en:
The dataset consists of the standardized precipitation (SPI) and the standardized precipitation evapotranspiration index (SPEI) index with a 30 arcsec (~1km) horizontal resolution.
Data for precipitation rates (pr) and potential evapotranspiration (pet) are taken from CHELSA V2.1 (https://doi.org/10.16904/envidat.228.v2.1). Both data sets are monthly time series from 1980 to 2018 at 30 arcsec. and have the unit of kg m-2 month-1. SPEI is a more reliable measure of drought than SPI as it additionally considers the effect of potential evapotranspiration. Potential evapotranspiration (pet) is the amount of water per area per time that can evaporate at the soil surface or be transpired by plants in absence of water supply limitations. SPEI effectively estimates for a given location how the climatic water balance, i.e., the difference between precipitation rate (pr) and potential evapotranspiration (pet), relates to the long-term mean. Here, pet was calculated with the Penman-Montheith approach, assuming surface conductance of a reference crop of 12 cm height following the definition of the Food and Agriculture Organization of the United Nations (FAO), originating from CHELSA-BIOCLIM+ database (https://www.doi.org/10.16904/envidat.332). To obtain global time series of SPEI, in each pixel the frequency distribution of water balance estimates (pr-pet) is approximated with a log-logistic probability distribution function. We calculate monthly SPEI using a 12-month memory and approximate the parameters of the log-logistic probability distribution based on the time series from 1980-2018. Such a 12-month time window is suitable to capture long-term drought events that are long enough to impose substantial impacts on agriculture, hydrology, and ecosystems while ones at shorter time scales would be more appropriate to detect short-term drought. For each month, SPEI is calculated considering the respective water-balance value and the values of the eleven preceding months. Here we use SPEI-12 in December to represent the overall water-balance condition of the respective year. The resulting SPEI data has a horizontal resolution of 130 arcsec (~1km). The calculation of SPI and SPEI is done in R with the package SPEI (https://www.doi.org/10.32614/CRAN.package.SPEI).

en: megadrought drought potential-evapotranspiration precipitation multi-year-drought chelsa extreme-events

envidat

en: EnviDat: the Environmental Data Portal

en: High resolution global standardized drought indices

envi

en: Environment

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics - Description
    Size: 1114 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a32ef5b4-fab9-4d15-b6da-c8244029027d/download/mymd_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD) statistics".

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics
    Size: 928956 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/fa3d92e1-1eb0-478c-900d-dca818e3b4ff/download/mymd10_stats.csv
    Description: Multiyear meteorological droughts (MYMD10) statistics

Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts, and the anomalies in kNDVI

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 257611 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/3149a573-b55c-499c-9efa-2cbe920bc483/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: Multiyear meteorological droughts (MYMD10) statistics - Description
    Size: 1384 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/c1c0dbc9-ec96-462e-bf62-bc90b6aad3ab/download/mymd10_stats_description.csv
    Description: Description of column names, and units of the fields contained in the dataset "Multiyear meteorological droughts (MYMD10) statistics".

en:
Resource Title: Multiyear meteorological droughts (MYMD)
    Size: 368640 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/24° (~5km) spatial resolution

en:
Resource Title: Kernel Normalized Difference Vegetation Index Anomaly (QKNDVI)
    Size: 6710886 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fqkndvi%2F
    Description: Global annual layers of the the kernel normalized difference vegetation index anomaly (qkndvi) at a 1/12° (~10km) spatial resolution.

en:
Resource Title: Standardised Precipitation Evapotranspiration Index (SPEI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspei12%2F
    Description: Global monthly layers of the Standardized Precipitation Evapotranspiration Index (SPEI) a 30 arcsec (~1km) spatial resolution

en:
Resource Title: Standardized Precipitation Index (SPI)
    Size: 209715200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fmonthly%2Fspi12%2F
    Description: Global monthly layers of the Standardized Precipitation Index (SPI) a 30 arcsec (~1km) spatial resolution

en:
Resource Title: CHELSA-drought-indices Technical Documentation
    Size: 335096 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/a4ec699c-1e4a-45ab-8b7c-ccdf09c6e828/download/chelsa_file_specification_drought_indicies.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: Multiyear meteorological droughts (MYMD10)
    Size: 107930 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fannual%2Fmymd10%2F
    Description: Global annual layers of the multiyear meteorological droughts (MYMD) at a 1/12° (~10km) spatial resolution

en:
Resource Title: Multiyear meteorological droughts (MYMD) statistics
    Size: 785961 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/8670a317-ca6b-4bce-9191-428e2827184e/resource/21046cb1-0a1c-4890-8025-aefb5d9f3f1d/download/mymd_stats.csv
    Description: Statistics of the multiyear meteorological droughts, containing the ID, duration, area, and empirical ranking of the droughts.

chelsa

display_name: chelsa

drought

display_name: drought

extreme-events

display_name: extreme-events

megadrought

display_name: megadrought

multi-year-drought

display_name: multi-year-drought

potential-evapotranspiration

display_name: potential-evapotranspiration


$oid: OBSOLETE

en:
Lebensraumkarte der Schweiz v1.2 2025/La carte des milieux naturels de Suisse v1.2 2025
The FOEN funded project ‘The Habitat Map of Switzerland:continual improvement’ conducted at the WSL, has improved on versions 1.0 and 1.1 of a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015). The datasets is now separated into two data sets:  The Habitat Map of Switzerland v1.2, ground cover layer,  and The Habitat Map of Switzerland v1.2, individual trees and shrubs outside forest v1.0 (above ground) layer.
The Habitat Map of Switzerland maps the TypoCH habitat types wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail).
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide datasets a) the high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), b) the harmonised mapping of agricultural fields area from the ‘Landwirtschaftliche Nutzfläche’ (LWN) mapping and, in settlements areas, c) the harmonised cadastral data (‘Amitliche Vermessung’ AV).
2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types (further detail below),
3: Combining existing species distribution models to determine habitat types, or
4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models (based on digital aerial photogrammetry and/or SwissSurface3D aerial laser scanning (ALS) data), the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 or Planet satellite imagery.
Further detail on the methodology can be found within the README document.

en: forest tof lidar dwarf-shrubs habitat-modelling urban sentinel-2 typoch shrub-forest ensemble-modelling wetland lebensraumkarte remote-sensing milieux-naturels grasslands random-forest

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.

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

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

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

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: The Habitat Map of Switzerland v1_2 2025

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

en:
Resource Title: LUT_einzelbaum_gebuesch_v_1_0.csv
    Size: 216 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/0035dd77-ea6d-4d3a-89bd-3ad6ee36302e/download/lut_einzelbaum_gebuesch_v_1_0.csv
    Description: Look up table for the data N2025_einzelbaum_gebuesche_v1_0_20251216
giving the full text names for each habitat type in German, French and Italian

format: CSV

media_type: text/csv

en:
Resource Title: symbology_v1_2_2025.zip
    Size: 61778 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/47c0e914-986f-4ad3-9bcf-49160023c030/download/symbology_v1_2_2025.zip
    Description: Symbology for the Habitat Map, ground layer and tree and shrub layer, and in ArcGIS and QGIS layer formats. German, French and Italian versions

format: ZIP

media_type: application/zip

en:
Resource Title: TypoCH_NUM_LookupTable_26112025.csv
    Size: 46705 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/28aace15-eb00-4ec2-98ef-b55acc18286f/download/typoch_num_lookuptable_26112025.csv
    Description: Look up table for the data N2025_HabitatMap_CH_v1_2_20251211
giving the full text names for habitat types in German, French and Italian for each habitat type as well as the key for the type of methodology used

en:
Resource Title: N2025_HabitatMap_CH_v1_2_20251211.gdb.zip
    Size: 7247757312 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/a90d17bf-221e-4819-a8b1-94b807a33720/download/n2025_habitatmap_ch_v1_2_20251211.gdb.zip
    Description: The Habitat Map of Switzerland version 1.2 2025. Ground cover layer, All of Switzerland. Vector data in file geodatabase format. Is complemented by the trees and shrubs layer.

en:
Resource Title: Data_Description_Lebensraumkarte_v1_2_Dec2025.pdf
    Size: 645376 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/564b16e5-0523-4431-94bc-3e6d1415c5a1/download/data_description_lebensraumkarte_v1_2_dec2025.pdf
    Description: Data description and documentation of methods

format: PDF

media_type: application/pdf

en:
Resource Title: N2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Size: 2469606195 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/cd4e36db-926c-4e2b-bb89-27dbe606dac3/download/n2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Description: The Habitat Map of Switzerland v1.2, non-forest trees and shrubs layer, v1.0. Vector dataset in file geodatabase format. Complements the ground cover layer dataset

dwarf-shrubs

display_name: dwarf-shrubs

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grasslands

display_name: grasslands

habitat-modelling

display_name: habitat-modelling

lebensraumkarte

display_name: lebensraumkarte

lidar

display_name: lidar

milieux-naturels

display_name: milieux-naturels

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

tof

display_name: tof

typoch

display_name: typoch

urban

display_name: urban

wetland

display_name: wetland


en: This data supplement contains the data associated with the manuscript: "Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions" (Janzing et al., 2025). It contains the data to create the figures in the paper and consists of model output from **PCRaster Global Water Balance Model (PCR-GLOBWB) 2.0** model over the larger Alpine region at 30 arcsec resolution. As the full model output takes up very high memory space, we here mostly provide time series for the different measurement stations used for evaluation and some additional maps needed to recreate the figures in the manuscript.

en: hydrological-simulations european-alps hydrology large-scale discharge

envidat

en: EnviDat: the Environmental Data Portal

en: Data supplement to Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions

envi

en: Environment

discharge

display_name: discharge

european-alps

display_name: european-alps

hydrological-simulations

display_name: hydrological-simulations

hydrology

display_name: hydrology

large-scale

display_name: large-scale


chelsacerra-daily

en:
CHELSA is a mechanistic downscaling model that links large-scale atmospheric conditions with local topographic factors to produce very high-resolution climate data. It includes commonly used climate variables for impact modeling, such as air temperature, precipitation, humidity, solar radiation, wind speed, and derived variables.
CHELSAcerra daily is a high resolution climate dataset for air-temperatures generated with the CHELSA downscaling model using the Copernicus regional reanalysis for Europe (CERRA).
Daily summaries are provided for: Daily Mean Near-Surface Air Temperature

en: climate europe air-temperature minimum-temperature reanalysis maximum-temperature

en: CHELSAcerra-daily

title_for_slug: chelsacerra-daily

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2013
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    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2013%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1988
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1988%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1999
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1999%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2002
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2002%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1991
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1991%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1997
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1997%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1990
    Size: 1 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1990%2FCERRA%2F
    Description:

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2004
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2004%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1985
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1985%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2015
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2015%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2014
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2014%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1998
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1998%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2008
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2008%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2005
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2005%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1996
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1996%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2010
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2010%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2001
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2001%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2006
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2006%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2000
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2000%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1993
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1993%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1994
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1994%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2003
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2003%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2007
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2007%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2011
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2011%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2012
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2012%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1992
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1992%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2009
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2009%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1986
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1986%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1989
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1989%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1987
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1987%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1995
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1995%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

air-temperature

display_name: air-temperature

climate

display_name: climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

reanalysis

display_name: reanalysis


en:
List of key debris flow variables from the WSL Illgraben monitoring station (2023) such as occurrence date and time, peak flow depth, peak flow velocity, total volume and bulk density.
This table contains values based on our current analysis methods. The list will be updated annually after each debris flow season, and as our methods continue to improve, individual values may change slightly in the future.

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

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

envi

en: Environment

en:
Resource Title: Readme.txt
    Size: 1523 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/ea1a8f18-6989-493b-ac4d-72b60966f112/download/readme.txt
    Description:

format: TXT

media_type: text/plain

en:
Resource Title: Illgraben debris-flow characteristics 2023
    Size: 786 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/8483e966-c20d-4403-93ed-26cc8fbf1d4d/download/df_characteristics_illgraben_2023.csv
    Description: List of key debris flow variables from the WSL Illgraben monitoring station (2023)

debris-flow

display_name: debris-flow

force-plate

display_name: force-plate

illgraben

display_name: illgraben

magnitude

display_name: magnitude

monitoring-station

display_name: monitoring-station


climarctic-seasons

en: This dataset includes measurements of potential microbial functions (potential extracellular enzyme activities and microbial functional genes abundance) and soil physico-chemical properties (pH, nutrients, texture, etc) in biocrusts and underlying mineral soils in High-Arctic tundra near Ny-Ålesund (Svalbard) during each season along a toposequence.

en: arctic microbial-biodiversity microbial-functions soil greenhouse-gases

en: Climarctic seasons

title_for_slug: climarctic-seasons

format: XLS

arctic

display_name: arctic

greenhouse-gases

display_name: greenhouse-gases

microbial-biodiversity

display_name: microbial-biodiversity

microbial-functions

display_name: microbial-functions

soil

display_name: soil


en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

en: food-webs host-enemy-interactions urban-ecosystems urban-ecology bees zurich wasps urbanization cavity-nesting hymenoptera trap-nest management-intensity

en: Data on interaction diversity in urban gardens

en:
Resource Title: Not used: data of the study
    Size: 15319 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/89ab594f-d989-4b77-afce-c6443cc1089d/download/dataset_betgard_predictors.csv
    Description:

en:
Resource Title: Script for the analyses v1.0
    Size: 53666 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/6f3ab130-4a41-4f08-ad61-ef692b41c871/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

format: OCTET

en:
Resource Title: Not used: readme
    Size: 6373 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/d35b12e9-ac52-44d3-82d3-102da2190c2d/download/readme.txt
    Description:

en:
Resource Title: Questionnaires management intensity anonymised
    Size: 30557 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/0f2466e6-a748-440e-a690-a13992c3e284/download/raw_questionnaires.csv
    Description: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en:
Resource Title: Data of the study
    Size: 14672 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/b181b669-3290-4f59-a30d-2933071e1090/download/dataset_betgard_predictors.csv
    Description: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

en:
Resource Title: Not used: raw questionnaires
    Size: 30569 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/13da58d0-ae92-4ed3-8c24-f099c4ce400c/download/raw_questionnaires.csv
    Description:

en:
Resource Title: Thesaurus
    Size: 9654 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/5f684f4b-8b68-4565-bed4-d7b7782cb036/download/thesaurus_data.xlsx
    Description: Variable names and their description.

en:
Resource Title: Raw data nests
    Size: 667409 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/1d6ef3da-b431-4fa9-8463-cad7fc487e6e/download/trapnest_data_bettergardens.csv
    Description: Host-enemy interaction data, used to compute the interaction diversity metrics

en:
Resource Title: Script for the analyses v2.0
    Size: 54771 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/94ea4ad2-dbb3-45a6-8782-31ba29b788fb/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

en:
Resource Title: Read me file
    Size: 5214 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/188e4fa7-8cdd-43e5-aae4-ae66c5fa73c5/download/readme.txt
    Description:

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich


en: The dataset contains measured values of soil liquid water content, matric potential, and soil texture of 40 soil samples in Davos, Switzerland. The measurements were used for determining van Genuchten parameter values through fitting of water retention curves, pedotransfer functions, and inverse fitting with Hydrus-1D.

en: glide-snow-avalanche soil-texture soil matric-potential measurements alpine soil-classification lwc

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 measurements of Seewer Berg and Davos

envi

en: Environment

en:
Resource Title: swb_hydrus_files.zip
    Size: 2906045 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d7ce01fb-cce5-45ea-85ec-44a25ac49a77/download/swb_hydrus_files.zip
    Description: Hydrus files used for the inverse fitting

en:
Resource Title: coordinates.csv
    Size: 1222 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/7494a93b-068b-4d87-8f33-a16d197d27bf/download/coordinates.csv
    Description: Coordinates of each soil location, location of the snow profiles, and location of the snow liquid water content measurements

en:
Resource Title: swb_px_direct_fitting.csv
    Size: 7529 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d4114528-bd8a-4335-b9ba-3d8eba7bb1fa/download/swb_px_direct_fitting.csv
    Description: Daily averaged values used for the direct fitting

en:
Resource Title: van_genuchten_parameter_values.csv
    Size: 3098 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/810089c7-a4f8-4e9a-a9b9-5d1a55676b81/download/van_genuchten_parameter_values.csv
    Description: Complete list of the van Genuchten parameter values for each soil and method

en:
Resource Title: README.txt
    Size: 1599 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/ffffb46c-fc15-49a7-b179-e20ff120fb48/download/readme.txt
    Description: Detailed information of each file in the dataset

en:
Resource Title: texture_data.csv
    Size: 1189 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/c1c4be41-28ff-4d20-97d5-aa6c28e74695/download/texture_data.csv
    Description: Texture data of the soil locations

alpine

display_name: alpine

glide-snow-avalanche

display_name: glide-snow-avalanche

lwc

display_name: lwc

matric-potential

display_name: matric-potential

measurements

display_name: measurements

soil-classification

display_name: soil-classification

soil-texture

display_name: soil-texture


en: This dataset consists of data related to capillary rise experiments performed with neutron radiography. There are 4 videos of capillary rise experiments as well as the files used to perform the inverse fitting with Hydrus. The videos show the upward flow of water in glass columns filled with sand and snow or sand, gravel, and snow. The videos show the 2D evolution of the unitless optical density with time. The Hydrus files were used to fit the parameter values of the Mualem-van Genuchten model. The experiments were performed at the Paul Scherrer Institute (PSI) in Villigen, Switzerland.

en: soil pore-water measurements water transport snow

en: Capillary rise rise experiments in snow using neutron radiography

en:
Resource Title: depricated.txt
    Size: 496 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/74c3db20-eaed-40de-a880-f042010cf6cc/download/readme.txt
    Description: Description of the videos

en:
Resource Title: README.txt
    Size: 1089 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/5631a26d-f9f0-4548-9e78-e6eecdffcee5/download/readme.txt
    Description: Descriptions of the nomenclature, Hydrus files, and videos.

en:
Resource Title: Hydrus_inverse_fitting_files.zip
    Size: 749844 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/a4e140c9-e73a-402e-9b59-63b6000d5bb6/download/hydrus_inverse_fitting_files.zip
    Description: The Hydrus files used for the inverse fitting of the hydraulic conductivity.

en:
Resource Title: capillary_rise_experiment_videos.zip
    Size: 10552661 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/4d5ee580-c1b4-49d4-868f-971b8383afa7/download/capillary_rise_experiment_videos.zip
    Description: Videos of the capillary rise experiments

pore-water

display_name: pore-water

snow

display_name: snow

soil

display_name: soil

transport

display_name: transport

water

display_name: water


c-n-p-release-treeline

en:
1. Chemical characteristics of litter layer sampled along elevation gradient across treeline ecotones in the Khibiny mountains (birch) and South Urals (spruce)
2. Release of C-N-P during decomposition at 5°C and 15° studied in an incubation experiment with microlysimeters
3. Data on microbial biomass C-N-P, potential activity of C-N-P requiring enzymes in the litter layer
4. Mineralization of 13C labeled glucose-6 phosphate, microbial 13C uptake, and net P immobilization of released P to identify microbial processing of labile organic P

en: treeline-ecosystems biogeochemical-cycling microbial-biomass carbon-cycle enzymatic-activities climate-change nutrient-fluxes litter-decomposition

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: C-N-P-Release Treeline

title_for_slug: c-n-p-release-treeline

biogeochemical-cycling

display_name: biogeochemical-cycling

carbon-cycle

display_name: carbon-cycle

climate-change

display_name: climate-change

enzymatic-activities

display_name: enzymatic-activities

litter-decomposition

display_name: litter-decomposition

microbial-biomass

display_name: microbial-biomass

nutrient-fluxes

display_name: nutrient-fluxes

treeline-ecosystems

display_name: treeline-ecosystems


forest-canopy-layer-code

en:
R script for large-scale mapping of forest canopy layering. The approach combines tree-based and area-based methods, using airborne laser scanning point clouds together with individual tree detection (ITD) information (tree height and position) to distinguish between single- and multi-layered forests. The output is a raster layer at 10m x 10m resolution, encoded as follows:
1: single-layered (class 1): Both point cloud and ITD approaches classify the forest as single-layered.
2: probably single-layered (class 2): ITD classifies the forest as single-layered, while the point cloud suggests multi-layered.
3: probably multi-layered (class 3): ITD classifies the forest as multi-layered, while the point cloud suggests single-layered.
4: multi-layered (class 4): Both point cloud and ITD approaches classify the forest as multi-layered.
Next to the R script, we also provide an example data set. The LAZ files in the example dataset are from the nationwide ALS data and are provided by the Federal Office of Topography swisstopo in accordance with its open data policy (swisstopo, 2022a, 2019). The detected individual trees were identified using Dalponte and Coomes' (2016) algorithm on a spike-free vegetation height model (cell size 0.5m). The provided forest mask corresponds to the NFI forest layer definition by Waser et al. (2015). For details and mentioned references, we refer to the related publication by Bast et al. (under revision; JAG).

en: mountain-forest protective-forest vhm itd forest-management forest lidar

envidat

en: EnviDat: the Environmental Data Portal

en: Forest Canopy Layer Code

title_for_slug: forest-canopy-layer-code

envi

en: Environment

forest

display_name: forest

forest-management

display_name: forest-management

itd

display_name: itd

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

protective-forest

display_name: protective-forest

vhm

display_name: vhm


en:
This dataset originates from a two-year transplant experiment conducted across a temperature gradient in Europe (mean annual temperatures: 8.4–21.8 °C). It includes physiological measurements of one invasive palm species (Trachycarpus fortunei) and two co-occurring native species (Ilex aquifolium and Tilia cordata). The dataset captures plant acclimation responses to air temperature, focusing on photosynthetic and respiratory traits that influence carbon balance.
Variables that can be extracted:
- Optimal temperature of photosynthesis (Topt)
- Photosynthetic rate at optimal temperature (Aopt)
- Thermal breadth of photosynthesis (T80)
- Respiration rate at 25 °C (R25)
- Temperature sensitivity of respiration (Q10)
Raw data are reported for all species across multiple sites and time points, enabling assessment of their acclimation capacity to warming. The dataset supports comparisons of functional plasticity between an invasive species and native taxa, providing insights into climate responses and invasion ecology.

en: invasive-species acclimation photosynthesis leaf spac-model respiration

en: Thermal acclimation fails to confer a carbon budget advantage to invasive species over natives

acclimation

display_name: acclimation

invasive-species

display_name: invasive-species

leaf

display_name: leaf

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

spac-model

display_name: spac-model


en: This dataset contains experimental acoustic and vibration signals recorded by the Phased Microphone Arrays (PMA) system during laboratory impact calibration tests. The PMA system is designed for surrogate monitoring of bedload transport. It consists of a stainless-steel plate mounted on elastomer supports and instrumented with an array of microphone elements and an accelerometer fixed to the internal plate. The microphone sensors (sensitivity = 11.2 mV/Pa, frequency response = 10 Hz - 20 kHz) record air-pressure fluctuations caused by particle impacts, while the accelerometer (sensitivity = 50.0 mV/g, frequency response = 0.5 Hz - ~10 kHz) measures vibrations of the internal plate. All channels were synchronously sampled at 10 kHz using a 16-channel, 24-bit data acquisition system. Additional data and details on experimental setup, signal analysis, and interpretation are available in the associated publication.

en: surrogate-measurement monitoring-techniques acoustic-signals bedload-transport microphone localization impact-test accelerometer particle-size natural-hazards

en: Acoustic Data from the PMA Bedload Monitoring System

accelerometer

display_name: accelerometer

acoustic-signals

display_name: acoustic-signals

bedload-transport

display_name: bedload-transport

impact-test

display_name: impact-test

localization

display_name: localization

microphone

display_name: microphone

monitoring-techniques

display_name: monitoring-techniques

natural-hazards

display_name: natural-hazards

particle-size

display_name: particle-size

surrogate-measurement

display_name: surrogate-measurement


en:
Data and code for the paper published in Ecography: Community structure and range shifts in Arctic marine fish under climate change
Abstract:
Arctic marine ecosystems are rapidly transforming due to climate change. Warming temperatures and shrinking sea ice are enabling boreal fish to expand northward, possibly disturbing cold-adapted Arctic species assemblages. Species range shifts have been documented in the Bering and Barents Seas, raising concerns about ecosystem restructuring. Range shifts are especially difficult to detect in the Arctic due to sparse and inconsistent data. Here, we studied fish composition from eDNA water samples taken in East Greenland, Svalbard, the Barents Sea, and the Kara Sea during the TOPtoTOP and Arctic Century expeditions. We examined the environmental drivers of fish community structure using global dissimilarity models. We calculated the decadal rate of temperature change to identify the fastest-changing areas. We compared fish detections from eDNA with published historical records for the Kara Sea to assess possible range expansions. We found that temperature was the main factor influencing the taxa turnover of fish communities, with Gadidae and Liparis sp. driving the greatest compositional differences. Over the past 30 years, temperatures increased by 0.2 to 0.6°C per decade at our study sites, with the highest increases in western Svalbard and the lowest in the eastern Kara Sea. Despite the apparent dependence on temperature, we identified only one species detected outside its known latitudinal range, and five species in the Kara Sea with recent occurrences or representing an extended distribution. Our study suggests that temperature, the main driver of fish community assembly, is increasing rapidly in the Arctic, and a few species have likely already shifted recently, or at least their detections are new in some areas. While these detections cannot be definitively linked to range shifts, our results highlight the need to improve monitoring of high-latitude fish communities to detect and predict future ecosystem changes.
Article:
Marques, V., Fopp, F., Jaquier, M., Ellingsen, K. E., Yoccoz, N., Jucker, M., ...Pellissier, L. (2025). Community structure and range shifts in Arctic marine fish under climate change. Ecography, e8014. doi: 10.1002/ecog.08014
Data:
The resource contains a zip file with the entire project structure.
Data README:
 Intro
This repo presents data and code associated with the paper "Community structure and range shifts in Arctic marine fish under climate change" published in Ecography
 Usage
Launch the `main.R` script to reproduce the entire analysis.
It executes code blocks to create the data necessary for the analysis and then creates the figures.
💣 attention, total size is expected ~20 Go and the script will query the CMEMS database to fetch environmental data
 Tools
To make the scripts run, you need R, R packages (see session info below), python3, and the copernicusmarine python tool (https://pypi.org/project/copernicusmarine/).
 SessionInfo
```
sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS 15.5
Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Zurich
tzcode source: internal
attached base packages:
[1] stats     graphics  grDevices
[4] utils     datasets  methods
[7] base
other attached packages:
 [1] lwgeom_0.2-14
 [2] metR_0.15.0
 [3] ggtext_0.1.2
 [4] scico_1.5.0
 [5] ggnewscale_0.5.0
 [6] colorspace_2.1-1
 [7] climetrics_1.0-15
 [8] rts_1.1-14
 [9] xts_0.14.0
[10] zoo_1.8-12
[11] ggpubr_0.6.0
[12] adespatial_0.3-23
[13] ggspatial_1.1.9
[14] colorplaner_0.1.4
[15] ape_5.8
[16] factoextra_1.0.7
[17] corrgram_1.14
[18] FactoMineR_2.11
[19] betapart_1.6
[20] gdm_1.5.0-9.1
[21] terra_1.7-78
[22] rnaturalearth_1.0.1
[23] ggrepel_0.9.5
[24] vegan_2.6-6.1
[25] lattice_0.22-6
[26] permute_0.9-7
[27] cowplot_1.1.3
[28] tidyterra_0.6.1
[29] sf_1.0-16
[30] egg_0.4.5
[31] gridExtra_2.3
[32] patchwork_1.2.0
[33] viridis_0.6.5
[34] viridisLite_0.4.2
[35] mgcv_1.9-1
[36] nlme_3.1-165
[37] MBA_0.1-0
[38] reshape2_1.4.4
[39] conflicted_1.2.0
[40] lubridate_1.9.3
[41] forcats_1.0.0
[42] stringr_1.5.1
[43] dplyr_1.1.4
[44] purrr_1.0.2
[45] readr_2.1.5
[46] tidyr_1.3.1
[47] tibble_3.2.1
[48] ggplot2_3.5.1
[49] tidyverse_2.0.0
[50] devtools_2.4.5
[51] usethis_2.2.3
loaded via a namespace (and not attached):
  [1] splines_4.4.0
  [2] later_1.3.2
  [3] bitops_1.0-7
  [4] minpack.lm_1.2-4
  [5] XML_3.99-0.16.1
  [6] lifecycle_1.0.4
  [7] rstatix_0.7.2
  [8] doParallel_1.0.17
  [9] MASS_7.3-60.2
 [10] flashClust_1.01-2
 [11] backports_1.5.0
 [12] magrittr_2.0.3
 [13] rmarkdown_2.27
 [14] yaml_2.3.8
 [15] remotes_2.5.0
 [16] httpuv_1.6.15
 [17] sp_2.1-4
 [18] sessioninfo_1.2.2
 [19] pkgbuild_1.4.4
 [20] mapproj_1.2.11
 [21] pbapply_1.7-2
 [22] DBI_1.2.3
 [23] RColorBrewer_1.1-3
 [24] ade4_1.7-22
 [25] maps_3.4.2
 [26] abind_1.4-5
 [27] pkgload_1.3.4
 [28] RCurl_1.98-1.14
 [29] itertools_0.1-3
 [30] yaImpute_1.0-34
 [31] rcdd_1.6
 [32] units_0.8-5
 [33] adegenet_2.1.10
 [34] codetools_0.2-20
 [35] xml2_1.3.6
 [36] adephylo_1.1-16
 [37] DT_0.33
 [38] tidyselect_1.2.1
 [39] RNeXML_2.4.11
 [40] raster_3.6-26
 [41] farver_2.1.2
 [42] jsonlite_1.8.9
 [43] e1071_1.7-14
 [44] phylobase_0.8.12
 [45] ellipsis_0.3.2
 [46] iterators_1.0.14
 [47] emmeans_1.10.4
 [48] systemfonts_1.1.0
 [49] foreach_1.5.2
 [50] progress_1.2.3
 [51] tools_4.4.0
 [52] ragg_1.3.2
 [53] snow_0.4-4
 [54] Rcpp_1.0.13
 [55] glue_1.8.0
 [56] xfun_0.44
 [57] withr_3.0.0
 [58] fastmap_1.2.0
 [59] boot_1.3-30
 [60] latticeExtra_0.6-30
 [61] fansi_1.0.6
 [62] spData_2.3.1
 [63] digest_0.6.35
 [64] timechange_0.3.0
 [65] R6_2.5.1
 [66] mime_0.12
 [67] estimability_1.5.1
 [68] wk_0.9.1
 [69] textshaping_0.4.0
 [70] jpeg_0.1-10
 [71] utf8_1.2.4
 [72] generics_0.1.3
 [73] data.table_1.15.4
 [74] class_7.3-22
 [75] prettyunits_1.2.0
 [76] httr_1.4.7
 [77] htmlwidgets_1.6.4
 [78] scatterplot3d_0.3-44
 [79] spdep_1.3-5
 [80] pkgconfig_2.0.3
 [81] gtable_0.3.5
 [82] picante_1.8.2
 [83] adegraphics_1.0-21
 [84] htmltools_0.5.8.1
 [85] carData_3.0-5
 [86] profvis_0.3.8
 [87] multcompView_0.1-10
 [88] scales_1.3.0
 [89] leaps_3.2
 [90] png_0.1-8
 [91] doSNOW_1.0.20
 [92] geometry_0.4.7
 [93] rnaturalearthhires_1.0.0.9000
 [94] knitr_1.47
 [95] rstudioapi_0.16.0
 [96] rncl_0.8.7
 [97] uuid_1.2-0
 [98] tzdb_0.4.0
 [99] checkmate_2.3.1
[100] coda_0.19-4.1
[101] magic_1.6-1
[102] proxy_0.4-27
[103] cachem_1.1.0
[104] KernSmooth_2.23-24
[105] parallel_4.4.0
[106] miniUI_0.1.1.1
[107] s2_1.1.6
[108] pillar_1.9.0
[109] grid_4.4.0
[110] vctrs_0.6.5
[111] urlchecker_1.0.1
[112] promises_1.3.0
[113] car_3.1-2
[114] xtable_1.8-4
[115] cluster_2.1.6
[116] evaluate_0.24.0
[117] mvtnorm_1.2-5
[118] cli_3.6.3
[119] compiler_4.4.0
[120] rlang_1.1.4
[121] crayon_1.5.2
[122] ggsignif_0.6.4
[123] labeling_0.4.3
[124] interp_1.1-6
[125] classInt_0.4-10
[126] plyr_1.8.9
[127] fs_1.6.4
[128] stringi_1.8.4
[129] deldir_2.0-4
[130] munsell_0.5.1
[131] Matrix_1.7-0
[132] hms_1.1.3
[133] seqinr_4.2-36
[134] shiny_1.8.1.1
[135] gridtext_0.1.5
[136] igraph_2.0.3
[137] broom_1.0.6
[138] memoise_2.0.1
[139] fastmatch_1.1-4
```
 Data content and reproducibility
Uncleaned raw table out of the bioinformatics pipeline can be found concatenated in `outputs/table_raw_before_cleaning.csv`, yet we caution readers to properly read the cleaning scripts should they wish to reproduce our analysis and this file is presently uncleaned.

en: environmental-dna fish arctic climate-change community-structure

en: Data and code for Community structure and range shifts in Arctic marine fish under climate change

arctic

display_name: arctic

climate-change

display_name: climate-change

community-structure

display_name: community-structure

environmental-dna

display_name: environmental-dna

fish

display_name: fish


en:
This repository contains data from the alpine Dischma watershed and its surroundings in eastern Switzerland and includes: (a) hourly hydrometeorological data with 100m spatial resolution, (b) remotely sensed snow depth data with 100m spatial resolution obtained at peak of winter, and (c) station measurements of variables such as snow depth and catchment runoff.
This dataset is particularly suited for (a) different simulation experiments using distributed and process-based models, including physics-based snow and hydrological models, (b) testing various snow data assimilation schemes, and (c) developing models representing snow-forest interactions.
The dataset is described in detail in:
Magnusson, J., Bühler, Y., Quéno, L., Cluzet, B., Mazzotti, G., Webster, C., Mott, R., and Jonas, T.: High-resolution hydrometeorological and snow data for the Dischma catchment in Switzerland, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-374, in review, 2024.
This dataset was published within the INARCH project:
https://inarch.usask.ca/

en: cryosphere inarch snow hydrology modelling dischma

en: A high-resolution snow and hydrometeorological dataset for the Dischma region in Switzerland

cryosphere

display_name: cryosphere

dischma

display_name: dischma

hydrology

display_name: hydrology

inarch

display_name: inarch

modelling

display_name: modelling

snow

display_name: snow


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

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

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

atmospheric-dynamics

display_name: atmospheric-dynamics

atmospheric-turbulence

display_name: atmospheric-turbulence

lidar

display_name: lidar

remote-sensing

display_name: remote-sensing

wind

display_name: wind

wind-energy

display_name: wind-energy


en:
This data set was used in the analysis by Techel et al. **Can model-based avalanche forecasts match the discriminatory skill of human danger level forecasts? A comparison from Switzerland**. Please note that the title of the preprint was *Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions*, submitted to *Natural Hazards Earth System Sciences* on 20 Aug 2024.
The final manuscript used data from three forecasting seasons (2022/2023, 2023/2024, 2024/2025) , the preprint two forecasting seasons (2022/2023, 2023/2024) .
Currently, the repository contains data from two avalanche forecasting seasons in Switzerland. The third season will be added (to be done, 30 June 2025).
**Interpolated predictions**
- The .zip file contains the interpolated predictions for the three models in nowcast- and forecast- mode. This data is needed to reproduce the figures and tables in the submitted preprint.
The other data are the **raw data** underlying the interpolations:
- Avalanche forecast by WSL Institute for Snow and Avalanche Research SLF, published at 17.00 local time, valid for the following 24 hours and relating to dry snow avalanche conditions.
- Model predictions in *nowcast*- and *forecast*-mode for three models (*danger level*, *instability*, *natural avalanche*), valid for 12.00 local time
- Subset of points extracted from GPS tracks (courtesy of Skitourenguru GmbH)
- Avalanche observations - natural avalanches and human-triggered avalanches
- Estimates of the snowline
- Randomly chosen subset of grid points used for generating reference distributions
For details regarding the data sets refer to the publication.

en: avalanche-forecast spatial-modelling machine-learning avalanche-release-probability forecast-models

envidat

en: EnviDat: the Environmental Data Portal

en: Evaluating the predictive performance of human avalanche forecasts and model predictions in Switzerland

envi

en: Environment

en:
Resource Title: Natural avalanches 2023/2024
    Size: 75730 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/00b8d3db-ecf1-4a75-9ed9-b707fa2f6324/download/natural_avalanches_2023-2024.csv
    Description: Natural avalanche observation (dry avalanches). 2023/2024 forecasting season.

en:
Resource Title: Randomly sampled subset of grid points from 1 km DEM
    Size: 17861 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/021d90e0-68bd-42b6-8815-e26c10d3a363/download/dem_filteredavalancheelevations.csv
    Description: Contains the randomly sampled subset of grid points from 1 km DEM. Three variables: coordinates (x, y) and elevation (elev).

en:
Resource Title: Snowline estimates 2023/2024
    Size: 2695027 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/87671683-a61d-45c0-92ff-d60fa3bd7e88/download/schneegrenze_beobachtungen_23-24.csv
    Description: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2023/2024 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en:
Resource Title: Avalanche forecast
    Size: 10232922 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/80146d72-7abb-4b39-8336-613b49ed9a3c/download/bulletinprepared.csv
    Description: Data contains forecasts relating to dry-snow avalanche conditions only. Forecast issued at 17.00 local time. Contains variables for the warning region (sector_id), publication date (date), danger level - sub-level combination expressed using numeric values (integer value of danger level -0.33 for sub-level minus, -0 for sub-level neutral, +0.33 for sub-level plus, altitude as indicated in the bulletin, and whether aspect (North = 0, Northeast = 45, ...) was indicated in the bulletin (no: 0, yes: 1).

en:
Resource Title: Model predictions (raw data)
    Size: 24502560 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/cb2836c0-bab2-4686-b38b-2f3562827e89/download/modelpredictions_rawdata.zip
    Description: Model predictions (raw data) for three models, in nowcast and forecast mode. Not all models are available for both seasons. - These data are the basis for the interpolated predictions, which can be found in the other zip-folder

en:
Resource Title: Natural avalanches 2022/2023
    Size: 73735 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/ca5a219a-bf68-49ee-82b2-d386e221f5ef/download/natural_avalanches_2022-2023.csv
    Description: Natural avalanche observation (dry avalanches). 2022-2023 forecasting season.

en:
Resource Title: Human-triggered avalanches 2023/2024
    Size: 38243 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/4e3cc5ed-ff9a-4d74-ae66-08a868de5332/download/human-triggered_avalanches_2023-2024.csv
    Description: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

en:
Resource Title: GPS data and human-triggered avalanches
    Size: 291620 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/48dfa07a-0f63-4e09-9160-6777085094e6/download/tracksavalanches_parametersubset.csv
    Description: Contains (1) the subset of points extracted from GPS tracks recorded during backcountry touring and uploaded to the website skitourenguru.ch and (2) the corresponding subset of human-triggered avalanches. Data (1) was provided by Skitourenguru GmbH and data (2) was collected by SLF. - Variables contained are date, Swiss coordinates (x, y), aspect (N = 0, NE = 45, ...), elevation (ele), and event (event = 1, non-event = 0).

en:
Resource Title: Snowline estimates 2022/2023
    Size: 2504217 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/be143570-31b9-4f62-a51c-05bde676f461/download/schneegrenze_beobachtungen_22-23.csv
    Description: Daily snowline estimates provided by observers for North (aspect = 0) and South (aspect = 180) slopes for the 2022/2023 season. For aspects in between North and South, values are interpolated. Contains observation date (date), coordinates (Swiss coordinates x, y), snowline elevation (snowline), and aspect.

en:
Resource Title: Model predictions (interpolated)
    Size: 85948873 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/d0599e29-dbf1-4d54-8c4b-10a248fd9fa2/download/model_predictions_interpolated.zip
    Description: The zip file contains csv-files the interpolated model predictions for three models, in forecast and nowcast-mode, for the three different data sets, as described in the publication.

en:
Resource Title: Human-triggered avalanches 2022/2023
    Size: 41461 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/f821b651-245a-47b6-95d4-64c5497b8b21/resource/32c06c01-381b-4def-9cc8-b0db86c457e9/download/human-triggered_avalanches_2022-2023.csv
    Description: The file contains the reported human-triggered avalanches. The variables are as follows: id, release date (date), name, Swiss coordinates (x,y), elevation (ele), remark, reported avalanche size expressed using avalanche activity index (sizeAAI), aspect, event type (type), event (yes = 1, no = 0)

avalanche-forecast

display_name: avalanche-forecast

avalanche-release-probability

display_name: avalanche-release-probability

forecast-models

display_name: forecast-models

machine-learning

display_name: machine-learning

spatial-modelling

display_name: spatial-modelling


defoliation-growth-data

en:
Using a literature review extracted data from 26 published papers which had data on individual tree defoliation and growth relationships In Europe.
This data set includes 415 defoliation-growth data points from 16 different tree species covering 15+ countries in Europe. Growth metrics used in individual papers were different, and included increments in terms of volume, tree rings width, radial growth, basal area and biomass. All growth metrics were converted into relative growth (presented in this dataset), expressed as a percentage of the growth of progressively defoliated trees in relation to the growth of those trees adopted as reference (control) defoliation level (i.e. the growth of the lowest defoliation level in each study was used as the reference growth point).

en: tree-growth defoliation literature-review relative-growth forest-health

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: Defoliation-Growth data

title_for_slug: defoliation-growth-data

defoliation

display_name: defoliation

forest-health

display_name: forest-health

literature-review

display_name: literature-review

relative-growth

display_name: relative-growth

tree-growth

display_name: tree-growth


en: Structural and functional changes of microbial communities in ephemeral stream sediments and adjacent soils between was assessed in an artificial newly created catchment at 3 and 13 years after catchment construction. Bacterial and fungal communities, respiration and extracellular enzyme activities were assessed.

en: microbial-biodiversity microbial-respiration ecosystem-functions soil-respiration beta-diversity

envidat

en: EnviDat: the Environmental Data Portal

en: Chicken Creek 10 years

en:
Resource Title: Bacterial amplicon sequencing
    Size: 7228320 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/79a1efb9-d34d-41ae-9f17-81e21192c9f7/resource/8fc928d0-5b3f-41a1-9326-e44a412ad6a1/download/bacteria-metagenomics-raw-data.xlsx
    Description: Bacterial ASVs and taxonomic tables

en:
Resource Title: Fungal amplicon sequencing
    Size: 1436018 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/79a1efb9-d34d-41ae-9f17-81e21192c9f7/resource/9195ccc2-7307-4f42-b698-52874737bf40/download/fungal-metagenomics-raw-data.xlsx
    Description: Fungal ASVs and taxonomic tables

en:
Resource Title: Microbial functions and metadata
    Size: 58930 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/79a1efb9-d34d-41ae-9f17-81e21192c9f7/resource/0f3324ec-664c-4977-a325-6bd37e1e52e9/download/functions-and-soil-metadata.xlsx
    Description: Extracellular enzyme activities, respiration and sites metadata

beta-diversity

display_name: beta-diversity

ecosystem-functions

display_name: ecosystem-functions

microbial-biodiversity

display_name: microbial-biodiversity

microbial-respiration

display_name: microbial-respiration

soil-respiration

display_name: soil-respiration


en:
Tropical reef fishes exhibit a large disparity of organismal morphologies contributing to their astonishing biodiversity. Morphological disparity, scaling from differences among individuals within populations to differences among species, is governed by ecological and evolutionary processes.
Here, we examined the relationship between intra- and interspecific disparity in 1111 individuals from 17 tropical reef fish species, representing 10 families with different dispersal abilities, across four Indian Ocean regions. We compared intraspecific measurements with species-level measures from a database of 1061 reef fish species. Species with high morphological disparity among individuals from distinct regions are found to be nested in families that display a high disparity among their genera. We show an association between the morphological disparity at the intra- and interspecific levels for several morphological ratios such as the caudal peduncle elongation. We evaluated the link between morphological disparity and genetic diversity with species dispersal ability. A structural equation model indicates that dispersal ability correlates positively with species genetic diversity, which is associated with morphological disparity.
Our results suggest that traits associated with dispersal may foster gene flow and morphological evolution. However, future works combining genomic, morphological and environmental data across more species is necessary to generalize these findings to other regions.

en: morphology landscape-evolution indian-ocean landscape landscape-genetics reef-fish

en: Continuity in morphological disparity in tropical reef fishes across evolutionary scales

envi

en: Environment

indian-ocean

display_name: indian-ocean

landscape

display_name: landscape

landscape-evolution

display_name: landscape-evolution

landscape-genetics

display_name: landscape-genetics

morphology

display_name: morphology

reef-fish

display_name: reef-fish


en: This data is related to the publication "Non-native Douglas fir seedlings outcompete native Norway spruce, silver fir and Scots pine under dry and nutrient-poor conditions". It contains growth and biomass data on Douglas fir seedlings in competition with three native conifers and four native broadleaf trees over three years und varying environmental conditions (i.e., water, nutrients and light availabilities).

en: douglas-fir climate-change norway-spruce drought european-beech

en: Data on Douglas fir seedlings from the DOCH-WO experiment

climate-change

display_name: climate-change

douglas-fir

display_name: douglas-fir

drought

display_name: drought

european-beech

display_name: european-beech

norway-spruce

display_name: norway-spruce


en:
This dataset consists of spatio-temporal soil measurements and local snow measurements which were recorded to investigate glide-snow avalanche release in the Seewer Berg slope (Davos, Switzerland) from Nov 2021 to June 2024. Investigations based on this dataset were published in the research article:
Fees A., Lombardo M., van Herwijnen A., Lehmann P., Schweizer J. (2025). The source, quantity, and spatial distribution of interfacial water during glide-snow avalanche release: experimental evidence from field monitoring. The Cryosphere
The dataset consists of:
- Soil measurements (temperature and liquid water content) at soil depths of -5cm, -10cm, and -20cm
- Matric potential at depths of -5cm, -10cm, and -20cm
- Manual snow profiles (Snow height, temperature, liquid water content, bulk density)
- Metadata and manual snow profiles on glide-snow avalanches that released in the Seewer Berg slope
- Snow height, air temperature and rain simulated with SNOWPACK.

en: avalanche glide-snow-avalanche soil-moisture avalanche-activity snow-profile

en: Spatio-temporal soil and local snow monitoring in a glide-snow avalanche prone slope above Davos Switzerland

en:
Resource Title: reference_location_sensors.csv
    Size: 4600810 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/f6bfdffe-9a8e-4c54-b557-269570fdd74f/download/reference_location_sensors.csv
    Description: This file contains all soil measruements (liquid water content and matric potential) recorded at the reference location.

en:
Resource Title: Setup_Dorfberg.pdf
    Size: 10566869 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/062a28fe-7ba3-48cf-a134-97b93aadaeab/download/setup_dorfberg.pdf
    Description: This file provides an overview of the dataset, the detailed measurement setup, and points out limitations.

en:
Resource Title: seewer_berg_sensors.csv
    Size: 73661482 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/ccde8ed4-1613-41f3-a486-f445837d249f/download/grid_sensors.csv
    Description: This file contains all sensor recordings in the Seewer Berg slope (time interval: 15 minutes).

en:
Resource Title: avalanche_activity.csv
    Size: 1098 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/0d3deb2c-8aad-4837-85ae-5334caa8f298/download/avalanche_activity.csv
    Description: This file contains the daily avalanche activity on Dorfberg as extracted from time-lapse photographs.

en:
Resource Title: README.txt
    Size: 6245 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/72e12972-344e-46ce-84af-ddca8924d9ec/download/readme.txt
    Description: This file explains all provided datasets, variables and their units.

en:
Resource Title: snow_profiles.csv
    Size: 4103 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/4a074b12-3c0b-4480-a72d-65368605062b/download/snow_profiles.csv
    Description:

en:
Resource Title: snow_profiles.csv
    Size: 4103 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/9f391cd2-3561-4479-bb54-fc1a4612b0b0/download/snow_profiles.csv
    Description: This file contains the aggregated data from manually recorded snow profiles in the reference location, 100m northwest of the Seewer Berg slope and in release areas of glide-snow avalanches in the Seewer Berg slope.

en:
Resource Title: avalanches_seewer_berg_shp.zip
    Size: 28023 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/c39ee8f9-4938-4ef5-93d4-78ec270d9749/download/avalanches_seewer_berg_shp.zip
    Description: This file contains the release areas (polygon) of glide-snow avalanches as a shapefile.

en:
Resource Title: snowcover_Seewer_Berg_manual.csv
    Size: 1011 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/d36d63a4-0924-4c55-b371-2ac0ea642d95/download/snowcover_seewer_berg_manual.csv
    Description:

en:
Resource Title: coordinates_sensors_shp.zip
    Size: 1925 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/f9aebdee-87a8-424a-8253-c0ede405505f/download/coordinates_sensors_shp.zip
    Description: This file contains the coordinates of the reference location and the sensors in the Seewer Berg slope as a shapefile.

en:
Resource Title: snowpack_simulation.csv
    Size: 831451 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/db4773c1-de98-4020-a199-03987a57362b/download/snowpack_simulation.csv
    Description: This file contains SNOWPACK simulations (snow height, air temperature, rain) at a virtual station in the reference location. The virtual station was interpolated between the Weissfluhjoch (WFJ2) and Klosters Madrisa (KLO2) IMIS Stations.

en:
Resource Title: Setup_Dorfberg.pdf
    Size: 10566929 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/f67ef742-fc62-497f-b34a-434ce587ba5c/resource/18c31d29-b035-4cc4-abbb-89389209963a/download/envidat_setup_dorfberg.pdf
    Description: This file provides an overview of the dataset, the detailed measurement setup, and points out limitations.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snow-profile

display_name: snow-profile

soil-moisture

display_name: soil-moisture


en: Raw data on plant morphological traits, phytochemistry and herbivory that were analyzed in the study entitled: Artificial night light intensity modulates herbivory and phytochemistry in European beech

en: alan insect-herbivores light-pollution european-beech phytochemistry

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: Raw data - Artificial night light intensity modulates herbivory and phytochemistry in European beech

envi

en: Environment

alan

display_name: alan

insect-herbivores

display_name: insect-herbivores

light-pollution

display_name: light-pollution

phytochemistry

display_name: phytochemistry


en: Data on soil nutrients and charcteristics, tree and understory biomass, foliage nutrients, mineralogy, soil temperature and moisture along an elevation gradient from boreal forest to mountain tundra in teh Khibiny mountains (Kola Penninsula, Russia). Samples were taken along two gradients at 7 elevation level either under tree canopy (tree) and in open areas (open).

en: soil-nutrients climate-change plant-traits biomass-dynamics plant-community treeline-ecosystems

biomass-dynamics

display_name: biomass-dynamics

plant-community

display_name: plant-community

plant-traits

display_name: plant-traits

soil-nutrients

display_name: soil-nutrients

treeline-ecosystems

display_name: treeline-ecosystems


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

en: afforestation picea-abies belowground-biomass subalpine isotopes

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

afforestation

display_name: afforestation

belowground-biomass

display_name: belowground-biomass

isotopes

display_name: isotopes

picea-abies

display_name: picea-abies

subalpine

display_name: subalpine


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

en: speed2zero wasserkraft datensatz schweiz kleinstwasserkraftwerke

en: CH-Kleinstwasserkraftwerke - ein schweizweiter Datensatz zu Kleinstwasserkraftwerken

en:
Resource Title: CH-Kleinstwasserkraftwerke.zip
    Size: 208809 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/79870366-f746-427a-b61b-d16ff0f803a0/download/ch-kleinstwasserkraftwerke.zip
    Description: Shapefile von CH-Kleinstwasserkraftwerke: 1'682 Kleinstwasserkraftwerke (≤ 300 kW) in der Schweiz.

en:
Resource Title: CH-WKA.zip
    Size: 166865 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/dfcc98f3-8087-44b6-88bb-e9046c91fbd9/download/ch-wka.zip
    Description: Shapefile der 2’388 registrierten Wasserkraftanlagen in der Schweiz aus den beiden Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW).

en:
Resource Title: CH-Kleinstwasserkraftwerke.svg
    Size: 9408747 bytes
    Format: image/svg+xml
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/6a4fe0c9-2daa-48ec-9625-a859c5edf30b/download/ch-kleinstwasserkraftwerke.svg
    Description: Die 1'682 erfassten Kleinstwasserkraftwerke im Datensatz CH-Kleinstwasserkraftwerke

format: svg+xml

en:
Resource Title: CH-Kleinstwasserkraftwerke.xlsx
    Size: 286462 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/7cd7672a-441d-45ad-bc1d-dfb44de1de45/download/ch-kleinstwasserkraftwerke.xlsx
    Description: .XLSX-Datei von CH-Kleinstwasserkraftwerke: 1'682 Kleinstwasserkraftwerke (≤ 300 kW) in der Schweiz.

en:
Resource Title: EZG_CH-Kleinstwasserkraftwerke.zip
    Size: 11420830 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/7d50319e-2fb2-4446-8f51-8b0e0c90fe2e/download/ezg_ch-kleinstwasserkraftwerke.zip
    Description: Shapefile der Einzugsgebiete (2 km² ), in denen sich die jeweiligen Kleinstwasserkraftwerke befinden (erstellt von Yasser Haddad. ETH).

en:
Resource Title: CH-KWA.xlsx
    Size: 245680 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/22386ad7-ab16-4738-bc7a-783a7546767d/download/ch-kwa.xlsx
    Description: .XLSX-Datei der 2’388 registrierten Wasserkraftanlagen in der Schweiz aus den beiden Datensätzen WASTA (> 300 kW) und CH-Kleinstwasserkraftwerke (≤ 300 kW).

en:
Resource Title: CH-Kleinstwasserkraftwerke.pdf
    Size: 4263857 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/5c8dda06-dac0-46a1-96a7-4776fffb014f/resource/55f0e6a2-2041-4cb2-b4a2-8ca4cefb770c/download/ch-kleinstwasserkraftwerke.pdf
    Description: Dokumentation: CH-Kleinstwasserkraftwerke

datensatz

display_name: datensatz

kleinstwasserkraftwerke

display_name: kleinstwasserkraftwerke

schweiz

display_name: schweiz

wasserkraft

display_name: wasserkraft


data-interactive-avalanche-segmentation

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

en: interactive deep-learning snow segmentation avalanche

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: Data interactive avalanche segmentation

title_for_slug: data-interactive-avalanche-segmentation

avalanche

display_name: avalanche

deep-learning

display_name: deep-learning

interactive

display_name: interactive

segmentation

display_name: segmentation

snow

display_name: snow


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

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

en: Schynige Platte Alpine Botanical Garden land-use experiment

envi

en: Environment

biodiversity

display_name: biodiversity

disturbance

display_name: disturbance

grassland-management

display_name: grassland-management

land-use-abandonment

display_name: land-use-abandonment

vascular-plant

display_name: vascular-plant


en:
The isotope composition of different forest water pools was analyzed at 10 sites of the Long-term Forest Ecosystem Research programme in 2021 and 2022. The sampling was done during the vegetation season and included fortnightly xylem water samples taken by stem increment cores and each year 3 bulk soil water sampling campaigns (in April, June, September of 2021 and 2022). Both sample types were cryogenically extracted at WSL and analyzed on a Picarro 2140 with Micro-Combustion-Module. Gravimetric water content in both sample types was computed based on pre-and post-extraction weights. In addition to xylem and bulk soil waters, we analyzed the isotope composition of soil solution from a suction cup lysimeters in three soil depths 0, 15, 50, 80 cm and precipitation from samplers below the canopy and outside of the forest, all collected fortnightly from collection periods of varying length (longest from 2017-2022).
Precipitation samples are further described [here](https://www.doi.org/10.16904/envidat.lwf.15). Lysimeter samples are described further  [here](https://www.doi.org/10.16904/envidat.lwf.28).

en: soil-solution water-isotopes water-budget forest-ecosystems xylem-water

en: Water isotope signatures in Swiss forest ecosystems in 2021 and 2022

en:
Resource Title: out2024-01-07-bulksoil-overview_s71t_.png
    Size: 813027 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/9f212b10-5843-4576-9925-591aec4314f6/download/out2024-01-07-bulksoil-overview_s71t_.png
    Description: Overview of most bulk soil water isotopic signatures.

format: PNG

media_type: image/png

en:
Resource Title: out2024-01-07-soilsolution-overview_s71t_.png
    Size: 1705534 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/19a99b8e-715f-4b5d-9a83-a58ce7262b39/download/out2024-01-07-soilsolution-overview_s71t_.png
    Description: Overview of most soil solution water isotopic signatures.

en:
Resource Title: out2024-01-07-bulksoil-all_isotope_samples_s71t__rounded.csv
    Size: 376212 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/f5a41abb-611e-4af1-9d09-da47572fe617/download/out2024-01-07-bulksoil-all_isotope_samples_s71t__rounded.csv
    Description: Water isotope signatures and gravimetric water content of bulk soil samples.

en:
Resource Title: out2024-01-07-Xylem-all_isotope_samples_s71t__rounded.csv
    Size: 225860 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/86b1d357-f693-41c2-bff6-6e3a36bbc0c3/download/out2024-01-07-xylem-all_isotope_samples_s71t__rounded.csv
    Description: Water isotope signatures and gravimetric water content of xylem samples.

en:
Resource Title: out2024-01-07_column-headers__s71t_.csv
    Size: 1800 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/6bbb0ae7-77c4-415e-8267-2b420c2f4e5d/download/out2024-01-07_column-headers__s71t_.csv
    Description: Column descriptions for soil solution, deposition, xylem and bulk soil samples.

en:
Resource Title: out2024-01-07-deposition-overview_s71t_.png
    Size: 1559360 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/f9d40459-1d3f-451f-8231-6f98dc372685/download/out2024-01-07-deposition-overview_s71t_.png
    Description: Overview of most deposition water isotopic signatures.

en:
Resource Title: out2024-01-07-soilsolution-all_isotope_samples_s71t__rounded.csv
    Size: 241479 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/04a0f364-c5a8-453e-b130-7749da954488/download/out2024-01-07-soilsolution-all_isotope_samples_s71t__rounded.csv
    Description: Water isotope signatures of soil solution samples.

en:
Resource Title: out2024-01-07-Xylem-overview_s71t_.png
    Size: 792919 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/81be7990-7d99-474b-8e6a-833a4198041d/download/out2024-01-07-xylem-overview_s71t_.png
    Description: Overview of most xylem water isotopic signatures.

en:
Resource Title: out2024-01-07-deposition-all_isotope_samples_s71t__rounded.csv
    Size: 160501 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/c6b075d0-ad47-404b-91a0-ca66b7ce433b/resource/284c6d51-fb35-470c-8c4f-c314109e4ec2/download/out2024-01-07-deposition-all_isotope_samples_s71t__rounded.csv
    Description: Water isotopic signature of deposition samples.

forest-ecosystems

display_name: forest-ecosystems

soil-solution

display_name: soil-solution

water-budget

display_name: water-budget

water-isotopes

display_name: water-isotopes

xylem-water

display_name: xylem-water


en:
This data set includes 21st century projections of dry- and wet-snow avalanche activity for seven sites in the Swiss Alps as well as the downscaled climate scenarios and SNOWPACK configuration files used to produce these projections. The methods used to produce these data are described in the research article:
Mayer, S., Hendrick, M., Michel, A., Richter, B., Schweizer, J., Wernli, H., and van Herwijnen, A.: Changes in snow avalanche activity in response to climate warming in the Swiss Alps, EGUsphere, 2024, 1-32, https://doi.org/10.5194/egusphere-2024-1026, 2024.
We used downscaled climate projections to drive the snow cover model SNOWPACK and evaluated future dry- and wet-snow avalanche occurrences in the vicinity of seven automatic weather stations from the IMIS network using machine learning models trained with observed records of avalanche activity. Projections are available for three different emission scenarios (Representative Concentration Pathways, RCP2.6, RCP4.5 and RCP8.5) and eight climate model chains from the CH2018 ensemble. The output of the model chain is given by a daily probability for dry- or wet-snow avalanche occurrences. These probabilities can then be used to classify a day as a dry- and wet-snow avalanche day (AvD) or non-avalanche day.

en: wet-snow-avalanche dry-snow-avalanche snow-instability avalanche climate-projections climate-change snow snow-stratigraphy

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:
Resource Title: SNOWPACK settings
    Size: 3070 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/b05a3845-4efc-429b-8a95-6e519b1eaef4/download/snowpack_settings.zip
    Description: contains .ini and .sno file indicating the settings used to drive SNOWPACK with the climate scenarios

en:
Resource Title: README.txt
    Size: 4232 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/e100befd-5ef4-495a-b922-ac8316cbdd4b/download/readme.txt
    Description:

en:
Resource Title: Climate scenarios .smet
    Size: 1768931461 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/12ca4022-4445-41aa-8720-a1caf547eb09/download/smet.zip
    Description: contains one .smet file per combination of station, climate model chain and RCP scenario. Each .smet file contains the downscaled meteorological data (time span 1.9.1981-31.8.2099) that was used to drive the SNOWPACK simulations.

en:
Resource Title: Projections of avalanche activity
    Size: 244124715 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/57e53301-e5b5-4366-b1e3-983088b73332/download/avd_projections.zip
    Description: contains one file per IMIS station that indicates the daily probability for the occurrence of dry- or wet-snow avalanches in the vicinity of the respective station for each day during the time period 1.12.1981-31.05.2099 (months December to May) and all climate model chains and RCP scenarios.

climate-change

display_name: climate-change

climate-projections

display_name: climate-projections

dry-snow-avalanche

display_name: dry-snow-avalanche

snow-instability

display_name: snow-instability

snow-stratigraphy

display_name: snow-stratigraphy

wet-snow-avalanche

display_name: wet-snow-avalanche


en:
This collection of datasets consists of various measurements taken during the year 2022 in Pfynwald. It combines 2 electrical resistivity transects which were monitored in May and July, before and after the irrigation season. The transects transverse all treatments (irrigation, control, irrigation stop). Each transect was repeated twice during the day for a period of 3 days to a week.
In addition there are raw and post-processed drone images (and resulting PRI maps), which were used to compare the below ground responses (from resistivity) to the above ground (crown) stress.
Here, the raw data is stored and a link to a git project is provided where python code is stored to reproduce all the results the published manuscript: "Does optimality partitioning theory fail for belowground traits?  Insights from geophysical imaging of a drought-release experiment in a dry Scots Pine forest", New Phytologist, Shakas et al., 2024. The in-depth explanations from each processing step are found in the code (git project).

en: drought pinus-sylvestris drone-data ert irrigation

en: Pfynwald Geoelectric Experiment 2022

envi

en: Environment

en:
Resource Title: SWPC_data_Pfynwald_NP2024_data.csv
    Size: 153809 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1e4afcde-3acf-4b78-ab2f-0376aab525be/resource/e0f3f914-7db4-4536-a47f-ee8b878b5ad1/download/swpc_data_pfynwald_np2024_data.csv
    Description: This .csv file contains the soil water potential data for all treatments (irrigation, irrigation-stop and control) and for the whole year of 2022. The data is given as a mean value and with an upper and lower uncertainty bound, given from the manufacturer. The depth of the sensor is given in cm, and the measured values are in units of kPa.

en:
Resource Title: 2022_NP.zip
    Size: 511138780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/1e4afcde-3acf-4b78-ab2f-0376aab525be/resource/167b27d0-27c2-48d3-b16b-83f4eb2bf740/download/2022_np.zip
    Description: This zip file contains all raw and processed data for the electrical resistivity and drone campaigns that took place in Pfynwald, 2022

drone-data

display_name: drone-data

drought

display_name: drought

ert

display_name: ert

irrigation

display_name: irrigation

pinus-sylvestris

display_name: pinus-sylvestris