latent-reserves-within-the-swiss-nfi

en:
The files refer to the data used in Portier et al. "‘Latent reserves’: a hidden treasure in National Forest Inventories" (2020) *Journal of Ecology*.

**'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for -40 to -70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database:

* Shrub forests were excluded.
* Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested.
* To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994).
* Plots had to originate from natural regeneration.
* Intensive livestock grazing must never have occurred on the plots.

The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php).
****
The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper.
The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement.

en: 'Latent reserves' within the Swiss NFI

en: switzerland near-natural-forest tree-mortality national-forest-inventory forest-reserves

title_for_slug: latent-reserves-within-the-swiss-nfi

de:
Resource Title: Data figure 3
    Size: 5508 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/744ed206-605b-43a0-a560-bd0f27777735/download/d_fig3.csv
    Description: This file contains the data required to reproduce Figure 3:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "VARIABLE" refers to the indicators described in the figure: Ellenberg indicators for light, temperature and moisture, as well as species richness.
- "mean" refers to the mean value of each indicator for each combination of forest type and elevation vegetation zone (corrected for the inclusion probability of each tree).
- "se" corresponds to the standard error.

For these calculations, site index was constrained to the range observed in 'latent reserves' with at least 40 years without intervention.

de:
Resource Title: Tree-level data for characterisation of 'latent reserves'
    Size: 7664896 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/1bb1a8e4-0581-451e-b9bf-1dbbac120f4a/download/d_treelevel.csv
    Description: This table contains the tree-level information required to reproduce the charaterisation of 'latent reserves' and comparison to managed forests:

* "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
* "SOURCE" differentiate inventoried trees ("W", DBH greater or equal to 12 cm) and young-growth trees measured on subplots ("JW").
* "SPECIES" refers to the species code of the Swiss NFI.
* "SPECIES_GROUP" refers to which species group a tree belongs to (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
* "ALIVE_NFI2" takes the value '1' when the tree was alive at the previous inventory (NFI2). Trees with no value (NA) were not measured at NFI2. This variable should be used to calculate mortality rates, as only trees that were present at NFI2 can be used to calculate the mortality rate between NFI2 and NFI3.
* "DEAD" takes the value '1& when a tree was observed dead at NFI3, and the value '0' when it was observed alive.
* "INCLUSION_PROB" represents the inclusion probability of a tree i.e. the number of trees that a given tree represents per hectare. This number depends on the DBH of the tree and on whether the plot area was reduced by a boundary (e.g. a forest edge). This variable should be used to weight the trees in some calculations.
* "DBH" is the diameter at breast height of a tree in centimeters.
* "LIGHT", "TEMPERATURE", "MOISTURE" refer to the value of the Ellenberg indicators for light, temperature and moisture that are species-specific. 'NA' is attributed when the value of an indicator is not available for a given species.

de:
Resource Title: Plot-level data for characterisation of 'latent reserves'
    Size: 1535133 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/3ce25df8-138f-4abd-a2da-4afea2df26c1/download/d_plotlevel.csv
    Description: This table contains the plot-level information required to reproduce the charaterisation of 'latent reserves' and comparison to managed forests:

* "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
* "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
* "DOMINANT_SPECIES" refers to the dominant species in a given plot (spruce, fir, other conifers, beech, other broadleaves)
* "TIME_SINCE_INTERVENTION" refers to the numbers of years since the last human intervention on the plot. This variable should be used to set the threshold of time since last intervention one wants to use to define 'latent reserves'.
* "VEGYEAR" refers to the number of vegetation years between the measurements of a plot for NFI2 and NFI3.
* "BA" provides the basal area in squared meters per hectare of a plot calculated from trees having a DBH of at least 12 cm.
* "BA_WITH_YG" provides the basal area in squared meters per hectare of a plot calculated from trees having a DBH of at least 12 cm as well as young growth trees.
* "STAND_DENSITY" provides the stand density in number of stems per hectare of a plot calculated from trees having a DBH of at least 12 cm.
* "STAND_DENSITY_WITH_YG" provides the stand density in number of stems per hectare of a plot calculated from trees having a DBH of at least 12 cm as well as young growth trees.
* "SITE_INDEX" refers to the site index of a plot, i.e. the total biomass productivity calculated according to Keller (1976).
* "DEADWOOD" refers to the amount of deadwood of a plot in tons per hectare.

******

Reference
Keller, W. (1976). Einfacher ertragskundlicher Bonitätsschlüssel für Waldbestände in der Schweiz. Zurich, Switzerland: ETH Zurich.

de:
Resource Title: Data figure 5
    Size: 16424 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/322cf1b9-04b6-4c9f-8060-83341a2719cf/download/d_fig5.csv
    Description: This file contains the data required to reproduce Figure 5:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "DOMINANT_SPECIES" refers to the dominant species in a given plot (spruce, fir, other conifers, beech, other broadleaves)
- "VARIABLE" refers to the attributes described in the figure: basal area in squared meters per hectare, median DBH in cm, stand density in number of stems per hectare, deadwood in tons per hectare, site index in tons per hectare per year. Basal area, median DBH and stand density are given both with and without including young-growth trees.
- "mean" refers to the mean value of each attribute for each combination of forest type and dominant species (corrected for the inclusion probability of each tree).
- "se" corresponds to the standard error.

For these calculations, site index was constrained to the range observed in ‘latent reserves’ with at least 40 years without intervention. Additionally, only NFI sample plots from the montane and subalpine zones were used as colline and submontane NFI plots from ‘latent reserves’ and managed forests are located in different geographical regions.

de:
Resource Title: Data figure 8
    Size: 2258862 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/24e1a8c9-6380-432a-8a0b-ca979da75b2d/download/d_fig8.csv
    Description: This file contains the data required to reproduce Figure 8:

* "SPECIES_GROUP" refers to the species groups used in the mortality analyses (spruce, fir, pine, larch, stone pine, beech, maple and ash, oak, chestnut, other broadleaves)
* "BASAL_AREA" refers to the values of the basal area in squared meters per hectare for which predictions were made
* "STAND_DENSITY" refers to the values of stand density in number of stems per hectare for which predictions were made
* "NORM_PRED_MORTALITY_PROB" refers to the normalised predicted mortality probability corresponding to a given species group and values of basal area and stand density.

de:
Resource Title: Data figure 6
    Size: 5834 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/c01ebb60-0184-4392-a562-4c3555e901fb/download/d_fig6.csv
    Description: This file contains the data required to reproduce Figure 6:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "MORTALITY_RATE" refers to the mean annual mortality rate of each species group calculated according to Sheil and May (1996)
- "LOWER_CI" and "UPPER_CI" refer to the lower and upper confidence intervals on the mortality rates, calculated according to Sheil and May (1996).

Reference
Sheil, D., & May, R. M. (1996). Mortality and recruitment rate evaluations in heterogeneous tropical forests. Journal of Ecology, 84(1), 91–100. doi: 10.2307/2261703

de:
Resource Title: Data figure 4
    Size: 198106 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/c9ce4b0e-a00a-4a96-811c-99dd23d2f9a5/download/d_fig4.csv
    Description: This file contains the data required to reproduce Figure 4:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "DBH_CL" refers to the DBH (diameter at breast height) class to which a tree belongs to, in centimetres.
- "DENSITY" refers to the proportion of trees (corrected for the inclusion probability of each tree) within each combination of forest type, elevation vegetation zone, species group and DBH class.

The inclusion probability of each tree was accounted for in the density calculation.

de:
Resource Title: Data figure 7
    Size: 62372 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/4adfbe81-302b-4654-a07c-87827098b257/download/d_fig7.csv
    Description: This file contains the data required to reproduce Figure 7:

- "SPECIES_GROUP" refers to the species groups used in the mortality analyses (spruce, fir, pine, larch, stone pine, beech, maple and ash, oak, chestnut, other broadleaves)
- "VARIABLE" refers to the explanatory variables used in the model and presented in the figure: DBH (diameter at breast height) and relBAI (relative basal area increment).
- "VALUE" refers to the the values of the variables for which predictions were made.
- "PRED_MORTALITY_PROB" refers to the predicted mortality probability for a given species group and value of either DBH or relBAI.

de:
Resource Title: Data for mortality analyses
    Size: 851216 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/5e3cd66f-bc2f-49ce-b300-0468eeee420c/download/d_mortality.csv
    Description: This table contains the tree- and plot-level data necessary to conduct the tree mortality analyses:

* "DEAD" takes the value '0' when the tree was alive at NFI3 and '1' when it was observed dead
* "SPECIES" refers to which species group the tree belongs to
* "relBAL" is the relative basal area of larger trees
* "DBH" is the diameter at breast height
* "relBAI" is the relative basal area increment of the tree
* "BA" is the basal area in squared meters per hectare (stand-level)
* "STAND_DENSITY_LOG" is the logarithm of the stand density in number of stems per hectare
* "BEERS_ASPECT_CORR" is the Beers aspect corrected for slope of the plot
* "SLOPE_SQRT" is the squared root of the slope of the plot in percentage
* "ELEVATION" is the elevation of the plot in meters above sea level
* "AWC" is the available soil water-holding capacity in millimeters
* "VEGYEAR" is the number of vegetation years between the measurements of the plots at NFI2 and NFI3.

de:
Resource Title: Data figure 2
    Size: 10362 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/702645a2-8965-40df-ae9d-8b81df220bd1/resource/d40bae83-10d7-4545-80f0-29d6d138571e/download/d_fig2.csv
    Description: This file contains the data required to reproduce Figure 2:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "DENSITY" refers to the proportion of trees (corrected for the inclusion probability of each tree) within each combination of forest type, elevation vegetation zone and species group.

Young-growth trees are not included in the density calculation.

forest-reserves

display_name: forest-reserves

national-forest-inventory

display_name: national-forest-inventory

near-natural-forest

display_name: near-natural-forest

tree-mortality

display_name: tree-mortality


$oid: OBSOLETE

de: EnviDat

en: We present stated preference data based on a national representative Swiss online panel survey for the preference of renewable energy infrastructure in landscapes. The data was collected between November 2018 to March 2019 using an online questionnaire and resulted on 1026 responses. The online questionnaire consisted of two main parts – (1) questions covering meanings related to landscapes, nature and renewable energy infrastructure, including the “fit” of landscape/REI combinations and (2) online choice experiment. While in the first part of the questionnaire we asked respondents about their personal connection to certain landscapes, to nature and to specific renewable energy infrastructures, we also asked them to evaluate the fitting of seven different Swiss landscapes (near natural alpine areas, northern alps, touristic alpine areas, agricultural plateau, urban plateau, jura ridges, urban alpine valley) with five different REI (wind, PV ground, PV roof, power lines) combinations. In the second part of the questionnaire, the stated choice experiment confronted respondents with 15 consecutive choice tasks, with each task involving a choice between two “energy system transformation” options and an opt-out option (none). Each choice option (beside the opt-out option) included four unlabeled attributes (landscape, wind energy infrastructure, photovoltaic energy infrastructure, high voltage overhead power line infrastructure) with varying levels. Due to data cleaning procedures (item nonresponse) the number of responses used within hybrid choice modelling and analysis was n=844 (12660 choice observations). An analysis of the hybrid choice model and further insights are presented in the article “How landscape-technology fit affects public evaluations of renewable energy infrastructure scenarios. A hybrid choice model.”

en: Hybrid choice modelling dataset for the effects of landscape-technology fit on public evaluations

en: mixed-renewable-energy-landscapes landscape renewable-energy-meanings survey perceived-landscape-quality hybrid-choice-model landscape-meanings stated-choice-model landscape-technology-fit renewable-energy energy

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

type: dataset

key: guid

value: Envidat Harvester

key: uri

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: ENERGYSCAPE choice model attributes and tasks
    Size: 36812 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/967dc54a-0e06-4b63-afc4-34b4d518fa94/download/energyscape_choice_tasks_and_attributes.pdf
    Description: This data provides overview about the choice model design, the choice tasks and the choice attributes.

format: PDF

media_type: application/pdf

de:
Resource Title: ENERGYSCAPE Landscape attribute of choice model
    Size: 498857 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/2615b640-9347-4c8e-890f-28c4b484900d/download/energyscape_attribute_landscape.pdf
    Description: This file illustrated the 7 landscapes applied in the choice model. The numbers appear are identical to the numbers in the base data.

de:
Resource Title: Energyscape RAW data
    Size: 277161 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/7b8aea81-5547-4940-a463-5eb862955145/download/energyscape_questionnaire_dataset.csv
    Description: This dataset contains the raw data of the questionnaire including headers (column names). One line represents one respondent. Details to each variable (including scales) can be found in an attached PDF file.

format: CSV

media_type: text/csv

de:
Resource Title: ENERGYSCAPE exemplary choice task
    Size: 1179703 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/5176eb19-8a0d-4607-8112-c2eb125df114/download/energyscape_choice_task_6321_7431.pdf
    Description: This file contains an exemplary choice task.

de:
Resource Title: ENERGYSCAPE Landscape-technology fit example
    Size: 67976 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/14bef48e-57ac-4139-a3f0-e3334f5fa2ba/download/energyscape_ltf_example.pdf
    Description: This file contains an exemplary illustration on how the landscape-technology fit concept was measures within the survey.

de:
Resource Title: ENERGYSCAPE base data variable description
    Size: 85200 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e408aaea-2ba5-47e8-8be4-2053c9528b0c/resource/b3362724-a5d3-445f-9692-60c7fdf9806e/download/energyscape_questionnaire_dataset_description.pdf
    Description: This file contains descriptions (variable name, variable description, scale) of all variables of the base data.

energy

display_name: energy

hybrid-choice-model

display_name: hybrid-choice-model

landscape

display_name: landscape

landscape-meanings

display_name: landscape-meanings

landscape-technology-fit

display_name: landscape-technology-fit

mixed-renewable-energy-landscapes

display_name: mixed-renewable-energy-landscapes

perceived-landscape-quality

display_name: perceived-landscape-quality

renewable-energy

display_name: renewable-energy

renewable-energy-meanings

display_name: renewable-energy-meanings

stated-choice-model

display_name: stated-choice-model

survey

display_name: survey


literature-data-of-sound-speed-in-snow

en: This dataset contains literature data for snow density and frequency dependency of speed of sound waves in snow. The data were either available as tabular data in the original publications or were digitized from plots contained in the original publications. The data were originally collected and used for first figure in Capelli et al. (2016) .

en: Literature data of sound speed in snow

en: snow sound-speed literature wave-speed frequency density

title_for_slug: literature-data-of-sound-speed-in-snow

de:
Resource Title: Gudra
    Size: 329 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/57a4d0db-9f75-48a0-907d-e3b92f7b9eb4/download/gudra.csv
    Description:

de:
Resource Title: Reiweger
    Size: 336 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/8e14d7f8-4e56-4635-8ec0-48481629f5ce/download/reiweger.csv
    Description:

de:
Resource Title: Marco
    Size: 1584 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/f8b3156d-5d99-4d7b-a023-a89ff440dcf9/download/marco.csv
    Description:

de:
Resource Title: Ishida
    Size: 768 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/5b225ccc-3ae1-4fcc-afec-dfcfa3f67a12/download/ishida.csv
    Description:

de:
Resource Title: Capelli
    Size: 476 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/568ce512-ea60-4e1e-aeb6-528fe84cc816/download/capelli.csv
    Description:

de:
Resource Title: Takei
    Size: 730 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/1d052d34-3212-4e27-9c43-6eac526faa86/download/takei.csv
    Description:

de:
Resource Title: Yamada
    Size: 3497 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/9db1ed1d-55b6-4070-ad87-ae16fbd322b2/download/yamada.csv
    Description:

de:
Resource Title: Oura
    Size: 351 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/c0e4bbb4-bddf-4973-a092-d1b7305bf121/download/oura.csv
    Description:

de:
Resource Title: Smith
    Size: 1068 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/3c370c13-7944-4712-91cd-4e0cd7f0bae5/download/smith.csv
    Description:

de:
Resource Title: Iwase
    Size: 546 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/fecf7f82-6ef0-469f-8a01-7f4d1d8145b4/resource/d3fb699f-2d12-4774-a2a1-ca9c45e2cb89/download/iwase.csv
    Description:

density

display_name: density

frequency

display_name: frequency

literature

display_name: literature

snow

display_name: snow

sound-speed

display_name: sound-speed

wave-speed

display_name: wave-speed


de: EnviDat

en:
The files refer to the data and R code used in Mey et al. "From small forest samples to generalised uni- and bimodal stand descriptions" (2021) _Methods in Ecology and Evolution_.
Generalised stand descriptions are coming from the simultaneous examination of samples that are representative for a specific target area (here, Switzerland) and link available information about forest stand attributes. They combine the modelling of uni- or bimodal diameter distributions and species compositions, i.e. the shares of stems of individual species. Generalised stand descriptions may be used to interpret tree species diversity, regeneration and harvest potentials on a plot-level basis, and to initialise forest models with representative stand data.
The data stored here were derived from the fourth campaigns of the Swiss National Forest Inventory (NFI). The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php).
---------------------------------------
The file 'Data Figures 2 and 4' is publicly available and contains the data used to produce the Figures 2 and 4 published in the paper.
The files 'Data diameter modelling' and 'Data species modelling' contain all the data required to reproduce the diameter and species model building. The access to these two files is restricted as they contain raw data from the fourth Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement.
The files 'Script diameter and species modelling' and 'Functions diameter modelling' are publicly available and provide the R code used to derive the generalised stand descriptions from the Swiss NFI data.

en: Generalised stand descriptions in Switzerland

envidat

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.

de: EnviDat: das Umwelt-Datenportal

envi

de: Umwelt

de:
Resource Title: Data species modelling
    Size: 450665 bytes
    Format: application/x-rds
    URL: https://www.envidat.ch/dataset/f8fe4971-0538-4d8e-b866-8d1cfd4b1584/resource/03162eba-0bd2-400a-b0f7-75c7cf117269/download/data_nfi4_species_modelling.rds
    Description: This rds file contains a data frame with single-tree and stand data required to reproduce the species composition model:

* 'clnr' refers to the plot number
* 'spec' refers to the main tree species group (12 groups)
* 'ba' refers to the basal area per hectare
* 'nph' refers to the number of stems per hectare
* 'drel' refers to the relative diameter ('drel' = (d - min(d)) / (max(d) - min(d)))
* 'temp' refers to the mean winter temperature (1988-2017, Dec-Feb)
* 'dev' refers to the development stage of the stand (e.g. 'Young growth')
* 'ftyp' refers to the potential climax forest type (e.g. 'Beech' refers to a beech-dominated stand)
* 'str' refers to the stand structure
* 'tillering' indicates whether the observed tree species on the NFI plot correspond to 'ftyp' ('TRUE') or not ('FALSE')
* 'prodreg' refers to the Swiss production region (ecoregion)
* 'fowner' refers to the forest ownership ('Public' or ' Private')

de:
Resource Title: Script diameter and species modelling
    Size: 16141 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/f8fe4971-0538-4d8e-b866-8d1cfd4b1584/resource/0e6e2a50-fb05-4236-b53f-a5bafaf7a069/download/script_diameter_and_species_modelling.r
    Description: This R script can be used to derive the uni- and bimodal Weibull log-likelihood regression models (in short: uni- and bimodal model), the species composition model and the main results presented in Mey et al. 2021 using data from the fourth Swiss NFI ('data_NFI4_diameter_modelling.rds' and 'data_NFI4_species_modelling.rds') and the R functions stored in 'functions_diameter_modelling.R'.

de:
Resource Title: Functions diameter modelling
    Size: 20702 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/f8fe4971-0538-4d8e-b866-8d1cfd4b1584/resource/e3f02601-e820-4df9-bcc9-c21bea82dc38/download/functions_diameter_modelling.r
    Description: This R file contains the functions used to produce the generalised diameter distributions in Mey et al. 2021.

de:
Resource Title: Data Figures 2 and 4
    Size: 744 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f8fe4971-0538-4d8e-b866-8d1cfd4b1584/resource/2e6a5bbe-6836-47b2-86bb-be16ba2fe81e/download/data_figures_2_4.csv
    Description: This csv file contains the data required to reproduce Figure 2 and Figure 4.

* 'stand_type' states whether a row corresponds to NFI4 average summary statistics describing a generalised beech-dominated, spruce-dominated or an unspecified forest stand in Switzerland in its unimodal or bimodal form (e.g. 'beech.uni' refers to a generalised unimodal beech-dominated stand)
* 'md' refers to the mean diameter
* 'dq10' refers to the 10% quantile of the diameter
* 'dq90' refers to the 90% quantile of the diameter
* 'spr' refers to the spread between minimal and maximal diameter
* 'nph' refers to the number of stems per hectare
* 'o.qmd' refers to the overstorey quadratic mean diameter
* 'rho.emp' refers to proportion parameter (rho) determined by breakpoint setting
* 'ba' refers to the basal area per hectare
* 'drel' refers to the relative diameter ('drel' = (d - min(d)) / (max(d) - min(d)))
* 'temp' refers to the mean winter temperature (1988-2017, Dec-Feb)
* 'dev' refers to the development stage of the stand (e.g. 'Young growth')
* 'ftyp' refers to the potential climax forest type (e.g. 'Beech' refers to a beech-dominated stand)
* 'str' refers to the stand structure
* 'tillering' indicates whether the observed tree species on the NFI plot correspond to 'ftyp' ('TRUE') or not ('FALSE')
* 'prodreg' refers to the Swiss production region (ecoregion)
* 'fowner' refers to the forest ownership ('Public' or ' Private')

de:
Resource Title: Data diameter modelling
    Size: 243750 bytes
    Format: application/x-rds
    URL: https://www.envidat.ch/dataset/f8fe4971-0538-4d8e-b866-8d1cfd4b1584/resource/9cadbc57-7eab-4415-bf97-229d52cd412b/download/data_nfi4_diameter_modelling.rds
    Description: This rds file contains a list of 5085 data frames required to reproduce the uni- and bimodal diameter model. Each data frame comprises single-tree diameters ('dbh') and assigned representation factors ('repfa') at a single Swiss NFI4 plot.

* 'dbh' refers to the diameter at breast height (130 cm)
* 'repfa' refers to the representation factor used to scale up to one hectare

forest-model-initialisation

display_name: forest-model-initialisation

forest-stand-description

display_name: forest-stand-description

national-forest-inventory

display_name: national-forest-inventory

small-forest-samples

display_name: small-forest-samples

tree-species-composition

display_name: tree-species-composition

weibull-function

display_name: weibull-function


en:
Cloud Condensation Nuclei (CCN) data: A Droplet Measurement Technologies (DMT) single-column continuous-flow streamwise thermal gradient chamber (CFSTGC; Roberts and Nenes, 2005) was deployed at the measurement site Weissfluhjoch (2700 m a.s.l., LON: 9.806475, LAT: 46.832964) to record the in-situ CCN number concentrations between February 24 and March 8 2019 for different supersaturations (SS). To account for the difference between the ambient (~735 mbar) and the calibration pressure (~800 mbar), the SS reported by the instrument is adjusted by a factor of 0.92. The CFSTGC was cycled between 6 discrete SS values ranging from 0.09% to 0.74%, producing a full CCN spectrum every hour. The raw CCN measurements are filtered to discount periods of transient operation and whenever the room temperature housing the instrument changed sufficiently to induce a reset in column temperature. Additional information can be found in Section 2.1.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).
Hygroscopicity data: The CCN number concentration measurements were directly related to the size distribution and total aerosol concentration data measured by the Scanning Mobility Particle Size Spectrometer (SMPS) instrument at the same station (https://www.envidat.ch/dataset/aerosol-data-weissfluhjoch) to infer the particles hygroscopicity parameter (kappa). For each SMPS scan, the particles critical dry diameter (Dcr) is estimated by integrating backward the SMPS size distribution, until the aerosol number matches the CCN concentration observed for the same time period as the SMPS scan. Assuming the particle chemical composition is internally mixed, the kappa is determined from Dcr and SS, applying Köhler theory. Additional information can be found in Section 2.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).
Predicted cloud droplet numbers: Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from the SMPS instrument deployed at Weissfluhjoch. The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at Davos Wolfgang and are extracted for the altitude of interest, being 1100 m above ground level for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

en: CCN, hygroscopicity, predicted cloud droplet numbers Weissfluhjoch

en: cloud-modeling dmt-ccn-chamber cloud-droplets hygroscopicity sigma-w supersaturation ccn weissfluhjoch raclets

de:
Resource Title: CCN data Weissfluhjoch
    Size: 79738661 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ecb08acd-01d0-40e6-ac42-584aab9fc27f/resource/80b5fb31-8f82-4648-bc82-d11373bd186a/download/ccnspectrumwfj.csv
    Description: In-situ CCN measurements were conducted between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* Filtered CCN number concentrations (in cmˉ³) measured at 6 discrete supersaturations (SS) ranging from 0.09% to 0.74%. The name of each CCN column is indicative of the SS developed within the instrument.
* Instrument characteristics such as sample temperature (in °C) and pressure (in mbar)
* A code that refers to the reason of filtering.

Missing or filtered CCN values are indicated by "-999", while a declaration of each "Error_code" can be found in the following list:

_Error_code_:

__0000__: Measurements without error

__1000__: Period of transient operation after a supersaturation change

__2000__: Sharp change (decrease) in the room temperature housing the instrument, which induces a reset in column temperature

__3000__: Irregular values in the room temperature housing the instrument

__9999__: Missing data

de:
Resource Title: Hygroscopicity parameter Weissfluhjoch
    Size: 344260 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ecb08acd-01d0-40e6-ac42-584aab9fc27f/resource/5032c15d-ac68-4e8f-822b-3503a34db837/download/hygroscopicitywfj.csv
    Description: The aerosol hygroscopicity parameter is derived combining the CCN and SMPS size distribution data collected between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The instrument supersaturation (SS%)
* The calculated hygroscopicity parameter (kappa)
* The calculated critical dry diameter of the particles (Dcr) in nm.

Missing values are indicated by "-999".

de:
Resource Title: Predicted cloud droplet number concentrations Weissfluhjoch
    Size: 256123 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ecb08acd-01d0-40e6-ac42-584aab9fc27f/resource/f732a28e-10b1-411f-a497-b784e1b716af/download/predicted_droplets_wfj_kappa0.25.csv
    Description: In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Weissfluhjoch station between February 24 and March 8 2019. For this, a hygroscopicity parameter of 0.25 is assumed, according to the CCN-derived values. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

ccn

display_name: ccn

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

dmt-ccn-chamber

display_name: dmt-ccn-chamber

hygroscopicity

display_name: hygroscopicity

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

weissfluhjoch

display_name: weissfluhjoch


en: Cloud droplet properties were predicted between February 24 and March 8 2019 for the measurement site Davos Wolfgang (1630 m a.s.l., LON: 9.853594, LAT: 46.835577). Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from a Scanning Mobility Particle Size Spectrometer (SMPS) instrument deployed at Davos Wolfgang (https://www.envidat.ch/dataset/aerosol-data-davos-wolfgang). The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at the same station and are extracted from the first bin of the instrument, being 200 m above ground level. The hygroscopic properties of the particles measured at Davos Wolfgang could not be estimated, owing to a lack of concurrent CCN measurements. As a sensitivity test, droplet calculations are performed assuming two different values of the aerosol hygroscopicity parameter, 0.1 and 0.25, based on the analysis carried out for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

en: Predicted cloud droplet numbers Davos Wolfgang

en: sigma-w supersaturation raclets cloud-modeling cloud-droplets wolfgangpass

de:
Resource Title: Predicted cloud droplet numbers (kappa=0.1) Davos Wolfgang
    Size: 312210 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e5a506af-7ff0-47ad-afe2-36de4b4e1ea9/resource/245ebcc2-4dd5-4339-9f76-b61411fa103b/download/predicted_droplets_wop_kappa0.1.csv
    Description: In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.1 is assumed, which is the lower limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

de:
Resource Title: Predicted cloud droplet numbers (kappa=0.25) Weissfluhjoch
    Size: 313834 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e5a506af-7ff0-47ad-afe2-36de4b4e1ea9/resource/b5c4c596-2dd4-45f4-b79f-61f91d82aad0/download/predicted_droplets_wop_kappa0.25.csv
    Description: In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Davos Wolfgang station between February 24 and March 8 2019. For this, as a sensitivity test, a hygroscopicity parameter of 0.25 is assumed, which is the upper limit determined from the analysis carried out for Weissfluhjoch (https://www.envidat.ch/dataset/ccn-hygroscopicity-predicted-cloud-droplet-numbers-weissfluhjoch). The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

wolfgangpass

display_name: wolfgangpass


energieproduktion-im-kanton-graubunden

de: Der Datensatz enthält eine Aufstellung der jährlichen Energieproduktion in Kilowattstunden (kWh), unterteilt nach verschiedenen Energieträgern im Kanton Graubünden. In den Daten finden sich spezifische Werte für die Erzeugung aus Biomasse, Windkraft, der thermischen Verwertung von Abfällen sowie aus Trinkwasserkraftwerken, Wasserkraftwerken und Photovoltaik-Anlagen.

it: L'insieme di dati contiene una distinta della produzione di energia annua in chilowattora (kWh), suddivisa per diversi vettori energetici nel Cantone dei Grigioni. Nei dati si trovano valori specifici per la produzione da biomassa, energia eolica, valorizzazione termica di rifiuti nonché centrali idroelettriche alimentate da acqua potabile, centrali idroelettriche e impianti fotovoltaici.

kanton-graubuenden

fr: Le canton des Grisons publie progressivement des données publiques en libre accès (Open Government Data) d’offices et de services cantonaux.

de: Der Kanton Graubünden veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.

en: The Canton of Graubünden is gradually publishing open government datasets from cantonal offices and agencies.

it: Il Cantone dei Grigioni pubblica su base continua serie di dati di uffici e servizi cantonali come Open Government Data.

de: Kanton Graubünden

en: Canton of Graubünden

fr: Canton des Grisons

it: Cantone dei Grigioni

political_level: canton

de: kanton-graubuenden

de: Energieproduktion im Kanton Graubünden

title_for_slug: energieproduktion-im-kanton-graubunden

value: DCAT Harvester Kt Graubünden GR

ener

de: Energie

en: Energy

fr: Énergie

it: Energia

de: Energieproduktion im Kanton Graubünden (csv)

it: Produzione di energia nel Cantone dei Grigioni (csv)

de: csv

it: csv

de: Energieproduktion im Kanton Graubünden (json)

it: Produzione di energia nel Cantone dei Grigioni (json)

de: json

it: json

format: JSON

media_type: application/json

de: Energieproduktion im Kanton Graubünden (jsonl)

it: Produzione di energia nel Cantone dei Grigioni (jsonl)

de: jsonl

it: jsonl

de: Energieproduktion im Kanton Graubünden (parquet)

it: Produzione di energia nel Cantone dei Grigioni (parquet)

de: parquet

it: parquet

format: PARQUET

de: Energieproduktion im Kanton Graubünden (rdfxml)

it: Produzione di energia nel Cantone dei Grigioni (rdfxml)

de: rdfxml

it: rdfxml

format: RDF XML

media_type: application/rdf+xml

de: Energieproduktion im Kanton Graubünden (jsonld)

it: Produzione di energia nel Cantone dei Grigioni (jsonld)

de: jsonld

it: jsonld

format: JSON-LD

de: Energieproduktion im Kanton Graubünden (turtle)

it: Produzione di energia nel Cantone dei Grigioni (turtle)

de: turtle

it: turtle

format: RDF Turtle

media_type: text/turtle

de: Energieproduktion im Kanton Graubünden (n3)

it: Produzione di energia nel Cantone dei Grigioni (n3)

de: Energieproduktion im Kanton Graubünden (xlsx)

it: Produzione di energia nel Cantone dei Grigioni (xlsx)

de: xlsx

it: xlsx

format: XLS

energia-rinnovabile

display_name: energia-rinnovabile


en:
This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci).
For details on the data please refer to this publication.
The dataset contains the following:
- shape files for the warning regions in the Alps
- highest forecast danger level for each warning region and day

en: avalanche-forecast european-alps snow warning-regions danger-level

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.

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

it: EnviDat: il portale dei dati ambientali

de: EnviDat

en: Forecast avalanche danger level European Alps 2011 - 2015

envi

de: Umwelt

it: Ambiente

de:
Resource Title: shape file warning regions Alps
    Size: 378119 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f2dff8e3-fdff-4626-b650-a8ba5c19ef27/resource/c8329c09-60f5-4181-8681-038ebf9615f4/download/warnregionen.zip
    Description:

format: ZIP

media_type: application/zip

de:
Resource Title: Forecast avalanche danger level
    Size: 4052358 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f2dff8e3-fdff-4626-b650-a8ba5c19ef27/resource/688bda43-8216-47b0-8a15-730034676551/download/data_dmax.csv
    Description: contains the highest forecast danger level (dangerLevelMax) for each day and warning region

avalanche-forecast

display_name: avalanche-forecast

danger-level

display_name: danger-level

european-alps

display_name: european-alps

snow

display_name: snow

warning-regions

display_name: warning-regions


en:
This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.
These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height.
The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file.
These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, 3293-3315, https://doi.org/10.5194/tc-15-3293-2021, 2021.
 Acknowlegements
Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged.

en: snow avalanche danger-level avalanche-danger avalanche-forecasting snow-instability

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

de:
Resource Title: Field observations of snow instabilities
    Size: 107300 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/5927f50c-3a33-4ceb-91bf-d583efd14cfe/download/snow_instability_field_data.csv
    Description: This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019.

de:
Resource Title: Read-me file
    Size: 133885 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/321f2050-93be-4772-b5d8-562f46658256/resource/b3aeef4d-1b54-467c-88b4-4d2da8076885/download/read-me.pdf
    Description: This read-me file contains the descriptions of the variables.

avalanche

display_name: avalanche

avalanche-danger

display_name: avalanche-danger

avalanche-forecasting

display_name: avalanche-forecasting

snow-instability

display_name: snow-instability


en:
The dataset contains a time series of countrywide Sentinel-1 synthetic aperture radar (SAR) composites for Switzerland and Liechtenstein starting in 2015. The temporal sampling step of the time series is 6 days and the compositing period 12 days resulting in 60 generated composites per year. Each composite contains the amplitude information of C-band backscatter and features a grid spacing of 10 m. The composites were generated according to the local resolution weighting (LRW) methodology described in Small et al. (2022, https://doi.org/10.1109/TGRS.2021.3055562). For the generation of each composite, backscatter information from all Sentinel-1 acquisitions of Switzerland and Liechtenstein during the compositing period was obtained.
The naming of each composite file follows the logic “S1_LRW_PD\-LRW compositing period in days\-\_SP\-Temporal sampling step in days\-_\-Start date and time for LRW composite generation\--\-End date and time for LRW composite generation\-.tif”, e.g. “S1_LRW_PD12_SP6_20150101000000-20150112235959.tif” for the first file. Each file contains four raster layers: 1) Vertically submitted and horizontally received (VH) and 2) vertically submitted and vertically received (VV) polarisation backscatter in the logarithmic dB scale, 3) composite local resolution, which is a measure for the quality of the pixel (for details, see Small et al. (2022, https://doi.org/10.1109/TGRS.2021.3055562), and 4) the number of contributing observations.
Contains modified Copernicus Sentinel data.

en: sentinel-1 c-band time-series earth-observation radar remote-sensing switzerland sar

en: Sentinel-1 Synthetic Aperture Radar Composite Backscatter Time Series of Switzerland

c-band

display_name: c-band

earth-observation

display_name: earth-observation

radar

display_name: radar

remote-sensing

display_name: remote-sensing

sar

display_name: sar

switzerland

display_name: switzerland

time-series

display_name: time-series


en:
**Schweizweite Hinweiskarten des lichtbedingten Verjüngungspotentials (Stand LFI VHM 2024)**
This is a dataset for Swiss forestry, for a description in English please see below.
Il s'agit d'un ensemble de données relatives à la sylviculture suisse. Pour une description en français, voir ci-dessous.
Si tratta di una serie di dati relativi alla silvicoltura svizzera. Per una descrizione in francese, vedere sotto.
Die Karte zeigt, wo die Lichtbedingungen für genügend Höhenzuwachs der Verjüngung (-= 300 cm) der jeweiligen Baumartengruppe ausreichen. Die Karte basiert auf gutachtlich erhobenen Feldaufnahmen in 39 Forstrevieren, verteilt über die ganze Schweiz und verschiedene Höhenlagen, sowie auf dem Kronenöffnungsgrad, der aus LiDAR Daten abgeleitet wurde. Die berücksichtigten Baumarten wurden anhand ihrer Lichtansprüche in die unten aufgeführten Klassen eingeteilt. Indikativ kann die Karte auch für andere Baumarten der jeweiligen Klasse verwendet werden:
- Lärche, Birke, Stiel- und Traubeneiche, Waldföhre und Kirschbaum: Lichtbaumarten (Klasse 1)
- Berg- und Spitzahorn: Halblichtbaumarten (Klasse 2)
- Fichte, Sommer- und Winterlinde: Halbschattenbaumarten (Klasse 3):
- Buche und Tanne: Schattenbaumarten (Klasse 4)
- Zu dunkel für das Aufwachsen sämtlicher Baumarten (Klasse 5)
Zweck: Die Karte zeigt, ob die lokal vorhandenen Lichtverhältnisse ausreichen, damit Jungbäume ohne zusätzlichen Eingriff vital ins Stangenholz aufwachsen können, und macht damit potenziell nötige waldbauliche Massnahmen frühzeitig erkennbar.
Hinweise zur Verwendung: Unterstützung von Försterinnen und Waldbewirtschaftern bei der Planung von Verjüngungseingriffen, der Jungwaldpflege, der Baumartenwahl und beim zeitlichen und räumlichen Monitoring, da die Karte bei neuen LiDAR-Befliegungen regelmässig aktualisiert wird.
Bemerkungen: Das Verjüngungspotential wurde ausschliesslich aufgrund des Kronenöffnungsgrads berechnet, der die Abschattung durch die umliegenden Baumkronen und dem Gelände berücksichtigt. Die direkte Sonneneinstrahlung wurde bisher nicht berücksichtigt, da damit statistisch weniger gute Ergebnisse erreicht werden. Somit kann auch die Hangexposition oder die Ausrichtung der Lücken bisher nicht berücksichtig werden. Ebenso können bisher keine Höhenstufen-spezifischen Unterteilungen erfolgen, da das verwendete nationale Modell in den statistischen Tests am besten abschneidet. In Beständen mit Bäumen und Sträuchern von ca. 3-7 Höhe werden die Lichtbedingungen in der Unterschicht überschätzt, d.h. die Karte zeigt in solchen Fällen ein zu hohes Verjüngungspotential. Die Karte wurde auf die Waldfläche gemäss LFI reduziert und Waldstrassen wurden so gut wie möglich ausmaskiert.
**Cartes nationales indiquant le potentiel de régénération lié à la lumière (état IFN VHM 2024)**
La carte montre les endroits où les conditions de luminosité sont suffisantes pour permettre une croissance en hauteur suffisante (-= 300 cm) de la régénération pour chaque groupe d'essences. La carte est basée sur des relevés effectués sur le terrain dans 39 districts forestiers répartis sur toute la Suisse et à différentes altitudes, ainsi que sur le degré d'ouverture de la canopée, dérivé des données LiDAR. Les essences prises en compte ont été classées dans les catégories ci-dessous en fonction de leurs besoins en lumière. La carte peut également être utilisée à titre indicatif pour d'autres essences de la catégorie correspondante :
Mélèze, bouleau, chêne pédonculé et chêne rouvre, pin sylvestre et cerisier : essences photophiles (classe 1)
Érable sycomore et érable plane : essences semi-photophiles (classe 2)
Épicéa, tilleul à petites feuilles et tilleul à grandes feuilles : essences semi-ombelibles (classe 3)
Hêtre et sapin : essences ombéliques (classe 4)
Trop sombre pour la croissance de toutes les essences (classe 5)
Objectif : la carte indique si les conditions de luminosité locales sont suffisantes pour que les jeunes arbres puissent atteindre le stade de perchis sans intervention supplémentaire et permet ainsi d'identifier à un stade précoce les mesures sylvicoles potentiellement nécessaires.
Conseils d'utilisation : aide les forestiers et les gestionnaires forestiers à planifier les mesures de rajeunissement, l'entretien des jeunes forêts, le choix des essences et le suivi temporel et spatial, car la carte est régulièrement mise à jour lors de nouveaux survols LiDAR.
Remarques : le potentiel de régénération a été calculé exclusivement sur la base du degré d'ouverture de la canopée, qui tient compte de l'ombrage causé par les cimes des arbres environnants et le terrain. L'ensoleillement direct n'a pas été pris en compte jusqu'à présent, car il donne des résultats statistiquement moins bons. De même, l'exposition des pentes ou l'orientation des clairières ne peuvent pas être prises en compte pour l'instant. De même, aucune subdivision spécifique à l'altitude ne peut être effectuée jusqu'à présent, car le modèle national utilisé obtient les meilleurs résultats dans les tests statistiques. Dans les peuplements composés d'arbres et d'arbustes d'une hauteur d'environ 3 à 7 mètres, les conditions d'ensoleillement dans la strate inférieure sont surestimées, c'est-à-dire que la carte indique dans ces cas un potentiel de régénération trop élevé. La carte a été réduite à la surface forestière selon l'IFN et les routes forestières ont été masquées autant que possible.
**Mappe indicative a livello nazionale del potenziale di ringiovanimento legato alla luce (stato LFI VHM 2024)**
La mappa mostra dove le condizioni di luce sono sufficienti per garantire un'adeguata crescita in altezza del rimboschimento (-= 300 cm) del rispettivo gruppo di specie arboree. La mappa si basa su rilevamenti sul campo effettuati da esperti in 39 distretti forestali distribuiti su tutto il territorio svizzero e a diverse altitudini, nonché sul grado di apertura della chioma ricavato dai dati LiDAR. Le specie arboree prese in considerazione sono state classificate in base alle loro esigenze di luce nelle classi elencate di seguito. La mappa può essere utilizzata in modo indicativo anche per altre specie arboree della rispettiva classe:
- Larice, betulla, farnia e faggio, pino silvestre e ciliegio: specie arboree che necessitano di luce (classe 1)
- Acero di montagna e acero riccio: specie arboree che necessitano di luce moderata (classe 2)
- Abete rosso, tiglio estivo e tiglio invernale: specie arboree di mezz'ombra (classe 3):
- Faggio e abete: specie arboree di ombra (classe 4)
- Troppo buio per la crescita di tutte le specie arboree (classe 5)
Scopo: la mappa mostra se le condizioni di luce locali sono sufficienti affinché i giovani alberi possano crescere vitalmente senza ulteriori interventi e rende così riconoscibili tempestivamente le misure selvicolturali potenzialmente necessarie.
Indicazioni per l'uso: supporto ai forestali e ai gestori forestali nella pianificazione degli interventi di ringiovanimento, nella cura dei boschi giovani, nella scelta delle specie arboree e nel monitoraggio temporale e spaziale, poiché la mappa viene aggiornata regolarmente con nuove rilevazioni LiDAR.
Osservazioni: il potenziale di rigenerazione è stato calcolato esclusivamente sulla base del grado di apertura della chioma, che tiene conto dell'ombreggiamento causato dalle chiome degli alberi circostanti e dal terreno. Finora non è stata presa in considerazione l'esposizione diretta al sole, poiché ciò comporta risultati statisticamente meno attendibili. Pertanto, non è stato possibile tenere conto dell'esposizione del pendio o dell'orientamento delle radure. Allo stesso modo, non è ancora possibile effettuare suddivisioni specifiche per altitudine, poiché il modello nazionale utilizzato ottiene i migliori risultati nei test statistici. Nei popolamenti con alberi e arbusti di circa 3-7 metri di altezza, le condizioni di luce nello strato inferiore sono sovrastimate, ovvero in questi casi la mappa mostra un potenziale di rigenerazione troppo elevato. La mappa è stata ridotta alla superficie forestale secondo l'IFN e le strade forestali sono state mascherate il più possibile.
**Switzerland-wide maps showing light-induced regeneration potential (as of NFI VHM 2024)**
The map shows where light conditions are sufficient for sufficient height growth of regeneration (-= 300 cm) for each tree species group. The map is based on expert field surveys in 39 forest districts spread across Switzerland and at various altitudes, as well as on the degree of canopy opening derived from LiDAR data. The tree species considered were divided into the classes listed below based on their light requirements. The map can also be used as a guide for other tree species in the respective class:
- Larch, birch, English oak, sessile oak, Scots pine, and cherry: light-demanding tree species (class 1)
- Sycamore maple and Norway maple: semi-light-demanding tree species (class 2)
- Spruce, small-leaved and large-leaved lime: semi-shade tree species (class 3):
- Beech and fir: shade tree species (class 4)
- Too dark for all tree species to grow (class 5)
Purpose: The map shows whether the local light conditions are sufficient for young trees to grow vigorously into pole wood without additional intervention, thus identifying potentially necessary silvicultural measures at an early stage.
Notes on use: Support for foresters and forest managers in planning regeneration measures, young forest maintenance, tree species selection, and temporal and spatial monitoring, as the map is regularly updated with new LiDAR flights.
Comments: The regeneration potential was calculated solely on the basis of the degree of canopy opening, which takes into account the shading caused by the surrounding tree crowns and the terrain. Direct sunlight has not been taken into account so far, as this leads to statistically less reliable results. This means that slope exposure or the orientation of gaps cannot be taken into account at this stage. Similarly, no altitude-specific subdivisions can be made at present, as the national model used performs best in statistical tests. In stands with trees and shrubs of approx. 3-7 m in height, the light conditions in the understorey are overestimated, i.e. in such cases the map shows an excessively high regeneration potential. The map has been reduced to the forest area according to the NFI, and forest roads have been masked out as much as possible.

en: forest-management rejuvenation light-availability lidar protection-forest

en: Switzerland-wide maps of light-induced regeneration potential (as of NFI VHM 2024)

de:
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    Description: Karte mit den Befliegungsjahren der LiDAR Daten, welche für die Berechnung des Verjüngungspotential verwendet wurden.

format: PNG

media_type: image/png

de:
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format: TIFF

media_type: image/tiff

de:
Resource Title: Verjüngungspotentialkarte_Kurzbeschrieb.pdf
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    URL: https://www.envidat.ch/dataset/c9b1019d-78cf-49b5-b065-25d8e2dd2700/resource/1f901079-7a5a-46a5-8246-a685d71e0c8f/download/verjungungspotentialkarte_kurzbeschrieb_17022026.pdf
    Description: Kurzbeschrieb inkl. Legende und Limitierungen

forest-management

display_name: forest-management

lidar

display_name: lidar

light-availability

display_name: light-availability

protection-forest

display_name: protection-forest

rejuvenation

display_name: rejuvenation


en: Gas exchange, online isotope discrimination, and chlorophyll fluorescence measurements were conducted on fully expanded leaves of grey alder (*Alnus incana*) and holm oak (*Quercus ilex*) tree saplings under different fractions of blue light (0–100%). Blue light was supplemented with red light to maintain a constant total light intensity. A detailed description of the measurements is provided in Diao *et al.* (2025) (https://doi.org/10.1093/jxb/eraf305). These measurements generated a dataset describing the responses of key leaf physiological parameters to varying blue/red light fractions, including net photosynthetic rate, stomatal conductance, mesophyll conductance, the maximum carboxylation rate of RuBP, non-photochemical quenching, etc. The dataset was further used for photosynthetic limitation analysis to disentangle the relative biochemical, mesophyll, and stomatal limitations on photosynthesis under different light-quality conditions. The results of the photosynthetic limitation analysis are also provided here.

en: fluorescence stomata gas-exchange photosynthesis light-quality

en: Light-quality responses of photosynthetic, stomatal, and mesophyll traits of Alnus incana and Quercus ilex

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

light-quality

display_name: light-quality

photosynthesis

display_name: photosynthesis

stomata

display_name: stomata


en:
This dataset contains bryophyte species count data and information about the observers bryophyte expertise for 2950 relevés conducted from 2011 to 2023 on 10-m2 plots in a long-term monitoring program in Switzerland. Plots were situated in raised bogs and fens of national importance, which were distributed across the whole country. The majority of the plots is represented by two relevés as sites are revisited every six years. The dataset was used in the paper mentioned below to test if species richness estimates differed among categories of observer expertise.
Moser T, Boch S, Bedolla A, Ecker KT, Graf UH, Holderegger R, Küchler H, Pichon
NA, Bergamini A (2025) Greater observer expertise leads to higher liverwort species richness in bryophyte surveys. _Journal of Vegetation Science_.

en: vegetation-survey liverworts mosses cover biodiversity-monitoring sphagnum fen observer-bias raised-bog

biodiversity-monitoring

display_name: biodiversity-monitoring

cover

display_name: cover

fen

display_name: fen

liverworts

display_name: liverworts

mosses

display_name: mosses

observer-bias

display_name: observer-bias

raised-bog

display_name: raised-bog

sphagnum

display_name: sphagnum

vegetation-survey

display_name: vegetation-survey


en:
Observational data used to quantitatively describe the key elements describing avalanche danger: snowpack stability, the frequency distribution of snowpack stability, and avalanche size.
The data set consists of
- Rutschblock test results (Switzerland)
- Extended Column Test results (Switzerland, Norway)
- Avalanche occurrence data (Switzerland, Norway).
The data were extracted from the respective operational databases of the national avalanche warning services in Switzerland (WSL Institute for Snow and Avalanche Research SLF Davos, Switzerland) and Norway (The Norwegian Water Resources and Energy Directorate NVE).
For further information regarding the data, please refer to the publication or contact the author.

en: Stability tests, avalanche observations, Switzerland, Norway

en: norway extended-column-test avalanche-danger switzerland avalanche-observations rutschblock-test

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.

de:
Resource Title: ECT data (Norway, Switzerland)
    Size: 241792 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ab401e00-0c6e-40c0-a24d-9e8716cb23da/resource/7618bcce-8c14-463d-8c4d-1dc4f5365085/download/ect_data_used_in_manuscript.csv
    Description:

de:
Resource Title: Rutschblock data (Switzerland)
    Size: 221029 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ab401e00-0c6e-40c0-a24d-9e8716cb23da/resource/30e5287d-6bc2-4810-bdc2-422976023486/download/rb_data_used_in_manuscript.csv
    Description:

de:
Resource Title: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region
    Size: 1514094 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ab401e00-0c6e-40c0-a24d-9e8716cb23da/resource/23823196-1d56-47d1-b6bd-cb0add4dbd7b/download/avalsize_used_in_manuscript.csv
    Description:

de:
Resource Title: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region
    Size: 256120 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ab401e00-0c6e-40c0-a24d-9e8716cb23da/resource/accef652-f988-4d75-8aff-4c4c06c24a74/download/maxavalsize_used_in_manuscript.csv
    Description:

avalanche-danger

display_name: avalanche-danger

avalanche-observations

display_name: avalanche-observations

extended-column-test

display_name: extended-column-test

norway

display_name: norway

rutschblock-test

display_name: rutschblock-test

switzerland

display_name: switzerland


en:
Long term monitoring of natural forests provides insights into ecological processes shaping forests without human intervention. To study natural forest dynamics, the former chair of silviculture at the Swiss Federal Institute of Technology (ETH) initiated a network of forest reserves in the late 1940's.
Since 2006, the monitoring is carried out in a cooperation project of  the chair of Forest Ecology at ETH, the Swiss Federal Research Institute for Forest, Snow and Landscape Research (WSL) and the Federal Office for the Environment (FOEN). The project relaunch led to a streamlining of the reserve network, which now contains 33 of the original reserves and 16 new reserves.
The main goal is to evaluate the effectiveness of the federal reserve policy by analysing to what extent forest reserves differ from managed forests in terms of structure, dynamics, and habitat quality.

en: natural-forest-dynamics forest-reserves switzerland long-term-monitoring permanent-plot

envidat

en: EnviDat: the Environmental Data Portal

en: Forest Reserves Monitoring in Switzerland

de:
Resource Title: Data Access (please log in)
    Size: 1 bytes
    Format: text/html
    URL: https://www.wsl.ch/en/employees/hobi.html
    Description:

format: HTML

media_type: text/html

de:
Resource Title: Metadata
    Size: 14607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1330f403-44aa-4fb9-9037-fbff2aa7226f/resource/c868e570-1899-4153-ba12-b4509e383779/download/metadata.csv
    Description: Metadata Forest Reserves Monitoring

de:
Resource Title: Metdata Description
    Size: 1117018 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/1330f403-44aa-4fb9-9037-fbff2aa7226f/resource/ffbb3df8-a991-48f0-8bda-912992b50d08/download/descriptionenvidat.pdf
    Description: This document gives an overview on the forest reserves monitoring network and describes the metadata contained in the file metadata.csv

forest-reserves

display_name: forest-reserves

long-term-monitoring

display_name: long-term-monitoring

natural-forest-dynamics

display_name: natural-forest-dynamics

permanent-plot

display_name: permanent-plot


en: This dataset comprises long-term daily 1 km gridded data of snow water equivalent and snow depth for Switzerland spanning the hydrological years 1962 until 2023. The SWE data were generated using the OSHD temperature index model and subsequent quantile mapping (Michel et al. 2024). The snow depth data were derived from the SWE data after applying the SWE2HS conversion algorithm. Details on theses datasets can be found in doi.org/10.5194/tc-19-4391-2025. The products were developed as part of the SPAtial Snow climatology for Switzerland (SPASS) project, a collaboration between MeteoSwiss and SLF.

en: swe 1km-resolution gridded-data snow-depth switzerland snow-climatology

envidat

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.

de: EnviDat: das Umwelt-Datenportal

en: SPASS - new gridded climatological snow datasets for Switzerland

envi

en: Environment

de:
Resource Title: SWECLQMD_ch01h.swiss.lv95_WY_1962_2023.zip
    Size: 1717986918 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/da0c9ee4-ff02-4848-bc65-cbcaae343636/resource/a5db7556-7a91-413a-8d90-4c02aa2e9e8c/download/sweclqmd_ch01h.swiss.lv95_wy_1962_2023.zip
    Description: Long-term daily 1 km gridded data of snow water equivalent for Switzerland. The SWE data were generated using the OSHD temperature index model and subsequent quantile mapping. Details can be found in Michel et al. (2024), see doi.org/10.5194/gmd-17-8969-2024. A first version of this SWE data was publised at https://zenodo.org/records/7886773

de:
Resource Title: HSCLQMD_ch01h.swiss.lv95_WY_1962_2023.zip
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    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/da0c9ee4-ff02-4848-bc65-cbcaae343636/resource/688d1caf-ed63-4cb8-8579-8c017bb7458c/download/hsclqmd_ch01h.swiss.lv95_wy_1962_2023.zip
    Description: Long-term daily 1 km gridded data of snow depth for Switzerland. The data were produced by applying the SWE2HS algorithm of Aschauer et al. (2023) to the SWE dataset, which can also be found in this directory. Details can be found in (doi.org/10.5194/gmd-16-4063-2023).

gridded-data

display_name: gridded-data

snow-climatology

display_name: snow-climatology

snow-depth

display_name: snow-depth

swe

display_name: swe


en:
This dataset contains several useful components for **Swiss Electricity system modeling**:
1. **High-voltage Swiss grid**: 2019 snapshot of the high-voltage (-150kV) grid composed of :
- Nodes: names, voltage, position.
- Lines: ends nodes, resistance, power capacity.
- Transformers: ends nodes, power capacity, resistance, tap ratio.
2. **Hydropower topology** : Representative description of Swiss reservoirs and plants (2019) composed of:
- Plants: Lower reservoir, Upper reservoir, pump/turbine, debit, power capacity.
- Reservoirs: Volume, altitude, position, canton.
3. **Inflows** into all the reservoirs: hourly time series post-processed from PREVAH model outputs from 2009 to 2019.
4. **Wind production per node**: COSMO-1 data processed and scaled to match SFOE annual production.
5. **Solar irradiance maps projected onto tilted surfaces**: hourly time series for 35° and 65° tilts, azimuth 180°. (same method as [Frischholz, Y. (2025)](https://www.doi.org/10.16904/envidat.632))
6. **Processed ERA5 (historical), ECMWF SEAS5 (seasonal forecast) and ECMWF TIGGE (short-term forecast)**:
- ERA5 Land: For inflow forecast model: historical runoff, snow depth, temperature and total precipitation per catchment (hourly, 2009-2019). For residual demand forecast model: historical temperature, u-v wind, ssrd per country (CH, AT, DE, FR, IT, hourly 2015-2019)
- ECMWF SEAS5: For inflow forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019). For residual demand forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019).
- ECMWF TIGGE: For inflow forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019). For residual demand forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019).
7. **Run-of-river production per electricity node**: 15-min resolution run-of-river production time-series (15min, 2009-2019). Raw data and documentation can be found on [https://data.sccer-jasm.ch/runofriver_production/2017-10-16/].
\
More details can be found on *README.txt*.

en: reservoir-inflow electricity-grid renewable-energy meteorological-data forecast-models hydropower solar-irradiance

de: EnviDat

en: Swiss electricity system modeling -- HV grid - hydropower topology and inflows - renewable productions - past and forecast meteorological data

envi

de: Umwelt

de:
Resource Title: data_IFM_RDFM.zip
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    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/7f514513-cb54-44a9-8ea4-8f8087048247/download/data_ifm_rdfm.zip
    Description: ERA5 Land, Seasonal forecast and short-term forecast meteorological data to train inflow and residual demand forecast models.

de:
Resource Title: node_RunOfRiver_15min.ftr
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    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/9923c621-7238-4b16-b20d-6736da165a5a/download/node_runofriver_15min.ftr
    Description: Run-of-river production on 15min resolution from 2009 to 2019 in Switzerland, aggregated by electrical nodes.

format: OCTET

de:
Resource Title: data_IFM_RDFM.zip
    Size: 1191853425 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/965d0b4b-a87f-4023-8bb8-a33dd2d86c5a/download/data_ifm_rdfm.zip
    Description:

de:
Resource Title: SwissGrid_data.zip
    Size: 17664 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/a1224789-8bb8-46cd-a36d-4cb81d6d47ec/download/swissgrid_data.zip
    Description: Description of Swissgrid high-voltage (>150kV) grid, including lines, transformers and nodes (snapshot of the grid in 2019) .

de:
Resource Title: PV_data.zip
    Size: 2072321720 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/e0e501b9-1041-4ff9-a3d9-485cce4aadac/download/pv_data.zip
    Description: Solar irradiance maps projected onto tilted surfaces: hourly time series for 35° and 65° tilts, azimuth 180°. (same method as [Frischholz, Y. (2025)](https://www.doi.org/10.16904/envidat.632))

de:
Resource Title: hydropower.zip
    Size: 21349007 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/66f009b8-0cef-4f4e-bc12-c3a7d684f229/download/hydropower.zip
    Description: Plants and reservoirs description, with associated hourly inflows (2009 - 2019).

de:
Resource Title: README.txt
    Size: 6216 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/0dc23d95-7563-4f21-a416-ca46643d9b69/download/readme.txt
    Description: Data structure and description.

format: TXT

media_type: text/plain

electricity-grid

display_name: electricity-grid

forecast-models

display_name: forecast-models

hydropower

display_name: hydropower

meteorological-data

display_name: meteorological-data

renewable-energy

display_name: renewable-energy

reservoir-inflow

display_name: reservoir-inflow

solar-irradiance

display_name: solar-irradiance


en: This dataset contains code and data to reproduce the figures and analyses in the article 'Environmental DNA metabarcoding reveals biodiversity recovery in tropical forest restoration across multiple landscapes' in Ecosphere journal. In this study, we analysed environmental DNA data from water and soil samples collected across gradients of forest regrowth at six sites in Colombia to assess the recovery of mammal and soil biodiversity associated with forest restoration.

en: soil-biodiversity colombia environmental-dna mammals forest-restoration biodiversity-assessment

en: Data and code underlying 'Environmental DNA metabarcoding reveals biodiversity recovery in tropical forest restoration across multiple landscapes'

de:
Resource Title: Raw Data.zip
    Size: 1610612736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/18ce28d1-0fa3-4f97-9690-78697dd39683/resource/b97d2608-f0d8-4544-a9a6-024f43b1d55d/download/raw-data.zip
    Description: Paired-end reads (specified by the R1 and R2 suffixes) for each individual sample. The reads have been demultiplexed using cutadapt but primers remain present in the sequences.

de:
Resource Title: Analysis Data and Code.zip
    Size: 15005123 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/18ce28d1-0fa3-4f97-9690-78697dd39683/resource/275e7eac-1898-48ed-8c91-e3d2ee840782/download/analysis-data-and-code.zip
    Description: A zipped folder containing the scripts and data necessary to reproduce the analyses described in the study. Further instructions are provided in scripts/ReadMe.txt

biodiversity-assessment

display_name: biodiversity-assessment

colombia

display_name: colombia

environmental-dna

display_name: environmental-dna

forest-restoration

display_name: forest-restoration

mammals

display_name: mammals

soil-biodiversity

display_name: soil-biodiversity


en:
The Swiss Federal Research Institute WSL has extensive experience with surrogate bedload transport measurements. The first measuring site was established in the Erlenbach stream, a small (first-order) catchment in the pre-alpine valley Alptal in central Switzerland. Continuous bedload transport measurements were started in 1986, using first piezoelectric sensors (1986 to 1999) and then geophone sensors (from 2002 onwards) underneath a steel plate and mounted flush with the streambed. In the meantime, the so-called Swiss plate geophone (SPG) system has been installed at more than 20 field sites, primarily in smaller and steeper streams in Switzerland, Austria, and Italy but also in a few larger rivers and in some other streams worldwide (Israel, USA, Japan).
Sediment transport observations in Switzerland with the SPG system concern the following streams: Erlenbach near Brunni (Alptal valley), Albula at Tiefencastel, Navisence at Zinal, Avançon de Nant near Pont de Nant, and Riedbach near Graechen (see map). The data in this repository primarily refer to calibration measurements with the SPG system. The publications listed here discuss primarily the performance of the measuring system but also process-based aspects of bedload transport.

en: mountain-stream surrogate-measurement river sediment-transport bedload-transport torrent

en: Sediment transport observations in Swiss mountain streams

de:
Resource Title: Hydrological drivers of bedload transport in Avançon de Nant
    Size: 224860 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/3e8ee124-0947-4d2a-aa1a-2fef979f838d/download/avancon-de-nant-hydrol-drivers.zip
    Description: Data used in paper: Antoniazza, G., Nicollier, T., Boss, S., Mettra, F., Badoux, A., Schaefli, B., Rickenmann, D., Lane, S.N., 2022. Hydrological Drivers of Bedload Transport in an Alpine Watershed. Water Resources Research, 58, e2021WR030663. https://doi.org/10.1029/2021WR030663

de:
Resource Title: Erlenbach-27-years-bedload-data.zip
    Size: 4320133 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/bb45250d-fa75-440d-9601-f5aa3ccdce35/download/erlenbach-27-years-bedload-data.zip
    Description:

de:
Resource Title: Data-variability-SPG-response
    Size: 1415578 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/44fb4007-2e14-485a-8021-1ff48a75246e/download/data-variability-spg-response.zip
    Description: Data used in paper: Antoniazza, G., Nicollier, T., Wyss, C.R., Boss, S., Rickenmann, D., 2020. Bedload Transport Monitoring in Alpine Rivers: Variability in Swiss Plate Geophone Response. Sensors 2020, 20, 4089; doi:10.3390/s20154089

de:
Resource Title: avancon-de-nant-event-3-August-2020.zip
    Size: 23603446 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/02f144f6-bde3-4578-94e2-be47dd83c74e/download/avancon-de-nant-event-3-august-2020.zip
    Description: Data used in paper: Antoniazza, G., Dietze, M., Mancini, D., Turowski, J.M., Rickenmann, D., Nicollier, T., Boss, S., Lane, S.N. (2023). Anatomy of an Alpine bedload transport event: A watershed-scale seismic-network perspective. Journal of Geophysical Research: Earth Surface, 128, e2022JF007000. https://doi.org/10.1029/2022JF007000

de:
Resource Title: Erlenbach-27-years-bedload-data.zip
    Size: 4320133 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/94f81288-de72-4562-8ee0-e748208a280c/download/erlenbach-27-years-bedload-data.zip
    Description: Erlenbach-27-years-bedload-dat
Data used in paper: Rickenmann, D., 2023. Bedload transport fluctuations, flow conditions and disequilibrium ratio at the Swiss Erlenbach stream: results from 27 years of high- resolution temporal measurements. Earth Surface Dynamics.

de:
Resource Title: EU-1min-1986-1999-286_Qbcalculated_full_QbrepM.csv
    Size: 10380902 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/8b29c4e6-8005-4a9c-add8-f9b93dd423ae/download/eu-1min-1986-1999-286_qbcalculated_full_qbrepm.csv
    Description:

de:
Resource Title: Albula-2016-1min_data.zip
    Size: 6218056 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/a75f0380-edc9-4c6d-a08e-f73deba3bf71/download/albula-2016-1min_data.zip
    Description: Bedload transport measurements with SPG system for Albula 2106.

de:
Resource Title: SPG field calibration data
    Size: 110305 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/173101e2-a6bb-4ddb-90d0-dfaea63aea73/download/field_calibration.xlsx
    Description: SPG field calibration data from the Erlenbach (since 2009), the Albula (2018), the Navisence (2019) and the Avançon de Nant (2019-2020) monitoring stations. Data used in following papers:
"Toward a General Calibration of the Swiss Plate Geophone System for Fractional Bedload Transport" submitted to Earth Surface Dynamics on the 14th of January 2022.
"Improving the Calibration of Impact Plate Bedload Monitoring Systems by Filtering Out Acoustic Signals from Extraneous Particle Impacts" submitted to Earth and Space Science on the 13th of August 2021.

de:
Resource Title: SPG flume experiment data
    Size: 270817 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/be0743a3-87fc-4e4d-bb42-3195224883be/download/flume_experiments.xlsx
    Description: SPG data from controlled flume experiments conducted at the Obernach outdoor flume facility (TU Munich) between 2018 and 2020. Data used in following papers:
"Toward a General Calibration of the Swiss Plate Geophone System for Fractional Bedload Transport" submitted to Earth Surface Dynamics on the 14th of January 2022.
"Improving the Calibration of Impact Plate Bedload Monitoring Systems by Filtering Out Acoustic Signals from Extraneous Particle Impacts" submitted to Earth and Space Science on the 13th of August 2021.

de:
Resource Title: Erlenbach_event-bedload_periods-A-B
    Size: 103076 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/cf94099a-e87d-4920-9587-73f6cdd78943/download/erlenbach_event-bedload_periods-a-b.zip
    Description: Data used in paper: Rickenmann, D., 2020. Effect of Sediment Supply on Cyclic Fluctuations of the Disequilibrium Ratio and Threshold Transport Discharge, Inferred from Bedload Transport Measurements over 27 Years at the Swiss Erlenbach stream. Water Resources Research, 56, e2020WR027741. https://doi.org/10.1029/2020WR027741

de:
Resource Title: Comparison of calibration characteristics of different acoustic impact systems
    Size: 30300 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0387b6bb-a4f8-4e0d-87e0-6eff063422bd/resource/4d2eb4f8-99eb-4223-8627-527d3e6c629f/download/calibration-measurements-paper-esurf-2022.zip
    Description: Data used in paper: Rickenmann, D., Ammann, L., Nicollier, T., Boss, S., Fritschi, B., Antoniazza, G., Steeb, N., Chen, Z., Wyss, C., Badoux, A. (2022). Comparison of calibration characteristics of different acoustic impact systems for measuring bedload transport in mountain streams. Earth Surface Dynamics Discussions, https://doi.org/10.5194/esurf-2022-7

bedload-transport

display_name: bedload-transport

mountain-stream

display_name: mountain-stream

river

display_name: river

sediment-transport

display_name: sediment-transport

surrogate-measurement

display_name: surrogate-measurement

torrent

display_name: torrent


en:
Jikradia olitoria Say is a Nearctic leafhopper that was recently identified in several European countries. Given its role as the vector of phytoplasmas associated with Grapevine Yellows diseases (GYD) in its native range, its presence in European vineyard agroecosystems could represent an important phytosanitary risk.
Systematic monitoring conducted over two consecutive years (i.e., 2023 and 2024) using chromotropic traps in seven sites allowed to confirm its widespread presence in the southern Alps, both inside vineyards as well as in the nearby forest edge compartment. Moreover, a subset of the collected specimens was analyzed to test potential infection by phytoplasmas associated with Flavescence dorée.

en: nearctic-leafhopper neobiota grapevine-yellows epidemiology flavescence-doree

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.

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.

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: First detailed record of Jikradia olitoria (Hemiptera: Cicadellidae) in the Swiss southern Alps and evaluation of its current potential as a vector of 16SrV-phytoplasmas

envi

de: Umwelt

de:
Resource Title: Table2 - Jikradia olitoria hatching events
    Size: 15278 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/83726448-91da-423c-8eb4-28a195c7f40a/resource/7bf9a0ee-2111-4144-8f11-f4f35784b74c/download/table2.docx
    Description: Jikradia olitoria hatching events divided by year and wood type. For the hatching experiment, wood was collected from the Giornico site due to the large J. olitoria adult population observed in 2023.

de:
Resource Title: Supplementary_table3 - Hatching events
    Size: 15852 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/83726448-91da-423c-8eb4-28a195c7f40a/resource/588d922d-1acd-4eab-9693-c76d4cf7d9a6/download/supplementary_table3.xlsx
    Description: Hatching events in 2024 and 2025.

de:
Resource Title: Supplementary_table1 - Trap captures 2023
    Size: 144783 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/83726448-91da-423c-8eb4-28a195c7f40a/resource/8c89de75-a018-44c1-b913-346b1dbc5356/download/supplementary_table1.xlsx
    Description: Trap captures in 2023.

de:
Resource Title: Supplementary_table2 - Trap captures 2024
    Size: 165550 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/83726448-91da-423c-8eb4-28a195c7f40a/resource/bba02f83-22d2-48d3-8d60-39e03be1cfb6/download/supplementary_table2.xlsx
    Description: Trap captures in 2024.

de:
Resource Title: Table1 - Jikradia olitoria total captures
    Size: 21647 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/83726448-91da-423c-8eb4-28a195c7f40a/resource/05806ade-fd08-4bfa-b2bb-a0991dec3377/download/table1.docx
    Description: Jikradia olitoria total captures divided by plot and trap type, mean captures per trap and ratio between the two sampling years. YST/plot = yellow sticky traps installed in each plot, L = landscape YST, V = vineyard YST, N YST = overall number of processed YST throughout the experiment.

epidemiology

display_name: epidemiology

flavescence-doree

display_name: flavescence-doree

grapevine-yellows

display_name: grapevine-yellows

nearctic-leafhopper

display_name: nearctic-leafhopper

neobiota

display_name: neobiota