rorcc

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

en: RoRCC

en: environmental-flow run-of-river-power-plants climate-change design-discharge hydropower

title_for_slug: rorcc

climate-change

display_name: climate-change

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


$oid: OBSOLETE

en:
This dataset contains the fire events, drivers and auxillery datasets analyzed in the study "Compounding preconditions of wildfires vary in time and space within Europe" of Miller et al. (2025) (DOI: 10.1038/s43247-025-02955-1).
A Jupyter-Notebook explaining the fire event datasets and code to reproduce the figures of Miller et al. (2025) are available on gitlab (see https://gitlab.com/jumi26/wildfire-drivers-in-europe).

en: Wildfire events and drivers across Europe

en: driver event-analysis forest-fire europe observations mountains

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

en: EnviDat: the Environmental Data Portal

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

format: ZIP

driver

display_name: driver

europe

display_name: europe

event-analysis

display_name: event-analysis

forest-fire

display_name: forest-fire

mountains

display_name: mountains

observations

display_name: observations


digitizing-historical-plague

en: We present newly digitized data on 6,929 plague outbreaks that occurred between 1347 and 1900 AD across Europe. The data base on an inventory initially published 1976. For georeferencing the information of Tele Atlas 2009 was used. The coordinates are in the reference systems ETRS89 and WGS84.

en: Digitizing historical plague

en: bubonic-plague plague-mapping black-death palaeo-epidemiology plague-outbreaks yersinia-pestis historical-plague plague-inventory

title_for_slug: digitizing-historical-plague

black-death

display_name: black-death

bubonic-plague

display_name: bubonic-plague

historical-plague

display_name: historical-plague

palaeo-epidemiology

display_name: palaeo-epidemiology

plague-inventory

display_name: plague-inventory

plague-mapping

display_name: plague-mapping

plague-outbreaks

display_name: plague-outbreaks

yersinia-pestis

display_name: yersinia-pestis


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

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

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

en:
Resource Title: HS and SWE observations
    Size: 1214806 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/04470a99-93e5-499d-b869-6c30dffdc2f5/resource/d1a89df0-4991-48a0-8fbc-35f72afb953e/download/validation.zip
    Description: Automated (HS) and manual (SWE) data used to evaluate model simulations

media_type: application/zip

en:
Resource Title: Station forcing data
    Size: 152284372 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/04470a99-93e5-499d-b869-6c30dffdc2f5/resource/282b7bc4-a607-4927-a2fd-858610a973c8/download/forcings.zip
    Description: All forcing data need to run JIM at HS and SWE stations. These are data downscaled directly from COSMO NWP data (WY14, WY15) and further enhanced by additional station observations of snow depth (HS) and air temperature (Ta) in WY17. Further information can be found in README file. Note that in WY14 and WY15, shortwave radiation was not split into direct and diffuse (not necessary for JIM) and that the default method in JIM for splitting precipitation phase was used. In WY 17, direct and diffuse were combined as input to JIM and JIM was forced with pre-processed liquid and solid precipitation phases.

en:
Resource Title: DEM
    Size: 568273 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/04470a99-93e5-499d-b869-6c30dffdc2f5/resource/705365e0-bdd9-4dca-966d-e8f9b9b7ede5/download/dem.txt
    Description: 1-km resolution DEM used for downscaling gridded NWP data to stations and for distributing BDE evaluations at HS-stations to SWE-stations

format: TXT

media_type: text/plain

en:
Resource Title: READ_ME
    Size: 1134 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/04470a99-93e5-499d-b869-6c30dffdc2f5/resource/30d1a503-fd18-43a5-9af9-e0e0f1855272/download/read_me.txt
    Description: File/data descriptor

jim

display_name: jim

jules-investigation-model

display_name: jules-investigation-model

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-simulation

display_name: snow-simulation


en:
Raw data of paper: A recent ash dieback infection neither affects emerald ash borer
performance nor triggers a substantial systemic phytochemical
defense response in European ash (https://doi.org/10.1007/s10340-025-01981-4)
Raw data on emerald ash borer (EAB) weight gain, mortality, development and longevity. Raw data of ash phloem and leaf chemistry. Raw data of ash dieback (ADB) lesion length.

en: Raw data-A recent ash dieback infection neither affects emerald ash borer performance nor triggers a substantial systemic phytochemical defense response in European ash

en: ash-dieback metabolomics fraxinus-excelsior pest-invasion agrilus-palnipennis

format: XLS

agrilus-palnipennis

display_name: agrilus-palnipennis

ash-dieback

display_name: ash-dieback

fraxinus-excelsior

display_name: fraxinus-excelsior

metabolomics

display_name: metabolomics

pest-invasion

display_name: pest-invasion


en:
This dataset groups numerical simulation outputs and validation measurement data produced in the context of the following [publication]: _not published yet_
The snow transport model [snowBedFoam] was used to analyse snow deposition around a specific type of Alpine PV structures named HELIOPLANT®.
The results of a sensitivity analysis of multiple key parameters that govern the spatial organisation of these structures are provided here. Measurements of snow distribution taken from the test-site of the [Gondosolar] project, are provided too.

To reproduce the results of the aforementioned publication, follow the instructions on this [repository].
[publication]: https://
[snowBedFoam]: https://www.doi.org/10.16904/envidat.223
[Gondosolar]: https://www.gondosolar.ch
[repository]: https://github.com/frischwood/snowbed-helio.git

en: Drifting and blowing snow distribution around structures for Alpine PV applications

en: photovoltaic renewable-energy alpine snow-transport preferential-deposition

en:
Resource Title: Browse simulation files
    Size: 1024 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.589%2Fsimulations%2F
    Description:

en:
Resource Title: simulations.zip
    Size: 11811160064 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.589/simulations.zip
    Description: This file contains the snowBedFoam simulations carried out to produce the results presented in: _article not published yet_.

## Content

### 1. /simulations
Groups all simulations folders organised by parameter (azimuth, groupsize, height, interspace) and by type of experiment (single_ref, group_ref).

### 2. /simulations/[parameter]/
For each parameter multiple simulations were carried out. Each simulation folder follows the same naming systematic:

`helioplant_n#_h#_ARL#_BL#_az#_windDir#`
- n: number of Helioplant units
- h: height-above-surface
- sp: regular distance between the units
- ARL: additional refinement level
- BL: boundary layer first cell height
- windDir: wind direction
- stag: staggered arangement (suffix)

Here is an example of a folder content for a specific parameter
(simulations/azimuth/):
- `helioplant_n9_h07_sp10_ARL45_BL0015_az30_windDir5`: following the naming systematic this folder corresponds to a simulation with 9 aligned Helioplant units with 0.7m of height-above-surface, an inter-unit distance of 10m an azimuth of 30° and a wind direction of 5°.

### 3. /simulations/[parameter]/[helioplant_n#_h#_ARL#_BL#_az#_windDir#]
Each simulation folder contains multiple sub-folders (0/, 100/, 300/, constant/ etc.) and files that define the experiment. For each simulation, the files used in the processing [scripts] are the following:
- 0/Cx: contains the x coordinates of sampling grid cells and of the Helioplants structures.
- 0/Cy: contains the y coordinates of sampling grid cells and of the Helioplants structures.
- 300/kinematicCloud-massCheckPatterns: contains the snow mass distribution values [kg/m2] for each grid cell.

[scripts]: https://github.com/frischwood/snowbed-helio.git

alpine

display_name: alpine

photovoltaic

display_name: photovoltaic

preferential-deposition

display_name: preferential-deposition

renewable-energy

display_name: renewable-energy

snow-transport

display_name: snow-transport


en:
Starter kit for the TreeMig framework that allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
The starter kit consists of a set of climate, land-use, topography and soil property input data for Switzerland, a script for installing the framework and running the GUI of the framework with the link to the input data, a tutorial covering a range of simulation examples for Switzerland and a transect through Europe, and an associated example simulation environment containing the model executables and other model inputs.

en: Starter Kit for the TreeMig framework v1 for easy simulation of spatio-temporal forest dynamics

en: forest-dynamics bioclimatic-variables forest species-interaction gui forest-model spatial-modelling treemig land-use species-migration r-package

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: TreeMig Simulation Environment and Input Data
    Size: 1602386904 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/c2ae78fd-418a-4cdb-a511-0914eb46224f/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en:
Resource Title: TreeMig_Tutorial_v2024_12.pdf
    Size: 3399819 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5188a2e1-470c-4ed7-83c6-26dc72bd18ab/download/treemig_tutorial_v2024_12.pdf
    Description: Tutorial for using the TreeMig framework; updated

format: PDF

media_type: application/pdf

en:
Resource Title: TreeMig Simulation Environment and Input Data
    Size: 1612103870 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5eef16d1-80af-442b-9da2-f64b4fa94671/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en:
Resource Title: TreeMig_Tutorial_2025-05-02.pdf
    Size: 2107648 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/a1dec65a-30ba-4688-90ac-50df5db73d4c/download/treemig_tutorial_2025-05-02.pdf
    Description: Tutorial for using the TreeMig framework; updated

en:
Resource Title: Description input data
    Size: 263110 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/3db8ca57-2838-4b26-82a9-9770b75b7096/download/readme_descriptioninputdata.pdf
    Description: Details where the input data come from and how they have been processed

en:
Resource Title: TreeMig_Tutorial_v2024_12_04.pdf
    Size: 6400462 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/d4c15251-917c-4102-b172-256fecd39161/download/treemig_tutorial_v2024_12_04.pdf
    Description:

en:
Resource Title: TreeMig Tutorial
    Size: 2046576 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/8e6ac324-ab2b-40bc-a12f-70960c8f4bd1/download/treemig_tutorial.pdf
    Description: Tutorial for using the TreeMig framework

bioclimatic-variables

display_name: bioclimatic-variables

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-model

display_name: forest-model

gui

display_name: gui

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-interaction

display_name: species-interaction

species-migration

display_name: species-migration

treemig

display_name: treemig


en: Laboratory experiments are presented on the phase change at the surface of sodium chloride – water mixtures at temperatures between 259 K and 240 K. High selectivity to the upper few nanometres of the frozen solution – air interface is achieved by using electron yield near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. We present the NEXAFS spectrum of the hydrohalite.

en: Data set on interfacial supercooling and the precipitation of hydrohalite in frozen NaCl solutions by X-ray absorption spectroscopy

en: arctic ice snow sea-salt-aerosol antarctica

en:
Resource Title: Fig 1C
    Size: 4075 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/72da8863-8f75-4cc6-8f19-e0794aba1825/download/fig1datac.txt
    Description: Data to Figure 1C

en:
Resource Title: Fig 1F_2
    Size: 4855 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/016e32e9-3a1d-433e-95b8-66a0a8cef4ec/download/fig1dataf_phoenix04042016_016.txt
    Description: Individual data to mean shown in Figure 1F

en:
Resource Title: Table1
    Size: 15287 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/89079eb2-5bc0-4032-ad8d-41db87a93c81/download/table1.txt
    Description: This table lists all data files in chronological order. "SampleTemp" refers to the reading of the PT-1000 at the side of the sample holder. "cellPressure" is the water vapour pressure during the measurements. From this, in presence of ice, the temperature of the ice sample can be calculated which is given in the column "iceTemp". "dT" is the difference, or temperature offset, between sensor's reading and the ice samples temperature. The offset is due to the sensor being mounted away from the cooled spot of the sample were it experiences heating from warmer parts of the sample holder. The off-set is used to calibrate the temperature sensor and the resulting temperature during the experiments is given in the column "temperature". "relHum" is the relative humidity above (supercooled) liquid and "concBrine" is the concentration of a NaCl solution in mol/l in equilibrium with ice at the experimental temperature. "Area" is the integrated PE signal.

en:
Resource Title: Fig 1D
    Size: 4831 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/b483a523-00ab-46ae-8dd4-12a80135158a/download/fig1datad.txt
    Description: Data to Figure 1D

en:
Resource Title: Fib 1B_3
    Size: 4849 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/83a80299-55d3-423e-9fbb-e5b0a962dd5d/download/fig1datab_phoenix04042016_020.txt
    Description: Individual data to mean shown in Figure 1B

en:
Resource Title: Fig 1E
    Size: 4834 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/b5116736-f648-48fc-b151-84f9e7425b02/download/fig1datae.txt
    Description: Data to Figure 1E

en:
Resource Title: Fig 1B_1
    Size: 4068 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/8b41e95e-ed56-46fd-96ff-1edfd7e95592/download/fig1datab_phoenix04042016_006.txt
    Description: Individual data to mean shown in Figure 1B

en:
Resource Title: Fig 1B_2
    Size: 5115 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/ddfc21ed-441b-457d-b97f-b798769fe961/download/fig1datab_phoenix04042016_007.txt
    Description: Individual data to mean shown in Figure 1B

en:
Resource Title: Fig 1B
    Size: 4055 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/e34c6b10-2a60-47ff-9861-c4532f9f6cd5/download/fig1datab.txt
    Description: Data in Figure 1B

en:
Resource Title: Code
    Size: 4438 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/4f8edf22-d8cf-42e9-aae8-88cf6d84ceec/download/bartelsrausch_cryosphere_nacl_2020.m
    Description: Matlab code to read and plot the data

en:
Resource Title: Read Me
    Size: 127587 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/06ee35fe-4ee5-4813-812c-5600ac828b25/download/bartelsrausch_cryosphere_nacl_2020-data-repository.pdf
    Description: Description of the data tables

en:
Resource Title: Fig 1F
    Size: 4852 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/4066e023-0d99-4ee8-9b28-7dcc5bae6e6a/download/fig1dataf.txt
    Description: Data to Figure 1F

en:
Resource Title: Table 2
    Size: 1399 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/0a3fb7b3-b96d-496a-86e2-00a635c1fdab/download/table2.txt
    Description: This table lists all NEXAFS data files in chronological order with PE carbon to oxygen signal intensity ratios -from which the atomic ratio were calculated in the paper - before ("preCtoO") and after ("postCtoO") each NEXAFS measurement. Also listed is the change in Na ("lossSodi"), O ("lossOxy"), Cl ("lossChlor"), and C ("lossCarb") signal intensity after the NEXAFS measurement compared to prior to the NEXAFS measurement.

en:
Resource Title: Fig 1A
    Size: 5110 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/b90f9e5e-d4a1-47ef-8654-659b2ee7734a/download/fig1dataa.txt
    Description: Data Figure 1A

en:
Resource Title: Fig 1F_1
    Size: 4856 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4f67a0e6-accb-40a1-b9f1-3c8f8eebf886/resource/927bbb3a-590d-46a1-8cc2-8eef6b2040a9/download/fig1dataf_phoenix04042016_015.txt
    Description: Individual data to mean shown in Figure 1F

antarctica

display_name: antarctica

arctic

display_name: arctic

ice

display_name: ice

sea-salt-aerosol

display_name: sea-salt-aerosol

snow

display_name: snow


en:
This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format.
The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication:
_Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical
instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_
The code and potential updates can be accessed directly through git via:
https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics

en: A numerical solver for heat and mass transport in snow based on FEniCS

en: snow python vapor-transport pattern-formation numerical-model

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

numerical-model

display_name: numerical-model

pattern-formation

display_name: pattern-formation

python

display_name: python

vapor-transport

display_name: vapor-transport


en:
The data consists of a collection of environmental data, tree-ring width and intra-annual δ13C measurements of tree rings of three conifer species (Pinus sylvestris, Picea abies, Abies alba), and the R scripts that were used to analyse the data. Data was collected at two pairs of north and south exposed sites in Switzerland, in the Eastern Grisons (Surava North and Surava South) and Central Valais (Buthan and Lens).
Intra-annual δ13C measurements were obtained using the laser ablation technique, which involved 10 sequential shots per ring. Shot 1 represents the δ13C value at the start of the ring, while Shot 10 corresponds to the δ13C value at the end of the ring's formation. Overall, the datasets consist of 400 profiles and 4000 isotope measurements.
Environmental data was collected at each site over decade, from 2012 to 2023. Key environmental variables include temperature, vapour pressure deficit (VPD), and soil water potential (SWP). Precipitation data was obtained from the EOBS v29.0e dataset (https://www.ecad.eu/download/ensembles/download.php) from the closest grid point. All data was aggregated on an hourly to daily scale.
In addition to environmental data, dendrometer data was used to derive the onset days, beginning of growth for each site (Onset_days.Rds). The data captures the dynamic relationship between environmental factors, such as soil and air moisture, and tree physiological responses, as reflected in δ13C variation. This dataset provides insights into the intra-seasonal interactions between environmental conditions and tree physiology. We provide the scripts for the main analyses performed in the Vitali, V. et al. 2025 article listed below, including the correlation of the isotope intra-annual time series with environmental variables.
This dataset contains all data on which the publication listed below is based.
Please cite this paper together with the citation for the datafile.

en: 10 years of intra-annual carbon isotopes in tree rings from 3 conifer species

en: tree-ring soil-water dendrochronology pinus-sylvestris picea-abies stable-isotopes drought abies-alba vpd

abies-alba

display_name: abies-alba

dendrochronology

display_name: dendrochronology

drought

display_name: drought

picea-abies

display_name: picea-abies

pinus-sylvestris

display_name: pinus-sylvestris

soil-water

display_name: soil-water

stable-isotopes

display_name: stable-isotopes

tree-ring

display_name: tree-ring

vpd

display_name: vpd


en:
Acknowledgements: The CORE format was proudly inspired by the Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) format, by considering how to leverage the ability of clients issuing HTTP GET range requests for a time-series of remote sensing and aerial imagery (instead of just one image).
License: The Cloud Optimized Raster Encoding (CORE) specifications are released to the public domain under a Creative Commons 1.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.
-----------------------
Summary:
The Cloud Optimized Raster Encoding (CORE) format is being developed for the efficient storage and management of gridded data by applying video encoding algorithms. It is mainly designed for the exchange and preservation of large time series data in environmental data repositories, while in the same time enabling more efficient workflows on the cloud. It can be applied to any large number of similar (in pixel size and image dimensions) raster data layers. CORE is not designed to replace COG but to work together with COG for a collection of many layers (e.g. by offering a fast preview of layers when switching between layers of a time series).
WARNING: Currently only applicable to RGB/Byte imagery. The final CORE specifications may probably be very different from what is written herein or CORE may not ever become productive due to a myriad of reasons (see also 'Major issues to be solved').
With this early public sharing of the format we explicitly support the Open Science agenda, which implies "shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process" (quote from: European Commission, Directorate General for Research and Innovation, 2016. Open innovation, open science, open to the world).
CORE Specifications:
1) a MP4 or WebM video digital multimedia container format (or any future video container playable as HTML video in major browsers)
2) a free to use or open video compression codec such as H.264, VP9, or AV1 (or any future video codec that is open sourced or free to use for end users)
Note: H.264 is currently recommended because of the wide usage with support in all major browsers, fast encoding due to acceleration in hardware (which is currently not the case for AV1 or VP9) and the fact that MPEG LA has allowed the free use for streaming video that is free to the end users. However, please note that H.264 is restricted by patents and its use in proprietary or commercial software requires the payment of royalties to [MPEG LA](https://www.mpegla.com/programs/avc-h-264/). However, when AV1 matures and accelerated hardware encoding becomes available, AV1 is expected to offer 30% to 50% smaller file size in comparison with H.264, while retaining the [same quality](https://trac.ffmpeg.org/wiki/Encode/AV1).
3) the encoding frame rate should be of one frame per second (fps) with each layer segmented in internal tiles, similar to COG, ordered by the main use case when accessing the data: either layer contiguous or tile contiguous;
Note: The internal tile arrangement should support an easy navigation inside the CORE video format, depending on the use case.
4) a CORE file is optimised for streaming with the moov atom at the beginning of the file (e.g. with -movflags faststart) and optional additional optimisations depending on the codec used (e.g. -tune fastdecode -tune zerolatency for H.264)
5) metadata tags inside the moov atom for describing and using geographic image data (that are preferably compatible with the [OGC GeoTIFF standard](https://www.ogc.org/standards/geotiff) or any future standard accepted by the geospatial community) as well as list of original file names corresponding to each CORE layer
6) it needs to encode similar source rasters (such as time series of rasters with the same extent and resolution, or different tiles of the same product; each input raster should be having the same image and pixel size)
7) it provides a mechanism for addressing and requesting overviews (lower resolution data) for a fast display in web browser depending on the map scale (currently external overviews)
Major issues to be solved:
- Internal overviews (similar to COG), by chaining lower resolution videos in the same MP4 container for fast access to overviews first); Currently, overviews are kept as separate files, as external overviews.
- Metadata encoding (how to best encode spatial extent, layer names, and so on, for each of the layer inside the series, which may have a different geographical extent, etc...; Known issues: adding too many tags with FFmpeg which are not part of the standard MP4 moov atom; metadata tags have a limited string length.
- Applicability beyond RGB/Byte datasets; defining a standard way of converting cell values from Int16/UInt16/UInt32/Int32/Float32/Float64/ data types into multi-band Byte values (and reconstructing them back to the original data type within acceptable thresholds)
Example
Notice: The provided CORE (.mp4) examples contain modified Copernicus Sentinel data [2018-2021].
For generating the CORE examples provided, 50 original Sentinel 2 (S-2) TCI data images from an area located inside Switzerland were downloaded from www.copernicus.eu, and then transformed into CORE format using ffmpeg with H.264 encoding using the [x264 library](https://www.videolan.org/developers/x264.html).
DISCLAIMER: Basic scripts are provided for the Geomatics peer review (in 2021) and kept as additional information for the dataset. Nevertheless, please note that software dependencies and libraries, as well as cloud storage paths, may quickly become deprecated over time (after 2021). For compatibility, stable dependencies and libraries released around 2020 should be used.

en: raster sentinel-2 gridded-data video-encoding geodata time-series research-data-management core

en:
Resource Title: View publication in the Digital Object Repository at WSL (DORA)
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A28180
    Description:

en:
Resource Title: CORE Dataset (80 GB)
    Size: 85899345920 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.230/CORE_S2A/
    Description:

en:
Resource Title: extract_S2A_CORE
    Size: 3147 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/387cd755-33df-4543-ae50-529df462b94f/resource/dec6f9ce-cef3-4da1-97a2-42e2d47315a6/download/extract_s2a_core.sh.zip
    Description: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

en:
Resource Title: reproduce_S2A_CORE
    Size: 4313 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/387cd755-33df-4543-ae50-529df462b94f/resource/5d8926a7-e8b9-4f01-a197-7edd0968e5c8/download/reproduce_s2a_core.zip
    Description: Disclaimer: provided for the Geomatics peer review in 2021 and left as additional information for the dataset. Software dependencies and libraries, as well as cloud storage paths, may change over time (after 2021).

core

display_name: core

geodata

display_name: geodata

gridded-data

display_name: gridded-data

raster

display_name: raster

research-data-management

display_name: research-data-management

time-series

display_name: time-series

video-encoding

display_name: video-encoding


en:
Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings.
FORECOMON 2021 - the 9th forest ecosystem monitoring conference.
7-9 June 2021, WSL, Birmensdorf, Switzerland
The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.
Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.

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

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

en:
Resource Title: FORECOMON – Proceedings
    Size: 2920688 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/ab0b32ad-43fa-41c3-93bd-68b6d6b7e4e7/download/abstractband_a4_forecomon_vrs14.pdf
    Description: Latest version

en:
Resource Title: Deprecated version 1.0
    Size: 2699168 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/1928196d-5fee-48c1-9b30-66362abf2045/download/icp_abstractband_web.pdf
    Description: First version of the proceedings containing errors. This early version it is kept, for traceability purposes, in conformance with DOI rules.

en:
Resource Title: Link to Proceedings in DORA WSL
    Size: 1 bytes
    Format: No Info
    URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A27202
    Description:

air-pollution

display_name: air-pollution

forest

display_name: forest

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

monitoring

display_name: monitoring


en:
Dataset content
Continuous soil measurements (10-min resolution) from the Pfynwald long-term irrigation experiment, covering five treatments: **control, irrigation, irrigation+VPD, roof, roof+VPD**.
Measurements were taken at multiple plots and at three depths (-0.1, -0.8, -1.2 m below soil surface).
Sensors include TEROS-21 (matric potential), TEROS-12 (volumetric water content), TEROS-21 (soil temperature), and TEROS-12 (electrical conductivity).
 Processing steps
**1. Raw retrieval** from the LWF database (`ada.v_messvar`, project `Pfynwald irrigation`), 10-min cadence.
**2. Range filtering** to remove physically implausible values:
   - SWP: drop values ≥ 0 kPa or ≤ −8000 kPa
   - VWC: drop values ≤ 0 or - 0.8 m³/m³
   - TEM: drop values - 40 °C or - −20 °C
**3. Duplicate aggregation** within the same 10-min timestamp by mean (median for SWP).
**4. Temperature correction (SWP_TC)**: matric potential is temperature-corrected using the TEROS-21 manufacturer equation referenced to T_ref = 20 °C:
   - Convert SWP (kPa) to head h = |SWP|·10.197, then pF = log10(h)
   - ΔpF = (919.890694·ΔT − 6.945352·ΔT²)·exp(−150.754657 / (pF + 9.153084))
   - SWP_TC = −10^(pF + ΔpF) / 10.197
**5. No gap filling applied.** Missing values remain absent from the delivered CSV.
 Methods
- Database query and aggregation: R, `data.table`, `rLWFpg`
- Temperature correction: in-house implementation of TEROS-21 manufacturer formula
- See repository / script reference below
 Limitations
- Values flagged out of range during step 2 are absent (not interpolated)
- Winter periods may include frozen-soil readings — these pass the range filter as physical sensor outputs but should be interpreted with caution by downstream users
- SWP_TC rows carry the messvar_id of the underlying SWP sensor; the corresponding TEM sensor used for correction is paired via site/plot/depth/datetime but not encoded in the messvar_id
- Sensor calibration uses manufacturer defaults; site-specific calibration was not performed
- Roofs were installed in spring 2024. Readings under "roof" / "roof_vpd" treatments before that reflect ambient conditions, not the experimental treatment.
- In 2025, three additional TEROS-21 sensors were added per roofed treatment at 10 cm depth to obtain a balanced sample relative to roof position (under panels, at panel edges, and in inter-panel gaps).
  This expansion means roofed treatments have six positions at 10 cm from 2025 onward, compared to three before.

en: Pfynwald VPDrought experiment soil parameters

en: teros-21 water-potential soil-moisture soil-temperature teros-12 pinus-sylvestris irrigation-manipulation drought-experiment electrical-conductivity vpdrought pfynwald irrigation

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: pfynwald_vpdrought_soil_10Minutes_2025.zip
    Size: 66201780 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/edaa3e3a-1045-4d2f-952f-e23689c20bb9/download/pfynwald_vpdrought_soil_10minutes_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_soil_10Minutes_2024.zip
    Size: 59025329 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/12bc2274-e48f-4ff1-8961-b86699aaa450/resource/3606ad5b-f308-4bfc-8aa4-db5b017ee47a/download/pfynwald_vpdrought_soil_10minutes_2024.zip
    Description:

drought-experiment

display_name: drought-experiment

electrical-conductivity

display_name: electrical-conductivity

irrigation

display_name: irrigation

irrigation-manipulation

display_name: irrigation-manipulation

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

vpdrought

display_name: vpdrought

water-potential

display_name: water-potential


en:
The following repository contains the data and code to reproduce the figures analyses of the paper "Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide". It contains three datasets and one .R file
---
The data results from a literature review on abundance distribution of urban bee communities worldwide, aiming at obtaining studies reporting total abundances of honeybees and wildbees in a given city, and species abundances of wildbees and honeybees in a given city.
---
1. **Data**:
- *20240308_cities_coords.csv*: the data contains the latitude and longitude of the included cities in the study. It is used for making the world map with the cities.
- *20241201_proportion_HB_WB.csv*: the data contains the total wild bee and honeybee abundances per city/urban aggregation, and the proportions.
- *20241201_rad_bees.csv*: the data contains the species abundances per city/urban aggregation
2. **Script**:
- *HoneybeeDominance_Analyses_Figures.R*: the script to run the analyses and make the plots. Analyses were done in R version 4.2.1, using the packages ggplot2, glmmTMB, multcomp, wesanderson, terra.

en: Data supporting ‘Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide’

en: sads honeybees anthophila cities urban-beekeeping wildbees dominance urban-ecosystems

envi

en: Environment

en:
Resource Title: Dataset proportion honeybees and wild bees
    Size: 14245 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/90c4bffd-bfc1-4100-99f5-a2ad3e9503a8/download/20241201_proportion_hb_wb.csv
    Description: The dataset provide the main features for each included dataset from published and unpublished research works.  Each row represents a dataset, which provides bee community data in one city / urban aggregation. Overall, it contains 68 datasets from 46 cities in 15 countries and five continents. The data is organised in the following columns:
- Article_ID: id used in the study
- DOI: doi of the publication, when available
- Authors
- Year: of publication
- Duration sampling (years)
- Start_sampling: month of the year
- End_sampling: month of the year
- Continent
- Country
- N. cities: number of cities included in the publication
- City
- Sampling type: active, passive or both
- Sampling methodology: within each sampling type.
- Habitats: list of sampling habitats
- N_habitats: number of sampling habitats
- Parks_similar: binnary (1 = yes; 0 = no)
- Agriculture: binnary (1 = yes; 0 = no)
- Private_gardens: binnary (1 = yes; 0 = no)
- Green_roofs: binnary (1 = yes; 0 = no)
- seminatural_natural_wasteland: binnary (1 = yes; 0 = no)
- other_unspecified: binnary (1 = yes; 0 = no)
- Number sites
- Abundance honeybees
- Abundance wild bees
- Total bees
- Proportion honeybees
- Proportion wildbees
- Area:. of the studied city/urban aggregation

format: CSV

media_type: text/csv

en:
Resource Title: R script for analyses and plots
    Size: 17744 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/2f39336d-f343-4325-8207-38372826ecf4/download/honeybeedominance_analyses_figures.r
    Description:

format: OCTET

en:
Resource Title: Dataset species abundance
    Size: 598032 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/a4e637d3-911b-4806-b0ba-cbbd17a34309/download/20241201_rad_bees.csv
    Description: This data resource provides the individual species abundance per city / urban aggregation. It contains data from 41 datasets from 37 studies collected in 33 cities / urban aggregations. It contains the following columns:
 - Article_ID
- DOI
- Authors
- Year
- Continent
- Country
- City
- Bee genus
- Bee species
- Bee merged
- Bee full
- Abundance
- Bee_ID_per_study: ID for the study

en:
Resource Title: Dataset coordinates study cities
    Size: 2196 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/9a73209e-98c0-4fee-a208-c726bf957efa/download/20240308_cities_coords.csv
    Description: The data contains the latitude and longitude of the studied cities / urban aggregations. It contains the following columns:
- Continent
-Country
- City
- Lat: Latitude
- Lon: Longitude

anthophila

display_name: anthophila

cities

display_name: cities

dominance

display_name: dominance

honeybees

display_name: honeybees

sads

display_name: sads

urban-beekeeping

display_name: urban-beekeeping

urban-ecosystems

display_name: urban-ecosystems

wildbees

display_name: wildbees


soil-respiration-exclosure-experiment

en:
Location of data collection
The Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (- 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume - 60% of the biomass in short-grass compared to - 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, - 5 g).
Experimental design
We selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil.
!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!
Data collection
In-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged.
Please acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli

en: Soil respiration - exclosure experiment

en: grazing grassland ungulates subalpine soil-respiration

title_for_slug: soil-respiration-exclosure-experiment

grassland

display_name: grassland

grazing

display_name: grazing

soil-respiration

display_name: soil-respiration

subalpine

display_name: subalpine

ungulates

display_name: ungulates


soil-solution-chemistry-lysimeters-lwf

en:
Fortnightly measurement of the soil solution chemistry in 4 soil depths  with zero-tension lysimeter below the litter layer and with tension lysimeters at depths of 15, 50 and 80 cm (8 replicates)
 Purpose:
To characterize the chemical status of the soil solution and to detect trends in soil water quality. To assess the effects of air pollution and climate chnage on soil water quality.
 Manual Citation:
 * Micha Pluess, Daniel Christen, 1999: Kurzanleitung Bodenlösung. Langfristige Waldökosystem-Forschung LWF, Birmensdorf, 2 S.
 * Nieminen  TM,  De  Vos  B,  Cools  N,  König  N,  Fischer  R,  Iost  S,  Meesenburg  H,  Nicolas  M,  O’Dea  P,  Cecchini  G,  Ferretti  M,  De  La  Cruz  A,  Derome  K,  Lindroos  AJ,  Graf  Pannatier  E,  2016:  Part  XI:  Soil  Solution  Collection  and  Analysis.  In:  UNECE  ICP  Forests  Programme  Co-ordinating  Centre  (ed.):  Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 20 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)
 Paper Citation:
 * Graf Pannatier, E.; Thimonier, A.; Schmitt, M.; Walthert, L.; Waldner, P., 2011: A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?. Environmental Monitoring and Assessment, 174, 1-4: 3-30. [doi: 10.1007/s10661-010-1754-3](http://doi.org/10.1007/s10661-010-1754-3)

en: Soil solution chemistry (lysimeters) LWF

en: long-term-forest-ecosystem-research icp-forests lwf swiss-forest-lab soil-solution-chemistry

title_for_slug: soil-solution-chemistry-lysimeters-lwf

format: HTML

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

lwf

display_name: lwf

soil-solution-chemistry

display_name: soil-solution-chemistry

swiss-forest-lab

display_name: swiss-forest-lab


en:
Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence-only SDMs that often rely on species observations from non-standardized sampling efforts. To address this issue, sampling background points with a target-group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence-only models.
Innovation: Recent methods correct for observer bias by using covariates related to accessibility in model calibrations (classic bias covariate correction, Classic-BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1’900 plant species. We evaluated model performance with spatial block split-sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps.
Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as bias covariate (Target-BCC) displayed most realistic modelled species distributions, with a clear positive correlation (r≃0.5) found between predicted and expert-based species richness. Although EBC must be carefully implemented in a species-specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence-only models, and overcome the standard need of an independent test dataset for model evaluation.

en: Novel methods to correct for observer and sampling bias in presence-only species distribution models

en: survey-effort independent-dataset environmental-stratification target-group covariate-correction random-stratified-sampling point-process-model cluster plant-species background-data

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

background-data

display_name: background-data

cluster

display_name: cluster

covariate-correction

display_name: covariate-correction

environmental-stratification

display_name: environmental-stratification

independent-dataset

display_name: independent-dataset

plant-species

display_name: plant-species

point-process-model

display_name: point-process-model

random-stratified-sampling

display_name: random-stratified-sampling

survey-effort

display_name: survey-effort

target-group

display_name: target-group


en:
Plant ecophysiological and associated environmental data for two tree species (*Fagus sylvatica* and *Quercus pubescens*) grown for five years in a factorial open-top climate chamber experiment (Model Ecosystem Facility, Birmensdorf, Switzerland) to test the long-term effects of heat (+5 °C) and soil drought (irrigation reduced by 50%). n = 4 trees per species and treatment, n = 48 trees total.
 Included data sheets:
- Environmental_Data.csv: Chamber-level environmental recorded every 10 minutes
- Tleaf.csv: Leaf temperatures recorded every 10 minutes
- Gas_exchange.csv: Leaf-level gas exchange data taken diurnally on four days during the growing season
- Leaf_traits.csv: Leaf functional traits
- TSMs_HSMs.csv: Photosynthetic thermal tolerance and leaf water potential data, summarized also in terms of leaf thermal safety margins and hydraulic safety margins, collected 3-4 times during the growing season
- Scorch.csv: Leaf-level leaf scorching data, including leaf thermal safety margins and scorching occurrence and presence, summarized by date

en: Hydraulic stress limits thermal acclimation in trees under chronic drought

en: functional-traits thermoregulation hydraulic-safety-margins quercus-pubescens leaf-scorching fagus-sylvatica hot-drought thermal-safety-margins gas-exchange

en:
Resource Title: TSMs_HSMs.csv
    Size: 15217 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/6c897b79-4cc6-46f5-87f0-83275921ede9/download/tsms_hsms.csv
    Description: Tree-level photosynthetic thermal tolerance, leaf water potentials, thermal safety margins, and hydraulic safety margins measured 3-4 times per tree during the growing season.

Variable List:
	- TreeID: Unique identifier for individual trees
 	- Species: Tree species
	- Campaign: Month of the growing season in which data was collected
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Waterpotential: midday leaf waterpotential (MPa)
	- WPtlp: Waterpotential at leaf turgor-loss-point (MPa) *Measured by Mas, E., Cochard, H., Deluigi, J., Didion-Gency, M., Martin-StPaul, N., Morcillo, L., Valladares, F., Vilagrosa, A., & Grossiord, C. (2024). Interactions between beech and oak seedlings can modify the effects of hotter droughts and the onset of hydraulic failure. New Phytologist, 241(3), 1021-1034. https://doi.org/https://doi.org/10.1111/nph.19358
	- HSM: Hydraulic safety margin (difference between WPtlp and Waterpotential, in MPa)
	- Tcrit: Critical thermal threshold of Photosystem II (degrees C)
	- T50: High leaf temperature at which Photosystem II function declines by 50% (degrees C)
	- Tleaf.max: Maximum leaf temperature during the week preceding thermal tolerance measurement
	- TSM.min: Minimum leaf thermal safety margin during the week preceeding thermal tolerance measurement (difference between Tcrit and Tleaf.max, in degrees C)

en:
Resource Title: Environmental_Data.csv
    Size: 19996344 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/8113d780-83c8-43bd-a823-f726ad3f21ab/download/environmental_data.csv
    Description: Chamber-level abiotic data recorded every 10 minutes.

Variable List:
	- Time (MM/DD/YYYY HH:MM)
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Tair: Air temperature (degrees C)
	- Tair_sd: Standard deviation of air temperature
	- RH: Relative humidity
	- RH_sd: Standard deviation of relative humidity
	- VPD: Vapor pressure deficit (kPa)
	- Tsoil: Soil temperature (degrees C)
	- Soil_m: Volumetric soil water content (m^3/m^3)
	- PPFD: Photosynthetic photon flux density (micromoles m^-2 s^-1) *collected from a weather station next to the open-top-chambers (50% intensity inside chambers)
	- windspeed: (m/s) *collected from a weather station next to the open-top-chambers

en:
Resource Title: Gas_exchange.csv
    Size: 4424 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/df082744-69a0-49b6-81b7-c3f02d24c9f0/download/gas_exchange.csv
    Description: Leaf-level gas exchange collected diurnally for each tree on 4 days of the growing season and summarized to growing-season mean.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Species: Tree species
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- gsw.mean: Mean stomatal conductance to water vapor (mol m^-2 s^-1)
	- E.mean: Mean transpiration rate (mol m^-2 s^-2)
	- Tdiff.mean: Mean difference between leaf and air temperature on the day of Licor measurements
	- lnE.mean: Mean of the natural log of the transpiration rate
	- lnE.mean~Tdiff.mean_slope: The slope of the linear least-squares relationship between the natural log of lnE.mean and Tdiff.mean

en:
Resource Title: Tleaf.csv
    Size: 28028436 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1860aa5f-68f2-4889-b0c9-bd907e48111f/download/tleaf.csv
    Description: Tree-level leaf temperature data recorded every 10 minutes.

Variable List:
	- Timestamp (MM/DD/YYYY HH:MM)
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
 	- Species: Tree species
	- Tair: Air temperature (degrees C)
	- Tleaf: Leaf temperature (degrees C)
	- Tdiff: Leaf-to-air temperature differential (degrees C)

en:
Resource Title: README.txt
    Size: 8110 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1fe7f58f-356a-4ed4-ae5f-a2b16755e9de/download/readme.txt
    Description: README file with more information about the dataset.

en:
Resource Title: Leaf_traits.csv
    Size: 7772 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/eaf9d8ce-80f5-489f-af97-e80760927aee/download/leaf_traits.csv
    Description: Tree-level leaf functional trait data.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
 	- Species: Tree species
	- Leaf_width (cm)
	- Leaf_area (cm^2)
	- Stomatal_density (count per cm^2)
	- Pore_length: Stomatal pore length (micrometers)
	- Guard_cell_width: Stomatal guard cell width (micrometers)
	- Leaf_thickness (mm)
	- Epidermal_thickness (mm)
	- Parenchyma_thickness (mm)
	- Parenchyma:Epidermis: Ratio between parenchyma and epidermal thickness
	- Reflectance: Reflectance of photosynthetically active radiation (400-700), fraction
	- Transmittance: Transmittance of photosynthetically active radiation (400-700), fraction
	- Absorptance: Absorptance of photosynthetically active radiation (400-700), fraction
	- Absorbance: Optical absorbance of photosynthetically active radiation (400-700 nm), unitless
	- g1: Medlyn-style stomatal slope calculated with Licor LI6800 data

en:
Resource Title: README.txt
    Size: 8090 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/1f818ee5-bfba-4996-b8fb-e6dc1c96fbb4/download/readme.txt
    Description: README file with more information about the dataset.

en:
Resource Title: Scorch.csv
    Size: 129956 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/e153f13e-330e-4c0a-8cff-59e625dc7e7c/download/scorch.csv
    Description: Tree-level leaf scorching occurrence and severity data summarized by date with daily leaf thermal safety margins.

Variable List:
	- TreeID: Unique identifier for individual trees
	- Date (MM/DD/YYYY)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Species: Tree species
	- Tleaf: Leaf temperature (degrees C) *measured by an infrared sensor integrated into the Cavicam
	- Tcrit: Critical thermal threshold of Photosystem II (degrees C) *daily entries inherit the Tcrit measured onthe next measurement date and applied to the interval preceding it (or are forward-filled when Tcrit could not be estimated in August or September)
	- TSM: Leaf thermal safety margin (difference between Tcrit and Tleaf, in degrees C)
	- Scorch_binary: Binary indicating whether scorching occurred on that date (0 = no, 1 = yes)
	- Percent_affected: Percent of the camera window affected by scorching during a scorching event

en:
Resource Title: Gas_exchange.csv
    Size: 4413 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8780a01e-98aa-46bb-9938-ba8e0568fa20/resource/cc7e702f-6d53-4192-944c-7671eaecf5bc/download/gas_exchange.csv
    Description: Mean values taken for each tree across the growing season. Measurements were taken diurnally (~1 measurement/hr) with a Licor LI6800 matching ambient chamber conditions on 4 days during the growing season (1 day in June, July, August, September).

- Number of variables: 11
- Number of cases/rows: 48
- Variable List:
	- TreeID: Unique identifier for individual trees
	- Chamber: open-top-chamber ID
	- Species: Tree species
	- Treatment: chamber abiotic treatment (C = control, H = heated, RM = reduced soil moisture, H_RM = heated and reduced soil moisture)
	- Heating: Yes or no
	- RM: Reduced soil moisture, yes or no
	- gsw.mean: Mean stomatal conductance to water vapor (mol m^-2 s^-1)
	- gsw.mean: Mean stomatal conductance rate (mol m^-2 s^-2)
	- Tdiff.mean: Mean difference between leaf and air temperature on the day of Licor measurements
	- lngsw.mean: Mean of the natural log of stomatal conductance
	- lngsw.mean~Tdiff.mean_slope: The slope of the linear least-squares relationship between the natural log of lngsw.mean and Tdiff.mean

fagus-sylvatica

display_name: fagus-sylvatica

functional-traits

display_name: functional-traits

gas-exchange

display_name: gas-exchange

hot-drought

display_name: hot-drought

hydraulic-safety-margins

display_name: hydraulic-safety-margins

leaf-scorching

display_name: leaf-scorching

quercus-pubescens

display_name: quercus-pubescens

thermal-safety-margins

display_name: thermal-safety-margins

thermoregulation

display_name: thermoregulation


en:
We established our study sites in the cities of Basel, Lugano and Zurich, and their peri-urban forests. We characterised urban tree cover of each city using a rectangular grid with squares of 100x100 m. Within each square, we measured the area covered by urban trees using the European Union's Copernicus Land Monitoring Service information, Urban Atlas Street Tree Layer 2018 [https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c](https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c).
Then we assigned each square to four categories of urban tree cover that roughly represented the main types of urban uses:
1) low cover, industrial/commercial areas, 0-20% tree cover;
2) intermediate cover, residential areas, 20-40% tree cover;
3) high cover, urban parks and cemeteries, 40-60% tree cover;
4) peri-urban forests (natural/semi-natural forests), 60-100% tree cover.
-br/--br/-
Our study sites consisted of eight 1.2 km-long transects in each city, equally distributed across the four tree cover categories.  We designed an experimental measurements of bird predation rate on herbivore insect larvae using artificial caterpillars. They mimicked a variety of common, cryptically-coloured herbivorous species, which are usually preyed by birds. We designed caterpillars with green water-resistant modelling clay (Staedtler Noris®), 4-6 cm long and approximately 0.5 cm wide. Caterpillars were threaded to a thin (Ø = 0.6 mm) zinc-plated iron wire and tethered to branches of trees or bushes at a height up to 2 m from the ground. We placed 2-4 caterpillar mimics every 200 m along each transect (five points per transect) or, when not possible due to absence of suitable branches, within 200 m from the point.
In total, we placed 270 caterpillar mimics at 115 points during the late breeding season (June-July 2023). Caterpillar mimics were checked after 10-14 days and replaced with new ones at new locations within 10 m from the previous ones. During each of the two visits, we counted the number of bird predation marks.

en: Urban bird predation on artificial caterpillars

en: biodiversity-experiment periurban urban-biodiversity urban birds insect-herbivores pest-invasion biodiversity urban-ecology

envi

en: Environment

biodiversity

display_name: biodiversity

biodiversity-experiment

display_name: biodiversity-experiment

birds

display_name: birds

insect-herbivores

display_name: insect-herbivores

periurban

display_name: periurban

pest-invasion

display_name: pest-invasion

urban

display_name: urban

urban-biodiversity

display_name: urban-biodiversity

urban-ecology

display_name: urban-ecology


en:
This data set contains roughly 5600 photographs of plants and plant parts from 153 sites recorded in all major biogeographic regions of Switzerland using smartphone cameras. Image names contain a letter referring to depicted plant parts: b = bark, i = inflorescence, f = infructescense, s = several parts, v = vegetative parts.
Photos are grouped in folders by observation (individual or population), i.e., photos in the same folder are of the same species, observed at the same time and sampling plot. At a higher organisational level, these folders are grouped by sampling plot (usually 3×3 m in open areas and 10×10 m in forests). The main folder contains metadata including taxon name, sampling time and location, as well as the TypoCH habitat type encoded as integers.
This data set accompanies the following publication:
Popp, M. R., Zimmermann, N. E. & Brun, P. Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland. _Ecological Informatics_ **103316** (2025) doi:[10.1016/j.ecoinf.2025.103316](https://doi.org/10.1016/j.ecoinf.2025.103316).

en: Photos of vegetative and reproductive parts of 560 vascular plant species taken in all biogeographic regions of Switzerland

en: vascular-plants species-observations photo plant-species testing

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

photo

display_name: photo

plant-species

display_name: plant-species

species-observations

display_name: species-observations

testing

display_name: testing

vascular-plants

display_name: vascular-plants


en: The data includes (1) amphibian occurrence data (2017-2019) for ten species across the cantons of Aargau and Zürich gathered from the Coordination Center for the Protection of Amphibians and Reptiles of Switzerland (http://www.karch.ch), (2) amphibian whole-life cycle environmental predictors (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related), and (3) local urban "green" and "grey" landcover data which can be used to identify opportunities for Blue-Green Infrastructure (through green or grey transitions) in support of regional landscape connectivity.

en: Amphibian and urban-rural landscape data Swiss Lowlands

en: circuit-theory integrated-modelling human-dominated-landscapes biodiversity ecological-corridors urban-spatial-planning

en:
Resource Title: Amphibian breeding sites of national importance - cantons of Aargau and Zürich
    Size: 39808424 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/fd5b1fe3-bdf9-4095-816a-edaf22178df2/download/breeding_sites_raster_30m.asc
    Description: Amphibian breeding sites of national importance (focal nodes) in the cantons of Aargau and Zürich, 30x30 m resolution, binarised ascii format.

format: pgp-keys

en:
Resource Title: Binarized "green" and "grey" landcover data (Cantons of Aargau and Zürich)
    Size: 531399 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/5752ef42-b6cc-4365-bb61-288dfa3d5d95/download/urban_green_grey.zip
    Description: "Green" landcover refers to lawns and vegetated urban surfaces such as, for example private gardens, public parks, cemeteries, green stripes along roadsides, etc. While "grey" landcover refers to impervious grounds such as roads, troittoirs, other impervious. Binarized maps, 30x30m resolution.

en:
Resource Title: Amphibian monitoring data
    Size: 310101 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/ce42d731-4b85-4da0-b356-35deb8f80607/download/amphibian_presence_2017_2019.csv
    Description: Processed amphibian occurrence data (2017-2019) in the cantons of Aargau and Zürich. The dataset includes information for the following species:  _Alytes obstetricans_,_Bombina variegata_, _Bufo bufo_, _Hyla arborea_, _Ichtyosaura alpestris_, _Lissotriton helveticus_, _Lissotriton vulgaris_, _Rana temporaria_, _Salamandra salamandra_, and _Triturus cristatus_.

en:
Resource Title: Amphibian species specific landscape resistance maps.
    Size: 51864736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/acaac64b-3ebe-4e97-ae24-a35736dfa1d5/download/resistance.zip
    Description: For each amphibian species we used the weighted average Ensemble model suitability map and converted it to a resistance map using an exponential decay function following (Duflot et al., 2018) using the species-specific mpa threshold previously computed (Preau et al., 2020). The function assigns a resistance value of 1,000 when habitat suitability equals zero, and a value of one when habitat suitability is greater than or equal to the binarization threshold. The exponential shape strengthens the barrier effect of less favorable areas.

en:
Resource Title: Amphibian whole life cycle predictors - 10m resolution
    Size: 734915785 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/26ceef50-633c-469b-970d-cd6e453e9500/download/amphibian_predictors_sdms.zip
    Description: Amphibian whole life cycle predictors include 6 variable types:
(1)	Topographic – slope [°]: derived from the Swiss Topographical Landscape model (swissTLM 3D 2015) at 2 m resolution (elevation uncertainty ± 0.5m) and, subsequently, aggregated to a median value;
(2)	Hydrologic: two predictors including nearest distance to water [m] (all water-related objects and rasterized lotic, lentic and reedbeds from the regional cadastral maps – AV: Daten der Amtliche Vermessung) and runoff coefficient [C] (between 0 and 1 relating amount of runoff to amount of precipitation, mapped AV: Daten der Amtliche Vermessung data against literature values for different land covers);
(3)	Edaphic – soil moisture variability (not available): can gathered from the spatial modelling of Ecological Indicator Values in Switzerland (Descombes et al., 2020) and resampled from 100m to 10m;
(4)	Vegetation: we calculated the median and standard deviation of the Normalized Difference Vegetation Index (NDVI) from all available cloud free Sentinel-2 pixels available between April and October for the years 2016 to 2019 (Drusch et al., 2012) and the median vegetation height [m] (not available) can gathered from Ginzler and Hobi (2015);
(5)	Land-use derived: includes three predictors, grassland density [grassland/cell] (not available) - can be gathered from Pazur et al. (2021), total grasslands area evaluated using a spatial weight matrix and a 250m neighborhood radius around each cell; urbanization [buildings/cell] – average building density for a 250m neighborhood around each cell based on the AV: Daten der Amtliche Vermessung ; and traffic intensity [vehicles/day] – average daily vehicle count (Nationales Personenverkehrsmodells);
(6)	Movement-ecology related: includes three predictors of proximity – nearest forest distance [m]; nearest rock-gravel and sandy area (RGS) distance [m] and nearest road distance [m] (considering any road type) – all calculated based on the AV: Daten der Amtliche Vermessung maps.

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

human-dominated-landscapes

display_name: human-dominated-landscapes

integrated-modelling

display_name: integrated-modelling

urban-spatial-planning

display_name: urban-spatial-planning


en:
To validate the critical crack length as implemented in the snow cover model SNOWPACK, PST experiments were conducted for three winter seasons (2015-2017) at two field site above Davos, Switzerland. This dataset contains manually observed snow profiles and stability tests. Furthermore, corresponding SNOWPACK simulations are included.
These data were analyzed and results were published in Richter et al. (2019).
Please refer to the Readme file for further details on the data.
These data are the basis of the following publication:
Richter, B., Schweizer, J., Rotach, M. W., and van Herwijnen, A.: Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK, The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, 2019.

en: Validating and improving the critical crack length in SNOWPACK

en: snow snowpack snow-stability-evaluation avalanche-forecast avalanche

en:
Resource Title: README
    Size: 18771 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/b6cfb0c3-2bb3-4fa1-859d-5861983aa785/download/readme.txt
    Description: README file explaining data structure and content

en:
Resource Title: Manually observed snow profiles
    Size: 27333 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/74bf515b-cd6b-4e97-be6d-4356f0af6d3d/download/manual_snow_profiles.zip
    Description: Manually observed snow profiles as csv-files containing depth [cm], thickness [cm], density [kg m-3], hand hardness, first grain type, second grain type, first grain size [mm], and second grain size [mm] of each layer.

en:
Resource Title: SNOWPACK simulations
    Size: 21903741 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/6b0dc93f-34d1-48e2-bf69-3f9254e34692/download/snowpack.zip
    Description: This dataset contains all SNOWPACK simulations, including input files, setup and output files.

en:
Resource Title: Extracted data
    Size: 197562 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/42774021-73e4-49b2-a714-b192a0e3cc14/download/extracted_data.zip
    Description: Extracted data contain validation and results published in Richter et al. (2019).

en:
Resource Title: Stability tests
    Size: 6975 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c460111d-cbd0-479d-bd34-48ba27abe5e4/resource/98cbbb6e-bfad-4b71-b920-e3def95143d3/download/stability_tests.zip
    Description: Stability tests including csv-files with CT, ECT and PST experiments for each year and each field site.

avalanche

display_name: avalanche

avalanche-forecast

display_name: avalanche-forecast

snow

display_name: snow

snow-stability-evaluation

display_name: snow-stability-evaluation

snowpack

display_name: snowpack


de: Der Datensatz enthält archäologische Fundstellen als interpretierte Flächen, wobei unterschieden wird zwischen Stätten, die sicher grossflächig sind (A-Fundstellen: z.B. Bauten/Siedlungen, Gräber/Friedhöfe), und Einzelfund-Stellen, die auf grossflächige Fundstellen hinweisen können (B-Fundstellen: z.B. Steinbeil). Die interpretierte Darstellung von archäologischen Fundstellen basiert auf Ausgrabungen und auf aktenkundigen Fundmeldungen, die teilweise bis zu 200 Jahre alt sind, vereinzelt auch auf Flurnamen (z.B. Muracher); sehr alte Fundmeldungen lassen sich manchmal nur schwierig interpretieren und ungenau lokalisieren. Der erste Durchgang der kantonsweiten Erfassung ist Ende 2005 abgeschlossen worden; die Ausarbeitung und Nachführung wird laufend zu Ergänzungen und einzelnen Änderungen führen. Angaben über Datierung, Art, Umfang und Erhaltungsgrad einer Fundstelle können über die Fundstellennummer, die als Attribut auch im GIS-Datensatz enthalten ist, auf Anfrage erschlossen werden.

de: Archäologische Fundstellen

de: Das AGIS Service Center unterstützt als kantonale Koordinationsstelle die Bereitstellung von Geoinformationen und Metadaten der kantonalen Verwaltung. Die zuständigen kantonalen Fachstellen stellen die öffentlichen Geodaten des Kantons Aargau mittels der Infrastruktur des AGIS Service Center in der Informatik Aargau als Webservices und zum Download bereit.

de: AGIS Service Center Kanton Aargau

political_level: canton

de: Kantonsarchäologie

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

de: AGIS Direktdownload

format: WMS

value: Aargau-Kt - Geocat Harvester


name: Bundesamt für Landwirtschaft, Fachbereich Marktanalysen

de: Jährliche Durchschnittspreise von ausgewählten Milchprodukten auf der Wertschöpfungsstufe Gastrogrosshandel

en: Annual average prices of selected dairy products at the catering wholesale stage of the value chain

fr: Prix moyens annuels de produits laitiers sélectionnés au stade du commerce de gros destiné à la restauration

it: Prezzi annuali medi di latticini scelti al livello della catena di valore del commercio all’ingrosso per la ristorazione

de: Marktzahlen Milch und Milchprodukte - Jährliche Gastrogrosshandelspreise

en: Market figures for milk and dairy products – Annual catering wholesale prices

fr: Chiffres du marché du lait et des produits laitiers - Prix annuels du commerce de gros destiné à la restauration

it: Cifre del mercato del latte e dei latticini  - Prezzi annuali nel mercato all’ingrosso per la ristorazione

en: price market-data

bundesamt-fur-landwirtschaft-blw

de: Das Bundesamt für Landwirtschaft (BLW) ist das Kompetenzzentrum des Bundes für den Agrarsektor. Es setzt sich für eine multifunktionale Landwirtschaft ein.

en: The Federal Office for Agriculture (FOAG) is the Confederation's competence center for all core issues relating to the agricultural sector. The FOAG promotes multifunctional agriculture.

fr: L’Office fédéral de l’agriculture (OFAG) est le centre de compétence de la Confédération pour les questions relevant du secteur agricole. Il œuvre pour une agriculture multifonctionnelle.

it: L’Ufficio federale dell’agricoltura (UFAG) è il centro di competenza della Confederazione per le questioni inerenti al settore agricolo. Esso si impegna per un'agricoltura multifunzionale.

en: Federal Office for Agriculture FOAG

de: Bundesamt für Landwirtschaft BLW

fr: Office fédéral de l'agriculture OFAG

it: Ufficio federale dell'agricoltura UFAG

political_level: confederation

value: LINDAS DCAT Harvester BLW

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: SPARQL Endpoint mit Vorauswahl des Graph

en: SPARQL Endpoint with graph preselection

fr: SPARQL Endpoint avec présélection du graphe

format: SPARQL

media_type: application/sparql-query

market-data

display_name: market-data

price

display_name: price


de: Monatliche Durchschnittspreise für importierte Früchten, Gemüse, Kartoffeln und ausgewählten Erzeugnissen daraus

en: Monthly average import prices of fruit, vegetables, potatoes, and selected derived products

fr: Prix moyens mensuels des importations de fruits, de légumes, de pommes de terre et d’une sélection de produits dérivés

it: Prezzi medi mensili delle importazioni di frutta, verdura, patate nonché di una selezione di loro prodotti

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Monatliche Importpreise

en: Market figures fruit, vegetables, and potatoes - Monthly import prices

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - Prix mensuels à l'importation

it: Cifre del mercato della frutta, della verdura e delle patate – Prezzi d’importazione mensili


de: Jährliche durchschnittliche Importpreise von Früchten, Gemüse, Kartoffeln und ausgewählten Erzeugnissen daraus

en: Annual average import prices of fruit, vegetables, potatoes, and selected derived products

fr: Prix moyens annuels des importations de fruits, de légumes, de pommes de terre et d’une sélection de produits dérivés

it: Prezzi medi annuali delle importazioni di frutta, verdura, patate nonché di una selezione di loro prodotti

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Jährliche Importpreise

en: Market figures fruit, vegetables, and potatoes - Annual import prices

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - Prix annuels à l'importation

it: Cifre del mercato della frutta, della verdura e delle patate – Prezzi d’importazione annuali


de: Monatliche Importe von Früchte, Gemüse, Kartoffeln und ausgewählten Erzeugnissen daraus

en: Monthly import quantities of fruit, vegetables, potatoes, and selected derived products

fr: Quantités mensuelles des importations de fruits, de légumes, de pommes de terre et d’une sélection de produits dérivés

it: Volumi d’importazione mensili della frutta, della verdura e delle patate nonché di una selezione di loro prodotti

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Monatliche Importmengen

en: Market figures fruit, vegetables, and potatoes - Monthly import quantities

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - importations mensuelles

it: Cifre del mercato della frutta, della verdura e delle patate – Volumi d’importazione mensili


de: Jährliche Importe von Früchten, Gemüse, Kartoffeln und ausgewählten Erzeugnissen daraus

en: Annual import quantities of fruit, vegetables, potatoes, and selected derived products

fr: Quantités annuelles des importations de fruits, de légumes, de pommes de terre et d’une sélection de produits dérivés

it: Volumi d’importazione annuali della frutta, della verdura e delle patate nonché di una selezione di loro prodotti

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Jährliche Importmengen

en: Market figures fruit, vegetables, and potatoes - Annual import quantities

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - Quantités importées annuelles

it: Cifre del mercato della frutta, della verdura e delle patate – Volumi d’importazione annuali


de: Monatliche Durchschnittspreise für Früchte, Gemüse und Kartoffeln auf der Wertschöpfungsstufe Konsum

en: Monthly average prices for fruit, vegetables and potatoes at the consumer level

fr: Prix à la consommation mensuels moyens des fruits, des légumes et des pommes de terre

it: Prezzi medi mensili per frutta, verdura e patate al livello della catena del valore Consumo

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Monatliche Konsumentenpreise

en: Market figures fruit, vegetables, and potatoes - Monthly consumer prices

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - prix à la consommation mensuels

it: Cifre del mercato della frutta, della verdura e delle patate - Prezzi al consumo mensili


de: Jährliche Durchschnittspreise für Früchte, Gemüse und Kartoffeln auf der Wertschöpfungsstufe Konsum

en: Annual average prices for fruit, vegetables and potatoes at the consumer level

fr: Prix à la consommation annuels moyens des fruits, des légumes et des pommes de terre

it: Prezzi medi annuali per frutta, verdura e patate al livello della catena del valore Consumo

de: Marktzahlen Früchte, Gemüse und Kartoffeln - Jährliche Konsumentenpreise

en: Market figures fruit, vegetables, and potatoes - Annual consumer prices

fr: Chiffres du marché des fruits, des légumes et des pommes de terre - prix à la consommation annuels

it: Cifre del mercato della frutta, della verdura e delle patate - Prezzi al consumo annuali

en: price market-data


de: Jährliche Mengenangaben für Eiweisspflanzen auf der Wertschöpfungsstufe Produktion

en: Annual quantities for protein crops at the production level

fr: Quantités annuelles des plantes protéagineuses au niveau de la production

it: Quantità annue delle piante proteiche al livello della produzione

de: Marktzahlen Eiweisspflanzen - Jährliche Produktionsmengen

en: Market figures for protein crops - Annual production quantities

fr: Chiffres du marché des plantes protéagineuses - Quantités de production annuelles

it: Dati di mercato delle piante proteiche - Quantità di produzione annue

en: market-data quantity

bundesamt-fur-landwirtschaft-blw

de: Das Bundesamt für Landwirtschaft (BLW) ist das Kompetenzzentrum des Bundes für den Agrarsektor. Es setzt sich für eine multifunktionale Landwirtschaft ein.

en: The Federal Office for Agriculture (FOAG) is the Confederation's competence center for all core issues relating to the agricultural sector. The FOAG promotes multifunctional agriculture.

fr: L’Office fédéral de l’agriculture (OFAG) est le centre de compétence de la Confédération pour les questions relevant du secteur agricole. Il œuvre pour une agriculture multifonctionnelle.

it: L’Ufficio federale dell’agricoltura (UFAG) è il centro di competenza della Confederazione per le questioni inerenti al settore agricolo. Esso si impegna per un'agricoltura multifunzionale.

en: Federal Office for Agriculture FOAG

de: Bundesamt für Landwirtschaft BLW

fr: Office fédéral de l'agriculture OFAG

agri

en: Agriculture, fisheries, forestry and food

quantity

display_name: quantity


de: Jährliche Durchschnittspreise und Richtpreise für Ölsaaten auf der Wertschöpfungsstufe Produktion

en: Annual average prices and reference prices for oilseeds at the production level

fr: Prix moyens annuels et prix indicatifs des oléagineux au niveau de la production

it: Prezzi medi annui e prezzi indicativi delle oleaginose al livello della produzione

de: Marktzahlen Ölsaaten - Jährliche Verarbeitungspreise

en: Market figures for oilseeds - Annual processing prices

fr: Chiffres du marché des oléagineux - Prix de transformation annuels

it: Dati di mercato delle oleaginose - Prezzi di trasformazione annui

bundesamt-fur-landwirtschaft-blw

it: Ufficio federale dell'agricoltura UFAG

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

de: SPARQL Endpoint mit Vorauswahl des Graph

en: SPARQL Endpoint with graph preselection

fr: SPARQL Endpoint avec présélection du graphe


de: Jährliche Mengenangaben für Ölsaaten auf der Wertschöpfungsstufe Produktion

en: Annual quantities for oilseeds at the production level

fr: Quantités annuelles des oléagineux au niveau de la production

it: Quantità annue delle oleaginose al livello della produzione

de: Marktzahlen Ölsaaten - Jährliche Produktionsmengen

en: Market figures for oilseeds - Annual production quantities

fr: Chiffres du marché des oléagineux - Quantités de production annuelles

it: Dati di mercato delle oleaginose - Quantità di produzione annue

it: Economia e finanze


de: Monatliche Durchschnittspreise für Ölsaaten auf der Wertschöpfungsstufe Konsum.

en: Monthly average prices for oilseeds at the consumer level

fr: Prix moyens mensuels des oléagineux au niveau de la consommation

it: Prezzi medi mensili delle oleaginose al livello del consumo

de: Marktzahlen Ölsaaten - Monatliche Konsumentenpreise

en: Market figures for oilseeds - Monthly consumer prices

fr: Chiffres du marché des oléagineux - Prix de consommation mensuels

it: Dati di mercato delle oleaginose - Prezzi di consumo mensili


de: Jährliche Durchschnittspreise für Ölsaaten auf der Wertschöpfungsstufe Konsum.

en: Annual average prices for oilseeds at the consumer level

fr: Prix moyens annuels des oléagineux au niveau de la consommation

it: Prezzi medi annui delle oleaginose al livello del consumo

de: Marktzahlen Ölsaaten - Jährliche Konsumentenpreise

en: Market figures for oilseeds - Annual consumer prices

fr: Chiffres du marché des oléagineux - Prix de consommation annuels

it: Dati di mercato delle oleaginose - Prezzi di consumo annui


de: Jährliche Durchschnittspreise und Richtpreise für Futtermittel auf der Wertschöpfungsstufe Produktion

en: Annual average prices and reference prices for feedstuffs at the production level

fr: Prix moyens annuels et prix indicatifs des aliments pour animaux au niveau de la production

it: Prezzi medi annui e prezzi indicativi dei mangimi al livello della produzione

de: Marktzahlen Futtermittel - Jährliche Bruttoproduzentenpreise, Richtpreise

en: Market figures for feedstuffs - Annual gross producer prices, reference prices

fr: Chiffres du marché des aliments pour animaux - Prix bruts annuels des producteurs, prix indicatifs

it: Dati di mercato dei mangimi - Prezzi annui lordi dei produttori, prezzi indicativi

en: price market-data


de: Jährliche Mengenangaben für Futtermittel auf der Wertschöpfungsstufe Produktion

en: Annual quantities for feedstuffs at the production level

fr: Quantités annuelles des aliments pour animaux au niveau de la production

it: Quantità annue dei mangimi al livello della produzione

de: Marktzahlen Futtermittel - Jährliche Produktionsmengen

en: Market figures for feedstuffs - Annual production quantities

fr: Chiffres du marché des aliments pour animaux - Quantités de production annuelles

it: Dati di mercato dei mangimi - Quantità di produzione annue

en: market-data quantity

bundesamt-fur-landwirtschaft-blw

en: The Federal Office for Agriculture (FOAG) is the Confederation's competence center for all core issues relating to the agricultural sector. The FOAG promotes multifunctional agriculture.