolitismo e alla sua posizione centrale tra la Svizzera tedesca e quella francese, è in costante sviluppo dinamico. Situata sul lago di Bienne e ai piedi delle montagne del Giura, vanta un'elevata qualità di vita.

political_level: commune

value: Stadt Biel/Bienne Basisdaten - geocat Harvester

fr: Quartiers

de: Quartiere


maintainer: Fachstelle Open Government Data des Kantons Zürich

label: Repository: Formale Leitlinien zur Datenpublikation des Kantons Zürich

label: Fachausschuss für offene Behördendaten: Standards

de: Leitlinien des Kantons Zürich für einfach nutzbare Behördendaten (Version 1.0)

media_type: text/html

de: Version 1.0 in Kraft seit dem 16. Dezember 2021.

format: HTML

mimetype: text/html

de: Handlungsleitende Normen, um offene Behördendaten ('Open Government Data', OGD) bereitzustellen, die einfach nutzbar sind. Der Fachausschuss Open Government Data des Kantons Zürich verwaltet die Normen gemäss der Maxime, den Bedürfnissen der Nutzenden zweckmässig und wirtschaftlich zu entsprechen. Die Fach- und Koordinationsstelle Open Government Data nimmt Feedback (Hinweise, Wünsche und Fragen) zu den Leitlinien entgegen. Entweder als 'Issue' im Repository (verlinkt unter 'Weitere Informationen') oder via E-Mail (verlinkt unter 'Kontakt'). Im Austausch mit den Nutzenden klärt sie deren Bedürfnisse, berät mit den Datenverwaltenden ('Data Custodians') mögliche Lösungen und schlägt diese vierteljährlich dem Fachausschuss zur Inkraftsetzung vor.

national-economy

fr: Economie nationale

de: Volkswirtschaft

en: National economy

it: Economia

fachstelle-ogd-kanton-zuerich

de: Fach- und Koordinationsstelle Open Government Data Kanton Zürich

de: Die Fach- und Koordinationsstelle Open Government Data (OGD) ist das kantonale Kompetenzzentrum für offene Behördendaten im Statistischen Amt. Wir unterstützen die Organisationseinheiten und Organe des Kantons bei der Bereitstellung ihrer nicht schützenswerten Daten als Open Data.

value: ZH-Kt Fachstelle OGD - DCAT Harvester


maintainer: Bundesamt für Energie BFE

fr: Contenu des bassins d'accumulation, dimanche 24:00 heures, bulletin hebdomadaire

it: Grado di riempimento dei bacini di accumulazione, domenica alle ore 24, rapporto settimanale livello di accumulazione

author: Bundesamt für Energie BFE

media_type: SERVICE

fr:
Ce relevé, élaboré chaque dimanche à 24h00, recense le contenu (en GWh et en %) des bassins d'accumulation suisses dans 4 régions différentes.
Le taux de remplissage des bassins d'accumulation est relevé dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Der Füllungsgrad der Speicherseen, Sonntag 24h, Wochenbericht Speicherinhalt gibt Auskunft über den Speicherinhalt der Schweizer Speicherseen für vier Regionen in GWh und als Füllgrad in % jeweils am Sonntag 24h auf wöchentlicher Basis. Der Füllungsgrad der Speicherseen wird im Rahmen der Elektrizitätsstatistik erhoben, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

statistical-basis

fr: Bases statistiques

de: Statistische Grundlagen

en: Statistical basis

it: Basi statistiche

energy

fr: Energie

de: Energie

en: Energy

it: Energia

territory

de: Raum und Umwelt

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


de: auto miv verkehrsnachfrage gemeinden strassenverkehr verkehrsmittelwahl velo oeffentlicherverkehr oev raumplanungsregionen verkehr

label: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

label: Gesetzliche Grundlage: Gesamtverkehrskonzept 2018 (GVK 2018) (Regierungsratsbeschluss Nr. 25/2018)

label: Gesamtverkehrsmodell Kanton Zürich im GIS-Browser

de: Verkehrsbeziehungen, Verkehrsaufkommen und Verkehrsmittelwahl MIV und ÖV nach Gemeinden

media_type: text/csv

de: Die Daten zeigen die Verkehrsnachfrage im öffentlichen Verkehr (‘oev’) und im motorisierten Individualverkehr (‘miv’) als absolutes Verkehrsaufkommen (Summe aller Personenwege an einem durchschnittlichen Werktag (DWV)) und als Modal Split (prozentuale Anteile der Verkehrsmittelarten an allen Personenwegen). Neben den Gemeinden werden auch die Verkehrsbeziehungen von und zu den Nachbarkantonen berücksichtigt ("_gebietart" = Aussenkorridor). ‘quelle_code’ und ‘ziel_code’ entsprechen den BFS-Nummern der Gemeinden zum angegebenen Gebietsstand (‘gebietsstand_jahr’). Die Verkehrsströme können nach Binnenverkehr und nach Quell-Ziel-Verkehr unterschieden. Beginnen und enden die Verkehrsbeziehungen im gleichen Gebiet (Quelle und Ziel sind identisch), handelt es sich um Binnenverkehr. Beginnen die Verkehrsbeziehungen in einem Betrachtungsgebiet und führen nach ausserhalb und umgekehrt so handelt es sich um Quell-Ziel-Verkehr.

de: Verkehrsbeziehungen, Verkehrsaufkommen und Verkehrsmittelwahl ÖV, MIV und Velo nach Regionen

de: Die Daten zeigen die Verkehrsnachfrage im öffentlichen Verkehr (‘oev’), im motorisierten Individualverkehr (‘miv’) und mit Velo ('vel') als absolutes Verkehrsaufkommen (Summe aller Personenwege an einem durchschnittlichen Werktag (DWV)) und als Bi- und Tri-Modal Split (prozentuale Anteile der Verkehrsmittelarten an allen Personenwegen). Bi-Modal Split umfasst ÖV und MIV, Tri-Modal Split auch Velo. Neben den Regionen werden auch die Verkehrsbeziehungen von und zu den Nachbarkantonen berücksichtigt ("_gebietart" = Aussenkorridor). ‘quelle_code’ und ‘ziel_code’ entsprechen den BFS-Nummern der Regionen zum angegebenen Gebietsstand (‘gebietsstand_jahr’). Die Verkehrsströme können nach Binnenverkehr und nach Quell-Ziel-Verkehr unterschieden werden. Beginnen und enden die Verkehrsbeziehungen im gleichen Gebiet (Quelle und Ziel sind identisch), handelt es sich um Binnenverkehr. Beginnen die Verkehrsbeziehungen in einem Betrachtungsgebiet und führen nach ausserhalb und umgekehrt so handelt es sich um Quell-Ziel-Verkehr.

de: Der Datensatz basiert auf dem Gesamtverkehrsmodell (GVM) des Kantons Zürich. Das GVM bildet die Verkehrsnachfrage auf Basis modellierter Nachfragebeziehungen von A nach B ab im öffentlichen Verkehr (ÖV), im motorisierten Individualverkehr (MIV) und im Fuss- und Veloverkehr. Im Ergebnis liegen die Beziehungsmatrizen in Personenwege für die Verkehrsmittelarten MIV, ÖV, Velo- und Fussverkehr für Gemeinden und Planungsregionen vor. Zum MIV gehören Autos, Motorräder und Mofas. Mit regelmässigen Aktualisierungen werden die laufenden Veränderungen im Verkehrsgeschehen nachgeführt und die Prognosen angepasst. Mehr Informationen zu den Daten in den Beschreibungen der Ressourcen.

auto

display_name: auto

gemeinden

display_name: gemeinden

miv

display_name: miv

oeffentlicherverkehr

display_name: oeffentlicherverkehr

oev

display_name: oev

raumplanungsregionen

display_name: raumplanungsregionen

strassenverkehr

display_name: strassenverkehr

velo

display_name: velo

verkehr

display_name: verkehr

verkehrsmittelwahl

display_name: verkehrsmittelwahl

verkehrsnachfrage

display_name: verkehrsnachfrage

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

en: Mobility and Transport

it: Mobilità e trasporti

afm-kanton-zuerich

de: Amt für Mobilität des Kantons Zürich

de: Wir gestalten und steuern die Verkehrsentwicklung im Kanton Zürich und legen Wert darauf, dass diese nachhaltig ist. Dazu übernehmen wir die strategische Planung für alle Verkehrsmittel und wahren die Interessen des Kantons gegenüber dem Bund.

value: DCAT Harvester Amt für Mobilität Kanton Zürich

de: Verkehrsnachfrage im ÖV, MIV und im Veloverkehr nach Gemeinden und Regionen im Kanton Zürich


ortsplan-farbig

title_for_slug: ortsplan-farbig

fr: einzelobjekt bodenbedeckung

de: einzelobjekt bodenbedeckung

en: einzelobjekt bodenbedeckung

it: einzelobjekt bodenbedeckung

spatial: Kanton Schwyz (SZ)

fr: Ortsplan farbig mit Daten aus der amtlichen Vermessung

format: WMTS

fr: Der Ortsplan ist ein Zusammenzug aus einzelnen Ebenen aus der Bodenbedeckung und den Einzelobjekten aus der amtlichen Vermessung: - Bodenbedeckung (alle Zoomstufen): befestigt, Wasserbecken, stehende und fliessende Gewässer, Wald, Acker,Wiese,Weide,Moor, Gärten/Intensivkultur/Reben, Fels/Abbau/Deponie, vegetationslos, Gletscher/Firn, Gebäude; - Projektierte Gebäude (nur Massstab 1:20'000-200); - Flächenelemente (alle Zoomstufen); - Linienelemente (10'000-2'000) Bahnen, (2'000-200) alle übrigen; - Punktelemente (2'000-200) Mast, Antenne, Baum; - Beschriftungen (2'000-200) Strassennamen, Hausnummern, Flurnamen, Platznamen.

amt-geoinformation-sz

de: Amt für Geoinformation Kanton Schwyz

de: Das Amt für Geoinformation verwaltet und veröffentlicht die Geodaten des Kantons Schwyz als OGC-Geodienste und als Datei-Download. Alle aktuell verfügbaren Geodaten, welche dem OGD unterliegen, sind hier aufgeführt.

value: SZ-Kt Geoinformation - Geocat Harvester

fr: Ortsplan farbig

de: Ortsplan farbig

en: Ortsplan farbig

it: Ortsplan farbig


einzelobjekt

title_for_slug: einzelobjekt

fr: Bodenbedeckung, vereinfacht aus der amtlichen Vermessung

format: WFS

fr: Die amtliche Vermessung (AV) beschreibt die Lage, die Form und den Inhalt eines Grundstückes. Die digitalen AV-Daten sind in thematische Informationsebenen gegliedert, die frei miteinander kombiniert werden können. Weitere Informationen (Genauigkeit, Toleranzstufen …) können aus der "Produkteinformation AV-Daten" entnommen werden. Die AV Informationsebene «Einzelobjekte» umfasst Objekte, die Merkmale der Bodenbedeckung enthalten, aufgrund ihrer Eigenschaft oder Ausdehnung aber keine oder nur eine unwesentliche flächenmässige Bedeutung haben.

fr: Einzelobjekt

de: Einzelobjekt

en: Einzelobjekt

it: Einzelobjekt


fr: Produkteinformation zu den AV-Daten

de: Produkteinformation zu den AV-Daten

en: Produkteinformation zu den AV-Daten

it: Produkteinformation zu den AV-Daten

fr: Die Kombination von Postleitzahl (PLZ4 mit Zusatzziffern), Ortschaft, Lokalisation (Strasse, Platz, benanntes Gebiet) und Gebäudeeingang (Hausnummer) ergibt eine Gebäudeadresse. Die Adresse dient zum raschen Auffinden eines Gebäudes. Damit eine eindeutige Zuordnung möglich ist, muss die Gebäudeadresse einmalig sein. Insbesondere Gebäude mit Wohnnutzung, Arbeitsstätten sowie Gebäude von allgemein öffentlichem Interesse müssen zwingend im Amtlichen Verzeichnis der Gebäudeadressen erscheinen. Daher ist die Vergabe von identischen Hausnummern bei sonst gleicher Adresse nicht zulässig (keine Mehrfachvergaben). Damit eine Adresse im Gebäude- und Wohnungsregister offiziell wird, muss sie von der zuständigen Stelle (Gemeinde) einmalig freigegeben werden.

fr: Gebäudeadressen

de: Gebäudeadressen

en: Gebäudeadressen

it: Gebäudeadressen


culture

fr: Culture, médias, société de l'information, sport

de: Kultur, Medien, Informationsgesellschaft, Sport

en: Culture, media, information society, sport

it: Cultura, media, società dell'informazione, sport

energy

de: Energie

geography

fr: Géographie

de: Geographie

it: Geografia

territory

fr: Territoire et environnement

de: Raum und Umwelt

it: Territorio e ambiente

spatial: Schweiz

fr: Service WMS-IFDG, couche "Projets pilotes et de démonstration"

de: WMS-BGDI Dienst, Layer "Pilot- und Demonstrationsprojekte"

en: WMS-FSDI service, layer "Pilot and demonstration projects"

it: Servizio WMS-IFDG, strato "ogetti pilota e di dimostrazione"

format: WMS

fr: Service WMTS-IFDG, couche , Layer "Projets pilotes et de démonstration"

de: WMTS-BGDI Dienst, Layer "Pilot- und Demonstrationsprojekte"

en: WMTS-FSDI service, layer "Pilot and demonstration projects"

it: Servizio WMTS-IFDG, strato "ogetti pilota e di dimostrazione"

fr: Map (Preview) Géoportail thématique - map.energie.admin.ch

de: Map (Preview) Fachportal - map.energie.admin.ch

en: Map (Preview) Thematic geoportal - map.energie.admin.ch

it: Map (Preview) Geoportale tematico - map.energie.admin.ch

de: Fachportal - map.energie.admin.ch

protocol: WWW:DOWNLOAD:Text (.csv), comma separated

de: Csv

media_type: Text (.csv), comma separated

de: Geopackage

de: Interlis

media_type: INTERLIS

format: INTERLIS

de: swisstopo REST API

format: API

fr: L'Office fédéral de l'énergie (OFEN) encourage le développement et l'expérimentation de nouvelles technologies, solutions et approches dans les domaines de l'utilisation économe et efficace de l'énergie, du transfert et du stockage d'énergie et de l'utilisation des énergies renouvelables. Le programme P+D se situe à l'interface entre la recherche et le marché et vise à relever le degré de maturité des nouvelles technologies, afin que celles-ci soient commercialisables à terme.Cette base de données contient les projets pilotes et de démonstration actuels soutenus par l'Office fédéral de l'énergie.

de: Das Bundesamt für Energie BFE fördert mit dem Pilot- und Demonstrationsprogramm (P+D-Programm) die Entwicklung und Erprobung von neuen Technologien, Lösungen und Ansätzen im Bereich der sparsamen und effizienten Energienutzung, der Energieübertragung und -speicherung sowie der Nutzung erneuerbarer Energien. Das P+D-Programm positioniert sich an der Schnittstelle zwischen Forschung und Markt und hat das Ziel, den Reifegrad von neuen Technologien zu erhöhen, um sie letztendlich zur Marktreife zu bringen. Dieser Datenbestand enthält aktuelle Pilot- und Demonstrationsprojekte, welche vom Bundesamt für Energie unterstützt werden.

en: With its Pilot and Demonstration programme the Swiss Federal Office of Energy (SFOE) promotes the development and testing of new technologies, solutions and concepts relating to the economical and ecological use of energy, the transmission and storage of energy and the use of renewable forms of energy. The Pilot and Demonstration programme acts as an interface between research and the market. Its main aim is to help increase the status of development of new technologies so that they can ultimately be brought onto the market.This dataset contains current pilot and demonstration projects supported by the Swiss Federal Office of Energy.

it: Con il Programma pilota e di dimostrazione (Programma P+D), l'UFE promuove lo sviluppo e la sperimentazione di nuove tecnologie, soluzioni e approcci nei settori dell'uso parsimonioso ed efficiente dell'energia, del suo trasporto e stoccaggio nonché dello sfruttamento delle fonti rinnovabili. Il programma P+D si posiziona all'interfaccia tra la ricerca e il mercato e mira ad aumentare il livello di maturità delle nuove tecnologie per portarle infine alla maturità di mercato.Questa banca dati contiene gli attuali progetti pilota e dimostrativi sostenuti dall'Ufficio federale dell'energia.

bundesamt-fur-energie-bfe

de: Bundesamt für Energie BFE

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).

value: BFE - Geocat Harvester

fr: Projets pilotes et de démonstration actuels de l'Office fédéral de l'énergie

de: Aktuelle Pilot- und Demonstrationsprojekte des Bundesamts für Energie

en: Current pilot and demonstration projects of the Swiss Federal Office of Energy

it: Progetti pilota e dimostrativi in corso dell'Ufficio federale dell'energia


energy

fr: Energie

it: Energia

geography

en: Geography

mobility

fr: Mobilité et transports

de: Mobilität und Verkehr

territory

en: Territory and environment

label: Bundesamt für Energie BFE - Detailbeschreibung

fr: Service WMS-IFDG, couche "Projets COMO"

de: WMS-BGDI Dienst, Layer "KOMO-Projekte"

en: WMS-FSDI service, layer "COMO projects"

it: Servizio WMS-IFDG, strato "Progetti sostenuti dal COMO"

fr: Service WMTS-IFDG, couche , Layer "Projets COMO"

de: WMTS-BGDI Dienst, Layer "KOMO-Projekte"

en: WMTS-FSDI service, layer "COMO projects"

it: Servizio WMTS-IFDG, strato "Progetti sostenuti dal COMO"

fr: Map (Preview)

de: Map (Preview)

en: Map (Preview)

it: Map (Preview)

fr: Géoportail thématique - map.geo.admin.ch

de: Fachportal - map.geo.admin.ch

en: Thematic geoportal - map.geo.admin.ch

it: Geoportale tematico - map.geo.admin.ch

fr: À titre d'organe de coordination et de contact, le Bureau de coordination pour la mobilité durable (COMO) est ainsi le premier interlocuteur de la Confédération en matière de mobilité durable. Il promeut les projets innovants par le biais d'une contribution financière et, comme de plateforme de connaissances, fournit des informations sur les projets en cours et les projets clôturés.COMO est porté par six services fédéraux: l'Office fédéral du développement territorial (ARE), l'Office fédéral des routes (OFROU), l'Office fédéral de l'environnement (OFEV), l'Office fédéral des transports (OFT), l'Office fédéral de la santé publique (OFSEP) de même que l'Office fédéral de l'énergie (OFEN). La carte donne un aperçu de l'ensemble des projets soutenus par le COMO.

de: Die Koordinationsstelle für nachhaltige Mobilität (KOMO) ist die zentrale Anlauf- und Koordinationsstelle und somit erste Ansprechpartnerin des Bundes in Sachen nachhaltiger Mobilität. Sie fördert innovative Projekte mit einem finanziellen Beitrag und stellt als Wissensplattform Informationen über abgeschlossene und laufende Projekte zur Verfügung.KOMO wird von sechs Bundesstellen getragen: dem Bundesamt für Raumentwicklung (ARE), dem Bundesamt für Strassen (ASTRA), dem Bundesamt für Umwelt (BAFU), dem Bundesamt für Verkehr (BAV), dem Bundesamt für Gesundheit (BAG) und dem Bundesamt für Energie (BFE). Die Karte gibt eine Übersicht zu allen von KOMO unterstützten Projekten.

en: The Coordination Office for Sustainable Mobility (COMO) is the central contact and coordination point and the first contact point at federal level in matters of sustainable mobility. It supports innovative projects with a financial contribution and, as a knowledge platform, provides information on completed and ongoing projects.Six federal offices are responsible for COMO: the Federal Office of Spatial Planning (ARE), the Federal Roads Office (FEDRO), the Federal Office for the Environment (FOEN), the Federal Office of Transport (FOT), the Federal Office of Public Health (FOPH) and the Swiss Federal Office of Energy (SFOE). The map provides an overview of all projects supported by COMO.

it: L'Ufficio di coordinamento per la mobilità sostenibile (COMO) funge da primo sportello di contatto e servizio di coordinamento ed è pertanto il primo interlocutore della Confederazione per le questioni attinenti alla mobilità sostenibile. Esso promuove progetti innovativi attraverso un contributo finanziario e, in quanto piattaforma delle conoscenze, mette a disposizione informazioni sui progetti conclusi o ancora in corso.Il COMO è diretto da sei Uffici federali: l'Ufficio federale dello sviluppo territoriale (ARE), l'Ufficio federale delle strade (USTRA), l'Ufficio federale dell'ambiente (UFAM), l'Ufficio federale dei trasporti (UFT), l'Ufficio federale della sanità pubblica (UFSP) e l'Ufficio federale dell'energia (UFE). La carta visualizza tutti i progetti sostenuti dal COMO.

fr: Office fédéral de l'énergie OFEN

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.

fr: Projets du Bureau de coordination pour la mobilité durable (COMO)

de: Projekte der Koordinationsstelle für nachhaltige Mobilität KOMO

en: Projects of the Coordination Office for Sustainable Mobility COMO

it: Progetti sostenuti dal Ufficio di coordinamento per la mobilità sostenibile (COMO)