en: snow-cover-fraction snow-water-equivalent snow-melt snow-climatology operational-snow-hydrological-service

en: Data package

en: This dataset comprises the climatology on gridded data of snow water equivalent and snow melt runoff spanning 1998-2022, with a spatial resolution of 1 km and daily temporal resolution. This data was produced with the conceptual OSHD model (Temperature Index Model).

operational-snow-hydrological-service

display_name: operational-snow-hydrological-service

snow-climatology

display_name: snow-climatology

snow-cover-fraction

display_name: snow-cover-fraction

snow-melt

display_name: snow-melt

snow-water-equivalent

display_name: snow-water-equivalent

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Climatological snow data since 1998, OSHD


maintainer: EnviDat Support

en: wingtra uav dsm drone-data photogrammetry

state: active

type: dataset

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.

format: SERVICE

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

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Photogrammetric Drone Data Wolfgang Arelen


en: magnitude force-plate debris-flow volume monitoring-station illgraben

media_type: text/csv

en: Illgraben debris-flow bulk volumes from 2000 to 2017.

format: CSV

en:
Debris-flow bulk volumes from the WSL monitoring station.
More information can be found in McArdell et al. (2007) and Schlunegger et al. (2009).

debris-flow

display_name: debris-flow

force-plate

display_name: force-plate

illgraben

display_name: illgraben

magnitude

display_name: magnitude

monitoring-station

display_name: monitoring-station

volume

display_name: volume

en: Debris-flow volumes at the Illgraben 2000-2017


en: forest monitoring long-term-forest-ecosystem-research air-pollution long-term-monitoring

en: Link to Proceedings in DORA WSL

media_type: application/pdf

format: PDF

en: FORECOMON – Proceedings

en: Latest version

en: Deprecated version 1.0

en: First version of the proceedings containing errors. This early version it is kept, for traceability purposes, in conformance with DOI rules.

en:
Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings.
FORECOMON 2021 - the 9th forest ecosystem monitoring conference.
7-9 June 2021, WSL, Birmensdorf, Switzerland

The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.

Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.

air-pollution

display_name: air-pollution

forest

display_name: forest

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

monitoring

display_name: monitoring

en: Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7–9 June 2021, Birmensdorf, Switzerland


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

media_type: 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 30th of August 2016.

format: ZIP

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 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 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 2nd of July 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 Findelengletscher on the 22th of September 2016.

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.

mimetype: application/pdf

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 Sankt Annafirn on the 15th 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 Griesgletscher on the 13th 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 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 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 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 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 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 19th of April 2016.

en: Bulk Data Access

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

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:
 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

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

educ

en: Education, culture and sport

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


en: long-term-forest-ecosystem-research deadwood swiss-forest-lab coarse-woody-debris icp-forests

en: Data Request

en:
Assessment of coarse woody debris on LWF plots using full count methods on defined subplots (applying ForestBiota protocoll)

 Purpose:

Assessing the amount of coarse woody debris

 Manual Citation:

 * Franziska Heinrich, 2005: Totholz-Aufnahme mit ForestBIOTA Protokoll. Langfristige Waldökosystem-Forschung LWF. Eidg. Forschungsanstalt WSL, Birmensdorf, 7 S.

 * ForestBiota, 2005. Stand structure assessment including deadwood. EU/ICP Forests Biodiversity Test-Phase (ForestBIOTA). [>>>](http://www.forestbiota.org)

 * Fischer, R., Fischer, R., Seidling, W., Granke, O., Meyer, P., Stofer, S., Travaglini, D., 2007. ForestBIOTA – Testphase zur Erfassung der biologischen Vielfalt. AFZ/Wald 62, 1070.

 Paper Citation:

 * Seidling, W., Travaglini, D., Meyer, P., Waldner, P., Fischer, R., Granke, O., Chirici, G., Corona, P., 2014. Dead wood and stand structure - relationships for forest plots across Europe. IForest - Biogeosciences and Forestry 7, 269-281.

coarse-woody-debris

display_name: coarse-woody-debris

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

swiss-forest-lab

display_name: swiss-forest-lab

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: Deadwood survey LWF 2005 - subplot (Forets Biota)


en: swiss-forest-lab icp-forests tree-growth stem-diameter long-term-forest-ecosystem-research

en:
Tree circumference change measurements from plastic girth bands

 Purpose:

Assessment of annual tree stem growth

 Manual Citation:

 * Dobbertin M, Neumann M, 2016: Part V: Tree Growth. In: UNECE ICP Forests, Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 17 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Etzold S, Waldner P, Thimonier A, Schmitt M, Dobbertin M (2014) Tree growth in Swiss forests between 1995 and 2010 in relation to climate and stand conditions: Recent disturbances matter. Forest Ecology and Management, 311: 41-55. [doi: 10.1016/j.foreco.2013.05.040](http://doi.org/10.1016/j.foreco.2013.05.040)

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stem-diameter

display_name: stem-diameter

tree-growth

display_name: tree-growth

en: Manual circumference band measurement LWF


ensemble-hydrograph-separation-scripts

title_for_slug: ensemble-hydrograph-separation-scripts

en: catchment runoff streamflow tracers hydrograph-separation isotopes

en: *deprecated* MATLAB scripts and demonstration files (*deprecated version* - build 20200718 - do not use!)

en:
The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder. These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

en: R scripts and demonstration files

en:
The ensemble hydrograph separation functions themselves are in EHS_v1.4.R.

EHS_demo_v1.4.R is a demonstration script that calls EHS_v1.4.R to analyze the demo input files. The resulting output files are in the "demo output files" folder.

en: MATLAB scripts and demonstration files (current version - build 20201119)

en:
The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

Build 20201119 has improved commenting, naming, and structuring, and also minor bug fixes in EHS_Fnew, EHS_TTD, and EHS_profile. Build 20200718 has been deprecated. Use build 20201119 instead.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder. These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

en:
Calculation scripts that perform ensemble hydrograph separation. Identical scripts in R and MATLAB are provided, along with demonstration input time series and the corresponding outputs. These scripts were tested on R version 3.6.2 (2019-12-12) and on MATLAB versions 2018b and 2109b.

These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.

ETH Zurich, WSL, James Kirchner, and Julia Knapp make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose. Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

catchment

display_name: catchment

hydrograph-separation

display_name: hydrograph-separation

isotopes

display_name: isotopes

runoff

display_name: runoff

streamflow

display_name: streamflow

tracers

display_name: tracers

en: Ensemble hydrograph separation scripts


lwf-lausanne-long-term-research-site

title_for_slug: lwf-lausanne-long-term-research-site

en: infrastructure plot lwf forest meteorological-measurements swiss-forest-lab meteorological-data

en: Lausanne Meteorological Data LWF

en: LWF plot Lausanne. Photo: Anne Thimonier Rickenmann, 2019

en:
![alt text](https://www.envidat.ch/dataset/9f35f697-a226-4719-aefd-b8c96fe5ae7c/resource/d6a48c12-62e6-4c04-9f63-a84d5964bc55/download/lwf_lausanne.jpg "LWF Lausanne")

LWF Plot Lausanne

- Community: Lausanne / canton VD
- Date of installation: 5 September 1994
- Size of the plot: 2 ha
- Altitude: 800-814 m
- Mean slope: 7%
- Geology (in German): Untergrund: Tertiär, Miozän, Burdigalien, obere Meeresmolasse; Sandstein - Oberfläche: Quartär, Würm; würmeiszeitliche Moräne
- Soil types (WSL) : Distric Cambisols
- Woodland association after EK72: 8: Milio-Fagetum
- Main tree species: Fagus sylvatica
- Management system: high forest
- Silvicultural system: group selection
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 59.9 cm
- Number of trees BHD >= 12 cm (2011): 650
- Maximum tree age: Abies alba 160-170 yr - Picea abies 160-170 yr - Fagus sylvatica 160-170 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/lausanne.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

educ

en: Education, culture and sport

en: LWF Lausanne long-term research site


radar-wind-profiler-davos-wolfgang

maintainer: Maxim Hervo

title_for_slug: radar-wind-profiler-davos-wolfgang

en: wolfgangpass wind-speed radar wind-direction raclets

en: Radar Wind Profiler Data

en: A Vaisala Lap3000 was installed at Davos Wolfgang to record wind profiles. The time format is number of days fom January 0, 0000 in UTC with a 10 minute resolution.

en: The RADAR wind profiler from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 2171 m above sea level to 11079 m, with a temporal resolution of 10 minutes.

raclets

display_name: raclets

radar

display_name: radar

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wolfgangpass

display_name: wolfgangpass

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: RADAR Wind profiler Davos Wolfgang


en: cone seed seminivorous spruce picea conophagous-insects

en: See ReadMe

en: In 1989 a nation-wide survey on spruce seed and cone insects was carried out at 29 locations distributed across the 5 main geographic regions of Switzerland. The cones were incubated in a controlled environment chamber and the emerging insects were collected and identified. The cones were kept for three years to allow diapausing insects to emerge. The methods are described in more detail in the corresponding publications.

cone

display_name: cone

conophagous-insects

display_name: conophagous-insects

picea

display_name: picea

seed

display_name: seed

seminivorous

display_name: seminivorous

spruce

display_name: spruce

en: Survey of spruce seed and cone insects in Switzerland


en: tree-ring-width long-term-forest-ecosystem-research dendrochronology icp-forests dominant-trees swiss-forest-lab stable-isotopes

en: Data Request

en:
Two stem core samples of 10 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 10 pre-dominant or dominant trees.

 Purpose:

N and C stable isotope signals

 Paper Citation:

 * Tomlinson, G., Siegwolf, R.T.W., Buchmann, N., Schleppi, P., Waldner, P., Weber, P., 2014. The mobility of nitrogen across tree-rings of Norway spruce (Picea abies L.) and the effect of extraction method on tree-ring d15N and d13C values. Rapid Commun. Mass Spectrom. 28, 1258-1264.

dendrochronology

display_name: dendrochronology

dominant-trees

display_name: dominant-trees

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stable-isotopes

display_name: stable-isotopes

swiss-forest-lab

display_name: swiss-forest-lab

tree-ring-width

display_name: tree-ring-width

en: Dendrochronological analyses of tree core samples (IsoN) adjacent to LWF sites


en: rainfall-thresholds random-forest debris-flow python illgraben landslide

en: Threshold code and example data

en: .zip file with code and example data. See the README.md for how to use it.

en:
This is the source code to compute rainfall thresholds for debris flows or landslides following Hirschberg et al. (2021).

 How to install and run the example

Pyhton has to be installed to run the codes. To make sure it works correctly, it is easiest to install Anaconda and create an environment with the right packages from the yml-file. To this end, in a command-line interpreter, change the working directory to where you saved this project and run the following:

`$ conda env create -f environment.yml`

`$ conda activate thresholds` or `$ source activate thresholds`

To run an example:

`$ python run_example()`

It will save a dat-file and a figure as Fig. 7 in Hirschberg et al. (2021), where more information can be found.

 License
GNU General Public License v3.0

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

landslide

display_name: landslide

python

display_name: python

rainfall-thresholds

display_name: rainfall-thresholds

random-forest

display_name: random-forest

educ

en: Education, culture and sport

en: Source code for: Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment


en: butterflies infospecies switzerland insects elevation biogeographical-region insect-decline occupancy-models

en: Mean annual occupancy estimates

en:
This file contains mean annual occupancy for all 390 species, study years (1970/1980-2020) and study regions (9 bioclimatic zones) as estimated from occupancy-detection models (MCMC: 4 chains, 1000 warmup each, 1000 sampling each). Each row corresponds to a unique combination of species, year and zone. The following columns are included:

-  **species**: Species name used in analyses

-  **year**: Year of the observation

-  **biogeo_elevation**: Bioclimatic zone of the observation, which is a combination of 5 biogeographic regions (Jura, Plateau, Nothern Alps, Central Alps, Southern Alps) and 2 elevational classes (high: above 1000 m. asl, low: below 1000 m. asl)

-  **n_squares**: Number of 1 km x 1 km squares of the respective zone, which were included in the analyses

-  **occ_m\_i[....]**: Mean annual occupancy estimates. Each column corresponds to one iteration of the MCMC sampling (4000 columns in total).

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

**Paper Citation**:

Neff, F., Korner-Nievergelt, F., Rey, E., Albrecht, M., Bollmann, K., Cahenzli, F., Chittaro, Y., Gossner, M. M., Martínez-Núñez, C., Meier, E. S., Monnerat, C., Moretti, M., Roth, T., Herzog, F., Knop, E. 2022. Different roles of concurring climate and regional land-use changes in past 40 years' insect trends. Nature Communications, DOI: [10.1038/s41467-022-35223-3](https://doi.org/10.1038/s41467-022-35223-3)

Please cite this paper together with the citation for the datafile. Please also refer to this publication for details on the methods.

 Summary

Mean annual occupancy estimates for 390 insect species (215 butterflies [Papilionoidea, incl. Zygaenidae moths], 103 grasshoppers [Orthoptera], 72 dragonflies [Odonata]) for nine bioclimatic zones in Switzerland. Covers the years 1970-2020 (for butterflies) and 1980-2020 (for grasshoppers and dragonflies). Mean occupancy denotes the average number of 1 km x 1 km squares in a zone occupied by the focal species. Occupancy estimates stem from occupancy-detection models run with species records data hosted and curated by [info fauna](http://www.infofauna.ch). Data on the level of single MCMC iterations of model fitting are included (4000 sampling iterations). The nine bioclimatic zones were defined based on biogeographic regions and two elevation classes (square above or below 1000 m. asl)

biogeographical-region

display_name: biogeographical-region

butterflies

display_name: butterflies

elevation

display_name: elevation

infospecies

display_name: infospecies

insect-decline

display_name: insect-decline

insects

display_name: insects

occupancy-models

display_name: occupancy-models

switzerland

display_name: switzerland

envidat

en: EnviDat: the Environmental Data Portal

en: Mean insect occupancy 1970–2020


en: sustainable-economy bioeconomy forest-clearances atree green-economy circular-economy

en:
The data consistes of three colums as described below and the rows contain all the forest clearance requests and decisions between 2001 and 2017:

First column

The ID of the forest clearance request, which is also contained in the related dataset available from FOEN

Second column

The sustainable economy content class of a forest clearance request: G = green economy, C = circular economy, GB = green and bioeconomy, GC = green and circular economy, GCB = green and circular bioeconomy. If a cell is empty, the content was not codable as "sustainable economy" related.

Third column

The type of infrastructure project: if based on the description of the forest clearnce request it was necessary to change the field "type of infrastructure", so the clearance could be attributed to the correct class, this is indicated in this third column.

en: The Federal Office for the Environment (FOEN) is responsible for granting exemptions for forest clearances that in principle are prohibited in Switzerland. Initiators of infrastructure projects have to submit an examption approval request to the cantonal forest administration which has to inform the FOEN. The FOEN thus administers a dataset of forest clearance requests and approval decisions that can be requested there. This dataset contains information on a coding of the content of all the forest clearance requests between 2001 and 2017, that elicits whether the reason for the clearance can be attributed to "sustainable economy" objectives such as "green economy", "bioeconomy" and "circular economy".

atree

display_name: atree

bioeconomy

display_name: bioeconomy

circular-economy

display_name: circular-economy

forest-clearances

display_name: forest-clearances

green-economy

display_name: green-economy

sustainable-economy

display_name: sustainable-economy

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: Content coding of exemption approval decisions for forest clearances


maintainer: M. Carol Resch

en: long-term-experiment vegetation diversity restoration grassland topsoil-removal nematodes

en: Nematode families

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-41: Nematode abundance (individuals per 100g dry soil) per family; nomenclature according to Bongers 1988

format: XLS

en: Coordinates of one research plot were wrong. This was corrected in the current version of the file.

en: Plant community composition (plant species)

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-252: Plant abundance per species (in total 252 plant species) expressed as cover percentage estimation according to van der Maarel (vdM 1979; 7 classes: 1-7); nomenclature according to Lauber & Wagner (1996)

en: Nemadotes and vegetation

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

X: X-Coordinate

Y: Y-Coordinate

Ri.veg: Total number of plant species

Div.veg: Shannon diversity of plant species

Ri.nem: Total number of nematode families

Div.nem: Shannon diversity of nematode families

abund: Total nematode abundance (individuals per 100g dry soil)

MI: Maturity index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI: Plant parasite index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI.MI: Plant parasite to Maturity index according to Bongers, van der Meulen, & Korthals 1997; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

CI: Channel index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

EI: Enrichment index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

SI: Structure index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

He.a: Herbivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.Ca.a	Sum of omnivorous and carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014
CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001

CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001

CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP3-5.a: Sum of C-P3, C-P4 and C-P5 nematode abundance (individuals per 100g dry soil) equivalent to structure indicators according to Ferris, Bongers, & de Goede 2001

protect.sp.pro: plant species categorized into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002)

tar.sp: Number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species)

Indi.moist: Plant indicator values for soil moisture according to Landolt et al. 2010

Indi.nutri: Plant indicator values for soil nutrients according to Landolt et al. 2010

Management: level of mowing and manuring frequency (35-40 kg N ha-1 application-1); intensity1 = mowing once and no manure; intensity2 = 2-3 times mowing and no manure; intensity3 = 2-3 times mowing and manuring; intensity4 = 4-5 times mowing and manuring

Tillage: last time of tillage

Land.use.history: for Initial plots = recent agricultural use; for all restored sites = agricultural use before restoration
Mowing	earliest date of biomass harvesting (excluding “Initial”) based on contracts between farmers and the Nature Protection Agency of Zurich

Soil.type: based on soil mapping survey 1991 (before restoration)

Soil.texture: determined by the sediment method (Gee & Bauder 1986) and classified into soil textural classes according to FAO (1990)

pH: soil pH (CaCl2)

Slope: slope gradient classes according to FAO (1990; %)

en: Nematode colonizer-persister classes

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001
CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001
CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

en: Nematode feeding types

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

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

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

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

 Methods
 Study area and experimental settings
The study was conducted in a nature reserve (Eigental: 47° 27’ to 47° 29’ N, 8° 37’ E, 461 to 507 m a.s.l.) that is located on the Swiss Central plateau close to Zurich airport (Canton Zurich, Switzerland). The mean annual temperature in this area ranges from 8.9 to 10.6 °C, mean annual precipitation from 910 to 1260 mm [10-year average (2007-2017); MeteoSchweiz, 2018]. The main soil types are calcaric to gleyic Cambisol and Gleysols. The reserve was established in 1967 to protect small remnants of oligotrophic semi-natural grasslands (roughly 12 ha). The plant community can be characterized as Molinion and Mesobromion (semi-wet to semi-dry), depending on the site-specific groundwater level and slope inclination (Delarze, Gonseth, Eggenberg, & Vust, 2015). These remnants represent species-rich islands in an otherwise intensively managed agricultural landscape. Semi-natural grasslands covered an area of 60,000 ha in the Canton Zurich in 1939, however, by 2005 only roughly 600 ha remained (Baudirektion Kanton Zürich, 2007). In 1990, the government of Canton Zurich decided to enlarge the nature reserve Eigental. The goal was to incorporate eleven patches of 20 ha adjacent intensively farmed land and transform these patches into semi-natural grasslands. The patches had a different agricultural history, ranging from permanent (no tillage for >50 years) to temporary grassland (as part of crop rotation; last tillage <5 years). On all freshly integrated patches fertilization was stopped in 1992 and from then on biomass was harvested three times a year and removed. After 5 years without noticeable effects on vegetation composition, the Nature Conservation Agency of Canton Zurich decided to increase the restoration efforts. In 1995, a large-scale experiment was initialized to evaluate if certain treatments can facilitate restoration within a reasonable timeframe of 5 to 10 years after treatment implementation.
The three restoration treatments used were:
i. “Harvest only”: Plots are being mowed two to three times a year and the biomass is removed.
ii. “Topsoil”: Topsoil was removed to a depth of 10 to 20 cm, depending on the depth of the O and A horizon, in four randomly selected areas within each of the eleven patches in late autumn 1995. The size of each topsoil removal area depended on individual patch size and was between 2700 and 7000 m2.
iii. “Topsoil+Propagules”: Propagules from target vegetation were added on half of the area where topsoil was removed, using fresh, seed-containing hay originating from a mixture of semi-dry to semi-wet species-rich grasslands of local provenance (within a radius of 7 km). Hay applications were conducted twice in 1995 and 1996. Repeated applications were chosen to account for the low quantity of available plant material per transfer, since area ratio between receptor and donor sites was roughly 1:1. In addition, hand-collected propagules from 15 selected target species of regional provenance (within a radius of 30 km) were equally applied in 1996 and 1997.
“Topsoil” and “Topsoil+Propagules” plots are mowed once a year, and the biomass is removed. Mowing on these plots started five years after the treatment was implemented.
Eleven permanent plots of 5 m x 5 m were randomly established in each treatment to monitor the vegetation development. The experiment was complemented with 11 control plots that represent the initial state of intensively managed grasslands, further referred to as “Initial”, and 11 control plots that represent the targeted state of donor sites for “Topsoil+Propagules”, further referred to as “Target”. Consequently, the experiment consists of 55 plots (5 treatments x 11 replicates). Management of intensively used grasslands includes mowing and fertilizing (manure) between two to five times a year, as well as different tillage regimes (no tillage for >50 years; last time of tillage <5 years).

 Nematode and plant sampling
Soil nematodes were sampled in 2 m x 2 m plots, randomly established at least 2 m away from the vegetation plots. We collected eight soil cores with a 2.2 cm diameter soil core sampler (Giddings Machine Company, Windsor, CO, USA) to a depth of 12 cm (representing the majority of the plant rooting system) in each plot at the beginning of July 2017. The eight cores within each replicate plot were combined, gently homogenized, placed in coolers and transported to the laboratory of NIOO in Wageningen, the Netherlands, within one week. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink, 1960) and concentrated, resulting in 6 mL nematode solution. The nematode solution was subdivided into three subsamples, two for morphological identification and quantification, and one for molecular work (not used in this study). For morphological identification and quantification, nematodes were heat-killed at 90 °C and fixed in 4 % formaldehyde solution (final volume 10 mL per subsample). All nematodes in 1 mL of formaldehyde solution were counted, and a minimum of 150 individuals per 1 mL sample (or all if less nematodes were present) were identified to family level using Bongers (1988). We then extrapolated the numbers of each nematode taxa identified to the entire sample and expressed them per 100 g dry soil for further analyses.
We calculated number of nematode taxa and Shannon diversity and assessed nematode community composition. In addition, we classified the nematode taxa into feeding types (herbivores, bacterivores, fungivores, omni-carnivores), structural and functional guilds (Table S4). Structural guilds assign nematode taxa according to life-history traits into five colonizer-persister (C-P) classes, ranging from one (early colonizers of new resources) to five (persisters in undisturbed habitats; Bongers 1990). C-P classes can be categorized as indicators for nutrient-enriched (C-P1), stressed (C-P2) and structured (C-P3 + C-P4 + C-P5) soil conditions (Ferris, Bongers, & de Goede, 2001). Functional guilds assign nematode taxa according to their C-P classification combined with their feeding habits (Ferris, Bongers, & de Goede, 2001). Based on the structural and functional guild classification we calculated five additional indices to assess soil nutrient status, disturbance and food web characteristics using NINJA (Sieriebriennikov, Ferris, & de Goede, 2014). 1) The Maturity index indicates the degree of different environmental perturbations (e.g., tillage, nutrient enrichment, pollution) and is used to monitor colonization and subsequent succession after disturbances (Bongers, 1990). 2) The ratio between the Plant Parasite (C-P of herbivorous nematodes only) to Maturity index is used to monitor the recovery of disturbed habitats incorporating information of life-history traits for all feeding types (Bongers, van der Meulen, & Korthals, 1997). 3) The Enrichment index indicates nutrient-enriched soils and agricultural management practices (Ferris, Bongers, & de Goede, 2001). 4) The Structure index provides information about the succession stage of the soil food web and therefore correlates with the degree of maturity of an ecosystem (Ferris, Bongers, & de Goede, 2001). 5) The Channel index provides information about the predominant decomposition pathways, where higher values stand for a higher proportion of energy transformed through the slow fungal decomposition channel (Ferris, Bongers, & de Goede, 2001). In addition, the Structure and Enrichment indices can be displayed in a biplot where nematode assemblages are plotted along a structure (x-axis) and enrichment (y-axis) trajectory (increasing index values). Each biplot quadrat reflects different levels of disturbance, soil nutrient pools and decomposition pathways (Ferris, Bongers, & de Goede, 2001).
The plant surveys were conducted on the 25 m2 permanent plots in June 2017. Plant species cover was visually assessed according to the semi-quantitative cover-abundance scale of Braun-Blanquet (1964; nomenclature: Lauber & Wagner, 1996). We calculated number of species and Shannon diversity, and assessed plant community composition. We also counted the number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species) and categorized plant species into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002). Furthermore, we calculated indicator values for soil moisture and soil nutrients for each species according to Landolt et al. (2010).

 References
Baudirektion Kanton Zürich (2007). 10 Jahre Naturschutz-Gesamtkonzept für den Kanton Zürich 1995-2005 – Stand der Umsetzung. Zürich: Baudirektion Kanton Zürich.
Bongers, T. (1988). De nematoden van Nederland. Utrecht: Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging.
Bongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia, 83, 14-19. doi:10.1007/BF00324627
Bongers, T., van der Meulen, H., & Korthals, G. (1997). Inverse relationship between the nematode maturity index and plant parasite index under enriched nutrient conditions. Applied Soil Ecology, 6, 195-199. doi:10.1016/S0929-1393(96)00136-9
Braun-Blanquet, J. (1964). Pflanzensoziologie, Grundzüge der Vegetationskunde (3rd ed.). Wien: Springer.
Delarze, R., Gonseth, Y., Eggenberg, S., & Vust, M. (2015). Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten (3rd ed.). Bern: Ott.
Ferris, H., Bongers, T., & de Goede, R.G.M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 13-29. doi:10.1016/S0929-1393(01)00152-4
Landolt, E., Bäumler, B., Erhardt, A., Hegg, O., Klötzli, F., Lämmler, W., … Wohlgemuth, T. (2010). Flora indicativa. Ecological indicator values and biological attributes of the Flora of Switzerland and the Alps (2nd ed.). Bern: Haupt.
Lauber, K., & Wagner, G. (1996). Flora Helvetica. Flora der Schweiz. Bern: Haupt.
MeteoSchweiz (2018). Klimabulletin Jahr 2017, Zürich: MeteoSchweiz.
Moser, D., Gygax, A., Bäumler, B., Wyler, N., & Palese, R. (2002) Rote Liste der gefährteten Farn- und Blütenpflanzen der Schweiz. Bern: BUWAL.
Oostenbrink, M. (1960). Estimating nematode populations by some selected methods. In N.J. Sasser & W.R. Jenkins (Eds.), Nematology (pp. 85-101). Chapel Hill: University of North Carolina Press.
Sieriebriennikov, B., Ferris, H., & de Goede, R.G.M (2014). NINJA: An automated calculation system for nematode-based biological monitoring. European Journal of Soil Biology, 61, 90-93. doi:10.1016/j.ejsobi.2014.02.004

diversity

display_name: diversity

grassland

display_name: grassland

long-term-experiment

display_name: long-term-experiment

nematodes

display_name: nematodes

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

vegetation

display_name: vegetation

en: Grassland restoration: nematodes and plant communities


stand-density-sdi

title_for_slug: stand-density-sdi

en:
The Stand Density Index (SDI) is a general measure for the density of a stocking and is based on the number of stems/ha and the average diameter of the tally trees on the sample plot.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

economic-region

display_name: economic-region

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

stand-density-sdi

display_name: stand-density-sdi

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Stand density (SDI)


lwf-chironico-long-term-research-site

title_for_slug: lwf-chironico-long-term-research-site

en: meteorological-data infrastructure forest lwf meteorological-measurements plot swiss-forest-lab

en: Chironico Meteorological Data LWF

en: LWF plot Chironico. Photo: Anne Thimonier Rickenmann, 2019

en:
![alt text](https://www.envidat.ch/dataset/67e14643-c7f2-4190-ae6e-c8c94f1c5f01/resource/1d23d53f-8572-47eb-b466-88dd8ad244c9/download/lwf_chironico.jpg "LWF Chironico")

LWF Plot Chironico

- Community: Chironico / canton TI
- Date of installation: 29 August 1995
- Size of the plot: 2 ha
- Altitude: 1342-1387 m
- Mean slope: 35%
- Geology (in German): Untergrund: Penninikum; Paragneisse u. Glimmerschiefer - Oberfläche: Quartär; karbonatfreie Moräne, Hängeschutt
- Provisional soil type (WSL) : Distric Cambisol
- Woodland association after EK72: 47: Calamagrostio villosae-Abietetum
- Main tree species: Picea abies
- Management system: high forest
- Silvicultural system: group selection
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 54.1 cm
- Number of trees BHD >= 12 cm (2011): 750
- Maximum tree age: Picea abies: 160-180 yr - Abies alba: 140-160 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/chironico.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

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: LWF Chironico long-term research site


area-of-shrub-forest

title_for_slug: area-of-shrub-forest

en:
All plots classified as shrub forest according to the NFI forest definition.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-shrub-forest

display_name: accessible-shrub-forest

area-of-shrub-forest

display_name: area-of-shrub-forest

shrub-forest

display_name: shrub-forest

type-of-shrub-forest-aerial-photo

display_name: type-of-shrub-forest-aerial-photo

en: Area of shrub forest


en: transition biodiversity enabling-factors hindering-factors forest landscape natural-hazards

en: ANEZET Interview Transcriptions

en: Transcriptions of the interviews with experts in the fields of biodiversity, forests, landscape and natural hazards

en:
We have analysed past transformations in Switzerland in four environmental domains, with the aim to
draw conclusions for current challenges, such as the net‐zero transformation. The data comprise transcripts of interviews with experts in the field of biodiversity, forests, landscape and natural hazard research.

biodiversity

display_name: biodiversity

enabling-factors

display_name: enabling-factors

hindering-factors

display_name: hindering-factors

landscape

display_name: landscape

natural-hazards

display_name: natural-hazards

transition

display_name: transition

en: ANEZET: Analysing Net-Zero Transformations


en: spatial-planning land-use-change digital-zoning-plans land-use-transformations land-use-simulations

en: Legend simulated maps

en:
Table of Content: 1. General context of the data set "LUSzoning”; 2. Background and aims of the study using the data set LUSzoning; 3. The data set LUSzoning.
1. General context of the data set "LUSzoning".
The data set "LUSzoning" stands for Land-use simulations integrating zoning regulations in Spanish functional urban areas. The data set has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2021. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, digital zoning plans) into quantitative land-change modelling approaches at the urban regional level.
2.	Background and aims of the study using the data set “LUSzoning”.
As part of the CONCUR project, a specific task was to integrate planning spatial policies in land-change modelling. Planning can be implemented in modelling using either hard or gradual restrictions. Different studies have addressed the inclusion of spatial planning policies in land-use change modelling. However, the integration of zoning constraints is generally established as hard or Boolean-based restrictions (e.g., whether urban development is allowed or not), while not accounting for the spatial heterogeneity or gradual characteristics within planning zones (e.g., whether planning regulations allow low, medium or high urban density), though these could improve real patterns simulations in urban areas. We assume Spanish General Zoning plans were suitable to explore the integration of planning into land-change modelling as soft constrains because they define land-use intensities in the buildable zoning areas. In light of the above considerations, the overall aim of the study was to model urban land-use changes using a multi-scenario approach that integrates digitized zoning plans for the Functional Urban Areas (FUAs) of Madrid, Barcelona, Valencia, and Zaragoza. The following specific objectives were addressed: i) to analyse the role of planning by defining three future scenarios that integrate digitized zoning plans and one scenario that assumes almost no planning intervention; ii) to introduce zoning constraints that reflect different degrees of urban densities; iii) to generate a transferable spatially-explicit modelling framework to integrate planning into land-use change simulations.
Four future land-use demands scenarios were defined for the FUAs. Storylines were created considering probable development scenarios related to zoning plans, current Spanish legislation and sustainability goals defined along two axes: a high market-oriented vs. high planning-intervention axis, and an axis of short-term economic growth vs. long-term sustainable growth. The sustainable development scenario (S1) is characterized by low gross floor area (GFA) growth that is limited to areas that are currently under development according to zoning plans. The business-as-usual scenario (S2) is characterized by medium GFA growth in the range of on-going trends. The strong development scenario (S3) is characterized by high GFA growth rates. Growth is restricted to buildable areas without urbanization project designated in zoning plans. The unrestricted development scenario (S4) prioritizes a high degree of market liberalization characterized by high GFA growth that surpasses population demands. S4 follows a rapid economic growth pattern with almost no planning intervention.
3.	 The data set “LUSzoning”.
The dataset includes 16 .asc raster layers providing the simulated land-uses under four defined scenarios for Barcelona, Madrid, Valencia and Zaragoza Functional Urban Areas (FUAs) for 2030. The simulated raster layers were created using CLUMondo simulation framework and have a spatial resolution of 30m. The .asc layers name include the name of the FUA and scenario number. For example, the output from simulating the urban growth for the city of Zaragoza under Scenario 2 is named “Zaragoza_S2.tif”. Furthermore, a .txt file named “Legend.txt” includes the numeric value of the land-use and the category of land-use that represents to interpret the .asc raster layers. The name of the land-use classes is a reclassification of the Urban Atlas 2012 land-use classes within the four Spanish FUAs analyzed.

digital-zoning-plans

display_name: digital-zoning-plans

land-use-change

display_name: land-use-change

land-use-simulations

display_name: land-use-simulations

land-use-transformations

display_name: land-use-transformations

spatial-planning

display_name: spatial-planning

en: LUSzoning: Land-use simulations integrating zoning regulations in Spanish functional urban areas


maintainer: Nander Wever

en: precipitation-amount snow-ice-temperature wind-speed shortwave-radiation snow-depth longwave-radiation wind-direction humidity air-temperature

en: Version 4

en:
Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: SNOWPACK sno file

en: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: SNOWPACK ini file (new syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en: Version 7 (current)

en:
Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en: Version 5

en:
Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 3

en:
Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en: Version 1

en:
Deprecated version. Release notes:

First release of dataset.

en: Undercatch correction

en: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

en: Version 6

en:
Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en: Version 2

en:
Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en: SNOWPACK ini file (old syntax)

en: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en: All versions

en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.

Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland


maintainer: Andrin Caviezel

en: rockfall-experiments deposition-points stonenodedata dem natural-hazards rockfall-runout sensor-stream induced-rockfall stonenode rockfall

en: StoneNode v1.0 Data for equipped experimental Runs.

en: Corresponding StoneNode v1.0 data streams belonging to the deposition points.

en: Induced Rockfall Data, Tschamut, GR

en:
 Induced Rockfall Experimental Data, Tschamut, GR, Switzerland

The archive contains site specific geographical data as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally availabe are the StoneNode v1.0 sensor streams for the equipped rocks.

The _OverviewFigures_ file serves as quick representation of the included data. It also contains the overview table for the rock masses in order to set the dimensions accordingly in RAMMS::ROCKFALL.

The archive contains the following folders:
<\ul>
* DEM: ArcGIS compatible DEM Tschamut_DEM_2m (grid resolution of 2 m) as well as the .asc grid used in RAMMS::ROCKFALL simulations
* _DepositionPoints_: containing two folders _RF Tschamut Frozen_ and _RF Tschamut WET_ containing each a shapefile with the complete deposition data of each series as well as deposition shapfiles for each rock shape.
* _DigitizedRocks_: Digitized point clouds of the used rocks as used for RAMMS::ROCKFALL simulations (.pts files) (dimensions have to be checked).
* _Orthofoto_: Orthophoto of the experimental site obtained via UAV with 5 cm resolution.

en:
 Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland.

The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of

* Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground)
* Digital Elevation Model (grid resolution 2 m) obtained via UAV
* Orthophoto (5 cm resolution) obtained via UAV
* Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL)
* StoneNode v1.0 raw data stream for equipped rocks.

Further information is found in

* A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/
* P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata

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: Induced Rockfall Dataset (Small Rock Experimental Campaign), Tschamut, Grisons, Switzerland


title_for_slug: twig-mass-of-live-trees

en:
Dry weight (mass) of branches with a diameter under 7 cm from living trees and shrubs starting at 12cm dbh.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

twig-mass-of-live-trees

display_name: twig-mass-of-live-trees

en: Twig mass of live trees


maintainer: Christian Rixen

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

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: Data Nutrient Addition Stillberg

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

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

fertilization

display_name: fertilization

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


en: governance strategic-plan landscape-principles green-infrastructure plan-evaluation

en: o	Detailed description of all the protocol items used to conduct the analysis and the way each question was coded

en: Coding results

en: o	Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

en:
The present dataset is part of the published scientific paper Hersperger, A.M., Bürgi, M., Wende, W., Bacău, S. and Grădinaru, S.R., 2020. Does landscape play a role in strategic spatial planning of European urban regions?. Landscape and Urban Planning, 194, p.103702.

The goal of this research was to assess the role of landscape in contemporary strategic spatial planning. In order to assess the role of “landscape” in the strategic spatial plans, we focused on how plans took advantage of landscape’s integrative power, how plans are based on knowledge on functioning of landscape systems, and how plans show the contribution of landscapes to human well-being. For each aspect, a number of items (detailed in Table 1 of the paper) were selected to assist the assessment.
This study is based on content analysis of the strategic spatial plans of 18 European urban regions. The strategic spatial plans were retrieved from the planning authorities’ websites. The cases study regions as well as the analyzed strategic spatial plans are presented in Table 2 of the paper.
The authors developed a protocol containing 28 items, out of which 16 were directly derived from information presented in Table 1. As a result, we provide the following outputs:
•	Protocol_items.docx – freely available - Detailed description of all the protocol items used to conduct the analysis.
•	Coding results.xlsx – available on request - Results of the coding procedure. Data were used to create Figures 2, 3, 4, 5, 6 and to qualitatively present the results in the research paper.

governance

display_name: governance

green-infrastructure

display_name: green-infrastructure

landscape-principles

display_name: landscape-principles

plan-evaluation

display_name: plan-evaluation

strategic-plan

display_name: strategic-plan

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Landscape in contemporary strategic spatial plans of European Urban regions


en: advection metamorphism snow stable-water-isotope 18o

en: Read-me

media_type: text/plain

en: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

format: TXT

mimetype: text/plain

en: Data files and read-me

en: raw data and micro-CT data available from contacts

en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope

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: Experiments on stable water isotopes,  snow metamorphism, and advection


en: orographic-precipitation snow-precipitation cosmo-wrf complex-terrain precipitation-variability

en: Snow depth maps over Dischma valley for 26 January 2016 and 9 March 2016 and snow depth differences between the two dates.

en: StationData

en:
The data presented here corresponds to the publication "Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication "The importance of near-surface winter precipitation processes in complex alpine terrain" (Gerber et al., 2018b). The dataset contains:

* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).
* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.
* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (> 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.

For more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).

Publications:

Bühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.

Gerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.

Gerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.

Gerber, F., and Sharma, V.: Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

orographic-precipitation

display_name: orographic-precipitation

precipitation-variability

display_name: precipitation-variability

snow-precipitation

display_name: snow-precipitation

en: DISCHMEX - High-resolution WRF simulations in complex alpine terrain and station measurements


en: snow-failure viscous-deformation acoustic-emissions sintering snow-avalanche snow fiber-bundle-model snow-mechanics

en: fiber-bundle-model-for-snow-failure

en: Data underlying Figures in publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted to "Geophysical Research Letters"

en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.

The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions


maintainer: Esther R. Frei

en: picea-abies treeline g-tree larix-decidua forest swiss-alps stillberg climate-change seedling-recruitment

en: climate data G-TREE experiment, Davos, Switzerland

en: GTREE Website

en:
 Background information
Climate change-induced range expansion of treeline populations depends on their successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules. The Global Treeline Range Expansion Experiment (G-TREE) is a global initiative involving researchers from Europe, North America, Australia and New Zealand (Brown et al., 2013). At 15 alpine and Arctic treeline sites worldwide the mechanisms determining the elevational and latitudinal distribution of tree populations are studied using a standardized experimental approach. In summer 2013, a multifactorial seedling recruitment experiment has been established at the Stillberg ecological treeline research site. The aim of this experiment, is to quantify the effect of multiple abiotic and biotic drivers on emergence, survival, and growth of *Larix decidua* and *Picea abies* seedlings in replicated plots along an elevation gradient with three sites below (1930 m a.s.l.), at (2090 m a.s.l.), and above treeline (2410 m a.s.l.; Frei et al., 2018). All plots have been surveyed annually to count seedlings and to measure their total height. Additional environmental factors, such as soil temperature, have been recorded.

 Experimental design
The Stillberg research area is located in the Eastern Swiss Alps near Davos, Switzerland. The site has been used for several long-term monitoring as well as experimental studies for the last four decades. Our G-TREE experiment consists of a lowest site located in a subalpine Larch-Spruce forest (*Larici-Picetum*) dominated by *Larix decidua* and *Picea abies* (1930 m a.s.l.), a transition zone site dominated by alpine shrubs (2100 m a.s.l.), and an uppermost site in an alpine meadow with some dwarf shrubs (2390 m a.s.l.). The three experimental sites were set up following the standard protocol of the global G-TREE initiative (Brown et al., 2013). In a split-plot design, 20 plots (224 cm × 45 cm) were established at each site, which were randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification (i.e. seeding and scarification, seeding only, scarification only, and full control), resulting in five replications per main treatment combination. Each plot was divided into 16 split-plots (22.5 cm × 28 cm), to which treatment combinations of four additional two-level factors species (larch and spruce), provenance (low- and high-elevation), herbivore exclosure (with and without exclosure), and seeding year (2013, 2014) were randomly assigned, which resulted in a total of 960 split-plots (Details see Frei et al. 2018).

 Data description
All plots have been surveyed annually to count seedlings and to measure their total height. Seedling height was assessed with a hand ruler as the total length from the original emerging point to the apical meristem (Details see Frei et al. 2018). Additionally, soil temperature at each site, has been continuously recorded since 2013. Here, we present data from eight years (2013–2021).

climate-change

display_name: climate-change

forest

display_name: forest

g-tree

display_name: g-tree

larix-decidua

display_name: larix-decidua

picea-abies

display_name: picea-abies

seedling-recruitment

display_name: seedling-recruitment

stillberg

display_name: stillberg

swiss-alps

display_name: swiss-alps

treeline

display_name: treeline

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: G-TREE: Global Treeline Range Expansion Experiment Davos, Switzerland


en: egg-development insect-vectors vitis scaphoideus-titanus grapevine-yellows orientus-ishidae southern-switzerland

en: Primer sequences used for internal control of amplification of the insects (Cytochrome Oxydase I).

en: Table 1. Plot characteristics and results of molecular analysis, trap captures, and total hatchings.

en: Plot characteristics in terms of type of experiment (M = molecular analysis; T = traps for adult insects; H = hatching experiment), coordinates, region, mean slope, distance from nearest vineyard (DV), last year in which plot was registered as vineyard (Last_T); symptomatic expression of Grapevine Yellows (GY); result of molecular analysis for FDp detection on gone-wild grapevines (pos = positive detection with Cq < 35; neg = negative detection); number (nr.) of yellow sticky traps (if applicable) and Scaphoideus titanus and Orientus ishidae captures per single trap; absolute (N) and specific (N / kg wood) hatching events of S. titanus and O. ishidae per plot.

en: Table 2. Embryonic development time.

en: Embryonic development time expressed as degree-days and days for gone-wild grapevines (GWGV) and the control. N = number of hatched nymphs; EDdd_min and EDdd_max = degree-days accumulated at the first and last hatching, respectively; EDdd_mean = mean accumulated degree-days; DDA = degree-days accumulated between first and last hatching; EDt_min and EDt_max = minimal and maximal time (days) of embryonic development, respectively; EDt_mean = mean time (days) of embryonic development; SE = standard error; HD = hatching period duration in days.

en: Nymph hatching raw data.

en: Nymph hatching raw data used for the inversed Kaplan-Meier.

en: Results of molecular analysis on sampled leaf material.

en:
Dataset used to test the potential role of gone-wild grapevines (GWGV) in forests of Southern Switzerland as a source of Flavescence dorée phytoplasma (FDp) inoculum and as a habitat for its main and alternative vectors, Scaphoideus titanus and Orientus ishidae. In the first phase, GWGV were located and sampled to test their FDp status. In addition, a set of chromotropic traps were placed to monitor the presence and abundance of FDp vectors. In the second phase, wood from GWGV in forests was collected and placed in cages to test the potential oviposition activity by FDp vectors.
The results showed that GWGV in forests are a reservoir of FDp and that they can sustain the whole life cycle of both S.titanus and O.ishidae. Eventually, the need to adapt the current FD management strategies are highlighted.

egg-development

display_name: egg-development

grapevine-yellows

display_name: grapevine-yellows

insect-vectors

display_name: insect-vectors

orientus-ishidae

display_name: orientus-ishidae

scaphoideus-titanus

display_name: scaphoideus-titanus

southern-switzerland

display_name: southern-switzerland

vitis

display_name: vitis

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: Gone-wild grapevines in forests may act as a potential habitat for “Flavescence dorée” phytoplasma vectors and inoculum


maintainer: Océane Hames

en: mosaic arctic-sea-ice openfoam snow-deposition snow-transport

en: snowBedFoam 1.0.

en:
OpenFOAM-2.3.0. scripts containing the implemented Eulerian-Lagrangian snow transport model.

The code file provided here is not updated. The most recent version of the script can be found on the WSL/SLF GitLab repository: https://gitlabext.wsl.ch/atmospheric-models/snowbedfoam-v1-0.git

en: Paper Draft

en: This is the initial draft of the paper where the snowBedFoam 1.0. results are tested against Terrestrial Laser Scan (TLS) measurements of snow dynamics on Arctic sea ice (MOSAiC expedition). It highlights the numerical limitations of our model as well as the measurement uncertainties, which may occur in such extreme environments.

en: MOSAiC Met City preliminary (Level 2) wind data

en:
Extract from the preliminary MOSAiC atmospheric data (Level 2) for the time period 6th to 13th of November, 2019.
This data was used to set up the fluid forcing parameters in the snowBedFoam simulations on MOSAiC sea ice. It is being published in this repository with the kind permission from Matthew Shupe and his team.
The final processed and quality controlled version of this dataset (Level 3) has not been published yet. A complete reference will be added in this description once it is released.

en:
snowBedFoam 1.0. is a snow transport solver implemented in the Computational Fluid Dynamics (CFD) software OpenFOAM. It is adapted from the standard multi-phase flow solver DPMFoam for application in snow-influenced environments.

To simulate aeolian snow transport, snowBedFoam 1.0. handles coupled Eulerian–Lagrangian phases, which involve a finite number of particles (snow) spread in a continuous phase (air). The snow erosion and deposition are modelled through physically-based equations such as the ones employed in the well-established LES-Lagrangian Stochastic Model (Comola and Lehning, 2017 ; Sharma et al., 2018). This modelling approach is computationally intensive and thus adapted to simulate snow movement and distribution on small scale terrain.

snowBedFoam 1.0. was tested against topographical data collected on Arctic sea ice during the MOSAiC expedition (Clemens-Sewall, 2021) . Together with atmospheric data from the MOSAiC Met City (Shupe et al., 2021) used for the fluid forcing, the model was able to accurately simulate the zones of erosion and deposition of snow along a complex ice ridge structure.

The core code of snowBedFoam 1.0. is also accessible on the WSL/SLF GitLab repository (more details in the Resources section).

arctic-sea-ice

display_name: arctic-sea-ice

mosaic

display_name: mosaic

openfoam

display_name: openfoam

snow-deposition

display_name: snow-deposition

snow-transport

display_name: snow-transport

en: snowBedFoam: an OpenFOAM Eulerian-Lagrangian solver for modelling snow transport


en: biogas mfa sfa circular-economy efa

en: Agricultural biogas plants in the circular economy - supplementary material

en:
This excel file contains:
-The summary of all values used for the inputs biomass characterisitcs based on literature.
-All input data for the flow analysis preformed with the programme STAN.
-Results tables

en:
Supplementary material for the publication " Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G.

Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions.

biogas

display_name: biogas

circular-economy

display_name: circular-economy

efa

display_name: efa

mfa

display_name: mfa

sfa

display_name: sfa

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using substance and energy flow analysis


en: swiss-forest-lab meteorological-measurements lwf forest infrastructure meteorological-data plot

en: Nationalpark Meteorological Data LWF

en: LWF plot Nationalpark. Photo: Oliver Schramm, 2011

en:
![alt text](https://www.envidat.ch/dataset/4a0ff376-83d2-4ae4-bf2e-c361eb050778/resource/51e98f2d-5524-4ea6-babb-9df0b9aba8f1/download/lwf_nationalpark.jpg "LWF Nationalpark")

LWF Plot Nationalpark

- Community: Zernez / canton GR
- Date of installation: 10 October 1995
- Size of the plot: 2 ha
- Altitude: 1890-1907 m
- Mean slope: 11%
- Geology (in German): Nacheiszeitlicher Schwemmfächer; kalkhaltige Moräne, Dolomite, Kalke, Tonschiefer, Rauhwacken
- Provisional soil types (WSL): Rendzic Leptosol
- Woodland association after EK72: 67: Erico-Pinetum montanae
- Main tree species: Pinus mugo
- Management system: high forest
- Silvicultural system: forest reserve
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 23.7 cm
- Number of trees BHD >= 12 cm (2011): 2450
- Maximum tree age: Pinus mugo 210 yr

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/nationalpark.html

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

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: LWF Nationalpark long-term research site


maintainer: Amelie Fees

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

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

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


maintainer: Jana von Freyberg

en: ecohydrology root-zone review uncertainties endmember-mixing-models stable-water-isotopes plant-water-uptake

en: Data set of MEE-20-04-264 (CSV)

en: Data set of MEE-20-04-264

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal ‘Methods in Ecology and Evolution’.

en: The following two tables contain information about the data sources of the values reported in Table 1 and 2 in the paper “Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources” published in the journal 'Methods in Ecology and Evolution'.

ecohydrology

display_name: ecohydrology

endmember-mixing-models

display_name: endmember-mixing-models

plant-water-uptake

display_name: plant-water-uptake

review

display_name: review

root-zone

display_name: root-zone

stable-water-isotopes

display_name: stable-water-isotopes

uncertainties

display_name: uncertainties

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Data set of: Plant and root-zone water isotopes are difficult to measure, explain, and predict: some practical recommendations for determining plant water sources