en:
Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport.
A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination.
Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the "helicopter" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based.
Road transport was investigated using network analysis, based on the data set "Forest access roads 2013" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account.
Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the "helicopter" category or transport with trucks under 26 tons).
The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland.
The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php)
Input data used:
- Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016).
- NFI forest mask, 10 m resolution (2015)
- Digital elevation model, 10m resolution (based on swissALTI3D 2016)
- Slope map, 10m resolution (based on swissALTI3D 2016)
- Soil suitability map, 10m resolution (based on soil suitability map BFS 2000)
- Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)

en: wood-extraction forest-accessibility wood-harvesting economic-efficiency forest timber-transport forest-roads switzerland

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: EnviDat: the Environmental Data Portal

en: Accessibility of the Swiss forest for economic wood extraction (2021)

en:
Resource Title: Data Request "Forest Accessibility"
    Size: 23228715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/b1a225d8-9db7-4a62-9d6a-224673f88b01/download/mapguete_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the overall suitability of the Swiss forest for economic wood extraction and transport

format: TIFF

media_type: image/tiff

en:
Resource Title: Data Request "Extraction Method"
    Size: 28660858 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/e57bf80a-9c2b-40d5-8938-5b9dad24549b/download/maperntemethoden_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the most suitable extraction method for wood in the Swiss forest

economic-efficiency

display_name: economic-efficiency

forest

display_name: forest

forest-accessibility

display_name: forest-accessibility

forest-roads

display_name: forest-roads

switzerland

display_name: switzerland

timber-transport

display_name: timber-transport

wood-extraction

display_name: wood-extraction

wood-harvesting

display_name: wood-harvesting


$oid: OBSOLETE

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

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

envidat

approval_status: approved

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

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

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

de: EnviDat: das Umwelt-Datenportal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: WRF_dia1103.zip
    Size: 9126805504 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_dia1103.zip
    Description:

format: ZIP

media_type: application/zip

en:
Resource Title: WRF_luk0912.zip
    Size: 10844792422 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_luk0912.zip
    Description:

en:
Resource Title: WRF_dia2702.zip
    Size: 8482560410 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_dia2702.zip
    Description:

en:
Resource Title: postprocessing.zip
    Size: 4301 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/postprocessing.zip
    Description:

en:
Resource Title: WRF_luk2310.zip
    Size: 9985798963 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.501/WRF_luk2310.zip
    Description:

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

grayzone

display_name: grayzone

numerical-simulation

display_name: numerical-simulation

wrf

display_name: wrf


photogrammetric-drone-data-gruenbodeli

en:
We conducted various drone flights at Grüenbödeli near Davos with the Sony RX1R II mounted on a Wingtra drone during 2020/21/22. The data was processed with the Agisoft Metashape Professional Software.
The following products are available for download:
- DSM 10cm resolution
- Orthomosaic 3cm/25mm resolution
- Snow Raster 10cm resolution
- original RGB images

en: photogrammetry drone-data orthophoto wingtra dsm uav snow-depth-mapping

en: Photogrammetric Drone Data Grüenbödeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra


en: To map and assess snow depth on different dates, 9 flights were conducted in the winter season of 2020/21 at the Latschüelfurgga in Davos. The data was captured with a Sony RX1R II mounted on a Wingtra drone and was processed with the Agisoft Metashape software. High-resolution DSMs, orthomosaics and snow height rasters, as well as the original RGB images from each flight are available.

en: dsm uav snow-depth-mapping photogrammetry drone-data orthophoto wingtra

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: Photogrammetric Drone Data Latschuelfurgga


en: We present forecasts of land-use/land-cover (LULC) change for Switzerland for three time-steps in the 21st century under the representative concentration pathways 4.5 and 8.5, and at 100-m spatial and 14-class thematic resolution. We modelled the spatial suitability for each LULC class with a neural network (NN) using -200 predictors and accounting for climate and policy changes. We used data augmentation to increase performance for underrepresented classes, resulting in an overall quantity disagreement of 0.053 and allocation disagreement of 0.15, which indicate good model performance. These class-specific spatial suitability maps outputted by the NN were then merged in a single LULC map per time-step using the CLUE-S algorithm, accounting for LULC demand for the future and a set of LULC transition rules. As the first LULC forecast for Switzerland at a thematic resolution comparable to available LULC  maps for the past, this product lends itself to applications in land-use planning, resource management, ecological and hydraulic modelling, habitat restoration and conservation.

en: land-use land-cover modelling landscape landscape-change machine-learning

en: EnviDat: the Environmental Data Portal

en: High resolution land use forecasts for Switzerland in the 21st century

en:
Resource Title: Code.zip
    Size: 407530 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/69945cd4-3dfc-4b1d-bdd4-e88cc577c3c9/resource/593cc9c4-deb1-4637-a328-9d68f0e15cd6/download/code.zip
    Description: Code used to produce the Land-use/land-cover forecasts for Switzerland across the 21st century at 100-m resolution.

The script is based on input data which are not included as they are not freely available, therefore it will not run as it is. These input data are described in the accompanying publication on Data Science access to them can be requested to their owners. Alternatively the code can be modified to run on other data.

en:
Resource Title: swiss_lulc_forecast_21th_century.zip
    Size: 16438707 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/69945cd4-3dfc-4b1d-bdd4-e88cc577c3c9/resource/347fffe5-f3cb-4309-914b-9057a30a32db/download/swiss_lulc_forecast_21th_century.zip
    Description: Compressed (.zip) file containing six georeferenced raster files in the GeoTIFF format with embedded coordinate reference system, and a table (comma separated values, .csv) encoding a colour palette for plotting (HEX colour codes for each class). GeoTIFF file names include the time-step and the RCP (e.g. “LULC_2020_2049_RCP45.tiff”). Each raster file has 3484x2207 square pixels (i.e. 7.7 megapixels) and is projected in the Swiss coordinate system CH1903+/LV95 (EPSG:2056).

land-cover

display_name: land-cover

land-use

display_name: land-use

landscape

display_name: landscape

landscape-change

display_name: landscape-change

machine-learning

display_name: machine-learning

modelling

display_name: modelling


en:
snowBedFoam 1.0. is a snow transport solver implemented in the computational fluid dynamics 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 physics-based equations similar to the ones employed in the well-established LES-Lagrangian Stochastic Model (Comola and Lehning, 2017 ; Sharma et al., 2018 ; Melo et al., 2022). This modelling approach is computationally intensive and thus adapted to simulate snow movement and distribution on small scale terrain.
First, snowBedFoam 1.0. was applied to 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 (Hames et al., 2022).
Second, snowBedFoam 1.0. was used to simulate the snow distribution around the German Antarctic research station Neumayer Station III. The effect of snow properties, fluid forcing and aerodynamic structures on the snow accumulation were assessed.
snowBedFoam 1.0 was implemented in 2 different OpenFOAM versions, namely OpenFOAM-2.3.0 and OpenFOAM-5.0. The latter offers more options for turbulence models and boundary conditions. The fundamental model equations were not changed from one implementation to the other, thus both still correspond to snowBedFoam 1.0. The two branches are called snowBedFoam-v1-2.3.0 (OpenFOAM-2.3.0)  and snowBedFoam-v1-5.0 (OpenFOAM-5.0). The core codes of snowBedFoam 1.0. are directly accessible on the WSL/SLF GitLab repository (more details in the Resources section).

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

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

envi

en: Environment

en:
Resource Title: MOSAiC Met City preliminary (Level 2) wind data
    Size: 37737 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/a9b2c876-ac90-4aa5-ab56-a06e82221894/download/mosaic_mettowerdata_level2.zip
    Description: 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:
Resource Title: Snowdrift measurements around Neumayer Station III
    Size: 32270 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/a6d100a5-ab97-41f4-b45a-dbed9fb30619/download/nm3-measurements.zip
    Description: Files containing the topographical data barometrically measured in June 2009 around the German Antarctic Research station Neumayer III. Those measurements are compared to the snowBedFoam simulations to assess the ability of the model to reproduce real snow distribution observations.

en:
Resource Title: Paper Draft
    Size: 3025070 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/0c5b7c6e-afa2-4a08-bb12-351648d1e1f9/download/snowbedfoam_mosaicseaice.pdf
    Description: 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.

format: PDF

media_type: application/pdf

en:
Resource Title: Neumayer III simulations
    Size: 296665509 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/6bce1ab3-5fab-4fe6-afb0-7aa90760e9d2/download/nm3-simulations.zip
    Description: Snow distribution results around Neumayer Station III obtained for the sensitivity analysis and comparison to measurements. The file contains several sub-folders, namely:
-COMP: simulation output for the comparison to measurements;
-FLOW: simulation output for the study of wind forcing impact;
-simulation_exampleCase: example case of a snowBedFoam simulation with the reference Neumayer Station mesh;
-SNOW: simulation output for the study of snow properties impact;
-STRUCT: simulation output for the study of structure properties impact.

en:
Resource Title: snowBedFoam-v1-2.3.0
    Size: 38674582 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/056080d7-e68d-4cb8-9b63-34ebf5998fe7/download/snowbedfoam-v1-0-main.zip
    Description: 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:
Resource Title: snowBedFoam-v1-5.0
    Size: 40167324 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8bdc13ec-e59e-4f08-aa0d-646745fb76a6/resource/87b34f08-3ae1-44d3-bd5a-aa502f8e83c3/download/snowbedfoam-v1-5.0.zip
    Description: OpenFOAM-5.0 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

antarctica

display_name: antarctica

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:
This dataset provides distribution data of lichens in Switzerland of the National Data and Information Centre, called Swiss Lichens. SwissLichens is a partner of InfoSpecies, the network of Swiss data and information centres for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.
The SwissLichens database currently contains more than 120’000 georeferenced lichen observations, distributed throughout Swizerland. The oldest observations date back to 1790. A large portion of the records dtae from the last two decades of the last century to the present day. The database is continuously updated with new findings. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from the literature.
Each record consists of the species name, information of the location (Swiss Coordinates, precision of the coordinates, elevation above sea level, municipality and canton), the date of observation, the ecotype (epiphytic, terricol, lignicol, saxicol), as well as information on the conservation status of the species (red list status, conservation priority status, status in the Nature and Cultural Heritage Act). Information on the ecology (habitat, substrate) is partially available.
They are free of charge for research projects and can be requested from InfoSpecies using a form.
Licence under www.infospecies.ch. Data is free of charge for research projects and available on request.

en: swisslichens lichens lichen-conservation lichen-distribution switzerland national-data-centre biodiversity

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: SwissLichens - Distribution of lichens in Switzerland

format: XLS

biodiversity

display_name: biodiversity

lichen-conservation

display_name: lichen-conservation

lichen-distribution

display_name: lichen-distribution

lichens

display_name: lichens

national-data-centre

display_name: national-data-centre

swisslichens

display_name: swisslichens

switzerland

display_name: switzerland


en:
This dataset contains all data on which the following publication below is based.
Paper Citation:
Frey B., Maurer C., Schneider K. (2023) Informationen zum Boden anhand der Gebundenheit der Rote-Liste Arten BAFU. Bundesamt für Umwelt BAFU. 26 p.
Please cite this paper together with the citation for the datafile.
Soil is the habitat and basis of life for countless creatures. The great importance of soil organisms for the fertility of our soils is widely recognized, but information is sparse on their distribution and possible endangerment in Switzerland. In the present project, target species, i.e. species that are closely linked to the soil, were identified, and for the the first time, information was gathered on the degree of endangerment of the soil ecosystem in Switzerland on the basis of Red List species. For eleven Red List  groups, the species' soil dependency was determined, i.e. whether their life cycle includes stages in or on the soil. The assessment of soil dependency was made using four classes, which enabled the classification not only of insects but also of vertebrates, land snails, lichens and fungi.

en: soil-biodiversity eco-fauna conservation lichens red-list soil-dependency ecosystem-protection soil-quality database fungi soil-organisms fauna info-fauna

envidat

en: EnviDat: the Environmental Data Portal

en: Information on soil based on the soil dependency of the FOEN red list species

en:
Resource Title: percentages_endangerment-categories.xlsx
    Size: 14873 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/a79f2c66-cf27-4427-b7ad-829931cb175a/download/percentages_endangerment-categories.xlsx
    Description: Proportion of endangered species grouped by the four soil dependency classes.

en:
Resource Title: soil_dependency.xlsx
    Size: 1367091 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/73beef16-17c8-46e4-a77b-adc5ec694918/download/soil_dependency.xlsx
    Description: Overview over the soil dependency and endangerment status of different groups of organisms.

en:
Resource Title: raw_data.xlsx
    Size: 422329 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/006ebf36-0cbf-415f-bd0c-0261bc32b1f5/resource/b2f4f53a-4ffa-4a44-8290-0c3c9c6b1a82/download/raw_data.xlsx
    Description: Raw dataset of species and their soil dependency as well as endangerment status.

conservation

display_name: conservation

database

display_name: database

eco-fauna

display_name: eco-fauna

ecosystem-protection

display_name: ecosystem-protection

fauna

display_name: fauna

fungi

display_name: fungi

info-fauna

display_name: info-fauna

red-list

display_name: red-list

soil-biodiversity

display_name: soil-biodiversity

soil-dependency

display_name: soil-dependency

soil-organisms

display_name: soil-organisms

soil-quality

display_name: soil-quality


en:
What are the research data files about:
Raw data on various beech (Fagus sylvatica) leaf traits. Beech leaf chemistry (primary and specialized metabolites), leaf damage measurements from various herbivore feeding guilds and crown health assessment
Which methods were used:
Field surveys on trees that showed either prematured defoliation due to drought-stress or showed not pre-mature defoliation. .
When and where was the data collected/analyzed:
Field data was collected in 2019, 2020
Data was analyzed in 2021-2023

en: drought-legacy herbivory climate-change phytochemistry fagus-sylvatica

en: Legacy effects of premature defoliation in response to an extreme drought event modulate phytochemical profiles with subtle consequences for leaf herbivory in European beech

envi

en: Environment

en:
Resource Title: Specialized_metabolome.xlsx
    Size: 3876111 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/57776282-fb31-43b3-be8a-42c4b8d25c71/resource/f1b46aa1-9647-4371-8c2c-442f78fe8831/download/specialized_metabolome.xlsx
    Description:

en:
Resource Title: Primary_metabolome.xlsx
    Size: 259529 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/57776282-fb31-43b3-be8a-42c4b8d25c71/resource/45798cb9-3888-4e89-8178-0f52330c08a8/download/primary_metabolome.xlsx
    Description:

en:
Resource Title: Overview_chemistry_herbivory.xlsx
    Size: 43689 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/57776282-fb31-43b3-be8a-42c4b8d25c71/resource/6283a18b-69af-4fd1-bbd0-294ee24ec06b/download/overview_chemistry_herbivory.xlsx
    Description:

climate-change

display_name: climate-change

drought-legacy

display_name: drought-legacy

fagus-sylvatica

display_name: fagus-sylvatica

herbivory

display_name: herbivory

phytochemistry

display_name: phytochemistry


en:
Data from a 17-year-long irrigation experiment (Pfynwald, Switzerland) in a naturally dry forest dominated by 100-year-old pine trees (Pinus sylvestris). This dataset includes measure tree-ring width and tree-ring isotope chronologies (stable isotope ratios of non-exchangeable hydrogen δ2H,  oxygen δ18O, and carbon δ13C), for the Pfynwald experiment, including control trees, irrigation and irrigation-stop treatments until the year 2019.
This dataset contains all data on which the following publication below is based.
Please cite this paper together with the citation for the datafile.

en: tree-ring-cellulose tree-rings pfynwald isotopes dendrochronology pinus-sylvestris scots-pine

en: Pfynwald 2019 - Dendrochronological and tree-ring isotope dataset

en:
Resource Title: ChronoData_treeRingWidthIsotopes.csv
    Size: 80920 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/17c0a7f0-d19e-4e18-aaa8-96e9f1a1585c/resource/a64e928b-b690-4a5a-8c26-afcacff9d5bc/download/chronodata_treeringwidthisotopes.csv
    Description:

format: CSV

media_type: text/csv

en:
Resource Title: All_tissues_Isotopes_Pfynwald2019.csv
    Size: 43235 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/17c0a7f0-d19e-4e18-aaa8-96e9f1a1585c/resource/14910e94-cf63-44dc-9539-aabade0801a0/download/all_tissues_isotopes_pfynwald2019.csv
    Description: Isotope measurements of tree-level tissues for the vegetative season 2019.

en:
Resource Title: Read me file.docx
    Size: 14171 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/17c0a7f0-d19e-4e18-aaa8-96e9f1a1585c/resource/90e7d0c0-b205-4c92-bb0b-eb1757fdd755/download/read-me-file.docx
    Description:

en:
Resource Title: ChronoData_treeRingWidthIsotopes.csv
    Size: 80920 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/17c0a7f0-d19e-4e18-aaa8-96e9f1a1585c/resource/fc48bd90-0a2e-4c70-a822-0e93e88ea7ad/download/chronodata_treeringwidthisotopes.csv
    Description:

dendrochronology

display_name: dendrochronology

isotopes

display_name: isotopes

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

scots-pine

display_name: scots-pine

tree-ring-cellulose

display_name: tree-ring-cellulose

tree-rings

display_name: tree-rings


soil-property-maps-for-the-swiss-forest

en:
We used 2071 forest soil profiles to model a wide range of soil properties for the forested area of Switzerland. The spatial prediction is based on the principle of «digital soil mapping». This involves linking soil profiles with soil forming factors using statistical or machine learning methods.
A quantile regression forest (QRF) approach was applied to predict the following soil properties at six depth ranges: clay, gravel, sand, fine earth density, SOC. The depth ranges correspond to the standard depths of the [GlobalSoilMap.Net](https://www.isric.org/) specification: 0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm. In addition, the total soil depth down to a non-root-permeable layer or solid rock soil thick was predicted. To quantify the uncertainty for each predicted pixel, the upper and lower limit of the 90% prediction interval derived from QRF was calculated. More details on the methods and results are described in Baltensweiler et al. 2021 and Baltensweiler et al 2022.
The soil property maps, and the uncertainty maps are provided as a GeoTIFF files at 25 m resolution. The excel file (xlsx) provides a short description of the raster layers.
**The soil and the uncertainty maps can be viewed in a simple web-GIS application available at:**
[www.wsl.ch/soilmaps](https://www.wsl.ch/soilmaps).

en: soil-properties switzerland soil forest soc soil-texture soil-ph dsm soil-depth

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: EnviDat: the Environmental Data Portal

en: Soil property maps for the Swiss forest

title_for_slug: soil-property-maps-for-the-swiss-forest

en:
Resource Title: depth_uncertainty_maps.zip
    Size: 69351779 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/b4dc7b7b-e800-45d4-8d03-997968710b56/download/depth_uncertainty_maps.zip
    Description:

en:
Resource Title: soc_maps.zip
    Size: 144898851 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/d80078ce-cf36-4590-8f01-e79de67f8b2f/download/soc_maps.zip
    Description:

en:
Resource Title: soc_uncertainty_maps.zip
    Size: 222671274 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/a214d4d2-72bd-451d-8fd5-a461b3a78b28/download/soc_uncertainty_maps.zip
    Description:

en:
Resource Title: density_maps.zip
    Size: 172162688 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/d5a87cce-64aa-40db-aa02-589fb89c7984/download/density_maps.zip
    Description:

en:
Resource Title: depth_map.zip
    Size: 37183065 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/7c58ee27-6410-41bc-b533-1c3842032878/download/depth_map.zip
    Description:

en:
Resource Title: pH_maps.zip
    Size: 129172696 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/639353b5-92a5-43d1-b0ec-4ce8ca7773c0/download/ph_maps.zip
    Description:

en:
Resource Title: sand_maps.zip
    Size: 65109556 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/1a2addd8-1b83-4502-b015-43face6c519b/download/sand_maps.zip
    Description:

en:
Resource Title: sand_uncertainty_maps.zip
    Size: 116700070 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/25bdf03f-226b-4274-8867-6553b2c12bd3/download/sand_uncertainty_maps.zip
    Description:

en:
Resource Title: SoilMaps_description.xlsx
    Size: 11429 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/5f08172f-967c-4aa3-beaf-a81338290f9e/download/soilmaps_description.xlsx
    Description:

en:
Resource Title: gravel_maps.zip
    Size: 80316578 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/c799d7c4-ae83-402d-976d-f23ef7021ad7/download/gravel_maps.zip
    Description:

en:
Resource Title: clay_uncertainty_maps.zip
    Size: 105083064 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/1059745c-d83e-4f31-b723-07cce9fb2104/download/clay_uncertainty_maps.zip
    Description:

en:
Resource Title: density_uncertainty_maps.zip
    Size: 143926943 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/5886ee25-bfb6-44a2-97a9-00d5c968d1c9/download/density_uncertainty_maps.zip
    Description:

en:
Resource Title: clay_maps.zip
    Size: 55978125 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/1616b34f-542a-4622-9bdd-e454500393c8/download/clay_maps.zip
    Description:

en:
Resource Title: gravel_uncertainty_maps.zip
    Size: 89436761 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/d7b44437-7fc2-4750-a322-e26887a830c6/download/gravel_uncertainty_maps.zip
    Description:

en:
Resource Title: pH_uncertainty_maps.zip
    Size: 192523204 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/9a0b1daa-a4e0-4c62-b348-ec23354105c6/resource/c5bea000-de46-4b93-8de8-f246c6135b9f/download/ph_uncertainty_maps.zip
    Description:

dsm

display_name: dsm

forest

display_name: forest

soc

display_name: soc

soil

display_name: soil

soil-depth

display_name: soil-depth

soil-ph

display_name: soil-ph

soil-properties

display_name: soil-properties

soil-texture

display_name: soil-texture

switzerland

display_name: switzerland


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: optimization ecosystem-services marxan landscape energy social-acceptance spatial-planning wind-power photovoltaic

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: EnviDat: the Environmental Data Portal

en: Optimizing renewable energy siting in the Swiss landscape

envi

en: Environment

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power


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

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

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

en:
Resource Title: Site Information
    Size: 34729 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/2bde3c93-9309-40e0-964e-d3b4f6f29804/resource/dfe9da2a-1d8e-4342-a4d7-82d5552e25c6/download/site_information.xlsx
    Description: This table contains information about the 254 forest sites used in the publication of Scherrer et al. 2024.

en:
Resource Title: Taxa Data
    Size: 1350953 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/2bde3c93-9309-40e0-964e-d3b4f6f29804/resource/5e5dd383-4a1d-42a0-af8d-4c4aa5fbbbe3/download/species_data.xlsx
    Description: This table contains information about the individual taxa found in the historic and current vegetation relevés in Scherrer et al. 2024.

air-pollution

display_name: air-pollution

climate-change

display_name: climate-change

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

forest-management

display_name: forest-management

ground-vegetation

display_name: ground-vegetation


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

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

en: Teaser videos Swiss landscapes under climate change

en:
Resource Title: Entremon subtitles FR
    Size: 38930364 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/c19ad933-34e0-4184-ba30-eabec0bcdb51/resource/79ff754a-4390-4c71-81a6-482a5b395582/download/entremont_subtitles_fr.mp4
    Description: Scenarios of landscape change under climate change in the Swiss mountains. Trailer in French with subtitles.

en:
Resource Title: Seeland subtitles DE
    Size: 38419246 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/c19ad933-34e0-4184-ba30-eabec0bcdb51/resource/e5b088dc-780e-4244-939d-46b0d7565084/download/seeland_subtitles_de.mp4
    Description: Scenarios of landscape change under climate change in the Swiss lowlands.
Trailer in German with subtitles.

en:
Resource Title: Entremont subtitles DE
    Size: 36993864 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/c19ad933-34e0-4184-ba30-eabec0bcdb51/resource/60dc7982-5b1a-4b8a-a21c-4ecdd4a5bccb/download/entremont_subtitles_de.mp4
    Description: Scenarios of landscape change under climate change in the Swiss mountains.
Trailer in German with written subtitles.

en:
Resource Title: Seeland subtitles FR
    Size: 38467901 bytes
    Format: video/mp4
    URL: https://www.envidat.ch/dataset/c19ad933-34e0-4184-ba30-eabec0bcdb51/resource/23cb4c0e-d84a-4fee-b271-6c267f0f638c/download/seeland_subtitles_fr.mp4
    Description: Scenarios of landscape change under climate change in the Swiss lowlands.
Trailer in French with subtitles.

landscape-change

display_name: landscape-change

policy-action

display_name: policy-action

scenario

display_name: scenario

visualization

display_name: visualization


en:
A rule-based algorithm [(Schwieder et al., 2022)](https://doi.org/10.1016/j.rse.2021.112795) was used to produce annual maps for 2018–2021 of grassland-management events, i.e. mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite time series. All satellite images were processed with the [FORCE](https://force-eo.readthedocs.io) framework.
The resulting maps provide information on the number and timing of grassland-management events at a spatial resolution of 10 m × 10 m for the whole of Switzerland. For the final maps, permanent grasslands were masked using a variety of land-use layers, according to [Huber et al. (2022)](https://doi.org/10.1002/rse2.298) but replacing the crop mask with the agricultural-use data from the cantons.
We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further tested the ecological relevance of the generated intensity measures in relation to nationwide biodiversity data (see [Weber et al., 2023](https://doi.org/10.1002/rse2.372)).
The webcam-based reference data used for verification was subsequently added on 14.02.2024.

en: remote-sensing management grassland land-use mowing use-intensity landsat sentinel-2

en: Grassland-use intensity maps for Switzerland

en:
Resource Title: Grassland-use intensity map 2018
    Size: 2244278154 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/a5da6789-de78-42d5-be38-c1d9daff7cff/download/grassland-use_intensity_2018_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2018. See readme file for more details.

en:
Resource Title: Preview time of 1st grassland management event 2020
    Size: 2634652 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/eeb08550-52de-4be6-aac9-d8daed43a51f/download/preview_time_of_1st_management_event_2020.png
    Description: Spatial distribution of the timing (day of year; DOY) of the first management event for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the timing of the first event of the year (Weber et al., 2023; IN REVIEW)

format: PNG

media_type: image/png

en:
Resource Title: Grassland-use intensity map 2020
    Size: 2252728445 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/2a301048-a736-442d-980e-852006dc61bb/download/grassland-use_intensity_2020_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2020. See readme file for more details.

en:
Resource Title: Webcam-based reference data
    Size: 57563 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/7561f6b0-7e0b-4b99-ad30-bd247546cf3a/download/webcam_reference_data.zip
    Description: Webcam-based reference data from 2020 and 2021 (see readme).

en:
Resource Title: Readme
    Size: 3433 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/06c9bd5e-ae9c-4c7f-9b29-2849a3aa971b/download/readme.txt
    Description: Metadata and description of the maps and webcam-based reference data.

format: TXT

media_type: text/plain

en:
Resource Title: Preview number of grassland management events 2020
    Size: 2192445 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/58dfd5b4-86d2-434b-932e-8857dcfacdf2/download/preview_number_of_management_events_2020.png
    Description: Spatial distribution of the number of management events for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the distribution of management frequency (Weber et al., 2023; IN REVIEW)

en:
Resource Title: Grassland-use intensity map 2019
    Size: 2202043962 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/fdfed95b-c1c7-4842-9329-896bbbfe1c17/download/grassland-use_intensity_2019_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2019. See readme file for more details.

en:
Resource Title: Grassland-use intensity map 2021
    Size: 2201662465 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/9d8f0f98-b7f9-434a-b711-70e864ec7703/download/grassland-use_intensity_2021_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2021. See readme file for more details.

grassland

display_name: grassland

land-use

display_name: land-use

landsat

display_name: landsat

management

display_name: management

mowing

display_name: mowing

remote-sensing

display_name: remote-sensing

use-intensity

display_name: use-intensity


en:
This dataset contains the output and reference data published in the paper "Automated snow avalanche release area delineation - validation of existing algorithms and proposition of a new object-based approach for large scale hazard indication mapping" Yves Bühler, Daniel von Rickenbach, Andreas Stoffel, Stefan Margreth, Lukas Stoffel, Marc Christen (2018) Natural Hazards And Earth System Sciences.
Abstract:
Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche cadastre information, terrain analysis, climatological datasets and numerical modelling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations.
In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche cadastre data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff mapped most avalanches in detail since many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference datasets. Because all tested algorithms do not provide meaningful delineation between individual potential release areas (PRA), we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10 – 30 years return period) and extreme (100 – 300 years return period). This approach opens the door for large scale avalanche hazard indication mapping in all regions where high quality and resolution digital terrain models and snow data are available.

en: hazard-indication-mapping snow ramms avalanche release hazard-mapping

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: EnviDat: the Environmental Data Portal

en: Automated Avalanche Release Area (PRA) Delineation Davos

envi

en: Environment

en:
Resource Title: RAMMS simulations NHESS
    Size: 24222947 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1a8ed871-a483-4900-b528-95e901b3910e/resource/88c5334b-40d3-47df-b8c7-d300ba46d19c/download/ramms_sim.zip
    Description: Simulated maximum pressures for the scenarios frequent and extreme taking the forest layer into account

en:
Resource Title: Potential Release  Area  NHESS
    Size: 4379100 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1a8ed871-a483-4900-b528-95e901b3910e/resource/b0aeb914-2c95-4db3-a257-3c51ff0b2e97/download/pra_nhess.zip
    Description: This folder contains the output of the different investigated algorithms plus the reference dataset, used for training and validation.

avalanche

display_name: avalanche

hazard-indication-mapping

display_name: hazard-indication-mapping

hazard-mapping

display_name: hazard-mapping

ramms

display_name: ramms

release

display_name: release

snow

display_name: snow


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

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

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

en:
Resource Title: dat_biomass.RDS
    Size: 18677 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/81ea91cb-998e-447d-aa21-d190065a31d2/resource/67190b79-d5fc-4db4-8c3f-b7d97d32244e/download/dat_biomass.rds
    Description: Biomass values for each permanent plot at each inventory. This dataset is used for data exploration and for the Biomass model, and to create Figure 2 and Figure 3.

format: OCTET

en:
Resource Title: dat_biomass_change.RDS
    Size: 38176 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/81ea91cb-998e-447d-aa21-d190065a31d2/resource/91298b80-c946-417a-b7e0-388040d2859d/download/dat_biomass_change.rds
    Description: Biomass change values between inventories for each permanent plot. It includes the explanatory variables as well. This dataset is used for the Biomass change model and to create Figure 4 and Figure 5.

en:
Resource Title: NFI_climspace_netCDF.RDS
    Size: 578 bytes
    Format: application/x-rds
    URL: https://www.envidat.ch/dataset/81ea91cb-998e-447d-aa21-d190065a31d2/resource/0cc704a3-8f8f-4eae-a9ca-8dd1cd8c9da9/download/nfi_climspace_netcdf.rds
    Description: Climatic space covered by the Swiss National Forest Inventory (NFI) that will be used in Figure 5.

en:
Resource Title: Long_term_biomass_script.Rmd
    Size: 19732 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/81ea91cb-998e-447d-aa21-d190065a31d2/resource/49c24a6e-5eb6-4870-ad14-0cc350d69e07/download/long_term_biomass_script.rmd
    Description: R markdown document used to download the data files, reproduce the analysis and plot generation.

biomass-dynamics

display_name: biomass-dynamics

carbon-storage

display_name: carbon-storage

environmental-gradients

display_name: environmental-gradients

forest-inventory

display_name: forest-inventory

forest-reserves

display_name: forest-reserves


en: This dataset contains the Fire Weather Index for Hydrological Bavaria from 1980 - 2099 as stated in the paper "Climate change impacts on regional fire weather in heterogeneous landscapes of Central Europe" published in Natural Hazards and Earth System Sciens (NHESS) 2023. The dataset contains daily Fire Weather Index values for all 50 members (subfolders of the dataset) of the CRCM5-LE (11 km spatial resolution) from 1980 to 2099 over the domain of Hydrological Bavaria.  Please cite this dataset as the publication:  Miller, J., Böhnisch, A., Ludwig, R., & Brunner, M. I. (2023). Climate change impacts on regional fire weather in heterogeneous landscapes of Central Europe. Natural Hazards and Earth System Sciences Discussions, 1-25. doi: 10.5194/nhess-2023-51.

en: europe climate-indicators indicator-values climate forest-fire european-alps fire meteorological-data mountains climate-change

en: Fire Weather Index for Hydrological Bavaria from 1980-2099 derived from the 50 member CRCM5-LE

climate

display_name: climate

climate-change

display_name: climate-change

climate-indicators

display_name: climate-indicators

europe

display_name: europe

european-alps

display_name: european-alps

fire

display_name: fire

forest-fire

display_name: forest-fire

indicator-values

display_name: indicator-values

meteorological-data

display_name: meteorological-data

mountains

display_name: mountains


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

en: flood engineering decision-making hydrology estimation-methods

en: Faktenblätter und Leitfaden für Hochwasserschätzmethoden in der Praxis

decision-making

display_name: decision-making

engineering

display_name: engineering

estimation-methods

display_name: estimation-methods

flood

display_name: flood

hydrology

display_name: hydrology


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

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

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: EnviDat: the Environmental Data Portal

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

anisotropy

display_name: anisotropy

crystallographic

display_name: crystallographic

elasticity

display_name: elasticity

fem

display_name: fem

geometrical

display_name: geometrical

microstructure

display_name: microstructure

x-ray-tomography

display_name: x-ray-tomography


en:
Nuclear microsatellite markers and genotype data for _Trichopria ddrosophilae_
This data set comprises (i) the characteristics of a set of 21 species-specific nuclear microsatellites for PCR amplification in _Trichopria drosophilae_ (ii) and genotype data for samples collected in southern Switzerland (Canton of Ticino), with few reference samples from Canton of Vaud, southern Germany, and northern Italy (lab-reared population).
Markers were developed by Ecogenics GmbH, Balgach (Switzerland), using MiSeq Nano 2x250 v2 format (on a mix of 10 individuals). Multiplex PCR assays for multilocus genotyping were established by Ecological Genetics (WSL Birmensdorf), and population genetic analyses are found in Gugerli et al., Agrarforschung Schweiz 2019.

en: switzerland drosophila-suzukii population-genetics trichopria-drosophilae nuclear-microsatellite-markers multilocus-genotypes biological-control simple-sequence-repeats

en: Nuclear microsatellite markers for Trichopria drosophilae, parasitoid wasp on Drosophila suzukii

envi

en: Environment

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-markers_characteristics
    Size: 6134 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9bd01ee4-8334-4d38-b64e-806fc839fa8c/download/trichopriadrosophilae_nucmicrosat_seqinfo.csv
    Description: Table comprising all pertinent information for multiplex PCRs of species-specific nuclear microsatellite makers for Trichopria drosophilae, comprising all 21 newly developed markers, details on full sequences with GenBank accession numbers, primer sequences (including labeling and pig-tails), and repeat motives. PCRs with respective annealing temperatures (AnnealingTemp) refer to Type-It Multiplex PCR Kit (Qiagen, Hilden, Germany).

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-multilocus-genotype_dataset
    Size: 100131 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9998d313-6c9a-4abc-b83b-a5b0c31c07cb/download/trichopriadrosophilae_nucmicrosat_genotypes.csv
    Description: Multilocus genotypes (biallelic coding for 21 nuclear microsatellites) of Trichopria drosophilae described in Gugerli et al. Agrarforschung Schweiz 2019. Missing data denoted as '999'. Population codes (PopNo) are the following: 1, Vezia; 3, Contone ; 5, Davesco; 6, Corteglia; 7, Mezzana; 8, Stabio; 9, Gordola; 10, Sementina; 12, Brusata di Novazzano; 14, Monteggio; 16, Giubiasco; 17, ComoBP; 18, VD; 19, Weil_D; 20, Dossenheim; 21, BioPlanet_Como. Coordinates (CoordCH_E, CoordCH_N) refer to the Swiss coordinates system CH1903.

biological-control

display_name: biological-control

drosophila-suzukii

display_name: drosophila-suzukii

multilocus-genotypes

display_name: multilocus-genotypes

nuclear-microsatellite-markers

display_name: nuclear-microsatellite-markers

population-genetics

display_name: population-genetics

simple-sequence-repeats

display_name: simple-sequence-repeats

switzerland

display_name: switzerland

trichopria-drosophilae

display_name: trichopria-drosophilae


en:
The data was generated during a landscape experiment performed on 69 plots in Sihlwald forest between 2016 and 2019. Branch bundles of different sizes consisting of beech branches were exposed in the forest for one year to be colonized by saproxylic beetles and later reared for one year in emergence traps. All beetles emerging from the branches were collected. Overall 244 branch bundles are included and we found 66 beetles species (23511 individuals) of which 43 were classified as saproxylic (20873 individuals).
 Species data (2 tables)
Two community matrices (including abundance): one for saproxylic beetles and one for all beetles. Beetles were classfied as saproxylic following an extended list of the list reported in Schmidl & Bussler (2004).
 Model data (1 table)
*Response variables*
Species richness and abundance of (saproxylic) beetles.
*Branch bundles*
Branch bundles consisted of 1, 3, 6 or 12 branches and each bundle size was installed at each of the 69 plots. The bundles consisted of standardized freshly cut beech branches (Fagus sylvatica) with a length of 80 cm and a diameter between 3 and 6 cm. Total surface and volume of each bundle is reported.
*Tree on which the bundle was installed*
Information on the tree to which the bundles were attached (tree species, dbh, distance and azimut from the plot center).
*Temperature and light availability*
Temperature (plot level) and light availability (bundle level) were calculated.
*Deadwood availability in the landscape*
Based on a map of lying dead wood, dead wood amount and isolation were calculated for concentric circles with a radius ranging from 20 to 200 m (in 10 m steps) around each branch bundle.
 Variable descriptions (1 table)

en: habitat-availability colonisation forest-management habitat-heterogeneity dead-wood conservation sloss biodiversity saproxylic-beetles

en: Beetle communities reared from beech branches and associated forest and environmental variables

en:
Resource Title: Community matrix (all beetles)
    Size: 34872 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/30938085-43a4-43f0-bdde-2f57dd557064/download/abundance_all_beetles.csv
    Description: Abundances of all beetle species for each branch bundle

en:
Resource Title: Variable description
    Size: 3005 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/8113973a-149d-4514-8b03-11201870881c/download/variable_description.csv
    Description: Detailed description of the forest and environmental variables

en:
Resource Title: Forest and environmental variables
    Size: 158262 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/66dbaff5-2b06-4e82-9f92-9e40d298f938/download/data_branch_bundles.csv
    Description: Data on the branch bundle, forest and environmental variables

en:
Resource Title: Community matrix (saproxylic beetles)
    Size: 23120 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/1873211d-631c-493e-a998-103395d5de43/download/abundance_saproxylics.csv
    Description: Abundances of saproxylic beetle species for each branch bundle

biodiversity

display_name: biodiversity

colonisation

display_name: colonisation

conservation

display_name: conservation

dead-wood

display_name: dead-wood

forest-management

display_name: forest-management

habitat-availability

display_name: habitat-availability

habitat-heterogeneity

display_name: habitat-heterogeneity

saproxylic-beetles

display_name: saproxylic-beetles

sloss

display_name: sloss


en: This repository contains PMCMx-UF model outputs used for the paper: D. Patoulias K. Florou S. N. Pandis and A. Nenes: New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale, Geophysical Research Letters,  in review, 2023.

en: modeling nucleation pmcamx-uf cloud-droplets total-number

en: Dataset for the publication New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale

cloud-droplets

display_name: cloud-droplets

modeling

display_name: modeling

nucleation

display_name: nucleation

pmcamx-uf

display_name: pmcamx-uf

total-number

display_name: total-number


en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.
The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).
In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

en: perialpine-lakes hydrologic-and-hydrodynamic-modelling lake-level-regulation climate-change switzerland

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: EnviDat: the Environmental Data Portal

en: Lake climate change scenarios CH2018

en:
Resource Title: Lake water level scenarios CH2018
    Size: 128937984 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/b461ac74-3c51-4c96-9602-6200405f7ef4/download/lake_water_level_scenarios_ch2018.xls
    Description: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
Resource Title: Lake characteristics
    Size: 668782 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/469b12d3-8184-4ce1-a2c8-881a5b81db3e/download/lake_characteristics.xlsx
    Description: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

en:
Resource Title: Lake outflow scenarios CH2018
    Size: 129406464 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/5d653540-4338-4d0f-bad3-4d083584964a/download/lake_outflow_scenarios_ch2018.xls
    Description: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes


en:
Background information
The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Long-term monitoring of the large-scale high-elevation afforestation has generated data about tree growth, survival, and vitality. In addition, detailed characteristics of the microsite conditions of the research were conducted. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone.
 Experiment description
The Stillberg afforestation experiment was established in 1975 by planting 92,000 seedlings of *Larix decidua*, *Pinus cembra* and *Pinus mugo* ssp. *uncinata* in the alpine treeline ecotone. The afforestation site is located on a northeast-facing slope with steep, topographically highly structured terrain and covers elevations from 2075 to 2230 m a.s.l. The afforestation site was divided into 4052 square plots of 3.5 × 3.5 m, arranged in a regular species-alternating pattern over the whole area. Each plot contained 25 trees of one species (1350 plots per species), and the seedlings were systematically planted 70 cm apart. The trees have been monitored since 1975. Specifically, tree mortality was assessed annually from 1975 until 1995 and has been documented every ten years since then, with surveys in 2005 and 2015 (the next survey is due in 2025). Height of the surviving trees was measured in 1975, 1979, 1982, 1985, 1990, 1995, 2005, and 2015. In 1995, 2005, and 2015, drivers of tree vitality were assessed for a subset of trees per plot. Additionally, an extensive set of environmental parameters characterizing microsite conditions of the afforestation area were recorded before and after the planting of the trees.
 Data description
The five datasets from the afforestation experiment comprise ecological and environmental data from the main afforestation experiment in five datasets with accompanying metadata (Stillberg_afforestation_all_metadata.xlsx). All data and metadata files are bundled in a ZIP-file (Stillberg_afforestation_v1.zip). In particular, a first dataset contains environmental data characterising microsite conditions of the 4000 plots with regard to soil, topography, vegetation and microclimatic conditions (Stillberg_afforestation_plot_data_v1.csv; Stillberg_afforestation_plot_metadata_v1.csv. In each plot, the natural tree regeneration was assessed by counting seedings of several tree species in 2005 and 2015 (Stillberg_afforestation_regeneration_data_v1.csv; Stillberg_afforestation_regeneration_metadata_v1.csv). Furthermore, specific information about each of the 92’000 planted trees of the tree species is available (Stillberg_afforestation_tree_parameter_data_v1.csv; Stillberg_afforestation_tree_parameter_metadata_v1.csv). Survival data for each of the 92’000 individual trees can be found in a separate dataset (Stillberg_afforestation_tree_survival_data_v1.csv; Stillberg_afforestation_tree_survival_metadata_v1.csv). Tree growth and vitality parameters are available for all trees from 1995, and for subsets of trees for 2005 and 2015 (Stillberg_afforestation_tree_measurements_data_v1.csv; Stillberg_afforestation_tree_measurements_metadata_v1.csv).

en: long-term-experiment stillberg afforestation treeline mountain-forest

en: Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland

envi

en: Environment

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline


en:
Background information
The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Over almost fifty years, research at the Stillberg site combined long-term monitoring of the large-scale high-elevation afforestation with experimental manipulations simulating global change impacts. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone across different compartments and scales, from individual trees, non-tree vegetation and soils to whole ecosystems, in the context of global change resulting in more than 150 publications.
 Dataset generation
We compiled a comprehensive list of scientific publications covering research at the Stillberg research site by conducting searches in the literature databases Web of Science and Google Scholar, as well as in the Digital Object Repository of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL (DORA). We compiled all publications about the afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, the G-TREE experiment, as well as other studies related to the Stillberg research site.
 Data description
The Stillberg bibliography (Stillberg_bibliography_data_v1.csv) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals. Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title. The bibliography is described in a metadata file (Stillberg_bibliography_metadata_v1.csv). The bibliography along with the metadata file are provided in a ZIP-folder (Stillberg_bibliography_v1.zip).

en: treeline-ecosystems literature-review mountain-ecology long-term-experiment stillberg

en: Bibliography of the long-term treeline research site Stillberg, Switzerland

literature-review

display_name: literature-review

mountain-ecology

display_name: mountain-ecology

treeline-ecosystems

display_name: treeline-ecosystems


en:
We conducted consecutive loading-relaxation experiments at low strain rates to study the viscoplastic behavior of the intact ice matrix in snow. The experiments were conducted using a micro-compression stage within the X-ray tomography scanner in the SLF cold laboratory.
Next, to evaluate the experiments, a novel, implicit solution of a transient scalar model was developed to estimate the stress exponent and time scales in the effective creep relation (Glen's law). The result reveals that, for the first time, a transition in the exponent in Glen's law depends on geometrical grain size. A cross-over of stress exponent $n=1.9$ for fine grains to $n=4.4$ for coarse grains is interpreted as a transition from grain boundary sliding to dislocation creep.
The dataset includes compression force data from 11 experiments and corresponding 3D image data from tomography scans.

en: x-ray-tomography snow-mechanics microstructure ice slow-snow-compression-experiments

en: A grain-size driven transition in the deformation mechanism in slow snow compression

en:
Resource Title: README
    Size: 2225 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2fbce191-4283-4b68-aa4c-ad90723146ed/resource/a23d3947-513f-47dc-aba2-a56fd8b4afcf/download/readme.txt
    Description: README file gives an overview of the organization of the data

en:
Resource Title: slow snow compression experiments
    Size: 96297572 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2fbce191-4283-4b68-aa4c-ad90723146ed/resource/faca29b9-a95f-4f86-a3f9-1bf7faedab29/download/2023_slow_snow_compression_paper_envidat.zip
    Description: Compression experiments, X-ray images and with supplemented README file

ice

display_name: ice

microstructure

display_name: microstructure

slow-snow-compression-experiments

display_name: slow-snow-compression-experiments

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography


en:
Background information
The Stillberg ecological treeline research site is located in the transition zone between the relatively humid climate of the Northern Alps and the continental climate of the Central Alps. In 1975, 92,000 seedlings of the high-elevation conifer species *Larix decidua* Mill. (European larch), *Pinus cembra* L. (Cembran pine), and *Pinus mugo* ssp. *uncinata* (DC.) Domin (mountain pine) were systematically planted across an area of 5 hectares along an elevation gradient of about 150 metres, with the aim to develop ecologically, technically, and economically sustainable afforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Alongside the ecological long-term monitoring of the afforestation, several meteorological stations have recorded local meteorological conditions at the Stillberg research site. Here, we provide the Davos Stillberg meteorological timeseries of five stations from 1975 (01-01-1975), the year of the afforestation establishment, until the end of the year 2022 (31-12-2022).
  Station description
The five meteorological stations were all installed at the same location (46°46′25.015″N 9°52′01.792″E) at 2090 m a.s.l., in the lower part of the afforestation area. In general, the five stations were operated sequentially (Stillberg_meteo_metadata_stations_v1.csv). However, there are some overlapping time periods when more than one station was operated in parallel. The stations have recorded environmental parameters, such as air and soil temperature, dew point temperature, air pressure, relative humidity, wind direction and velocity, radiation, precipitation, and snow depth (Stillberg_meteo_metadata_parameters_v1.csv). The meteorological measurements were recorded hourly from 1975 until 1996 and have been recorded in 10-minute intervals since 1997.
 Data description
We processed the Davos Stillberg meteorological timeseries with the MeteoIO meteorological data pre-processing library (Bavay & Egger, 2014). Data files are provided for each station and quality level separately and named according to the station (see ‘Stillberg_meteo_metadata_stations_v1.csv’). From the raw data in their original formats, we generated three data quality levels: raw standardized (folder ‘raw_standardized’), edited (folder ‘raw_edited’) and filtered (folder ‘filtered’). The processing level is indicated in the headers of the data files. The whole processing protocol is described in a set of human-readable configuration files that are used by MeteoIO to generate the required data quality levels. This improves long-term reproducibility (Bavay et al., 2022), as the data could be regenerated in the future, even using a completely different software, to account for additional data points or to introduce new data corrections. The first quality level (raw standardized) is generated by parsing the original data files and interpreting them in order to convert all data points to a common format and meteorological parameter naming scheme, while excluding unreadable or duplicated data lines. The generated data files are derivatives of CSV files, with a standardised header that contains the metadata that are necessary to interpret and use the data (use metadata) and to populate a data index (search metadata). The latter is a textual implementation of the Attribute Convention for Data Discovery (ACDD) metadata standard (Attribute Convention for Data Discovery 1-3, 2022). The second quality level (edited) builds on the raw data by performing low-level data editing, such as removing some data periods that are known to be unusable (often based on maintenance records or anecdotal evidence) or applying undocumented calibration factors (for example, when there seems to be an obvious offset on a measured parameter for a period between two documented maintenance operations). The third quality level is generated by applying statistical filters on the data (per station and per meteorological parameter) to exclude presumably wrong values. We did not perform gap filling, as no single strategy could be relied upon that would work best for all possible data usage scenarios.

en: wind-speed dew-point-temperature air-temperature wind-direction stillberg treeline snow-depth relative-humidity precipitation-sum soil-temperature shortwave-radiation air-pressure

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: EnviDat: the Environmental Data Portal

en: Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.

en:
Resource Title: Stillberg_meteo_v2.0.zip
    Size: 256217522 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/78cb26bb-7d1d-4dce-a0a9-04082c984033/download/stillberg_meteo_v2.0.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v2.0.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological resea...

en:
Resource Title: Stillberg_meteo_v1
    Size: 69344042 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/590394ac-fb28-4033-8edf-42245f219cce/download/stillberg_meteo_v1.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en:
Resource Title: Stillberg_meteo_v1.1.zip
    Size: 137597369 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/e29d869c-bb1e-422a-bb6a-93738ac15539/download/stillberg_meteo_v1.1.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v1.1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed