en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Othmarsingen in Switzerland where one station is located within a natural deciduous forest stand (OTB) with European beech (_Fagus sylvatica_; 120-140 yrs) and lime trees (_Tilia sp._; 120-140 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, OTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Othmarsingen is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

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

envi

en: Environment

en:
Resource Title: Site photo of the forest station (OTB)
    Size: 319164 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/b1937555-6a89-4452-93f9-3cf418382fb6/download/otb.jpg
    Description: Site photo of the forest station from above (viewing downwards the slope).

en:
Resource Title: Site photo of the field station (OTF)
    Size: 11868194 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/74f4dcb2-e18d-40bb-bb18-8383f907a285/download/otf.jpg
    Description: Site photo of the field station from below (viewing upwards the slope).

en:
Resource Title: Data plot of the field station (OTF)
    Size: 302026 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/663df714-b0fb-45d3-b83f-3e80755a0a1a/download/otfplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Data plot of the forest station (OTB)
    Size: 255873 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f01faaab-8cee-4b07-b95c-1498f5b09285/download/otbplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Field station data (OTF)
    Size: 11582801 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/5b4e810a-ce77-47dc-9e23-ba691ade9192/download/otffield.csv
    Description: Data file.

en:
Resource Title: Site aerial photo (Othmarsingen)
    Size: 7687492 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/d74e4b24-bd75-4ce2-8bb5-4c04b77d8099/download/otfront.jpg
    Description: Site aerial photo from both Othmarsingen stations. Source: Google. 2016. Site aerial photo from both Othmarsingen stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Forest station data (OTB)
    Size: 10501901 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/70a7c0f0-0ab9-4d31-b80c-c656c9fca7d9/resource/f5f71a78-9574-4bcc-a326-4d455b6821a4/download/otbforest.csv
    Description: Data file.

long-term

display_name: long-term


$oid: OBSOLETE

en:
This data set includes GPS-derived snow water equivalent (SWE), snow depth (HS) and liquid water content (LWC) data for three entire snow-covered seasons (2015-2016, 2016-2017, 2017-2018) at the study plot Weissfluhjoch 2540 m a.s.l. (Davos, Switzerland). The procedure to derive these snow properties is described in Koch et al. (2019). The novel approach is based on a combination of GPS signal attenuation and time delay.
The dataset also includes corresponding validation data for SWE and HS measured at Weissfluhjoch, and some additional meteorological data used for interpretation of the snow cover evolution.
Please refer to the Read-me file for further details on the data.
These data are the basis of the following publication:
- Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., Prasch, M., Schweizer, J., and Mauser, W., 2019. Retrieval of snow water equivalent, liquid water content and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55(5), 4465-4487. https://doi.org/10.1029/2018WR024431

en: liquid-water-content snow snow-depth gps snow-cover

envidat

approval_status: approved

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

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

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

de: EnviDat: das Umwelt-Datenportal

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

en: GPS-derived data of SWE, HS and LWC and corresponding validation data

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

en:
Resource Title: Dataset with GPS-derived snow cover properties and validation data
    Size: 90714 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/01f4a113-7ad0-4993-9efa-f30bbe0f0474/download/gps-derived_snow_properties.csv
    Description: This file includes the data as described in the Read-me file.

format: CSV

media_type: text/csv

en:
Resource Title: Read-me
    Size: 109310 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cd57ac77-a276-4783-88c9-f52f51552d2c/resource/d491aadc-0a43-4caa-8b32-09c988ec4841/download/readme.pdf
    Description: The read-me file contains the description of the data provided.

format: PDF

media_type: application/pdf

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

snow

display_name: snow

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth


en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

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

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards

en:
Resource Title: Forest station data (SCB)
    Size: 10593777 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/f5242372-a0bd-42fa-a3be-038395f57134/download/scbforest.csv
    Description: Data file.

en:
Resource Title: Data plot of the field station (SCF)
    Size: 304254 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/43a2b0ef-6611-4bf2-9d60-60577413515d/download/scfplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Site photo of the field station (SCF)
    Size: 8615493 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/68696b24-8c46-48ad-8bb2-c15468b466ce/download/scf.jpg
    Description: Site photo of the field station from above (viewing downwards the slope).

format: jpeg

en:
Resource Title: Site photo of the forest station (SCB)
    Size: 388600 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/00b2b4fa-a6b1-40b7-b1b7-f5c35c91b1a2/download/scb.jpg
    Description: Site photo of the forest station from below (viewing upwards the slope).

en:
Resource Title: Further details on the data repository
    Size: 17153511 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/ee5c2d0d-e229-42e3-9144-37e92827f614/download/furtherdetailsschanis.pdf
    Description: Meta data documentation.

en:
Resource Title: Site aerial photo (Schänis)
    Size: 7026512 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/9a6bd255-998b-44c0-9ab2-cc501f9bb78b/download/scfront.jpg
    Description: Site aerial photo from both Schänis stations. Source: Google. 2016. Site aerial photo from both Schänis stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en:
Resource Title: Data plot of the forest station (SCB)
    Size: 253856 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/7a59ef22-0dea-4b48-b92e-8aaca534665c/download/scbplot.pdf
    Description: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en:
Resource Title: Field station data (SCF)
    Size: 10669678 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7e6a34bc-3c2c-45f2-8e3b-1b58f1ba5074/resource/9bd7e72f-3b65-4250-9f24-f945c4476a0e/download/scffield.csv
    Description: Data file.

climate-change

display_name: climate-change

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed


data-broedlin-cnp

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

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

envidat

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

en: Data Broedlin CNP

title_for_slug: data-broedlin-cnp

envi

en: Environment

en:
Resource Title: Data Broedlin-CNP
    Size: 1189635 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/9dd9a649-405d-413a-ad44-d859ea084bba/resource/c4fce049-b79d-495f-a44d-94f1d59b913a/download/broedlin_cnp_rawdata.xlsx
    Description:

format: XLS

en:
Resource Title: Data Broedlin-CNP-Release
    Size: 1249259 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/9dd9a649-405d-413a-ad44-d859ea084bba/resource/2ec747a1-3a2b-4743-b89f-db13a372c49f/download/broedlin_et_al_cnp_rawdata_v2.xlsx
    Description: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

nitrogen

display_name: nitrogen

phosphorus

display_name: phosphorus

soil

display_name: soil

stoichiometry

display_name: stoichiometry


en:
Naturally, large parts of the Swiss Plateau are characterised by wetlands
and meandering rivers. That this is no longer the case today is the result
of centuries of efforts to obtain dry land. But how did this process take
place? What were the relevant actors and what were their motivations? And
what can be said about the ecological consequences of this development?
In a research project on the history of wetlands in Switzerland since 1700,
we conducted (a) a historical analysis of the development of land use in
wetlands and the actors involved, (b) a historical-cartographic
reconstruction of wetland extent since 1850 and (c) an evaluation of
ecological effects of changes in wetlands on various organisms groups.
The series of GIS layers on wetland history stem from the second part of
the project. The area reconstruction is based on digitized and homogenized
signatures from national map series, as they have been available since
about 1850. Details about the digitalization process and the homogenization
procedures applied ("Rekonstruktionen") are included in Stuber & Bürgi
2019.
Book Citation:
 - Stuber M, Bürgi M (2019) Vom «eroberten Land» zum Renaturierungsprojekt. Geschichte der Feuchtgebiete in der Schweiz seit 1700. "Bristol Schriftenreihe", Band 59. Haupt Verlag, Bern, Stuttgart, Wien. 262 Seiten.

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

envidat

en: EnviDat: the Environmental Data Portal

en: History of wetlands in Switzerland since 1850

format: ZIP

ecology

display_name: ecology

environmental---history

display_name: environmental---history

environmental--policy

display_name: environmental--policy

historical-carthography

display_name: historical-carthography

switzerland

display_name: switzerland

wetlands

display_name: wetlands


automatic-classification-of-avalanches

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

en: avalanche monitoring seismic machine-learning localization

en: Automatic Classification of Avalanches

title_for_slug: automatic-classification-of-avalanches

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic


en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX  for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:
- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11
*References*:
-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH.  Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation  for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

en: snowmelt precipitation soil-moisture hydrology climate-change discharge

en: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland

en:
Resource Title: Daily simulated data for the reference period
    Size: 31447784 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/a67b4308-25ca-47ea-9aed-f529b8dc7f4d/download/reference.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

media_type: application/zip

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/05c1a038-40c2-423a-8ad9-f11b43689cf1/download/catchment_shapes.zip
    Description: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

en:
Resource Title: Daily simulated data for the future period
    Size: 1010416415 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6c1c0a28-a23f-4777-88b2-982841adb9b8/resource/be17bcca-3f34-414f-960e-bcbdd855ba81/download/climate_simulations.zip
    Description: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

climate-change

display_name: climate-change

discharge

display_name: discharge

hydrology

display_name: hydrology

precipitation

display_name: precipitation

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture


en: Data obtained in the free-air CO2 enrichment (FACE) experiment at Hofstetten, NW Switzerland, between 2009 and 2016. This dataset contains analyses of the soil solution throughout the experiment, especially for nitrate, as well as different analyses done at the end of the experiment: ammonium and nitrate captured by ion-exchange resin bags and extracted from soil cores, gross N mineralisation and nitrification measured by isotope dilution.

en: co2 picea-abies nitrogen face soil forest

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: Nitrogen availability under trees exposed to CO2 enrichment (FACE)

en:
Resource Title: Water analyses
    Size: 65553 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/50749920-cf85-4140-8802-54beffcf490e/download/water-analyses.csv
    Description: Analyses of water, especially soil solution

en:
Resource Title: Collection points
    Size: 453 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/1e7dfaf0-d504-4bab-ae3b-8f96181b4e84/download/points.csv
    Description: Collection points under the trees

en:
Resource Title: Gross N mineralisation and nitrification
    Size: 1183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/f6a9e85f-187b-4a55-9f57-e243d14906ab/download/mineralisation-nitrification.csv
    Description: Gross rates of N mineralisation and nitrification (15N dilution)

en:
Resource Title: Resin bags
    Size: 1237 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/594288d3-95ff-4ad6-914e-d3e9c1d0ea42/download/resin-bags.csv
    Description: Ammonium, nitrate and their 15N in resin bags

en:
Resource Title: Soil C and N
    Size: 1298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/dc99385c-0ab8-4c7f-88cd-cf53ba0aea41/download/soil-c-n.csv
    Description: Analyses of C, N and their stable isotopes in the soil, and soil pH

en:
Resource Title: Collection of soil solution
    Size: 33840 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6be8b9ed-d122-4f25-bdc1-26efe41a0ce0/resource/3cfe06e1-c280-4b18-903a-321ceef6044a/download/soil-solution.csv
    Description: Soil solution collected by suction cups

face

display_name: face

forest

display_name: forest

nitrogen

display_name: nitrogen

picea-abies

display_name: picea-abies

soil

display_name: soil


en: The dataset provides simulated 1) precipitation, 2) discharge, 3) soil moisture, and 4) low-flow simulations for 307 medium-sized catchments in Switzerland for the period 1981-2018. The data were simulated using the hydrological model PREVAH in its gridded-version. The simulated time series are provided at daily resolution. A detailed description of the modeling approach can be found in Brunner et al. 2019 submitted to NHESS.

en: soil-moisture hydrological-simulations prevah discharge low-flow precipitation drought-2018

envidat

en: EnviDat: the Environmental Data Portal

en: Hydro-meteorological simulations for the period 1981-2018 for Switzerland

envi

en: Environment

en:
Resource Title: Shapefile of 307 catchments in Switzerland
    Size: 103266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/7ebed8a1-98ce-4833-b1dd-64246bd07e5f/download/catchment_shapes.zip
    Description: Shapefile of 307 catchments for which simulations of precipitation, discharge, soil moisture, and low flow are provided. The OBJECTID entry corresponds to the data columns in the textfiles of the simulated data provided.

en:
Resource Title: Low-flow storage
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/a1338c95-09df-4bce-8d9c-7b059ae2f6a1/download/low_flow.txt
    Description: Simulated low-flow storage for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

format: TXT

media_type: text/plain

en:
Resource Title: Discharge
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/4c11fec4-0846-48a0-8dfe-9f7f5a4b574f/download/discharge.txt
    Description: Simulated discharge for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

en:
Resource Title: Soil moisture
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0ad6127b-f7d6-4356-9ac4-283166385578/download/soil_moisture.txt
    Description: Simulated plant-available soil moisture for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm.

en:
Resource Title: Precipitation
    Size: 53492028 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/62573c81-105f-4830-8ad1-6e745b13ae2a/resource/0f551cfd-804d-4f3a-80d9-c33562ea8b45/download/precipitation.txt
    Description: Simulated precipitation for the 307 medium-sized catchments. The first column provides the date in the format YYYYMMDD. One column corresponds to one catchment. Unit: mm/d.

hydrological-simulations

display_name: hydrological-simulations

low-flow

display_name: low-flow

prevah

display_name: prevah


en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).
 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

en: snow model erosion sediment-transport mars

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: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation

en:
Resource Title:
    Size: 3626 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/6ee21796-08ad-4069-a4cb-da6c35ffede7/download/figure4a.txt
    Description: Datasets of Figure 4a

en:
Resource Title:
    Size: 3587 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/1f30b883-fc62-4bbf-a8f5-88f716008097/download/figure2.txt
    Description: Datasets of Figure 2

en:
Resource Title:
    Size: 1434 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/8ab9bafb-62f5-4420-80da-a2a96d22be74/download/figure3a.txt
    Description: Datasets of Figure 3a

en:
Resource Title:
    Size: 2904 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/709f4330-9a35-4685-aac8-347067a5e483/download/figure4b.txt
    Description: Datasets of Figure 4b

en:
Resource Title:
    Size: 2190 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/82479779-1b20-486f-b4bc-414c6024c25d/download/figure3b.txt
    Description: Datasets of Figure 3b

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport

snow

display_name: snow


snow-depth-mapping

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground - 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths - 15m and smaller than - -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.
The work is published in:
Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

en: aerial-imagery avalanche snow-depth snow-water-equivalent image-matching snow-hydrology dsm

envidat

en: EnviDat: the Environmental Data Portal

en: Snow Depth Mapping

title_for_slug: snow-depth-mapping

en:
Resource Title: Snow depth mapping in high-alpine catchments using digital photogrammetry
    Size: 8122296 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/3b711e29-cea1-48e8-8de6-a008850c4f94/download/snow-depth-mapping-in-high-alpine-catchments.pdf
    Description:

en:
Resource Title: Snow depth map 20140417
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/5cf5d3a5-555d-429e-9819-6c93ccce6dfc/download/snowmap_2014_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

format: TIFF

media_type: image/tiff

en:
Resource Title: Snow depth map 20160126
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/9229984f-b417-45e5-8dbe-031f295d0406/download/snowmap_20160126_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en:
Resource Title: Snow depth map 20100416
    Size: 412324171 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/4ba96052-9e3e-4b7a-9968-2dcc58fc96c0/download/snowmap_2010_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20160309
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/ceae68a6-28f9-43f4-8ff5-9715588ade57/download/snowmap_20160309_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20130415
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/da3ca703-c629-45c0-8dac-e78645b0fa5e/download/snowmap_2013_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

en:
Resource Title: Snow depth map 20150415
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/578e95ce-ffa0-4fc6-8109-d9653b2c622a/download/snowmap_2015_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20160420
    Size: 392871502 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/bc035833-3193-4394-af92-f8d195d5e034/download/snowmap_20160420_ads_100_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m

en:
Resource Title: Snow depth map 20120320
    Size: 412272526 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/32acdacc-98dd-4fa7-87e8-449278bd24f0/resource/aff41055-8e6e-4287-b52d-2c2fb61633c2/download/snowmap_2012_ads_80_extent_maskiert_nosnow0_noausreisser.tif
    Description: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent


en:
Throughfall, litterflow and soil solution were sampled during one whole year under five Oriental beech trees in a mixed Hyrcanian beech forest. The amounts of Ca2+, Mg2+, K+ and Na+ in these fluxes were calculated based on their concentrations and the sampled volumes, and subsequently compared with the respective fluxes in the rainfall and soil solution of an adjacent forest gap.
In addition six soil profiles, one close to every single tree and one in the forest gap, were analyzed for pH, CaCO3, organic matter and texture.

en: magnesium fagus-orientalis-lipsky potassium calcium biogeochemical-cycling

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: Base cation dynamics in an Oriental beech forest

envi

en: Environment

biogeochemical-cycling

display_name: biogeochemical-cycling

calcium

display_name: calcium

fagus-orientalis-lipsky

display_name: fagus-orientalis-lipsky

magnesium

display_name: magnesium

potassium

display_name: potassium


seilaplan

en:
Cable-based technologies have been a backbone for harvesting on steep slopes. The layout of a single cable road is challenging because one must identify intermediate support locations and heights that guarantee structural safety and operational efficiency while minimizing set-up and dismantling costs. Seilaplan optimizes the layout of a cable road by
Seilaplan stands for Cable Road Layout Planner. Seilaplan is able to calculate the optimal rope line layout (position and height of the supports) between defined start and end coordinates on the basis of a digital elevation model (DEM).
The program is designed for Central European conditions and is designed on the basis of a fixed suspension rope anchored at both ends. For the calculation of the properties of the load path curve an iterative method is used, which was described by Zweifel (1960) and was developed especially for standing skylines. When testing the feasibility of the cable line, care is taken that 1) the maximum permissible stresses in the skyline are not exceeded, 2) there is a minimum distance between the load path and the ground and 3) when using a gravitational system, there is a minimum inclination in the load path. The solution is selected which has a minimum number of supports in the first priority and minimizes the support height in the second priority.
The newly developed method calculates the load path curve and the forces occurring in it more accurately than tools available on the market to date (status 2019) and is able to determine the optimum position and height of the intermediate supports.
The reason for the more accurate results of the new tool is the assumption that the skyline is anchored at both end points. Forest cable yarders used in Europe have a skyline that is fixed at both ends. The behaviour of fixed-anchored suspension ropes is very difficult to describe mathematically and cannot be solved analytically. For this reason, simplified linearized assumptions have so far been used in the forestry sector, which corresponds to the behaviour of a weight-tensioned suspension rope and is known as the Pestal method (1961). Weight-tensioned suspension ropes are used for passenger transport.
For the calculation of the load path curve we use an iterative method, which was described by Zweifel (1960) and developed especially for fixed anchored suspension ropes. This makes mathematics much more demanding, but leads to more accurate and realistic results. Since there are no current models which describe the installation costs with adequate accuracy, the solution sought is the one which has a minimum number of supports in the first priority and minimises the support height in the second priority (Figure 2). The presented method is the first one, which starts from a fixed anchored supporting rope and identifies the mathematically optimal column layout at the same time. In contrast to methods that assume a weight-tensioned suspension rope, this approach achieves more realistic solutions with longer spans and lower support heights, which ultimately leads to lower installation costs. Background information on rope mechanics and calculation methods is documented in Bont and Heinimann (2012).
License: GNU, General Public License, Version 2 or newer.
Literature:
Bont, L., & Heinimann, H. R. (2012). Optimum geometric layout of a single cable road. European journal of forest research, 131(5), 1439-1448.

en: software qgis catenary-load-path cable-yarding cable-planning steep-terrain-harvesting python

en: Seilaplan

title_for_slug: seilaplan

cable-planning

display_name: cable-planning

cable-yarding

display_name: cable-yarding

catenary-load-path

display_name: catenary-load-path

python

display_name: python

qgis

display_name: qgis

software

display_name: software

steep-terrain-harvesting

display_name: steep-terrain-harvesting


stem-radius-change-data-pfynwald

en:
**Continuously measured stem radius change data (time series) from high-precision point dendrometers (Natkon) mounted on the stems of Pinus sylvestris trees at 1.5 m in the Pfynwald VPDrought experimental area.**
The data originates from the **TreeNet database**. The published data represents the highest quality data following automatic and manual corrections (LM data level).
**The dataset contains the following files:**
- 10-minute resolution time series (.parquet)
- Daily resolution time series (.csv and .parquet)
- Metadata (.csv)
- Readme (.txt)
Main variables are stem radius changes (SRC), tree water deficit (TWD) and radial stem growth (GRO).

**The site area contains the following site_ids (treatments)**
| 86 | Pfynwald-Control
| 89 | Pfynwald-Irr_Stop
| 90 | Pfynwald-Irrigation
| 145 | Pfynwald-Irrigation_VPD
| 146 | Pfynwald-Roof
| 147 | Pfynwald-Roof_VPD
The measurements cover data from 2011 to 2025. All data is in UTC + 1 hour (Central European Time CET, winter time, no DST).

en: pinus-sylvestris ecophysiology forest time-series drought-legacy dendrometer treenet bark-growth climate-change data-publication drought-experiment wood-growth alps drought-stress treewaterdeficit automated-monitoring

envidat

en: EnviDat: the Environmental Data Portal

en: Stem Radius Change Data Pfynwald

title_for_slug: stem-radius-change-data-pfynwald

en:
Resource Title: Pfynwald_Dendro_2010-2025.zip
    Size: 446097419 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/60f3c95c-fe5d-49f0-89af-f325ef864cf0/resource/aec4c998-c6dd-4000-bd4e-c9bc79fe7b22/download/pfynwald_dendro_2010-2025.zip
    Description:

en:
Resource Title: Pfynwald_README.txt
    Size: 12082 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/60f3c95c-fe5d-49f0-89af-f325ef864cf0/resource/8c24a11c-ecda-404c-9dd4-078629e89559/download/pfynwald_readme.txt
    Description:

alps

display_name: alps

automated-monitoring

display_name: automated-monitoring

bark-growth

display_name: bark-growth

climate-change

display_name: climate-change

data-publication

display_name: data-publication

dendrometer

display_name: dendrometer

drought-experiment

display_name: drought-experiment

drought-legacy

display_name: drought-legacy

drought-stress

display_name: drought-stress

ecophysiology

display_name: ecophysiology

forest

display_name: forest

pinus-sylvestris

display_name: pinus-sylvestris

time-series

display_name: time-series

treenet

display_name: treenet

treewaterdeficit

display_name: treewaterdeficit

wood-growth

display_name: wood-growth


en:
**Continuously measured stem radius change data (time series) from high-precision point dendrometers (Natkon) mounted on the stems of Pinus sylvestris trees at 1.5 m in the Pfynwald VPDrought experimental area.**
The data originates from the TreeNet database. The published data represents the highest quality data following automatic and manual corrections (LM data level).
The dataset contains the following files:
- 10-minute resolution time series (.parquet)
- Daily resolution time series (.parquet)
- Readme (.txt)
Main variables are stem radius changes (SRC), tree water deficit (TWD) and radial stem growth (GRO).
The measurements cover data from 2011 to 2025. All data is in UTC + 1 hour (Central European Time CET, winter time, no DST).

en: drought twd pinus-sylvestris pfynwald irrigation vpd stem-growth point-dendrometer vpdrought

en: Pfynwald VPDrought  experiment stem radius changes (TreeNet)

en:
Resource Title: pfynwald_vpdrought_dendrometer_2025.zip
    Size: 62493309 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/571cf7ad-edda-4e1f-9e9d-45014c39a9e2/resource/cea43ffe-6437-4b0e-8d58-398026cbde41/download/pfynwald_vpdrought_dendrometer_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_dendrometer_2024.zip
    Size: 61781663 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/571cf7ad-edda-4e1f-9e9d-45014c39a9e2/resource/425594e2-7210-49a8-82b7-1bdfc4cbaf33/download/pfynwald_vpdrought_dendrometer_2024.zip
    Description:

drought

display_name: drought

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

point-dendrometer

display_name: point-dendrometer

stem-growth

display_name: stem-growth

twd

display_name: twd

vpd

display_name: vpd

vpdrought

display_name: vpdrought


en: This dataset includes the diversity of soil prokaryotes, fungi and micro-eukaryotes in unmanaged forest reserves with managed forests across nine locations within Switzerland. Forests have been exploited for resources for centuries, which has caused disturbances, altered community structure, and reduced diversity at different scales. Strict forest reserves, where no forest management is practiced, have been implemented to promote biodiversity, by allowing old trees with microhabitats and high deadwood amounts. However, the effectiveness of forest reserves on soil microbial diversity and functional traits are little known at a national scale in Swiss forests. The associated metadata includes local environmental conditions, such as soil pH, organic C, N, deadwood volume, MAT and MAP, and forest type (coniferous vs deciduous).

en: microeukaryotes prokaryotes soil-biodiversity forest-management fungi

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: Management practices shape soil fungal diversity and functional traits in Swiss forests

en:
Resource Title: Environmental data
    Size: 13926 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/04e9459c-7024-46c3-9c33-a50a33da55b2/resource/c27f01d0-217e-4b50-88c0-70421ec0334f/download/forest-management-soilbd-environmental-data-envidat.csv
    Description: Environmental Data such as soil abiotic properties

en:
Resource Title: Fungi
    Size: 2931315180 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Fungi%20%28ITS%29%2F
    Description:

en:
Resource Title: Microeukaryotes
    Size: 2512555868 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Microeukaryotes%20%2818S%29%2F
    Description:

en:
Resource Title: Prokaryotes
    Size: 2738041651 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.780%2FForestMan_SoilBD_Prokaryotes%20%2816S%29%2F
    Description:

forest-management

display_name: forest-management

fungi

display_name: fungi

microeukaryotes

display_name: microeukaryotes

prokaryotes

display_name: prokaryotes

soil-biodiversity

display_name: soil-biodiversity


en:
This dataset contains the results of greenhouse gas emission modeling for the five Swiss Shared Socioeconomic Pathways (SSP-CH) up to the year 2100. Six sector-specific reduced-complexity models were developed specifically for this analysis, enabling the modelling of the SSP-CH storylines. Accordingly, the dataset comprises the outputs of all six models, generated both in the absence of and under the implementation of additional climate policy packages, referred to as Shared Policy Assumptions (SPAs; see related publications).
- Transport model (energy consumption by energy source and transport type/fleet mix)
- Housing model (heating demand and GHG emissions per building category)
- Electricity model (electricity consumption, electricity generation by energy source, installed capacity, district heating)
- Industry model (energy consumption by energy source, subdivided into raw materials/building materials, consumer goods, and processed goods)
- Agriculture model (feed digestion in livestock, manure storage, and nitrogen fertilization)
- Export/Import model (product quantities in import and export, broken down into consumer goods, raw materials/building materials, and processed goods)
- Synthesis model

en: greenhousegas-modelling qualitative-scenarios socioeconomic-scenarios national-ssp emissions-scenarios

envidat

en: EnviDat: the Environmental Data Portal

en: Results of greenhouse gas modelling of the Swiss Shared Socioeconomic Pathways (SSP-CH)

envi

en: Environment

en:
Resource Title: SSP-CH_GHG_housing_model.xlsx
    Size: 3051356 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/913c1ae0-418b-4f31-8b51-9ef1e364b3fd/download/ssp-ch_ghg_housing_model.xlsx
    Description: SSP-CH GHG modelling results of Housing model (heating demand and GHG emissions per building category). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_transport_model.xlsx
    Size: 9070182 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/be82872b-5fd7-4498-a4b9-2141dd5eb00f/download/ssp-ch_ghg_transport_model.xlsx
    Description: SSP-CH GHG modelling results of Transport model (energy consumption by energy source and transport type/fleet mix). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_transport_model.xlsx
    Size: 9070182 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/c147c40f-3431-4847-a954-5a80b6a38cf1/download/ssp-ch_ghg_transport_model.xlsx
    Description: This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_industry_model.xlsx
    Size: 465818 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/3e81b975-33bf-4327-bf18-3ae32f36b21d/download/ssp-ch_ghg_industry_model.xlsx
    Description: SSP-CH GHG modelling results of Industry model (energy consumption by energy source, subdivided into raw materials/building materials, consumer goods, and processed goods). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_electricity_model.xlsx
    Size: 1195377 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/b543e472-b1c0-488c-8a71-ff09be0d140d/download/ssp-ch_ghg_electricity_model.xlsx
    Description: SSP-CH GHG modelling results of Electricity model (electricity consumption, electricity generation by energy source, installed capacity, district heating). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_imp_exp_model.xlsx
    Size: 11240735 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/c80f618c-fd87-4c43-920e-77c8081ccd5a/download/ssp-ch_ghg_imp_exp_model.xlsx
    Description: SSP-CH GHG modelling resluts of Export/Import model (product quantities in import and export, broken down into consumer goods, raw materials/building materials, and processed goods). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_Synthesis_model.xlsx
    Size: 386540 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/a1e54990-11c5-43cf-b922-d839925b4078/download/ssp-ch_ghg_synthesis_model.xlsx
    Description: SSP-CH GHG modelling results of Synthesis model. This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

en:
Resource Title: SSP-CH_GHG_agriculture_model.xlsx
    Size: 624865 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c02b9e4b-32dc-46bb-aa43-9d648665b089/resource/b8d73680-8159-46ac-98f6-9d97131f5c2e/download/ssp-ch_ghg_agriculture_model.xlsx
    Description: SSP-CH GHG modelling results of Agriculture model (feed digestion in livestock, manure storage, and nitrogen fertilization). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Program. The following individuals participated in the compilation of this data: Oberpriller, Q., Schmid, N., Kemmler, A., Gubler, L., Bogler, S., Giger, D., Piegsa, A., Brutsche, A., Kreidelmeyer, S., Vu M. Ph., Black, B., Kirchner, A., Füssler, J.

emissions-scenarios

display_name: emissions-scenarios

greenhousegas-modelling

display_name: greenhousegas-modelling

national-ssp

display_name: national-ssp

qualitative-scenarios

display_name: qualitative-scenarios

socioeconomic-scenarios

display_name: socioeconomic-scenarios


en: This dataset comprises qualitative data for the development of the five Swiss Shared Socioeconomic Pathways (SSP-CH) up to the year 2100. First, it comprises projections of 22 socioeconomic factors, each represented by four to five factor-specific trajectories that form the basis of the qualitative scenario storylines. Second, it includes an input table providing concise qualitative characterizations of 63 socioeconomic factors across the five SSP-CH scenarios.

en: ssp-storylines national-ssps scenario-development socioeconomic-scenarios qualitative-scenarios

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: Shared Socioeconomic Pathways for Switzerland (SSP-CH): qualitative data for scenario development

en:
Resource Title: Input-table_final_e.xlsx
    Size: 45599 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/9eef7ee5-8a6d-47c2-9952-447cd39018e4/download/input-table_final_e.xlsx
    Description: SSP-CH Input table: qualitative description of 63 socioeconomic factors in the 5 SSP-CH (english). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

en:
Resource Title: SSP-CH_Faktorprojektionen_d.pdf
    Size: 3030385 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/11d2b1ab-8a77-407e-9732-db22a853e03f/download/faktorprojektionen_beschreibung_d.pdf
    Description: SSP-CH factor projections of 20 socioeconomic factors (german). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

en:
Resource Title: Input-Tabelle_final_d.xlsx
    Size: 198502 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/3e5310e5-4038-4782-b3c9-b64100709e32/resource/3458c684-6a22-437e-99cf-20c9f494d521/download/input-tabelle_final_d.xlsx
    Description: SSP-CH Input table: qualitative description of 63 socioeconomic factors in the 5 SSP-CH (german). This data was compiled as part of the Project "Socioeconomic Scenarios for Switzerland" within the NCCS-Impacts Programme. The following individuals participated in the compilation of this data: Gubler, L., Tschumi, P., Pütz, M., Seidl, I.

national-ssps

display_name: national-ssps

scenario-development

display_name: scenario-development

ssp-storylines

display_name: ssp-storylines


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

envidat

en: EnviDat: the Environmental Data Portal

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

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.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

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: 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

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_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:

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:
Spatio-temporal vegetation models are essential for simulating dynamics and shifts
in species distributions over large areas, particularly under global change. One such
model is the dynamic forest landscape model TreeMig. We have developed a frame-
work that makes the model more user-friendly, improves its functionality, and expands
its possibilities. The framework consists of the improved TreeMig model, the R pack-
age ‘TreeMig-R’ for pre-processing input data, model execution and visualization and a
graphical user interface (GUI) for ease of use. The code of the TreeMig Package and the GUI is stored here.

en: r-package landscape gui dynamic-modelling forest-model

en: Code of TreeMig Package version 1

envi

en: Environment

dynamic-modelling

display_name: dynamic-modelling

landscape

display_name: landscape


en:
We used 1463 observations of early leaf discoloration presence or absence in Switzerland's European beech (*Fagus sylvatica L.*) forests between 2018 and 2023 and interpolated Sentinel-2 vegetation index time series from Koch et al. (2024) to train a support vector classifier of early leaf discoloration. We applied this classifier to the European beech dominated forest area of Switzerland over the same time period to estimate a probability of early leaf discoloration between 0 and 1 (high probability of early leaf discoloration). The maps intentionally exclude legacy effects of drought like crown dieback or mortality which occurred in prior years.
Early leaf discoloration maps are available at the end of every summer month (June, July, August, and September) 2017 to 2023. Additional maps are available every 5-days during the summer months of 2018. Probability of early leaf discoloration at each date is provided as a GeoTIFF file with a scaled value range of 0 to 10,000 such that a probability of 0.9 is represented by a value of 9000 (a high probability of early leaf discoloration). An optimized probability threshold of 0.4 (4000) is recommended for classification into discolored and not discolored pixels. More details on the methods and results can be found in the publication of Bloom et al. (2026).
***These maps represent an interpreted remote sensing product that approximates ground observations of early leaf discoloration across Switzerland's European beech dominated forests.***
Given ongoing efforts to operationalize an early discoloration pipeline, all data is currently available upon reasonable request. An example of the 2018 5-day time series in the Hardwald (Canton Basel-Land) is available for immediate download.

en: sentinel-2 switzerland european-beech early-defoliation forest drought-2018 drought early-warning

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: Early leaf discoloration maps for Switzerland's European beech forests

drought

display_name: drought

early-defoliation

display_name: early-defoliation

early-warning

display_name: early-warning

european-beech

display_name: european-beech

switzerland

display_name: switzerland


en:
The TreeMig framework allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
Here, case study examples in Switzerland are given that simulate the dynamics and spatial spread of competing tree species in a region in Switzerland, the invasion of a hypothetical invasive tree species, and the control of this species via a management model coupled to TreeMig.  The datasets consist of the installation- and GUI starting-script,  example environmental input data for Switzerland, the simulation environment, and further R-scripts for running the simulations and plotting the simulation results directly from R and for coupling TreeMig to the forest management model.

en: climate-change land-use forest-management species-migration treemig spatial-modelling bioclimatic-variables example-applications r-package forest forest-dynamics

envidat

en: EnviDat: the Environmental Data Portal

en: Case study applications demonstrating the use and potential of the TreeMig framework v1

en:
Resource Title: installAndRunTreeMigWrapperAndGUI_std.R
    Size: 553 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/916c8a50-1d57-4e28-97c8-f50b8a9f7bf7/download/installandruntreemigwrapperandgui_std.r
    Description: R-script to install the TreeMig framework and start the graphical user interface

en:
Resource Title: readme_descriptioninputdata.pdf
    Size: 263110 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/5abbe67b-ab73-413b-bff8-5cccf5347b1c/download/readme_descriptioninputdata.pdf
    Description:

en:
Resource Title: ExampleApplicationsTreeMig.zip
    Size: 1676301558 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/609e85c8-98d0-4043-be91-48bd32c162ea/download/exampleapplicationstreemig.zip
    Description: 1) Simulation environment TMEnvironmentExampleApplications for the simulation of the case study applications. It contains a) simulation settings (folder C),  b) species parameters (folder P), c) folders S, R and P for the state files and results and plots to be produced, and the binaries of the TreeMig model.
2) Input data for Switzerland in TMInputData (Climate, soil, land cover, DEM)
3) Several R scripts (folder Scripts) to run and plot the simulations directly from R without having to use the graphical user interface.
For learning how to use TreeMig we recommend the starter kit https://www.doi.org/10.16904/envidat.533.

en:
Resource Title: ExampleApplicationsTreeMig.zip
    Size: 1686005000 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/0f59997f-3e90-4b25-9e5b-37b641d9769b/download/exampleapplicationstreemig.zip
    Description: 1) Simulation environment TMEnvironmentExampleApplications for the simulation of the case study applications. It contains a) simulation settings (folder C),  b) species parameters (folder P), c) folders S, R and P for the state files and results and plots to be produced, and the binaries of the TreeMig model.
2) Input data for Switzerland in TMInputData (Climate, soil, land cover, DEM)
3) Several R scripts (folder Scripts) to run and plot the simulations directly from R without having to use the graphical user interface.
For learning how to use TreeMig we recommend the starter kit https://www.doi.org/10.16904/envidat.533.

en:
Resource Title: InstructionsForRunningTheSimulations.pdf
    Size: 127302 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/32c74611-c61e-48be-998b-6722bbb697c8/download/instructionsforrunningthesimulations.pdf
    Description: A condensed instruction for running the presented simulations.

en:
Resource Title: InstructionsForRunningTheSimulations.pdf
    Size: 68995 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4e735cce-be7e-4279-9f96-893d8d789924/resource/830a45db-7985-42f6-8864-4961fe5ef5a2/download/instructionsforrunningthesimulations.pdf
    Description: A condensed instruction for running the presented simulations.

bioclimatic-variables

display_name: bioclimatic-variables

climate-change

display_name: climate-change

example-applications

display_name: example-applications

forest

display_name: forest

forest-management

display_name: forest-management


en:
Regional disturbance predisposition maps for windthrow, bark beetle and snow breakage. The maps are created using spatially explicit data of classified forest structure and site factor parameters. The classified input parameters were weighted according to their effect on windthrow, bark beetle and snow breakage predisposition using an expert-based model. The predisposition raster maps (10 x 10 m) represent the sum of expert-weighted effects on the predisposition and are provided as raw values (sum of the effects on predisposition) and as classified layers.
Classified predisposition maps are encoded as follows:
1: low predisposition (-50% quantile based on raw predisposition values)
2: increased predisposition (50–75% quantile)
3: high predisposition (-75–95% quantile)
4: extreme predisposition (-95% quantile)
Also included are the derived forest structure maps for development stage, dominant stand height, number of stems and canopy cover used for the predisposition mapping, as well as the R scripts and example data to re-create these parameters. Forest structure parameters are based on a data set of individual trees detected using a high-resolution vegetation height model. Further included are ArcPy scripts and example data to re-create the predisposition maps. Running the ArcPy scripts requires a valid ArcGis license including the extensions "SpatialAnalyst", "ImageAnalyst" and "3D".
The example data provided here is assembled from different sources; please check the related publication Bührle et al. (in review) for data sources and further information about the processing, the expert-based model, the forest structure derivation and the predisposition mapping.
Also consider reviewing the related datasets and publications Bast et al. (2025) for more information about canopy layering derivation and individual tree detection (ITD).

en: canopy-cover development-stage predisposition-mapping itd forest-structure windthrow stem-number tree-detection snow-breakage als bark-beetle predisposition stand-height

en: Regional bark beetle windthrow and snow breakage disturbance predisposition maps

en:
Resource Title: 01_predispostion_maps.zip
    Size: 19881001 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/59df8818-2e56-4794-9152-3652c20fe6fc/download/01_predispostion_maps.zip
    Description: Classified and raw value predisposition maps for bark beetle, windthrow and snow breakage

en:
Resource Title: 02_python_scripts_predisposition_mapping.zip
    Size: 438323 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/e165fc12-ca86-423f-807a-d7cf1c8535a5/download/02_python_scripts_predisposition_mapping.zip
    Description: ArcPy-Python scripts and demo data to create the bark beetle, windthrow and snow breakage predisposition maps.

en:
Resource Title: 04_forest_structure_maps.zip
    Size: 34068234 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/cd162993-bc30-46c1-816b-0722c3d83a50/download/04_forest_structure_map.zip
    Description: Maps of development stage, number of stems, dominant stand height and canopy coverage based on single trees detected from a vegetation height model.

en:
Resource Title: 03_rcode_forest_structure.zip
    Size: 103693681 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/171b832f-9fd1-40c0-b2d6-f8f137b572e8/resource/42199442-7c55-48ed-a3a7-04aaf9967da0/download/03_rcode_forest_structure.zip
    Description: R-codes and demo data to derive the forest structure parameters: development stage, number of stems, dominant stand height, and canopy coverage based on single trees detected from a vegetation height model. These parameters are necessary input parameters for predisposition mapping.

als

display_name: als

bark-beetle

display_name: bark-beetle

canopy-cover

display_name: canopy-cover

development-stage

display_name: development-stage

forest-structure

display_name: forest-structure

itd

display_name: itd

predisposition

display_name: predisposition

predisposition-mapping

display_name: predisposition-mapping

snow-breakage

display_name: snow-breakage

stand-height

display_name: stand-height

stem-number

display_name: stem-number

tree-detection

display_name: tree-detection

windthrow

display_name: windthrow


en:
Phenology, growth, NSC and Amax data used for the following paper:
Early-season warming advances autumn senescence in temperate tree saplings in association with early growth dynamics  published in Plant Cell & Environment 2026.

en: leaf-senescence warming-experiment nsc growth tree-phenology

envidat

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

en: Data for the paper: Early-season warming advances autumn senescence in temperate tree saplings in association with early growth dynamics

envi

en: Environment

en:
Resource Title: ReadMe_Data information.docx
    Size: 17668 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/90ccc75b-bc5e-4968-92a2-38d3452341a8/resource/28146b13-81fd-4625-bc7a-6f55ee39796d/download/readme_data-information.docx
    Description:

en:
Resource Title: Data.zip
    Size: 42598 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/90ccc75b-bc5e-4968-92a2-38d3452341a8/resource/6a336540-7ba5-471e-b452-db20bc540b6a/download/data.zip
    Description: Data used in the paper published in Plant Cell & Environment Vitasse et al. 2026

growth

display_name: growth

leaf-senescence

display_name: leaf-senescence

nsc

display_name: nsc

tree-phenology

display_name: tree-phenology

warming-experiment

display_name: warming-experiment


en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

en: drought gas-exchange vpd photosynthesis acclimation pinus-sylvestris fluorescence

envidat

en: EnviDat: the Environmental Data Portal

en: 2013-2020 gas exchange at Pfynwald

en:
Resource Title: Instrument details
    Size: 1174 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/e7342279-bf44-451b-afa2-78cb77babf5e/download/instrumentdetails_pfynwald.csv
    Description: Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Variable names and units
    Size: 15839 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/39614a56-a982-4123-a8d6-e9aaa51c838a/download/variable_names_units.xlsx
    Description: Variable names, description and units for the Pfynwald Gas exchange data

en:
Resource Title: Methods ACi curves
    Size: 731 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c7536938-120e-4975-97e4-e40649637634/download/methodsmetadata_acicurves.csv
    Description: Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods fluorescence
    Size: 534 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/1d2343e4-bdf9-4ff0-9582-0c9ef11e139e/download/methodsmetadata_fluoresence.csv
    Description: Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods diurnal measurements
    Size: 593 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/45f2d648-386c-42bb-b766-6f804e7c7de6/download/methodsmetadata_diurnal.csv
    Description: Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Pfynwald gas exchange
    Size: 4072706 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/3d0f2a0a-c365-4f15-a8e7-312943cbcad6/download/pfynwald_gasexchange_201306_202010.csv
    Description: Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods survey
    Size: 596 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/229fbf92-a0ff-44b5-b799-b55fabe2b99c/download/methodsmetadata_point.csv
    Description: Parameters and methods for point measurements / survey measurements

en:
Resource Title: Methods light response
    Size: 607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c5ef8bc5-79ab-4aec-9e02-d031e1e7d976/download/methodsmetadata_lightcurves_darkresp.csv
    Description: Methods and parameters for light response curves

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd


vegetation-height-model-lidar-nfi

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on
LiDAR data acquired in the framework of the **swissSURFACE3D** campaign (swisstopo).
To derive vegetation height, the classified point cloud got normalized by calculating height above ground for all points not belonging to the class ground (2). Vegetation point (class 3,4,5) got then rasterized to a grid size of 0.5 m using an interpolation distance of one grid cell. Raster cells not belonging to a vegetation class got set to 0 m above ground.
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI).
Each year about 1/6 of switzerland surface is updated using swissSURFACE3D data in leaf-off state.

en: nfi forest three-dimensional vegetation-classification vegetation point-cloud vegetation-height

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: Vegetation Height Model LiDAR NFI

title_for_slug: vegetation-height-model-lidar-nfi

en:
Resource Title: 2024 Vegetation Height Model LiDAR NFI
    Size: 149786984448 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2024%2F
    Description: Vegetation Height Model of Switzerland for the year 2024 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

en:
Resource Title: 2025 Vegetation Height Model LiDAR NFI (current)
    Size: 160202280141 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2025%2F
    Description: Vegetation Height Model of Switzerland for the year 2025 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

forest

display_name: forest

nfi

display_name: nfi

point-cloud

display_name: point-cloud

three-dimensional

display_name: three-dimensional

vegetation

display_name: vegetation

vegetation-classification

display_name: vegetation-classification

vegetation-height

display_name: vegetation-height


en:
Background information
Climate change-induced range expansion of treeline populations depends on their successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules. The Global Treeline Range Expansion Experiment (G-TREE) is a global initiative involving researchers from Europe, North America, Australia and New Zealand (Brown et al., 2013). At 15 alpine and Arctic treeline sites worldwide the mechanisms determining the elevational and latitudinal distribution of tree populations are studied using a standardized experimental approach. In summer 2013, a multifactorial seedling recruitment experiment has been established at the Stillberg ecological treeline research site. The aim of this experiment, is to quantify the effect of multiple abiotic and biotic drivers on emergence, survival, and growth of *Larix decidua* and *Picea abies* seedlings in replicated plots along an elevation gradient with three sites below (1930 m a.s.l.), at (2090 m a.s.l.), and above treeline (2410 m a.s.l.; Frei et al., 2018). All plots have been surveyed annually to count seedlings and to measure their total height. Additional environmental factors, such as soil temperature, have been recorded.
 Experimental design
The Stillberg research area is located in the Eastern Swiss Alps near Davos, Switzerland. The site has been used for several long-term monitoring as well as experimental studies for the last four decades. Our G-TREE experiment consists of a lowest site located in a subalpine Larch-Spruce forest (*Larici-Picetum*) dominated by *Larix decidua* and *Picea abies* (1930 m a.s.l.), a transition zone site dominated by alpine shrubs (2100 m a.s.l.), and an uppermost site in an alpine meadow with some dwarf shrubs (2390 m a.s.l.). The three experimental sites were set up following the standard protocol of the global G-TREE initiative (Brown et al., 2013). In a split-plot design, 20 plots (224 cm × 45 cm) were established at each site, which were randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification (i.e. seeding and scarification, seeding only, scarification only, and full control), resulting in five replications per main treatment combination. Each plot was divided into 16 split-plots (22.5 cm × 28 cm), to which treatment combinations of four additional two-level factors species (larch and spruce), provenance (low- and high-elevation), herbivore exclosure (with and without exclosure), and seeding year (2013, 2014) were randomly assigned, which resulted in a total of 960 split-plots (Details see Frei et al. 2018).
 Data description
All plots have been surveyed annually to count seedlings and to measure their total height. Seedling height was assessed with a hand ruler as the total length from the original emerging point to the apical meristem (Details see Frei et al. 2018). Additionally, soil temperature at each site, has been continuously recorded since 2013. Here, we present data from eight years (2013–2021).

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

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

envi

en: Environment

climate-change

display_name: climate-change

g-tree

display_name: g-tree

larix-decidua

display_name: larix-decidua

picea-abies

display_name: picea-abies

seedling-recruitment

display_name: seedling-recruitment

stillberg

display_name: stillberg

swiss-alps

display_name: swiss-alps

treeline

display_name: treeline


en:
In the associated study [1], two time-lapse temperature gradient metamorphism series of three-dimensional micro-computed tomography images of snow (obtained by [2]) have been used to model the decrease of specific surface area (SSA) over time based on the pore-scale physics. We conducted finite element simulations of one-way coupled heat and mass diffusion in order to estimation the spatial pattern of water vapor deposition and sublimation, which controls the evolution of the SSA over time. We notably studied the influence of the condensation coefficient, a key but poorly constrained physical parameter.
This dataset provides the parameters used for the mesh generation and the finite element simulations. It also includes the ice fraction, specific surface area per unit volume and surface average of mean curvature and vapor field obtained as outputs from the mesh process and the simulations.
[1]: Braun, A., Fourteau, K., and Löwe, H.: A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1947, 2023.
[2]: Pinzer, B. R., Schneebeli, M., and Kaempfer, T. U.: Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography, The Cryosphere, 6, 1141–1155, https://doi.org/10.5194/tc-6-1141-2012, 2012.

en: snow metamorphism time-series microstructure fem x-ray-tomography

envidat

en: EnviDat: the Environmental Data Portal

en: Simulation parameters and outputs for a rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism

format: ODS

fem

display_name: fem

metamorphism

display_name: metamorphism

microstructure

display_name: microstructure

snow

display_name: snow

time-series

display_name: time-series

x-ray-tomography

display_name: x-ray-tomography


ensemble-hydrograph-separation-scripts

en:
Calculation scripts that perform ensemble hydrograph separation.  Identical scripts in R and MATLAB are provided, along with demonstration input time series and the corresponding outputs.  These scripts were tested on R version 3.6.2 (2019-12-12) and on MATLAB versions 2018b and 2109b.
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.
ETH Zurich, WSL, James Kirchner, and Julia Knapp make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: isotopes catchment runoff tracers streamflow hydrograph-separation

en: Ensemble hydrograph separation scripts

title_for_slug: ensemble-hydrograph-separation-scripts

en:
Resource Title: MATLAB scripts and demonstration files (current version - build 20201119)
    Size: 178465 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/27da91e3-24b1-4d76-883e-37619652d785/download/ehs-v1.4-matlab-scripts-build-20201119.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

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

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

en:
Resource Title: *deprecated* MATLAB scripts and demonstration files (*deprecated version* - build 20200718 - do not use!)
    Size: 227403 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/bd43b9fb-7fda-4c26-a38c-31016f035429/download/ehs-v1.4-matlab-scripts.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

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

en:
Resource Title: R scripts and demonstration files
    Size: 235119 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/212f3a19-0530-4cd9-b10d-cd387ac98018/download/ehs-v1.4-r-scripts-and-demo-files.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_v1.4.R.

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

catchment

display_name: catchment

hydrograph-separation

display_name: hydrograph-separation

isotopes

display_name: isotopes

runoff

display_name: runoff

streamflow

display_name: streamflow

tracers

display_name: tracers