maintainer: Markus Schlegel

en: air-sampling metabarcoding monitoring spore-dispersal environmental-dna

en: Data files and analysis scripts (Version 2)

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of macrofungi". Please refer to README.pdf inside the archive for more information.

en: Data files and analysis scripts (Version 1)

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of macrofungi* ([Schlegel et al. 2024](https://doi.org/10.1111/1755-0998.13941)).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were under-represented in the air.
*Version 1* of the dataset was submitted during the review phase. *Version 2* contains minor changes and clarifications, and is up to date with the [published supplement](https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1755-0998.13941&file=men13941-sup-0001-AppendixS1.pdf) of the study.
The contents of the ZIP archive:
* analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

air-sampling

display_name: air-sampling

environmental-dna

display_name: environmental-dna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal

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: Supporting information for case study on the application of spore sampling for the monitoring of macrofungi


maintainer: Zhao

en: urban-land-use austin planning land-dynamics driving-factors

state: active

type: dataset

en: Potential driving factors of urban transformations of Austin over 25 years

media_type: application/zip

format: ZIP

en: In this study, the Austin metropolitan area, Texas, U.S., one of the fastest urban transformations and transformations regions, is selected to test the hypothesis that spatial planning and policies are important factors of urban transformations. Despite ample previous work in understanding the interactions between human and urban form transformation at specific areas, the actual interventions and outcomes of planning and policies (e.g., ‘smart growth’) on urban forms have been poorly measured. In this study, the potential influencing factors of urban transformations of Austin over 25 years were selected and collected.

austin

display_name: austin

driving-factors

display_name: driving-factors

land-dynamics

display_name: land-dynamics

planning

display_name: planning

urban-land-use

display_name: urban-land-use

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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: genetic-structure monitoring conservation-genetics melanargia-galathea genetic-diversity

media_type: text/csv

format: CSV

en:
Individual genotypes assessed at six nuclear microsatellite loci (two alleles per locus) for individuals of the butterfly Melanargia galathea (Marbled white) that were collected throughout Switzerland, along the regular grid of the Biodiversity Monitoring (BDM) of Switzerland. For each individual, the sampling site (number) and the genotype are given. Note that due to privacy restrictions, the original geographic coordinates remain disclosed. For original coordinates, data holders should be contacted (Swiss Federal Office for the Environment; Biodiversity Monitoring Switzerland).
The data refer to the following publication: Terzer et al., Distinct spatial patterns of genetic structure and diversity in the butterfly Marbled White (Melanargia galathea) inhabiting fragmented grasslands. Conservation Genetics, https://doi.org/0.1007/s10592-023-01593-4.

conservation-genetics

display_name: conservation-genetics

genetic-diversity

display_name: genetic-diversity

genetic-structure

display_name: genetic-structure

melanargia-galathea

display_name: melanargia-galathea

en: Nuclear microsatellite genotypes of the butterfly Melanargia galathea


maintainer: EnviDat Support

en: dem orthoimage alps findelengletscher drone gletscher uav griesgletscher dsm orthophoto sankt-annafirn glacier

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of April 2015.

mimetype: application/zip

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 22th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 15th of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 26th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 15th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 19th of April 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 21th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 30th of August 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 13th of September 2016.

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

format: SERVICE

media_type: application/pdf

en: This .pdf contains an orthoimage for each dataset as well as a Table which displays the number of flights made, image acquired, number of GCP set and the total area covered.

format: PDF

mimetype: application/pdf

en: This folder contains all UAV flights paths that we created for the Sankt Annafirn, the Findelengletscher and Griesgletscher. They have been created with the software eMotion2, that was developped for the eBee platform from Sensefly.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 28th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 3rd of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 09th of April 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 2nd of July 2016.

en:
 UAV-derived DSMs and orthoimages

Unmanned Aerial Vehicle (UAV) surveys were conducted between 2015 and 2016 on the Sankt Annafirn, Findelen- and Griesgletscher, situated in the Swiss Alps. Three surveys at the Sankt Annafirn allowed for a full glacier coverage, four surveys at Griesgletscher allowed an almost full glacier coverage and seven surveys at Findelengletscher allowed for a partial coverage of the glacier tongue (see individual datasets for exact extent). For each survey, a high resolution orthoimage and a Digital Surface Model (DSM) was created.

 UAV surveys:

Prior flight, Ground Control Points (GCPs) were deployed on the glacier surface and measured with a differential GPS (Trimble R7 or Leica GPS 1200). They allowed precise georeferencing of the UAV-derived datasets. UAV flight plans were planned with the software *eMotion 2* and a SenseFly eBee was used as surveying platform. The images were then processed with the software Agisoft Photoscan Pro 1.1.6 .

The location and dates of each survey can be found in the table together with the number of flights performed (Nflights), the number of acquired images (Nimages), the number of GCPs set (NGCPs) and the surveyed area.

A folder for each dataset is available (see folder name in table), which contains:

- An orthoimage *glacier_date_photoscan_oi_CH1903+_LV95_0.1m.tif*

- A Digital Surface Model *glacier_date_photoscan_dsm_CH1903+_LV95_0.1m.tif*

- The Agisoft Photoscan automatic processing report  *glacier_date_photoscan_report.pdf*

where:

- *glacier* is the name of the surveyed glacier

- *date* is the date of the UAV image acquisition

- *photoscan* is the name of the photogrammetric software

- *oi* or *dsm* the type of dataset

- *CH1903+_LV95* is the coordinate system and datum of the dataset

- *0.1m* is the resolution of the dataset in meter

- *.tif* is the extention of the dataset

Details about the UAV surveys, the image processing and the accuracy of the UAV-derived products can be found in this publication below.

Paper Citation:
 > _Gindraux et al. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’Imagery on Glaciers, Remote Sensing, 9, 186, 1-15, [doi: 10.3390/rs9020186](https://doi.org/10.3390/rs9020186)._

The folder UAV_flight_paths.zip contains all UAV flights performed on the Sankt Annafirn, Findelengletscher and Griesgletscher. The flights were planned with the software eMotion2 and have the .afp extention.

alps

display_name: alps

dem

display_name: dem

drone

display_name: drone

dsm

display_name: dsm

findelengletscher

display_name: findelengletscher

glacier

display_name: glacier

gletscher

display_name: gletscher

griesgletscher

display_name: griesgletscher

orthoimage

display_name: orthoimage

orthophoto

display_name: orthophoto

sankt-annafirn

display_name: sankt-annafirn

uav

display_name: uav

en: UAV-derived Digital Surface Models and orthoimages for three alpine glaciers


en: food-preferences latent-semantic-analysis national-dishes agro-food-trade food-taste-similarity

en: National dishes, migration data and data for bilateral food trade flows

en:
The data include information on national dishes, migration data and data for bilateral food
trade flows for 5 years as well as importer and exporter GDP, population, distance between
most populated cities, bilateral information on Preferential Trade Agreements, common
official primary langauge, common colonizer post-1945, colonial relationship for overall
171 countries. The final data set contains 145,350 observations (29,070 country pairs for
5 years)

en: dyadic food similarity measures, pairwise similarity and dissimilarity (chord diagram)

en:
The figures show the distribution of two dyadic food tastes similarity measures on the base of
the national dishes: (i) the Manhattan distance and the (ii) latent semantic analysis. The chord diagram
shows the results for country pairs with most and less similarity on basis of the LSA-approach.

en: information on ingredients of national dishes

en: shows information of ingredients of all national dishes of 171 countries and their names

en: The data described in this article were collected daily over the period 4 June 2018 to 23 August 2018 and contains information of several data sources. The database includes information on national recipes and their ingredients for 171 countries, measures for food taste similarities between all 171 countries as well as bilateral migration and agro-food trade data for 5 years. The database can be used for analyzing e.g., the relation between food preferences and international trade or food preferences and health outcomes (e.g., obesity) across countries.

agro-food-trade

display_name: agro-food-trade

food-preferences

display_name: food-preferences

food-taste-similarity

display_name: food-taste-similarity

latent-semantic-analysis

display_name: latent-semantic-analysis

national-dishes

display_name: national-dishes

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Data of national dishes, their similarity and trade flows


ceilometer-klosters

title_for_slug: ceilometer-klosters

en: raclets cloud-base-height ceilometer klosters vertical-visibility

en: Ceilometer data Klosters

en: Ceilometer installed at Klosters measuring cloud base height, cloud cover and backscatter profile. The time resolution is 30 seconds, with time given in number of days from January 0, 0000, UTC. More information on the variables in the manufacturer manual.

en: Cloud base height (m) and vertical visibility (m) were measured with the VAISALA Ceilometer CL31 in Klosters (LON: 9.880413, LAT: 46.869019). The CL31 is an instrument with constant reliability for all weather conditions and simultaneous detection of three cloud layers in heights up to 7.6 km.

ceilometer

display_name: ceilometer

cloud-base-height

display_name: cloud-base-height

klosters

display_name: klosters

raclets

display_name: raclets

vertical-visibility

display_name: vertical-visibility

en: Ceilometer Klosters


maintainer: Daniela Brito Melo

en: snow-cohesion drifting-snow large-eddy-simulations saltation mixed-grain-transport

en: Data in Figures

en: Simulation results presented in Figures 1 to 11 of the research article "Modeling snow saltattion: the effect of grain size and interparticle cohesion" in csv format.

en: LES-LSM code

en: Source code used to perform the analysis presented at the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion". The source code is also available at the WSL/SLF GitLab Repository (https://gitlabext.wsl.ch/atmospheric-models/les-lsm).

en:
This dataset includes the parallel application and the main results supporting the research article "Modeling snow saltation: the effect of grain size and interparticle cohesion" published at the Journal of Geophysical Research: Atmospheres.
The code is a flow solver based on the Large Eddy Simulation (LES) technique coupled with a Lagrangian Stochastic Model (LSM). The interaction of snow particles with the bed is modeled with statistical and physically-based models for aerodynamic entrainment, rebound and splash, following the works of Groot Zwaaftink et al. (2014), Comola and Lehning (2017) and Sharma et al. (2018). This algorithm was also used by Sigmund et al. (2021) to model snow sublimation.

drifting-snow

display_name: drifting-snow

large-eddy-simulations

display_name: large-eddy-simulations

mixed-grain-transport

display_name: mixed-grain-transport

saltation

display_name: saltation

snow-cohesion

display_name: snow-cohesion


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

en: wind-direction pressure relative-humidity holoballoon temperature wind radiosonde raclets

en: Radiosond Template Files

en:
The "template" files contain standard parameters, i.e. ambient pressure (mbar and Pa), temperature (°C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), as well as additional information, e.g. time (UTC and local time), dew point (°C), mixing ration (g/kg), density (kg m³), altitude (m MSL), height above ground (ft and m AGL), and geographic coordinates (longitude, latitude). If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosond Sounding Files

en:
The "soundings" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosondes (Windsond, Sparv Embedded AB) were started in Davos Wolfgang (LON: 9.853594, LAT: 46.835577) to report height profiles of pressure, relative humidity and temperature at specific days. In addition to regular launches of radiosondes, sondes were attached to [HoloBalloon](https://www.envidat.ch/group/clouds-in-situ-raclets) to report the ambient conditions of the in-situ measurements. Further profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/clouds-in-situ-raclets) which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.

holoballoon

display_name: holoballoon

pressure

display_name: pressure

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

en: Radiosondes


en: number-of-dead-persons avalanche-accident-statistics number-of-caught-persons avalanche-accidents avalanche-fatalities

en: Fatal avalanche accidents in Switzerland since 1995-1996

mimetype: text/csv

en:
Attention: this data is not updated after 2022 anymore.
This data collection contains information concerning all accidents by snow avalanches causing at least one fatality in Switzerland. The data set commences on 01/10/1995. After the completion of a hydrological year, the new data is added.
The following information is provided:
 * avalanche identifier
 * date of the accident
 * accuracy of the date in range of days before and after
 * canton
 * name of the locality
 * start zone of the avalanche
  * coordinates (Swiss coordinate system, approximately in middle of start zone)
  * accuracy of the coordinates in meters
 * elevation (in meteres above sea level, app. in middle of start zone)
 * slope aspect (main orientation of start zone)
 * slope inclination (in degree, steepest point within start zone)
 * number of dead persons
 * number of caught persons
 * number of fully buried persons
 * forecasted avalanche danger level
 * activity/location of the accident party at the time of the incident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

number-of-caught-persons

display_name: number-of-caught-persons

number-of-dead-persons

display_name: number-of-dead-persons

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


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

en: Site photo of the field station (LAF)

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

mimetype: image/jpeg

en: Field station data (LAF)

en: Data file.

en: Forest station data (LAB)

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 forest station (LAB)

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

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: 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

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

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


en: wasserkraft datensatz schweiz kleinstwasserkraftwerke speed2zero

en: Shapefile der 2’388 registrierten Wasserkraftanlagen in der Schweiz aus den beiden Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW).

en: Shapefile der Einzugsgebiete (2 km² ), in denen sich die jeweiligen Kleinstwasserkraftwerke befinden (erstellt von Yasser Haddad. ETH).

en: .XLSX-Datei der 2’388 registrierten Wasserkraftanlagen in der Schweiz aus den beiden Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW).

format: XLS

en: Die 1'682 erfassten Kleinstwasserkraftwerke im Datensatz CH-Kleinstwasserkraftwerke

en: Shapefile von CH-Kleinstwasserkraftwerke: 1'682 Kleinstwasserkraftwerke (≤ 300 kW) in der Schweiz.

en: .XLSX-Datei von CH-Kleinstwasserkraftwerke: 1'682 Kleinstwasserkraftwerke (≤ 300 kW) in der Schweiz.

en:
In der Schweiz werden Wasserkraftanlagen (WKA) mit einer Leistung von mehr als 300 kW systematisch erfasst und in der nationalen Wasserkraftstatistik (WASTA) zusammengetragen. Die WASTA bildet eine umfangreiche Datengrundlage für Analysen bezüglich Wasserkraft, auch im Kontext von Klimawandel, Biodiversitätsverlust und Energiewende. Nicht erfasst auf nationaler Ebene waren bis anhin die sogenannten Kleinstwasserkraftwerke, WKA mit einer Leistung von weniger als 300 kW. Kleinstwasserkraftwerke tragen zwar nicht wesentlich zur Schweizer Elektrizitätsversorgung bei, haben jedoch aufgrund ihrer hohen Anzahl Auswirkungen auf die Gewässerökologie, die mit den Klimawandel noch stärker unter Druck gerät.
Der neu erstellte Datensatz CH-Kleinstwasserkraftwerke umfasst 1'682 WKA mit einer Leistung von weniger als 300 kW. In den zwei Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW) sind zurzeit 2’388 WKA erfasst. Im Austausch mit den 26 Kantonen wurde jedoch klar, dass es sich nicht um eine vollständige Sammlung von Kleinstwasserkraftwerken handelt. Die 1'682 Kleinstwasserkraftwerke machen rund 70% aller erfassten WKA in der Schweiz aus, tragen jedoch mit weniger als 600 GWh/Jahr lediglich rund 1.5% zur schweizerischen Wasserkraftproduktion bei. In einem optimistischen Szenario, in dem die jährliche Produktionserwartung tendenziell überschätzt wird, liegt dieser Anteil um 0.3% höher. Von den erfassten 2’388 WKA erzeugen die 10% der grössten Anlagen über 90% der schweizerischen Wasserkraftproduktion. Der Datensatz CH-Kleinstwasserkraftwerke ist im Rahmen der ETH-Initiative SPEED2ZERO entstanden, die Klimadienstleistungen in den Bereichen Klimawandel, Biodiversitätsverlust und Energiewende erbringt (https://speed2zero.ethz.ch).
Hier verfügbare Datensätze:
- CH-Kleinstwasserkraftwerke - der hier vorgestellte Datensatz mit 1'682 Kleinstwasserkraftwerken
- EZG-Kleinstwasserkraftwerke - die Einzugsgebiete (2 km² ), in denen sich die 1'682 Kleinstwasserkraftwerke befinden (erstellt von Yasser Haddad. ETH)
- Metadaten - sämtliche Metadaten zum Datensatz CH-Kleinstwasserkraftwerke
- CH-WKA - eine Zusammenstellung sämtlicher 2'388 erfassten Wasserkraftanlagen in der Schweiz aus den beiden Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW)

datensatz

display_name: datensatz

kleinstwasserkraftwerke

display_name: kleinstwasserkraftwerke

schweiz

display_name: schweiz

wasserkraft

display_name: wasserkraft

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: CH-Kleinstwasserkraftwerke - ein schweizweiter Datensatz zu Kleinstwasserkraftwerken


maintainer: Frank Hagedorn

en: fertilization nutrient-fluxes nitrogen seasons forest-topsoil soil-temperature beech zero-tension-lysimeters dissolved-organic-phosphorus phosphorus

en:
Data on dissolved organic and inorganic phosphorus and nitrogen concentrations in leachates and their corresponding
fluxes from the litter layer, the Oe/Oa horizon, and the A horizon of two German beech forest sites.
Leachate samples were taken in April 2018, July 2018, October 2018, Feb./Mar. 2019, and July 2019
with zero-tension lysimeters after artificial irrigation. Soil samples were taken in July 2019.
For more details please refer to the publication.

beech

display_name: beech

dissolved-organic-phosphorus

display_name: dissolved-organic-phosphorus

fertilization

display_name: fertilization

forest-topsoil

display_name: forest-topsoil

nitrogen

display_name: nitrogen

nutrient-fluxes

display_name: nutrient-fluxes

phosphorus

display_name: phosphorus

seasons

display_name: seasons

soil-temperature

display_name: soil-temperature

zero-tension-lysimeters

display_name: zero-tension-lysimeters

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: Phosphorus and nitrogen leaching from beech forest soils


maintainer: Christian Rixen

en: fertilization stillberg treeline tree-rings dwarf-shrubs nitrogen-isotope

en: Data Nutrient Addition Stillberg

en: This link leads to the figshare repository, which contains all nutrient addition data.

en: Project Description Nutrient Addition Stillberg

media_type: text/html

en: Link to Nutrient Addition project description on the WSL website (in German).

format: HTML

en: Metadata Nutrient Addition Stillberg Experimental Design

media_type: image/png

en: Nutrient addition map of the study area with the investigated plots. Each circle (study block) contains one control plot and two plots that received NPK fertilizer corresponding to 15 (NPK15) or 30 (NPK30) kg N ha-1 a-1. Contour lines specify the elevation (m a.s.l.) in steps of 10 m.

format: PNG

en:
 Background information

The availability of nitrogen (N) and phosphorus (P) is considered to be a major factor limiting growth and productivity in terrestrial ecosystems globally. This project aimed to determine whether the growth stimulation documented in previous short‐term fertilisation trials persisted in a longer‐term study (12 years) in the treeline ecotone, and whether possible negative effects of nutrient addition offset the benefits of any growth stimulation.
Over the course of the 12 study years, NPK fertiliser corresponding to 15 or 30 kg N ha−1 a−1 was added annually to plots containing 30‐year‐old *Larix decidua* or 32‐year-old *Pinus uncinata* individuals with an understorey of mainly ericaceous dwarf shrubs. To quantify growth, annual shoot increments of trees and dwarf shrubs as well as radial growth increments of trees were measured. Nutrient concentrations in the soil were also measured and the foliar nutritional status of trees and dwarf shrubs was assessed.

 Experimental design

Over an elevation gradient of 140 m across the treeline afforestation site Stillberg, 22 locations were chosen that covered the whole range of microenvironmental conditions (*see* Nutrient addition experimental design.png). Half of the blocks included European larch (*L. decidua*) and the other half included mountain pine (*P. uncinata*). Within each block, three plantation quadrats were randomly selected as experimental plots and each plot was assigned to a control (no fertilisation) or to one of two fertiliser dose treatments (15 kg and 30 kg N ha−1 a−1). Treatments were assigned randomly but confined so that the location of fertilised plots within a block was not directly above control plots to avoid nutrient input from drainage. For details about the experiment, *see* Möhl et al (2019).

 Data description

The available datasets contain climate variables (2004-2016), nutrient isotope measurements (2010 & 2016), shrub growth measurements (2004-2016), soil parameter measurements and annual ring and shoot measurements (2004-2016). All data can be found here:
<https://figshare.com/articles/dataset/Twelve_years_of_low_nutrient_input_stimulates_growth_of_trees_and_dwarf_shrubs_in_the_treeline_ecotone/7025858>

dwarf-shrubs

display_name: dwarf-shrubs

nitrogen-isotope

display_name: nitrogen-isotope

stillberg

display_name: stillberg

tree-rings

display_name: tree-rings

treeline

display_name: treeline

en: Nutrient addition experiment at the Alpine treeline site Stillberg, Switzerland


maintainer: Ueli Reber

en: policy-documents biodiversity text-corpus environmental--policy policy-analysis bgb switzerland

en: Replication files

en:
 Introduction

The ZIP file contains all data and code to replicate the analyses reported in the following paper.

Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)

If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.

 Data folder

The data folder contains the following files.

* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors

The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.

 Text corpus

The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.

* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
* The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)

The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.

* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text

The following list contains the coding scheme for the doc_type variable.

* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court

 Code folder

The code folder contains all R code for the analyses. The files are numbered chronologically.

* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper

The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.

Package versions and setup details are noted in the code files.

 Contact

Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

en: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"


en: dsm drone-data uav photogrammetry wingtra

en: Data Access

en:
- DSM 10cm resolution
- Orthomosaic 3cm resolution
- Agisoft Metashape Processing Report
- original RGB images

All generated products are also available as a cloud optimized geotiff.

en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Photogrammetric Drone Data Wolfgang Arelen


en: catchment-data meteorological-data snowpack snow-hydrology rain-on-snow

en: The file contains all data needed to run simulations with the snow cover model SNOWPACK.

media_type: text/plain

format: TXT

mimetype: text/plain

en: Meteorological data used to run SNOWPACK for 58 catchments in the Swiss Alps. The data consists of a 2 km grid of "virtual meteorological stations" for each catchment. It was used to simulate snow cover processes during rain-on-snow events, therefore meteorological data of each catchment contains at least one rain-on-snow event. Further information can be found in the attached readme.txt and in Würzer & Jonas et al. (2017), currently under review in Hydrological Processes.

catchment-data

display_name: catchment-data

meteorological-data

display_name: meteorological-data

rain-on-snow

display_name: rain-on-snow

snow-hydrology

display_name: snow-hydrology

snowpack

display_name: snowpack

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: Meteorological data for investigation of rain-on-snow events in 58 catchments in Switzerland


en: snow-temperature water-front snowmicropen ice-layers weissfluhjoch snow-stratigraphy

en: README

en: WFJ_ICE_LAYERS dataset

en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack


maintainer: Amelie Fees

en: avalanche-activity snowpack-simulation time-lapse-photography glide-snow-avalanche avalanche

en: Glide-snow avalanche activity

en: Table that contains all glide-snow avalanche events that were detected in time-lapse photographs (season 2008/09 to 2021/22). The columns are explained in the README.txt

en: SNOWPACK simulations

en: SNOWPACK simulations (.pro and .smet) covering season 2008/09 to 2021/22 at 10 virtual locations on Dorfberg. The locations correspond to the most common glide-snow avalanche paths.

en: Glide distances for opening glide-cracks

en: This folder contains all glide-cracks where glide-distances were extracted from time-lapse photographs. Glide-distances were calculated in x-direction (width) and y-direction (downslope, length) by georeferencing the images.

en: README.txt explaining the dataset and columns of tables in more detail.

en:
This dataset includes the processed data of the glide-snow avalanche activity and dynamics on Dorfberg (Davos, Switzerland) covering seasons 2008/09 to 2021/22. This dataset was described in the research article:

Fees, A., van Herwijnen A., Altenbach, M., Lombardo, M., Schweizer, J.: Glide-snow avalanche characteristics at different time-scales extracted from time-lapse photography, Annals of Glaciology, 91

We extracted the dynamics of opening glide-cracks and the glide-snow avalanche activity from time-lapse photographs. Glide-snow avalanches were separated into surface and interface events using the liquid water content which was simulated with SNOWPACK at 10 virtual stations on Dorfberg.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snowpack-simulation

display_name: snowpack-simulation

time-lapse-photography

display_name: time-lapse-photography

en: Glide-snow avalanche activity on Dorfberg, Davos, Switzerland


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

en: Description

en: Description of the predictors provided in this dataset

en: Predictors

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

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

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

Paper Citation:

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

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


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

en: Forest station data (NEB)

en: Data file.

en: Data plot of the field station (NEF)

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

en: Site photo of the field station (NEF)

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

en: Site aerial photo (Neunkirch)

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

en: Field station data (NEF)

en: Data plot of the forest station (NEB)

en: Site photo of the forest station (NEB)

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

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 Neunkirch in Switzerland where one station is located within a natural deciduous forest stand (NEB) with European beech (_Fagus sylvatica_; 160 yrs), sycamore maple (_Acer pseudoplatanus_; 160 yrs) and lime trees (_Tilia sp._; 110 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NEF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Neunkirch 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: Neunkirch, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


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

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

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

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

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

biodiversity

display_name: biodiversity

ecology

display_name: ecology

forest

display_name: forest

microclimate

display_name: microclimate

radiation-transfer

display_name: radiation-transfer

statistical-interpolation

display_name: statistical-interpolation

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


data-interactive-avalanche-segmentation

title_for_slug: data-interactive-avalanche-segmentation

en: interactive avalanche snow deep-learning segmentation

en:
Images and corresponding avalanche annotations used for interactive avalanche segmentation:
SLF train, vali and test
WebNew
GroundPic
UserPic
UIBK dataset: List of images used
Pictures are from SLF (mostly from the Dischma Cams) if not otherwise indicated. If used, the data needs to be properly cited!

avalanche

display_name: avalanche

deep-learning

display_name: deep-learning

interactive

display_name: interactive

segmentation

display_name: segmentation

snow

display_name: snow

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: Data interactive avalanche segmentation


maintainer: Henning Löwe

en: granular-snow angle-of-repose discrete-element-modelling fast-sintering grain-shape

en: Angle of repose and 3D CT images

en:
5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.

This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.

The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow

en: Angle of repose experiments with natural and spherical snow


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: crack-propagation rutschblock weak-layer snow-avalanche propgatoin-saw-test failure-initiation slab-tensile-support snow-stability-evaluation avalanche-forcasting slab

en: data set on snow instability

en: Read-me file on snow instability data

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

en: Data set on snow instability


en: remote-sensing wind wind-energy lidar atmospheric-dynamics atmospheric-turbulence

format: OCTET

en:
This data include wind speeds, wind directions, turbulence, temperature, pressure and humidity data of 10 LiDAR locations along a transect in the Gotthard wind park taken in during the summer of 2023.
The data is quality controlled and annotated according to CF-1.8 data principles. The methods behind this data collection are explained in an article under review called "Resolving three-dimensional wind velocity fields with sequential wind-Doppler LiDAR for wind energy in the complex terrain - Gotthard Pass, Switzerland".

atmospheric-dynamics

display_name: atmospheric-dynamics

atmospheric-turbulence

display_name: atmospheric-turbulence

lidar

display_name: lidar

remote-sensing

display_name: remote-sensing

wind

display_name: wind

wind-energy

display_name: wind-energy

educ

en: Education, culture and sport

en: Sequential Wind-Doppler LiDAR wind profile measurements on the Gotthard pass in Switzerland - Summer 2023


biogas-aus-hofdunger-in-der-schweiz

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

en: bioenergy manure switzerland biogas review

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

envidat

en: EnviDat: the Environmental Data Portal


maintainer: Virginie Marques

en: environmental-dna plankton fish biodiversity marine dna-metabarcoding fjord

en: Metabarcoding data

en: Raw metabarcoding data for both primers (teleo and 18S) and corresponding file to perform the demultiplexing and primer trimming

en: Code, data and figures

en: Here there are all the data and code to reproduce the figures and analysis presented in the paper, with a README.md file

en:
This dataset contains the raw environmental DNA data associated with the publication *Environmental drivers of eukaryotic plankton and fish biodiversity in an Arctic fjord* in the journal Polar Biology (2023).

 Methods

**Sampling**
We sampled the Lilliehöök fjord on the west coast of Spitsbergen (Svalbard, Norway) over 3 days from 3 to 5 of August 2021. Samples were taken from the glacier front up to the fjord mouth of the Krossfjorden system, around 30 km long, after the Lilliehöök fjord merged with the mouth of Möller fjord. The fjord’s maximum depth has been recorded at 373 m (Svendsen et al. 2002) and has no sill at its entrance, thereby facilitating water exchange with the open ocean of the West Spitsbergen Current. We used a research vessel to sample 5 sites for a total of 15 samples, sampling 3 depths per site (3-m, chlorophyll a maximum and 85-m, unless sea floor was shallower). Shallow and intermediate samples between 3-m and 12-m represent ~35-L of water filtered in-situ using long tubing and a peristaltic pump, and all other deeper samples were taken from a total of 3 Niskin bottles (General Oceanics), representing 22-L of water sampled per sample. Water was filtered through a VigiDNA filtration capsule (SPYGEN) with a 0.20-µm pore size using an Athena peristaltic pump (Proactive Environmental Products, Bradenton, Florida) with a flow rate of ~1-L/min. Each sample was handled with single use tubing and gloves.

**Molecular**
To perform the amplification, we used two sets of primers: teleo (forward: ACACCGCCCGTCACTCT, reverse: CTTCCGGTACACTTACCATG; Valentini et al. 2016) and the universal eukaryotic 1389F/1510R primer pair, amplifying the V9-18S rDNA gene (Amaral-Zettler et al. 2009) (forward: TTGTACACACCGCCC, reverse: CCTTCYGCAGGTTCACCTAC).

 Data content:

+ Metabarcoding data: This zip file contains the 2 sequencing libraries filtered to only retain the samples used in the present study.
+ Code, data and figure: This zip file contains all data and code to reproduce the figures and the analysis in the study, with an associated README explaining the content of each folder.

 Additional informations
For more details, please see the Methods in the associated publication: DOI: 10.1007/s00300-023-03187-9.

biodiversity

display_name: biodiversity

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

fish

display_name: fish

fjord

display_name: fjord

marine

display_name: marine

plankton

display_name: plankton

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: Data: Environmental drivers of eukaryotic plankton and fish biodiversity in an Arctic fjord


data-broedlin-cnp

title_for_slug: data-broedlin-cnp

en: dissolved-organic-matter drying-rewetting carbon forest mineralization stoichiometry phosphorus soil nitrogen

en: Data Broedlin-CNP

en: Data Broedlin-CNP-Release

en: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

en: Mircocosm experiment to identify the individual patterns and controls of C, N, and P mobilization in soils under beech forests. Organic and mineral horizons sampled along a nutrient availability gradient in Germany were exposed to either permanent moist conditions or to dry spells in microcosms and quantified the release of inorganic and organic C, N, and P.

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry

en: Data Broedlin CNP


maintainer: Adam Winstral

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

en: HS and SWE observations

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

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: 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: 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

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation

educ

en: Education, culture and sport

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


en: laboratory-study snow-atmosphere-interactions chemistry ice atmosphere

en:
The table lists all NEXAFS raw data with the following columns:

* name:						raw file name
* xRayEkinRange_eV: 		Smallest and largest X-ray photon energy in eV
* scientaPassEnergy_eV: 	Pass energy of electron analyzer in eV
* scientaDwellTime_ms: 		Dwell time of electron analyzer in ms
* regionName:				O K-edge for all data
* scientaAcquisitionMode: 	Fixed energy (snapshot) mode
* scientaEkinRange_eV: 		Smallest and largest energy of the kinetic energy window used for detection in this work
* scientaEkinStep_eV		Not defined in fixed energy mode
* scientaLensMode:			Tune table
* scientaRegionIterations: 	Iterations (sweeps)
* scientaSequenceIterations: Iterations (sweeps)
* sampleTemp_dC: 			Temperature as monitored at the sample holder in °C
* cellPressure_mbar: 		Total pressure in measurement cell in mbar
* iceTemp_dC: 				Temperature of ice sample calculated based on vapour pressure (assuming total pressure equals partial pressure of water) in °C
* smplX_mm: 				positon of measurement spot, x dimension in mm
* smplY_mm: 				positon of measurement spot, y dimension in mm
* smplZ_mm: 				positon of measurement spot, z dimension in mm
* sealingTemp:				temperature at base of sample manipulator
* lastModifiedDatestr: 		time and date when data aquisition was finished
* sample: 					sample description

en: Near Ambient Pressure partial Auger-Meitner electron yield X-ray absorption spectra and photon flux data. X-ray energy in eV in column 1, analyzer electron count intensity in arb. units in column 2.

en: Processed data as shown in Figure 4 of publication. X-ray energy in eV in column one, electron count intensity in arb. units in column 2.

en: Data are compiled that have been used to demonstrate the impact of high water partial pressure on X-ray absorption spectra of ice.

atmosphere

display_name: atmosphere

chemistry

display_name: chemistry

ice

display_name: ice

laboratory-study

display_name: laboratory-study

snow-atmosphere-interactions

display_name: snow-atmosphere-interactions

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: An ice oxygen K-edge NEXAFS spectroscopy data set on gas-phase processing


en: stomatal-stringency anisohydric water-use-strategy water-potential root-distribution

en: The data file contains the data shown in the Figures 2-7 in Walthert et al. (2024).

en:
This dataset represents the data shown in the Figures 2 - 7 of Walthert et al. (2024): Coordination between degree of isohydricity and depth of root water uptake in temperate tree species. Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2024.174346). A detailed methodical description of the data can be found in the Methods section of the paper.

Abstract
In an increasingly dry environment, it is crucial to understand how tree species use soil water and cope with drought. However, there is still a knowledge gap regarding the relationships between species-specific stomatal behaviour, spatial root distribution, and root water uptake (RWU) dynamics.
Our study aimed to investigate above- and below-ground aspects of water use during soil drying periods in four temperate tree species that differ in stomatal behaviour: two isohydric tracheid-bearing conifers, Scots pine and Norway spruce, and two more anisohydric deciduous species, the diffuse-porous European beech, and the ring-porous Downy oak. From 2015 to 2020, soil-tree-atmosphere-continuum parameters were measured for each species in monospecific forests where trees had no access to groundwater. The hourly time series included data on air temperature, vapour pressure deficit, soil water potential, soil hydraulic conductivity, and RWU to a depth of 2 m. Analysis of drought responses included data on stem radius, leaf water potential, estimated osmotically active compounds, and drought damage.
Our study reveals an inherent coordination between stomatal regulation, fine root distribution and water uptake. Compared to conifers, the more anisohydric water use of oak and beech was associated with less strict stomatal closure, greater investment in deep roots, four times higher maximum RWU, a shift of RWU to deeper soil layers as the topsoil dried, and a more pronounced soil drying below 1 m depth. Soil hydraulic conductivity started to limit RWU when values fell below 10-3 to 10-5 cm/d, depending on the soil. As drought progressed, oak and beech may also have benefited from their leaf osmoregulatory capacity, but at the cost of xylem embolism with around 50% loss of hydraulic conductivity when soil water potential dropped below -1.25 MPa. Consideration of species-specific water use is crucial for forest management and vegetation modelling to improve forest resilience to drought.

anisohydric

display_name: anisohydric

root-distribution

display_name: root-distribution

stomatal-stringency

display_name: stomatal-stringency

water-potential

display_name: water-potential

water-use-strategy

display_name: water-use-strategy

en: Water-use strategies of temperate tree species


en: sper01 vertebrates spermatophytes edna vert01 switzerland freshwater environmental-dna

en: Data access

en:
Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes

From 22-Jun-2020 to 26-Jun-2020, we sampled five sites comprising one low, two intermediate and two high-elevation sites per catchment (Fig. 1a). We visited two catchments per day—one in the morning and one in the afternoon—for a total of ten catchments. All samples per catchment were collected within a maximum four-hour period by three groups of samplers. The intermediate and high-elevation sites were situated along two tributaries leading into the low-elevation site of the river. We used three filters for each relative elevation class and filtered 60 L per relative elevation class. We sampled 30 L per tributary for a combined volume of 60 L at the intermediate and high-elevation sites. In total, 180 L were sampled in total per catchment. A filtration device composed of either the Athena® peristaltic pump (Proactive Environmental Products LLC; 1 L/min nominal flow) or the Subspace® underwater peristaltic pump (Subspace Pictures; 1 L/min nominal flow), combined with a VigiDNA® 0.2 µM cross-flow filtration capsule (VigiDNA, SPYGEN) was used in order to filter a large water volume. We used a finer mesh than the recommended VigiDNA® 0.45 µM cross-flow filtration capsule to maximise the capture of biological material since mountain water does not transport high quantities of sediments. For each filtration capsule, we used disposable sterile tubing. At the end of each filtration, we emptied the water inside the capsules, replaced it with 80 ml of CL1 conservation buffer (SPYGEN), and stored it at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Goldberg et al. 2016; Valentini et al. 2016). Each water sample was processed using disposable gloves and single-use filtration equipment. We used two primer sets targeting vertebrates (Vert01, forward: − TTAGATACCCCACTATGC, reverse: − TAGAACAGGCTCCTCTAG, mean marker length: 97 bp) and spermatophytes (g-h/Sper01, forward: − GGGCAATCCTGAGCCAA, reverse: CCATTGAGTCTCTGCACCTATC, mean marker length: 48 bp). Though both primers are relatively broad with low species-level resolution, we selected them as the goal was to minimise cost and effort and maximise the identification of a broad range of taxa which can represent the species assemblages of the region. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

edna

display_name: edna

environmental-dna

display_name: environmental-dna

freshwater

display_name: freshwater

spermatophytes

display_name: spermatophytes

switzerland

display_name: switzerland

vertebrates

display_name: vertebrates

en: Environmental DNA Freshwater Switzerland VaudCatchment Modipl 2020


maintainer: Dirk Nikolaus Karger

en: climatology free-climate-data climate precipitation climate-change climate-layers temperature bioclim

en: CHELSA Technical Documentation

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

en: CHELSA V1.2 (deprecated)

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

format: GeoTIFF

en: CHELSA V2.1 (current)

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.

Paper Citation:
 > _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

temperature

display_name: temperature

educ

en: Education, culture and sport


en: picea-abies afforestation isotopes subalpine belowground-biomass

en: This data set provides soil organic carbon, total nitrogen, and stable carbon isotope (13C) values of mineral soil (0-45cm), organic horizons (Oi, Oe, Oa), and root biomass of an afforestation sequence (0-130years) on a subalpine pasture in Jaun, Switzerland.

afforestation

display_name: afforestation

belowground-biomass

display_name: belowground-biomass

isotopes

display_name: isotopes

picea-abies

display_name: picea-abies

subalpine

display_name: subalpine

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: Soil organic carbon stock of an afforestation sequence on a subalpine pasture


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

en: Site photo of the forest station (NOB)

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

en: Data plot of the field station (NOF)

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

en: Forest station data (NOB)

en: Data file.

en: Data plot of the forest station (NOB)

en: Site aerial photo (Novaggio)

en: Site aerial photo from both Novaggio stations. Source: Google. 2016. Site aerial photo from both Novaggio stations. Retrieved November 15, 2016, from https://www.google.ch/maps

en: Field station data (NOF)

en: Site photo of the field station (NOF)

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

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 Novaggio in Switzerland where one station is located within a natural deciduous forest stand (NOB) with Turkey oak (_Quercus cerris_; 70 yrs), sweet chestnut (_Castanea sativa_; 90 yrs) and silver birch (_Betula pendula_; 70 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Novaggio is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

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


swiss-fluxnet-site-lageren

title_for_slug: swiss-fluxnet-site-lageren

en: greenhouse-gas eddy-covariance forest flux swiss-forest-lab swiss-fluxnet meteorological-measurements

en: Fluxnet2015 dataset

en: The flux and meteo data of the Swiss FluxNet site Lägeren are also part of the Fluxnet2015 dataset.

en: Data access

en: The flux and meteo data of the Swiss FluxNet site Lägeren are openly available from the European Fluxes Database Cluster.

en: Site description

en:
The Swiss FluxNet Site Lägeren is a managed mixed deciduous mountain forest located on the steep Lägeren mountain (NW of Zurich, Swiss Plateau). The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and the National Air Pollution Monitoring Network (NABEL). In addition to Swiss FluxNet, the site is part of the Long-term Forest Ecosystem Research (LWF) of WSL and the biological drought and growth indicator network (TreeNet) of WSL.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O), soil respiration campaigns
- Continuous CO2 profile measurements.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

All data are available from the European Fluxes Database Cluster, but are also part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae//](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Swiss FluxNet Site Lägeren


vegetation-height-model-nfi

maintainer: Christian Ginzler

title_for_slug: vegetation-height-model-nfi

en: point-cloud 3d photogrammety forest vegetation-height-model

en: 2016 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2016' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2011 to 2016.

en: Thumbnail

en: 2015 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2015' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2010 to 2015.

en: Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

en: 2012 Vegetation Height Model NFI

en:
Data 'Vegetation Height Model NFI 2012' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2007 to 2012.

en: 2019 Vegetation Height Model NFI (current)

en:
Data 'Vegetation Height Model NFI 2019' available on request (christian.ginzler@wsl.ch).

A national vegetation height model was calculated for Switzerland using digital aerial images. We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using the digital terrain model (DTM) SwissAlti3D based on airborne laser data. Buildings are masked out using the NDVI information of the aerial images to produce a vegetation height model, and to produce a vegetation height model (VHM). Such a model will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from 2013 to 2019.

en:
A national vegetation height model was calculated for Switzerland using digital aerial images.
We used the stereo aerial images acquired by the Federal Office of Topography swisstopo using the ADS80 sensor to first calculate a digital surface model (DSM) with a very high spatial resolution
(1 × 1 m and 0.5 x 0.5 m). The DSM was then normalized to obtain the actual
vegetation heights using a digital terrain model (DTM)
based on laser data with the buildings masked out, and to
produce a vegetation height model (VHM). Such a model
will be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very
high level of detail. For covering the whole of Switzerland,
we use summer aerial images from six years.

Latest version is from 2019.

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

vegetation-height-model

display_name: vegetation-height-model

en: Vegetation Height Model NFI


swiss-fluxnet-site-davos

title_for_slug: swiss-fluxnet-site-davos

en: swiss-fluxnet meteorological-measurements greenhouse-gas swiss-forest-lab flux eddy-covariance forest icos

en: Fluxnet2015 dataset

en: Processed flux and meteo data are also part of the Fluxnet2015 dataset.

en: Data access

en: The flux and meteo data of the Swiss FluxNet site Davos are openly available. Near real-time flux and meteo data are uploaded daily to the ICOS Carbon Portal.

en: Site description

en: Processed data

en: Processed flux and meteo data are available from the European Fluxes Database Cluster.

en:
The Swiss FluxNet Site Davos is a managed subalpine evergreen forest, located on the Seehorn mountain near Davos in the Swiss Alps. The site is dominated by Norway spruce. The tower is owned by the Federal Office for the Environment (FOEN).
Ecosystem flux measurements of CO2, H2O (since 1997) as well as CH4 and N2O (since 2016) are performed with the eddy covariance method.
In addition to Swiss FluxNet, the site is part of the National Air Pollution Monitoring Network (NABEL), the Long term Forest Ecosystem Research (LWF), the biological drought and growth indicator network (TreeNet) and of ICOS Switzerland (Integrated Carbon Observation System). Since November 2019, the site is an ICOS Class 1 Ecosystem station.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour (since 1997) as well a CH4 and N2O (since 2016) are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor) and laser spectrometers (for CH4 and N2O), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O, since 2023 also CH4).
- Continuous profile concentration and forest floor flux measurement of CO2, H2O, CH4, N2O.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

Near real-time flux and meteo data uploaded daily to the ICOS Carbon Portal. Processed flux and meteo data are also available from the European Fluxes Database Cluster and part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/)

icos

display_name: icos

educ

en: Education, culture and sport

en: Swiss FluxNet Site Davos


en: fagus-sylvatica forest climate-change air-pollution ground-vegetation forest-management

en: Site Information

en: This table contains information about the 254 forest sites used in the publication of Scherrer et al. 2024.

en: Taxa Data

en: This table contains information about the individual taxa found in the historic and current vegetation relevés in Scherrer et al. 2024.

en: This dataset comprised 254 historical (1937 – 1948) and resurveyed (2019 – 2022) vegetation relevés of beech-dominated forests sites in the Swiss Jura mountains. The data contains species lists as well as site information.

air-pollution

display_name: air-pollution

climate-change

display_name: climate-change

fagus-sylvatica

display_name: fagus-sylvatica

forest-management

display_name: forest-management

ground-vegetation

display_name: ground-vegetation

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: Resurveyed vegetation releves of beech forests in the Swiss Jura Mountains


maintainer: Jürg Schweizer

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

en: Snow avalanche data

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

en: Avalanche activity data

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

en: Readme

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

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

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


en: environmental---history environmental--policy historical-carthography ecology switzerland wetlands

en: Wetlands 1850 - 2010 (shapefiles)

en:
 History of wetlands - GIS-Layers
 Location of wetlands based on signatures in topographic maps
* Basis 1850: original measuring table sheets Dufour created between the years 1834 and 1863.
* Basis 1900/ Basis 1950: The Siegfried maps were updated and published at regular intervals between 1870 and 1949. This long period of time made it possible to reconstruct wetlands for two periods based on the Siegfried Maps: the first edition (hereinafter referred to as "1900") and the last edition ("1950").
* Basis 2010: Map sheets from the National Map from 2006 to 2011 were used for the most recent time period of the reconstruction.
 Location of wetlands due to reconstructions
The reconstruction **must not** be interpreted in the sense of a surface-accurate separation, but shows without claim to location accuracy the approximate extent of the areas that would have corresponded to the mapping criteria for wetlands used in today's topographic maps around 1850, 1900 and 1950. The basics can be found in Stuber & Bürgi 2019, chapter 5.4.

en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?

In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.

The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.

Book Citation:
 > Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands

educ

en: Education, culture and sport

en: History of wetlands in Switzerland since 1850


en: outdoor-lighting artificial-lighting alan sustainability ecosystem-services

en: R code for NMDS of ground-dwelling arthropods

en: Raw data for flying insects and ground-dwelling arthropod combined analysis

en: R code of ground-dwelling arthropod analysis.

en: Raw data Moran's I test

en: Raw data for flying insects NMDS analysis

en: R code of flight-active and ground-dwelling arthropod combined analysis.

en: Raw data for ground-dwelling arthropod analysis

en: R code for PERMANOVA Analysis of ground-dwelling arthropods.

en: Raw data for flying insects analysis

en: R code of flight-active insects analysis.

en: R code for NMDS of flight-active insects

en: R code for PERMANOVA Analysis of flight-active insects.

en: Raw data for ground-dwelling arthropod NMDS analysis

en: Raw data and R Code to do all the analysis performed for the paper "Advancing sustainable LED solutions to mitigate light-pollution impacts on arthropods". Including data for both flight-active insects and ground-dwelling arthropods combined (PT_TRF_all.csv), flight-active insects alone (ALANeX_PT_all_clean_control.csv) and ground-dwelling insects alone (ALANeX_TRF_all_clean_control.csv). For the NMDS analysis, there is a data set for the flight-active insects (ALANeX_PT_NMDS.csv) and the ground-dwelling arthropods (ALANeX_TRF_NMDS.csv). For the Morans I use the 'ALANeX_MoransI.csv' dataset.

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

ecosystem-services

display_name: ecosystem-services

outdoor-lighting

display_name: outdoor-lighting

sustainability

display_name: sustainability

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.