en: dissipated-energy breaking-energy eota stonenode sensor-technology rockfall-experiments windthrow protective-effect forest lying-deadwood rockfall

en: VideoArchive_HD_Resolution (individual video directory)

en: This archive contains all recorded runs from RF32, RF33, RF35, RF37 and RF44 in HD quality (roughly 1900x1200 pixels). The file size is, therefore rather big (>40GB). Single videos can be downloaded in the "individual video directory"

en: All soil moisture data measurements acieved by GS1 and MPS6 sensors and logged by a Decagon EM 50 data logger. Additionally, the location of the data logger (.shp file) and the area, which is considered as represented by the measurements (also .shp files) are saved in this .zip file.

en: A (not further analyzed) attempt to describe the tree deflections after rock impacts summarized in an Excel spreadsheet.

en: input data for the ramms simulations including DEM (.asc), the deadwood files (.pts), the treefile, the release line, othophoto, rocks and soil parameters.

en: During RF44 (10.04.2021) we placed several deadwood logs. Their arrangement was recorded by a terrestrial laser scanner. Additionally, the logs diameter were measured every 3 m (within the excel file)

en:
Two tables per experimental run: a jump table including all parablic jumps, sliding and rolling. On the other hand also the table of all soil impacts, inbetween two jumps.
These tables are the results from the trajectory reconstruction, which based on the synchronisation of StoneNode data the Videodata and their geolocations. This synchronisation was dane based on the excel spread sheets, which are aditionally saved in this zip folder.

en: Figures of the rotational and gyroscopic StoneNodeData and where available the impact categories.

en: LiDAR data sets of the experimental area.

en: Matlab datasets containing all the available in-situ StoneNode data featureing acceleration (acc) and rotational data (gyr).

en: The spatial data, such as the deposition points, the orthophotos, the digital surface models (drones), the detected and measured trees, and the shape files of the deadwood-areas, are summarized in this archive.

en: We conducted an experimental rockfall campaign on a forested slope with deadwood and on with the windthrown area cleared in Schiers (CH). Two different rock categories were used: natural rocks with masses between 30 and 85 kg and artificial EOTA-concrete rocks with rock masses ranging from 45 kg up to 3200 kg. In contrast to the intended research article publication, also all information about the experimental runs of the smaller rock masses are available. Besides the geometries of those rocks, the data set contains three LiDAR point clouds, orthophotos, the release point (and release line used in RAMMS), the retrieved single tree positions with DBH, and energy absorption threshold, video footage, and all reconstructed trajectories.

breaking-energy

display_name: breaking-energy

dissipated-energy

display_name: dissipated-energy

eota

display_name: eota

forest

display_name: forest

lying-deadwood

display_name: lying-deadwood

protective-effect

display_name: protective-effect

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

sensor-technology

display_name: sensor-technology

stonenode

display_name: stonenode

windthrow

display_name: windthrow

en: Shape still matters - experimental quantification of deadwood effects on rockfall dynamics


maintainer: Matthias Haeni

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

state: active

type: dataset

en: Site aerial photo (Beatenberg)

en: Site aerial photo from both Beatenberg stations. Source: Google. 2016. Site aerial photo from both Beatenberg stations. Retrieved November 11, 2016, from https://www.google.ch/maps

format: SERVICE

mimetype: image/jpeg

en: Data plot of the forest station (BAB)

media_type: application/pdf

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

format: PDF

mimetype: application/pdf

en: Site photo of the forest station (BAB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Field station data (BAF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Forest station data (BAB)

en: Site photo of the field station (BAF)

en: Site photo of the field station from below (viewing upwards the slope).

en: Data plot of the field station (BAF)

en:
High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Beatenberg in Switzerland where one station is located within a natural coniferous forest (BAB) with Norway spruce (_Picea abies_; 190-210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Beatenberg is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the
Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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.

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Beatenberg, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


en: swiss-forest-lab long-term-forest-ecosystem-research icp-forests deadwood coarse-woody-debris

en: Data Request

en:
Assessment of coarse woody debris on Sanasilva plots (16x16 km grid) using the full count methods on subplots applying BioSoil protocoll

 Purpose:

Assessing the amount of coarse woody debris

 Manual Citation:

 * A. Bastrup-Birk, P. Nevile, G. Chirici, T. Houston, 2006: The BioSoil ForestBiodiversity Field Manual Version 1.0/1.1/1.1A for the Field Assessment 2006-07. Working Group on ForestBiodiversity, Forest Focus Demonstration Project BioSoil 2004-2005, 47 S.

coarse-woody-debris

display_name: coarse-woody-debris

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

en: Deadwood survey Sanasilva 2013


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: envidat wsl research-data-management juypter-notebooks open-science

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

envidat

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

en: EnviDat Supports Open Science


maintainer: EnviDat Support

en: co2 nitrogen forest face picea-abies soil

en: Resin bags

en: Ammonium, nitrate and their 15N in resin bags

en: Water analyses

en: Analyses of water, especially soil solution

en: Gross N mineralisation and nitrification

en: Gross rates of N mineralisation and nitrification (15N dilution)

en: Collection points

en: Collection points under the trees

en: Collection of soil solution

en: Soil solution collected by suction cups

en: Soil C and N

en: Analyses of C, N and their stable isotopes in the soil, and soil pH

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

face

display_name: face

forest

display_name: forest

nitrogen

display_name: nitrogen

picea-abies

display_name: picea-abies

soil

display_name: soil

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


lwf-celerina-long-term-research-site

title_for_slug: lwf-celerina-long-term-research-site

en: lwf plot swiss-forest-lab forest infrastructure meteorological-data meteorological-measurements

en: LWF plot Celerina. Photo: Oliver Schramm, 2011

en: Celerina Meteorological Data LWF

en:
![alt text](https://www.envidat.ch/dataset/0c244fe7-886a-4a1c-add5-5f706e995a29/resource/28e97caa-65fc-4396-8bca-860721eddfa2/download/lwf_celerina.jpg "LWF Celerina")

LWF Plot Celerina

- Community: Celerina / canton GR
- Date of installation: 3 July 1996
- Size of the plot: 2 ha
- Altitude (m): 1846-1896
- Mean slope: 34%
- Geology (in German): Untergrund: ostalpin; prätriadische Tiefengesteine - Oberfläche: Quartär; karbonatfreie Moräne
- Soil types (WSL): n.d.
- Woodland association after EK72: 59: Larici-Pinetum cembrae
- Main tree species: Pinus cembra
- Management system: high forest
- Silvicultural system: group selection
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 48.6 cm
- Number of trees BHD >= 12 cm (2011): 469
- Maximum tree age: Pinus cembra uneven-aged - 210-250 years

More Information: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/celerina.html

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

meteorological-measurements

display_name: meteorological-measurements

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: LWF Celerina long-term research site


salvage-logging

title_for_slug: salvage-logging

en:
Volume of stemwood with bark of all trees and shrubs starting at 12 cm dbh that were removed from the forest as a result of damage occurring (e.g. windthrow, avalanches, insects, rockfall), and not because of management planning. This theme is derived on the level of a sample plot from the cuttings of the sample trees and the salvage cut proportion (according to information from the forester). *In the calculation no D7/tree height data were used. The values calculated like this have not been corrected for bias, but allow for cantons or forest districts a more robust estimation of changes and could thus be better interpreted.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

avalanches-silvaprotect

display_name: avalanches-silvaprotect

canton

display_name: canton

cause-of-salvage-logging

display_name: cause-of-salvage-logging

landslide-mudflow-silvaprotect

display_name: landslide-mudflow-silvaprotect

main-type-of-harvest

display_name: main-type-of-harvest

potential-cost-for-timber-harvesting

display_name: potential-cost-for-timber-harvesting

processes-in-channels-silvaprotect

display_name: processes-in-channels-silvaprotect

rockfall-silvaprotect

display_name: rockfall-silvaprotect

salvage-logging-star

display_name: salvage-logging-star

en: Salvage logging*


soil-solution-chemistry-lysimeters-lwf

title_for_slug: soil-solution-chemistry-lysimeters-lwf

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

en: Data Request

en:
Fortnightly measurement of the soil solution chemistry in 4 soil depths with zero-tension lysimeter below the litter layer and with tension lysimeters at depths of 15, 50 and 80 cm (8 replicates)

 Purpose:

To characterize the chemical status of the soil solution and to detect trends in soil water quality. To assess the effects of air pollution and climate chnage on soil water quality.

 Manual Citation:

 * Micha Pluess, Daniel Christen, 1999: Kurzanleitung Bodenlösung. Langfristige Waldökosystem-Forschung LWF, Birmensdorf, 2 S.

 * Nieminen TM, De Vos B, Cools N, König N, Fischer R, Iost S, Meesenburg H, Nicolas M, O’Dea P, Cecchini G, Ferretti M, De La Cruz A, Derome K, Lindroos AJ, Graf Pannatier E, 2016: Part XI: Soil Solution Collection and Analysis. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 20 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Graf Pannatier, E.; Thimonier, A.; Schmitt, M.; Walthert, L.; Waldner, P., 2011: A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?. Environmental Monitoring and Assessment, 174, 1-4: 3-30. [doi: 10.1007/s10661-010-1754-3](http://doi.org/10.1007/s10661-010-1754-3)

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

soil-solution-chemistry

display_name: soil-solution-chemistry

en: Soil solution chemistry (lysimeters) LWF


en: pfynwald forest pinus carbon fauna-data litter soil drought

format: XLS

en:
Data from a 17-year-long irrigation experiment (Pfynwald, Switzerland) in a naturally dry forest dominated by 100-year-old pine trees (Pinus sylvestris).
Data include: (1) properties of soils sampled in 2011 and 2019 (SOC and N concentrations and stocks, soil masses, 13C and 15N natural abundances, C/N ratios, clay content, pH, inorganic C, stoniness, bulk density); (2) litter mass loss and initial litter chemistry of dominant tree species (Quercus, Pinus, Viburnum) from a litter decomposition experiment carried out in 2014-2015; (3) soil fauna abundance sampled in 2015; (4) soil volumetric water content and soil temperature at 10 cm depth measured during the litter decomposition experiment in 2014-2015; (5) soil mesofauna (Acari and Collembola) diversity and community composition from sampling in 2017; (6) irrigation-induced changes in litterfall (2013-2014, 2016-2017), fine-root production (data 2015 from Brunner et al., 2019, Frontiers in Plant Science), annual soil respiration (estimated for 2014-2015), litter mass loss from litter decomposition experiment (May-October 2014), and SOC stocks measured in 2011 and 2019; (7) Moisture dependency of microbial soil respiration (0-10 cm depth, adapted from Joseph et al., 2020 PNAS), soil respiration measured in 2015 and abundance of Acari, Collembola and Lumbricidae sampled in 2015.

carbon

display_name: carbon

drought

display_name: drought

fauna-data

display_name: fauna-data

forest

display_name: forest

litter

display_name: litter

pfynwald

display_name: pfynwald

pinus

display_name: pinus

soil

display_name: soil

en: Soil fauna drives SOC storage in a long-term irrigated dry pine forest


en: soil-water-potential long-term-forest-ecosystem-research long-term-monitoring swiss-forest-lab soil-moisture-water-content wdb

en: Data request

en:
Since 2001 soil water content and soil water potential are measured in 40 plots of the *[Intercantonal Forest Observation Program](https://www.envidat.ch/dataset/interkantonale-walddauerbeobachtung-wdb)*. Soil water content and soil water potential is measured in hourly resolution in 3 depths according to the soil horizons.

The following parameters about soil water balance are measured:

 * Volumetric soil water content (SMT-100, Truebner)
 * Soil water potential (TEROS21, METER)

More information about the analytical methods and results can be found in *[Braun et al. (2021)](https://doi.org/10.5281/zenodo.5724756)*.

long-term-monitoring

display_name: long-term-monitoring

soil-moisture-water-content

display_name: soil-moisture-water-content

soil-water-potential

display_name: soil-water-potential

swiss-forest-lab

display_name: swiss-forest-lab

wdb

display_name: wdb

en: Soil moisture and soil water potential measurements of the Intercantonal Forest Observation Program


en: elevation parasitoids predators gradient pinus insects pests bark-beetles

en: Gradients

en:
The column headers refer to:

- SamplingCode: WSL fauna database code referring to year and trap type (not relevant)
- SamplingDate: Date when the emergence traps were emptied, corresponds roughly to the date of emergence
- TreeNumber: Tree ID
- Defoliation: percentage of needle loss or crown transparency, according to international standards, of the trees prior to felling
- BarkSurface: bark surface area of stem parts exposed in emergence traps
- YearOfAttack: Year of colonization. Technically, the colonization window opened on 1st of January and closed in June, when sections of the tree stems were transported to the institute
- YearOfEmergence: Emergence year of a given cohort of insects in the greenhouse
- YearAfter Attack: Temporal difference between year of colonization and year of emergence of a given cohort of insects, corresponding to total development time
- Region: AO Aosta (ITA), GR Grisons (CH), VS Valais (CH)
- Location: locality nearest to the gradient
- Elevation: Site where trees were felled and exposed to colonization
- Aspect: north (N) or south (S) facing slope
- Species: taxonomic species according to Fauna Europaea
- Family: taxonomic family
- Order: taxonomic order: Col. Coleoptera, Hym. Hymenoptera, Dipt Diptera, Raph Raphidioptera
- Guild: Phyto phytophagous, Pred predatory, para parasitoid
- Number: number of sampled individuals of a given species at a given date.
- Density: number of emerged insects per m2 bark surface
- Identifyer: specialist who identified the insects

en:
The colonization of cut pine stems by wood-inhabiting insects was investigated at various elevations. The study sites were located in the regions of Aosta Valley (Italy), Valais (Switzerland), and Grisons (Switzerland). In each region, there were two gradients in pine (Pinus sylvestris) forests, with three study sites at 900 m, 1200 m, and 1600 m a.s.l. each. Vital trees were felled in late autumn and the stems were colonized by pioneering xylophagous insects and their natural enemies next spring. Pieces of these stems were cut and exposed in emergence traps in a greenhouse. In each region the survey was done in two consecutive years.

Please contact author for terms of use.

bark-beetles

display_name: bark-beetles

elevation

display_name: elevation

gradient

display_name: gradient

insects

display_name: insects

parasitoids

display_name: parasitoids

pests

display_name: pests

predators

display_name: predators

educ

en: Education, culture and sport

en: Pine insects along elevational gradients


en: COST European Snow Booklet (ESB) - DORA Link

media_type: text/html

en: DORA Link of the COST European Snow Booklet (ESB).

format: HTML

en: European Snow Booklet unpublished metadata

en: The entire station metadata of all European institutions that contributed data is stored in METADATA_unpublished.xlsx. This file, however, cannot be accessed, since not all institutions gave permission to publish their station metadata. If you wish to access the metadata, please send a request to marty@slf.ch stating clearly why you want to access these metadata. NOTE: in this file ONLY station metadata (Lat/Lon/Altitude) is given, NO measured snow depth data.

en: COST European Snow Booklet (ESB)

en: Please find here the web version of the COST European Snow Booklet (ESB).

en: European Snow Booklet public metadata

en:
The core of the European Snow Booklet (ESB), the country reports of 38 European countries, are based on information and metadata on snow measurements collected through a comprehensive survey, the ESB Questionnaire, between August 2017 and March 2018. The station metadata (for example location, elevation, measurement start date) from each country was provided by one or several institutions responsible for snow observations. By answering the questionnaire the contacts agreed that the information and metadata provided could be presented in the ESB. For cases where institutions indicated that information on station locations could be made publicly available, the metadata for the variables snow depth (HS), depth of snowfall (HN) and water equivalent of the snow cover (SWE), is additionally provided here for download (METADATA.xlsx).
Please note that not all institutions gave permission to publish their station metadata. This metadata has to be requested from the non-personal institution contacts provided in the METADATA.xlsx file. In some cases, however, no institutional contact is available and thus the contact of the country representative who filled in the questionnaire is used.
For current, updated station metadata we refer to the (non-personal) institutional contacts provided in METADATA.xlsx and/or the institution webpages. Note, however, that we cannot guarantee for completeness of the dataset for all countries because operational networks are prone to changes.

en: List of authors and list of the editorial board of the European Snow Booklet

en:
Here you can find the list of all lead authors of the different chapters of the European Snow Booklet (ESB).
In addition a list of the editorial board that reviewed the ESB is given.

en:
The European Snow Booklet (ESB) is a book of reference for snow measurements that has been produced through collaboration with many European snow practitioners and snow scientists in the framework of the European Cooperation in Science and Technology (COST) Action ES1404 “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction (HarmoSnow)”. The ESB provides a unique collection of information about operational snow observations in the European countries and the methods used to perform basic measurements of snow on the ground: snow depth (HS), depth of snowfall (HN), water equivalent of the snow cover (SWE) and presence of snow on the ground (PSG). Information and station metadata (for example location, elevation) for these basic snow variables were collected through a comprehensive survey, the ESB questionnaire between August 2017 and March 2018. Numerous institutions of 38 European countries provided detailed information describing the status of the operational snow observations and the methods used at the time of the survey. Based on the information provided, a country report was written for each European country. Similarities and differences among the countries, that is, the choice of snow variables to be measured, the measurement principles applied, the number of stations, or the spatial and elevational station distribution are pointed out. Thus the collection of country reports demonstrates the relevance of snow measurements for each country. Thus, the intention of the ESB is to foster better knowledge transfer regarding snow measurements between the snow science and operational communities and to improve the communication of information to the general public.

For detailed information on the European countries, we refer to the ESB, which can be downloaded here (envidat.ch). Please note that the ESB is not a living document and information and station metadata are from August 2017 till March 2018, except for Latvia (metadata updated in December 2018).

depth-of-snowfall

display_name: depth-of-snowfall

harmonisation-of-snow-measurements

display_name: harmonisation-of-snow-measurements

snow-depth

display_name: snow-depth

snow-measurement-methods

display_name: snow-measurement-methods

water-equivalent-of-the-snow-cover

display_name: water-equivalent-of-the-snow-cover

envidat

en: EnviDat: the Environmental Data Portal

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

en: European Snow Booklet – an Inventory of Snow Measurements in Europe


en: availability potential-assessment bioenergy sustainability biomass-resources

en: Biomass Potentials Switzerland

en: Biomass Potential Switzerland Municipalities

en: Domestic biomass potential based on 2014 data at the municipality level for the theoretical and sustainable potential for 10 types of biomass.

en: Biomass Supply Costs

en: Biomass Potentials Switzerland Cantons

en: Switzerland has a reliable and cost efficient energy system. Due to phase out of nuclear energy it is necessary to find new options to maintain this powerful energy system. The Swiss energy strategy 2050 aims to reduce CO2-emissions, increase efficiency and promote renewable energies. The Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) examined relevant woody and non-woody biomass quantities (cubic meters, fresh-, dry weight) and their energy potentials (in Petajoules: primary energy and biomethane) with a similar methodological approach. The work was done within the frame of the Swiss Competence Centers for Energy Research (SCCER) especially in line with the SCCER Biomass for Swiss energy future (Biosweet). With a uniform and consistent approach for the current potentials ten biomass categories were estimated and aggregated for the whole of Switzerland. In this context solutions for the technical, social and political challenges are promoted. First, considering the different biomass resources characteristics and available data, appropriate methods at the finest scale possible were elaborated to estimate the annual quantities which could theoretically be collected (theoretical potential). Then, explicit and rational restrictions for sustainable bio-energy production were defined according to the current state of the art and subtracted from the theoretical potential to obtain the sustainable potential. The main restrictions are competing material utilizations, environmental factors and supply costs. Finally, the additional sustainable potential was estimated considering the current bioenergy production. Our main purpose was to provide potentials for developing conversion technologies as well as a detailed and comprehensive basis of the Swiss biomass potentials for energy use for economic and political decision makers. The complete report is available under https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A13277/datastream/PDF/view

availability

display_name: availability

bioenergy

display_name: bioenergy

biomass-resources

display_name: biomass-resources

potential-assessment

display_name: potential-assessment

sustainability

display_name: sustainability

en: Potentials of domestic biomass resources for the energy transition in Switzerland


bole-wood-mass-of-live-trees

title_for_slug: bole-wood-mass-of-live-trees

en:
Dry weight (mass) of the stemwood with bark of the living trees and shrubs starting at 12 cm dbh.  The correction for bias with the sample Tarif trees may be so drastic that it results in negative values with small numbers of trees.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

biogeographical-region

display_name: biogeographical-region

bole-wood-mass-of-live-trees

display_name: bole-wood-mass-of-live-trees

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

educ

en: Education, culture and sport

en: Bole wood mass of live trees


en: longwave-radiation outgoing shortwave-radiation davos incoming

en: Parameter file

media_type: text/plain

format: TXT

mimetype: text/plain

en: Metadata

en: DATA ACCESS

en: Processing doc

en:
Incoming and outgoing shortwave and longwave 2 min radiation measurements in Davos Dorf, CH.

 References
1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019.
2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf.

davos

display_name: davos

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

en: ASRB_DAV: Shortwave and longwave radiation measurements (2 min) in Davos Dorf


en: snow snow-water-equivalent gcos snow-profile snow-height

en: STATION METADATA

en: Snowprofile from 11 observer sites in Switzerland compiled for the Global Climate Observing System (GCOS). Height of snow (cm) and snow water equivalent (mm) are recorded every 2 weeks since the 1947 (depending on station). Attached metadata file gives details of each station.

gcos

display_name: gcos

snow

display_name: snow

snow-height

display_name: snow-height

snow-profile

display_name: snow-profile

snow-water-equivalent

display_name: snow-water-equivalent

envidat

en: EnviDat: the Environmental Data Portal

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

en: GCOS SWE data from 11 stations in Switzerland


en: coarse-woody-debris long-term-forest-ecosystem-research deadwood swiss-forest-lab icp-forests

en: Data Request

en:
Assessment of coarse woody debris on LWF plots using the line intersect method and full count methods on subplots (repetition of the 2005 survey)

 Purpose:

Assessing the amount of coarse woody debris

 Manual Citation:

 * ForestBiota, 2005. Stand structure assessment including deadwood. EU/ICP Forests Biodiversity Test-Phase (ForestBIOTA). [>>>](http://www.forestbiota.org)

coarse-woody-debris

display_name: coarse-woody-debris

deadwood

display_name: deadwood

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab

en: Deadwood survey LWF 2013 - subplot


latent-reserves-within-the-swiss-nfi

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

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

en: Data figure 4

en:
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.

en: Data figure 7

en:
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.

en: Data figure 3

en:
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.

en:
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.

en: Data for mortality analyses

en:
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.

en: Data figure 2

en:
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.

en: Data figure 5

en:
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.

en: Data figure 6

en:
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

en: Data figure 8

en:
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.

en:
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.

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.

forest-reserves

display_name: forest-reserves

national-forest-inventory

display_name: national-forest-inventory

near-natural-forest

display_name: near-natural-forest

switzerland

display_name: switzerland

tree-mortality

display_name: tree-mortality

educ

en: Education, culture and sport

en: 'Latent reserves' within the Swiss NFI


espon-digiplan

title_for_slug: espon-digiplan

en: spatial-planning digitalisation efficiency transparency innovation geoportal

en: Switzerland 2020 all transcripts Digiplan Task 2

en: All transcripts are written in German.

en: Questionnaire Digiplan Task 2 CH_D

en: This document contains the questionnaire, which was used for the expert interviews in the context of Digiplan Task 2. The questionnaire was adapted to the context of the country or the to the context of the interviewee in some interviews. Therefore, some additional questions were asked or some questions were skipped.

en: Germany 2020 all transcripts Digiplan Task 2

en: Metadata of the written transcripts

en: Additional information (position of expert, date of the interviews) on the transcripts can be found in this document.

en: The dataset as a part of the international project ESPON Digiplan. The aim of this international project is to assess the extent, organisation and financing of digitisation of plan data as well as the use of these data in ESPON member countries. As a part of the in-depth case study, 7 virtual expert interviews in Switzerland and 5 virtual expert interviews in Germany were conducted with experts on the topic of digitisation of plan data. The documents contain the transcripts of the interviews. The transcripts aim to capture the content of the interviews, which is why voice raising and lowering, as well as pauses in the interview, were not specifically recorded. The interviews were conducted in German, therefore the transcripts are also in German.

digitalisation

display_name: digitalisation

efficiency

display_name: efficiency

geoportal

display_name: geoportal

innovation

display_name: innovation

spatial-planning

display_name: spatial-planning

transparency

display_name: transparency

envidat

en: EnviDat: the Environmental Data Portal

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

en: ESPON Digiplan


en: soil-water-content soil-moisture swiss-forest-lab long-term-forest-ecosystem-research icp-forests

en: Data Request

en:
Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA).

 Purpose:

Monitoring of the soil water matrix potential

 Paper Citation:

 * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123)

soil-moisture

display_name: soil-moisture

soil-water-content

display_name: soil-water-content

en: 10-HS Pfynwald


en: ATREE survey on climate regulatoin services of forests in "stacked" format

en: The data contains information from XXX respondents. The information of each respondent is represented by 27 rows, one row for each of the three options that were presented in 9 choice situations. This is the "stacked" data-format resulting from a conjoint analysis survey experiment. The data has to be rearranged depending on the software used for analysis.

en: Questionnaires für ATREE climate regulation of forests survey

en: These are the questionnaires that were distributed among the forest owners (mostly as an online-form but for some respondents also as "paper-and-pencil" version) invited to participate in the survey. There are 10 versions of this questionnaire as the conjoint survey experiment was based on 10 different versions of the 9 choice situations that are presented in the survey, which were assigned randomly to the invited participants.

en: Forest owners of the Canton of Lucerne were survey about their willingness to employ different forest management measures to provicde climate regulation services by forests. Of the nearly 3000 forest owners that received an invitation to a online-survey and the 900 forest owners that received a paper and pencil survey, 1055 valid responses were received. The questionnaire contained a survey experiment in which 9 choice situations were presented to the respondents in which they had the choice between two options and the status quo. This survey experiment part of the survey was completed by 990 respondents.

atree

display_name: atree

forest-carbon-sink

display_name: forest-carbon-sink

forest-management

display_name: forest-management

fuel-wood

display_name: fuel-wood

wood-carbon-sink

display_name: wood-carbon-sink

educ

en: Education, culture and sport

en: ATREE forest owners survey about climate regulation services of forests


en: forest modeling climate-change-impact forest-dynamics hydrology

en: FORHYCS v 1.0.0 model code (28-10-2019)

media_type: application/zip

en: Model code for FORHYCS as described in the Speich et al. discussion paper in GMDD. Includes code for the parent models PREVAH and TreeMig, as well as the new interface routines and output modules.

format: ZIP

en: Scripts and sample datasets v. 1.0.0

en: Scripts and sample files for the documentation of FORHYCS (version 1.0.0)

en: Documentation

en: Technical documentation for the FORHYCS model. Includes an overview of the model code; changes from the parent models PREVAH and TreeMig; a description of the file format for grid inputs/outputs and a description of the file structure on a HPC cluster.

en: Link to FORHYCS in Github

en:
Model code, technical documentation and auxiliary files for the dynamic ecohydrological model FORHYCS (FORests and HYdrology under Climate change in Switzerland). FORHYCS combines two pre-existing models, the hydrological model PREVAH and the forest landscape model TreeMig.

License: GPL v3

climate-change-impact

display_name: climate-change-impact

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

hydrology

display_name: hydrology

modeling

display_name: modeling

en: FORHYCS v. 1.0.0 model code


maintainer: Frank Techel

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

en: avalanche occurrence data (Norway, Sitzerland) - avalanche sizes per day and warning region

en: ECT data (Norway, Switzerland)

en: avalanche occurrence data (Norway, Sitzerland) - largest avalanche size per day and warning region

en: Rutschblock data (Switzerland)

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.

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

envidat

en: EnviDat: the Environmental Data Portal

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

en: Stability tests, avalanche observations, Switzerland, Norway


maintainer: Anita C. Risch

en: herbivore nitrogen fertilization nutrient-network mineralization nitrification ammonification climate grassland soil global-change

en: Risch et al. 2020 - Raw data for publication "Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties"

en:
we assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

Study sites and experimental design
The 22 sites contributing to this project are part of the Nutrient Network Global Research Cooperative (NutNet, https://nutnet.umn.edu/). Mean annual temperature across our 22 sites ranged from -4 to 22°C, mean annual precipitation from 252 to 1,592 mm, and elevations from 6 to 4,261 m above sea level (Fig. 1, Supplementary Table S1). Soil organic C varied from 0.8 to 7.8%, soil total N from 0.1 to 0.6%, and the soil C:N ratio from 9.1 to 21.5. Soil clay content spanned from 3.0 to 35%, and soil pH from 3.4 to 7.6 (Supplementary Table S2). Thus, the sites covered a wide range of environments in which grasslands occur (Fig. 1, Supplementary Table S1 & S2).
At each site, the effects of nutrient addition and herbivore removal were tested via a randomized-block design (Borer et al., 2014; Supplementary Fig. S1a). Three replicate blocks with 10 treatment plots each were established at each site, with the exception of the site at bldr.us, where only two blocks were established (Supplementary Fig. S1a). The 10 plots were randomly assigned to a nutrient or fencing treatment, but only a subset of four plots was used in the current study, each with a different treatment (see below; Supplementary Fig. S1a). All plots were 5 x 5 m and divided into four 2.5 x 2.5 m subplots (Supplementary Fig. S1b). Each subplot was further divided into four 1 x 1 m square sampling plots, one of which was set aside for soil sampling (Borer et al., 2014; Supplementary Fig. S1b). Plots were separated by at least 1 m wide walkways.
In this study, we collected data from the following four treatments: (i) untreated control plots (Control), (ii) herbivore removal plots (Fence), (iii) plots fertilized with N, P, K, plus nine essential macro and micronutrients (NPK), and (iv) plots with simultaneous fertilizer addition and herbivore removal (NPK+Fence; Supplementary Fig. S1a). The number of years of treatment differed among sites (2 – 9 years since start of treatment; Supplementary Table S1). For the nutrient additions, all sites applied 10 g N m-2 yr-1 as time-release urea; 10 g P m-2 yr-1 as triple-super phosphate; 10 g K m-2 yr-1 as potassium sulfate. A micro-nutrient mix (Fe, S, Mg, Mn, Cu, Zn, B, Mo, Ca) was applied at 100 g m-2 together with K in the first year of treatments but not thereafter.
The vertebrate herbivore removal treatment (Fence) was established by fencing two plots, one control and one NPK plot, within each of the blocks (Supplementary Fig. S1a). We designed the fences so that they would effectively exclude aboveground mammalian herbivores with a body mass of over 50 g (Borer et al., 2014). At the majority of sites, the height of the fences was 180 cm, and the fence design included wire mesh (1 cm holes) on the first 90 cm along with a 30 cm outward-facing flange stapled to the ground to exclude burrowing animals; climbing and subterranean animals may potentially still access these plots (Borer et al., 2014). For slight modifications in fence design at a few sites see Supplementary Table S3. While most sites only had native herbivores, a few sites (4) were also grazed by domestic animals (Supplementary Table S1).
Potential and realized soil net N mineralization, ammonification, nitrification and other soil properties
Each site participating in the study received a package containing identical material from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) to be used for sampling and on-site N incubations. For the field incubation, we followed the protocol by Risch et al. (2015, 2019). Briefly, we drove a 5 x 15 cm (diameter x depth) steel cylinder 13.5 cm deep into the soil after clipping the vegetation at randomized locations in each plot. The top 1.5 cm of the cylinder remained empty to capture incoming N from run-off or deposition with a polyester mesh bag (mesh-size 250 µm) filled with 13.2 ± 0.9 g of acidic and alkaline exchanger resin (1:1 mixture; ion-exchanger I KA/ion-exchanger III AA, Merck AG, Darmstadt). The bag was fixed in place with a metal Seeger ring (Bruetsch-Rüegger Holding, Urdorf, Switzerland). We then removed 1.5 cm soil at the bottom of the cylinder and placed another resin bag to capture N leached from the soil column. The exchange resin was saturated with H+ and Cl- prior to filling the bags by stirring the mixture in 1.2M HCl for 1 h and then rinsing it with demineralized water until the electrical conductivity of the water reached 5 μS/cm. The cylinders were then re-inserted into the cored hole, level with the soil surface, and incubated for an average of 42 days (range 40 to 57days). The individual site coordinators chose the timing of incubation to start approximately six weeks prior to peak plant biomass production. All incubations were completed between February 2015 and January 2016 accounting for differences in growing season between northern and southern hemispheres. At the end of the incubation, the cylinders were re-collected and immediately shipped to WSL in an insulated box together with cold packs to halt further mineralization. Gloves were worn at all times to avoid contamination of the samples. Upon arrival at WSL, we extracted the resin bags and a 20 g subsample of sieved soil (4 mm) separately in a 100 ml PE-bottle with 80 ml 1 M KCl for 1.5 h on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience). We measured NO3- (colorimetrically; Norman & Stucki, 1981) and NH4+concentrations (flow injection analysis; FIAS 300, Perkin Elmer) on these filtrates.
At the start of the field incubation, we additionally collected two soil cores of 5 x 12 cm (diameter x depth) in each sampling plot and composited them to measure potential soil net Nmin, soil chemical and biological properties (see below). We also collected an additional sample (5 x 12 cm) to assess soil physical properties, which remained within the steel cylinder. Both ends were tightly closed with plastic caps. Cores were carefully packed to avoid further disturbance, and together with the composited soil samples, were shipped to the laboratory at WSL within a few days after collection.
From the composited samples, we extracted an equivalent of 20 g dry soil with KCl, as described above, and measured NO3- and NH4+concentrations. Realized soil net Nmin was then calculated as the difference between the inorganic N content of samples collected at the end of the incubation (plus N extracted from the bottom resin bag) and the N content at the beginning of the incubation; values were scaled to represent daily mineralization rates (mg N kg-1soil d-1; Risch et al., 2015). Realized soil net Nmin values represent an average period of 42 days prior to peak biomass, typically the highest period of biological activity, and not the entire year (Risch et al., 2019).
A second subsample of the composited sample was used to determine potential soil net Nmin in the laboratory (Risch et al., 2019). Briefly, we weighed duplicate samples (8 g dry soil) into 50-ml Falcon tubes. Soil moisture was brought to 60% of the field capacity of each plot, the Falcon tubes tightly closed and then incubated at 20°C for 42 days in a dark room. Every week the Falcon tubes were opened and ventilated. At the end of the incubation, the soil samples were extracted the same way as described above and NO3- and NH4+ was determined. Potential soil net Nmin was calculated as the difference between the N content before and after the incubation and scaled to represent daily values (mg N kg-1soil d-1). Using our NO3- and NH4+ measures we also calculated potential and realized soil net nitrification and soil net ammonification to be able to better understand the drivers of fertilization and herbivore removal effects on potential and realized soil net Nmin.
A third subsample of the composite soil sample was sieved (2 mm mesh) and microbial biomass (μg Cmic g-1 soil dry weight) was estimated by measuring the maximal respiratory response to the addition of glucose solution (4 mg glucose per g soil dry weight dissolved in distilled water; substrate-induced respiration method) on approximately 5.5 g of soil (Anderson & Domsch, 1978). The rest of the composited sample was dried at 65°C for 48 h, ground and sieved (2 mm mesh) to assess a series of soil chemical properties (Risch et al., 2019). We measured the percentage of clay as an indicator of soil texture (Gee & Bauder, 1986; Risch et al., 2019).
Statistical analyses
Potential and realized soil net Nmin were square root transformed to account for a highly skewed data distribution (yt = sign(y)*sqrt|y|; negative values in the data set impeded log transformation). To assess treatment effects on potential and realized soil net Nmin, we used linear mixed effects models (LMMs) fitted by maximum likelihood using the lme function from the nlme package (version 3.131.1; Pinheiro et al., 2016), R version 3.6.1; R Foundation for Statistical Computing. Treatment (Control, Fence, NPK, NPK+Fence) was a fixed factor, with site and block as random factors, where block was nested within site. We also tested for effects of time since start of treatments in preliminary analyses by adding total treatment years as an additional fixed factor. We did not find a significant effect of years of treatment, and thus dropped this variable from the models. The LMMs were corrected using varIdent if the homogeneity of variance criterion was not met (Pinheiro et al., 2016). To visualize our results, we calculated treatment effects using Cohens’ d statistic (Cohen, 1977; Koricheva et al., 2013). Note that calculating response ratios (or log response ratios) was not possible with our data, as we have both negative and positive values. We also fitted LMMs for potential and realized soil net ammonification and nitrification to gain more insight into how global change affects the processes underpinning potential and realized soil net Nmin. We also sqrt-transformed (see above) these dependent variables. Treatment was included as a fixed factor with random factors as described above. In addition, we assessed how potential and realized soil net Nmin were related to potential and realized soil net ammonification and nitrification, respectively. For this, we calculated site averages for each treatment separately. We then ran LMMs, with potential and realized soil net Nmin as the dependent variable, potential and realized soil net ammonification/nitrification as the independent ones. Site was included as a random factor.
Based on our previous work (Risch et al., 2019) and the existing literature (Schimel & Bennett, 2004; Liu et al., 2017), we developed a priori causal conceptual models of relationships among treatments, environmental drivers, and potential and realized soil net Nmin (Supplementary Fig. S2) to test with structural equation modelling (SEM) using a d-sep approach (Shipley, 2009; Lefcheck, 2016). The variables included in the model were long-term climatic conditions, specifically, site-level mean annual precipitation (MAP) and temperature of the wettest quarter (T.q.wet), plot-level soil texture (clay content) and soil microbial biomass. Mean annual precipitation and T.q.wet were obtained from WorldClim (Hijmans et al., 2005) (http://www.worldclim.org/) and together with the experimental treatments were predicted to directly affect soil properties and soil net Nmin (Supplementary Fig. S2). Soil clay content was, in turn, predicted to affect microbial biomass and soil net Nmin. Because we determined microbial biomass prior to incubating the samples in the laboratory or field, we assumed that the abundance of these microbes would be responsible for N process rates and not vice versa (Supplementary Fig. S2). We tested our conceptual model (Supplementary Fig. S2) using the piecewiseSEM package (version 2.0.2; Lefcheck, 2016) in R 3.4.0, in which a structured set of linear models are fitted individually. This approach allowed us to account for the nested experimental design, and overcome some of the limitations of standard structural equation models, such as small sample sizes (Shipley, 2009; Lefcheck, 2016). We used the lme function of the nlme package to model response variables, including site as a random factor. Good fit of the SEM was assumed when Fisher’s C values were non-significant (p > 0.05). For all significant interactions between covariates and experimental treatments detected in the SEMs, we calculated treatment effect sizes, i.e. the differences in potential or realized soil net Nmin between Control and treatments (Fence, NPK, NPK+Fence) and plotted these values against the climate or soil covariates. Finally, we fitted LMMs for the soil variables included in our SEMs, with treatment as the fixed factor, and with site and block as random factors, where block was nested within site.

en:
This dataset contains all data on which the following publication below is based.

Paper Citation:

Risch Anita C., Zimmermann, Stefan, Moser, Barbara, Schütz, Martin, Hagedorn, Frank, Firn, Jennifer, Fay, Philip A., Adler, Peter B., Biederman, Lori A., Blair, John M., Borer, Elizabeth T., Broadbent, Arthur A.D., Brown, Cynthia S., Cadotte, Marc W., Caldeira, Maria C., Davies, Kendi F., di Virgilio, Augustina, Eisenhauer, Nico, Eskelinen, Anu, Knops, Johannes M.H., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Prober, Suzanne M., Seabloom, Eric W., Siebert, Julia, Silveira, Maria L. , Speziale, Karina L., Stevens, Carly J., Tognetti, Pedro M., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties. Global Change Biology

Please cite this paper together with the citation for the datafile.

We assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

ammonification

display_name: ammonification

climate

display_name: climate

fertilization

display_name: fertilization

global-change

display_name: global-change

grassland

display_name: grassland

herbivore

display_name: herbivore

mineralization

display_name: mineralization

nitrification

display_name: nitrification

nitrogen

display_name: nitrogen

nutrient-network

display_name: nutrient-network

soil

display_name: soil

educ

en: Education, culture and sport

en: Anthropogenic change and soil net N mineralization


en: forest-canopy forest-snow snow-modeling snow-hydrology meteorological-data

en: Meterorological forcing

en: Mmeteorological forcing data for FSM2 at hourly resolution, corresponding to the location of the 5DF automatic weather station / snow measurement field 5DF. Data is available from 1 Sept 2015 to 21 Aug 2021 (WY 2016-21)

en: Surface data

en: Surface fields for model domain at 2m spatial resolution, including simulation domain, elevation, and canopy structure datasets

en: This dataset contains surface datasets (in particular canopy structure fields) and meteorological input (water years 2016-2021) required to run the snow model FSM2 over the Fluela valley. Land surface datasets are available for a 1.5x2.5km model domain at 2m spatial resolution, meteorological input at hourly resolution is provided for a point and corresponds to the location of the automatic weather station / snow measurement field 5DF in Davos. Corresponding FSM2 simulations are used and analyzed in the publication 'Canopy structure, topography and weather are equally important drivers of small-scale snow cover dynamics in sub-alpine forests' by Mazzotti et al. (submitted to HESSD). This publication should be cited whenever the dataset is used.

forest-canopy

display_name: forest-canopy

forest-snow

display_name: forest-snow

meteorological-data

display_name: meteorological-data

snow-hydrology

display_name: snow-hydrology

snow-modeling

display_name: snow-modeling

en: Input datasets for forest snow modelling in Fluela valley, WY 2016-21


en: pore-water tramm landslide-testsite cces landslides pressure-perturbations

en: TRAMM Ruedlingen data

en: TRAMM project data from the Ruedlingen site (exp 1 + 2). Measured parameters include soil suction, water level, soil volumetric water content, rain intensity, and soil temperature.

mimetype: application/zip

en:
A landslide testsite dataset related to pore water pressure perturbations on the stability of unsaturated silty sand slopes leading to the initiation and propagation of the shear deformations and eventual rapid mass movements. This project was initiated and led by the Institute of Geotechnical Engineering (IGT) of the Swiss Federal Institute of Technology (ETH Zurich) and was incorporated in a Swiss national (TRAMM) and a European Union (SafeLand) multidisciplinary research project. Field site: The experimental slope is 7.5 m wide by 35 m long, located in the Swiss lowlands on an east facing slope over-looking the river Rhine, at an altitude of ~ 350 masl. Originally there were forestry covertures of circa 80%, heights of 5-20 m. Shrubs up to 1-5 m high and a free herb layer covered ~ 50% of the surface. The average gradient was determined to be from 38° to 43° with a slightly concave surface. The underlying rock consists mainly of Molasse, which is formed by alternate layers of sea deposits under the Tethys Sea (Seawater Molasse) and land deposits (Freshwater Molasse). Several augured samples, as well as an outcrop of the bedrock about 20 m above the selected field, revealed horizontal layering of fine grained sand- and marlstone at the test site. The sandstone was later proven to be highly permeable and fissured. Grain-size distributions were determined and the soil was classified as medium-low plasticity silty sand. Site instrumentation:Measurements of soil suction, groundwater level, soil volumetric water content, rain intensity and soil temperature were taken and combined with geophysical monitoring using Electrical Resistance Tomography (ERT) and investigations into subsurface flow by means of tracer experiments. Deformations were monitored during the experiment, both on the surface via photogrammetrical methods and within the soil mass, using a flexible probe equipped with strain gauges at different points and two axis inclinometers on the top and acoustic sensors. Instruments were installed mainly in three clusters at depths of 15, 30, 60, 90, 120, and 150 cm below the ground surface over the slope, including jet-fill tensiometers, TDRs, Decagon TDRs, piezometers, soil temperature sensors, deformation probes, earth pressure cells, acoustic sensors and rain gauges. A ring-net barrier (provided by Geobrugg AG) was set up at the foot of the slope to protect the road. Experiments: A sprinkling experiment was carried out in September 2008 to investigate the hydrological and mechanical response of the slope (Experiment 1), followed by a second one to trigger a landslide in March 2009 (Experiment 2).

Publications

1. Lehmann, P., F. Gambazzi, B. Suski, L. Baron, A. Askarinejad, S. M. Springman, K. Holliger, and D. Or (2013), Evolution of soil wetting patterns preceding a hydrologically induced landslide inferred from electrical resistivity survey and point measurements of volumetric water content and pore water pressure, Water Resour. Res., 49, 7992–8004, doi:[10.1002/2013WR014560](http://dx.doi.org/10.1002/2013WR014560).

2. Springman, S. M., Kienzler, P., Casini, F., & Askarinejad, A. (2009). Landslide triggering experiment in a steep forested slope in Switzerland. In 17th International Conference of Soil Mechanics and Geotechnical Engineering, Alexandria, Egypt (pp. 1698-1701). doi: [10.3233/978-1-60750-031-5-1698](http://dx.doi.org/10.3233/978-1-60750-031-5-1698)

cces

display_name: cces

landslide-testsite

display_name: landslide-testsite

landslides

display_name: landslides

pore-water

display_name: pore-water

pressure-perturbations

display_name: pressure-perturbations

tramm

display_name: tramm

en: TRAMM project Ruedlingen experimental landslide dataset, Switzerland


en: paleo-environmental-modeling range-dynamics population-genetics landscape-genetics process-based-modeling geogenomics

en: Rivers and glaciers

en: Input rasters required to set up gen3sis simulations

en: Metadata

en: Fossil records

en: Chamois fossil records with estimated time span and coordinates. Please see the sheet "references_data_sets" for the references and read the read_me.txt file prior to using the data.

en: Habitat suitability raster

en:
Habitat suitability raster stacks (.grd) files for different terrain slope scenarios use (see main publication its supporting information for details) for Northern chamois until 20,000 years BP in 100 year time steps.

 Description of layer names:
* prob: habitat suitability ranging continuously from 0 (unsuitable) to 1 (very well suitable).
*bin: binary classification of habitat suitability based on TSS threshold optimization (see main publication and supporting information for details).
*glm: generalized linear model (to model and predict habitat suitability)
*gam: generalized additive model
*gbm: generalized boosted regression model
*rf: random forest
*ensemble: average of all 4 model types

en: Chamois occurrences

en: Coordinates (0.05° resolution) of chamois occurrences across the Alps. See Suppl. mat. Table S1 for more information and citation of the data sets used.

en: gen3sis simulations

en:
Scripts to run gen3sis simulations, including configs used for the publication.

1.2_gen3sis_input_generation.R creates the input files required for 2.2_gen3sis_simulation_chamois.R, which is running the gen3sis simulations.
 3_gen3sis_track_simulation_over_time.R and 4_gen3sis_divergence_sampling_locations.R can be used to start the analysis.

en: Genetic data Northern chamois across Alps

en: ddRADseq data (vcf file and sampling locations) of 449 Northern chamois (Rupicapra rupicapra) sampled across the European Alps

en:
 General description

Genomic data, habitat suitability raster files and scripts to run gen3sis to simulate cumulative divergence over time as approximation for genetic differentiation. Scripts for basic analysis of the simulations (e.g., create distance matrix from sampling locations) are provided, too. See original publication (doi link will be provided after publication) for details. The study area are the European Alps.
All data is uploaded as zipped file. Unzip them after the download and put all data in one folder.
See linked publications for correct citation of the data used, use of the data without correct citation is not allowed.

Corresponding author: Flurin Leugger, email: flurin.leugger@gmail.com

 Description of the data (content of the different zip folders)

 Abiotic data

 Glaciers
Folders with raster stacks with glaciated areas at 0.05° resolution in WGS84 projection from Seguinot et al. (2018).
Seguinot, J., Ivy-Ochs, S., Jouvet, G., Huss, M., Funk, M., & Preusser, F. (2018). Modelling last glacial cycle ice dynamics in the Alps. _The Cryosphere, 12(10)_, 3265–3285. https://doi.org/10.5194/tc-12-3265-2018

 Rivers
* river_raster_elevation_class.tif: raster file (.tif) at 0.05° resolution and WGS84 projection with large rivers (scenario 2 from publication). The rivers (each cell) is classified according to the elevation of the cell.
Natural Earth. (2018). Rivers + lake centerlines version 4.1.0. Retrieved January 22, 2020, from https://www.naturalearthdata.com/downloads/50m-physical-vectors/50m-rivers-lake-centerlines
* river_raster_strahler_class_5km.tif: raster file at 0.05° resolution and WGS84 projection with medium rivers. The rivers are classified according to their Strahler order.
Food and Agriculture Organization of the United Nations. (2014). Rivers in Europe (Derived from HydroSHEDS). Retrieved January 29, 2020, from http://www.fao.org/geonetwork/srv/fr/google.kml?uuid=e0243940-e5d9-487c-8102-45180cf1a99f&layers=AQUAMAPS:37253_rivers_europe

 Fossil records
* chamois_fossil_combined_public.xlsx: list with fossil records until 20,000 years BP from Central Europe, see linked references for citation.

 Chamois occurrences
* chamois_occurrence.csv: Chamois presences from all sources used for the publication (see Suppl. mat. Table S1 for detailed information and correct citations of the data) aggregated at 0.05° resolution (~5km).

 Gen3sis
* config: folders with all configuration files used to run the simulations for the publication (different dispersal divergence parameters).
* scripts: scripts (and helper functions) to run the gen3sis simulations including scripts for the beginning of the subsequent analysis.

 Genetic
* populations.snps.light.vcf: vcf file of the sampled Northern chamois _(Rupicapra rupicapra)_ . The genomic data encompasses 20k SNPs (from ddRAD sequencing).
* Sequencing_final_without_slovakia.txt: sampling locations of Northern chamois _(Rupicapra rupicapra)_

 HSM
* habitat_suitability_hindcasting: Aggregated habitat suitability raster files (stacks, .grd files) at 0.05° resolution and WGS84 projection from 20,000 years BP until today in 100 year time steps. There are separate folders for each environmental variable scenario used (different terrain slope variables) an the different occurrence/pseudo-absence sampling strategy used.
* ODMAP_LeuggerEtAl2021-10-25.csv: ODMAP protocol

geogenomics

display_name: geogenomics

landscape-genetics

display_name: landscape-genetics

paleo-environmental-modeling

display_name: paleo-environmental-modeling

population-genetics

display_name: population-genetics

process-based-modeling

display_name: process-based-modeling

range-dynamics

display_name: range-dynamics

envidat

en: EnviDat: the Environmental Data Portal

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

en: Simulating population divergence of Northern chamois in the Alps based on habitat dynamics


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

en: Link to Proceedings in DORA WSL

en: Deprecated version 1.0

en: First version of the proceedings containing errors. This early version it is kept, for traceability purposes, in conformance with DOI rules.

en: FORECOMON – Proceedings

en: Latest version

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

The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.

Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.

air-pollution

display_name: air-pollution

forest

display_name: forest

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

long-term-monitoring

display_name: long-term-monitoring

monitoring

display_name: monitoring

educ

en: Education, culture and sport

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


en: hysteresis snow-water-equivalent snow-depth subgrid-topography snow-cover-modeling source-code

en: Seasonal fractional snow-covered area algorithm

en: Release Version 1 from https://gitlabext.wsl.ch/snow-models/fractional-snow-covered-area

en:
This is the source code for computing the seasonal fractional snow-covered area. It is written in Fortran 90. The code reads snow depth (HS) and snow water equivalent (SWE) data from the provided example file HS_SWE.txt and writes the computed fractional snow-covered area (fSCA) to a file fSCA.txt.

The current version can be found in the WSL/SLF Gitlab repository:
https://gitlabext.wsl.ch/snow-models/fractional-snow-covered-area

hysteresis

display_name: hysteresis

snow-cover-modeling

display_name: snow-cover-modeling

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

source-code

display_name: source-code

subgrid-topography

display_name: subgrid-topography


en: soil-degradation fallout-radionuclides sediment-transport soil-erosion tracking

en: Erosion Pu samples

en: We have measured Pu-239+240 in soil samples at erosional sites in the catchment.

en: Reference Pu samples

en: We have collected 19 Bulk soil samples in and 3 depth incremental soil profiles in undisturbed reference locations.

en: Quantifying the rates of soil redistribution worldwide poses a significant challenge, which has been addressed using various methods such as direct sediment measurements, models, and the use of isotopic, geochemical, and radionuclide tracers. Among these tracers, the isotope of Plutonium, specifically 239+240Pu, is a relatively recent addition to the study of soil redistribution. However, there is still a lack of direct validation for 239+240Pu as a tracer for soil redistribution. To address this gap, we conducted a study in Southern Italy using a unique sediment yield dataset that extends back to the initial fallout of 239+240Pu. Soil samples were collected from the catchment area as well as undisturbed reference sites, and 239+240Pu was extracted, measured using ICP-MS, and converted into soil redistribution rates.

fallout-radionuclides

display_name: fallout-radionuclides

sediment-transport

display_name: sediment-transport

soil-degradation

display_name: soil-degradation

soil-erosion

display_name: soil-erosion

tracking

display_name: tracking

en: Plutonium-239+240 and sediment yield data for a small catchment in Southern Italy


en: naturalness nais protective-forest tree-species-composition nfi

en: Scherrer et al. 2023 - Data for analysis and figures

en:
This archive contains all the data needed to reconstruct the analysis and figures of
Scherrer, D., Allgaier Leuch, B., Fischer, C., Frehner, M. & Wohlgemuth, T. (2023) Maintaining the protective function of mountain forests under climate change by the concept of naturalness in tree species composition. Frontiers in Forests and Global Change, in review.

en: Scherrer et al. 2023 - Scripts

en:
This archive contains all the R-scripts to run the analysis and reconstruct the figures from
Scherrer, D., Allgaier Leuch, B., Fischer, C., Frehner, M. & Wohlgemuth, T. (2023) Maintaining the protective function of mountain forests under climate change by the concept of naturalness in tree species composition. Frontiers in Forests and Global Change, in review.

en: Data and scripts used by Scherrer et al. 2023 in the publication 'Maintaining the protective function of mountain forests under climate change by the concept of naturalness in tree species composition'. The analysis is based on data about the tree species composition of the canopy layer in the NFI4 and information about the potential natural forest of the sites based on the NaiS classification system.

nais

display_name: nais

naturalness

display_name: naturalness

nfi

display_name: nfi

protective-forest

display_name: protective-forest

tree-species-composition

display_name: tree-species-composition

envidat

en: EnviDat: the Environmental Data Portal

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

en: Naturalness of tree species composition in protective forests


causal-effect-of-mfoz

title_for_slug: causal-effect-of-mfoz

en: fujian-province propensity-score-matching built-up-land-change selection-bias causality the-major-function-oriented-zone

en: Data and Stata code for repeating the results

en:
Data.xlsx is the variables of 952 townships
Table 1-2 NN(1-1)_noreplace_caliper(0.01).do is STATA code to produce the results in Table 1 and 2
Figure 5 Distribution of the propensity scores.R is R code rto produce Figure 5
Figure 5 Standard mean difference.R is R code rto produce Figure 5

en:
Title: Closer to causality: How effective is spatial planning in governing built-up land expansion in Fujian Province, China?

Research objective: The Major Function Oriented Zone (MFOZ), the first strategic spatial plan in China, is developed to achieve a coordinated regional development, through spatial regulation and zoning of development. The MFOZ he MFOZ divided land into four major function-oriented zones: The development-optimized zone, the development-prioritised zone, the development-restricted zone, and the development-prohibited zone. We used propensity score marching to evaluate the effect of the MFOZ on built-up land expansion in Fujian Province over three time intervals (2013–2015, 2013–2018 and 2013–2020).

Data: Data.xlsx contains the variables of 954 towns in Fujian Province.
Town_ID is the town unique ID;
County_ID is the county unique ID;
City_ID is the city unique ID;
MFOZ is the the development-prioritised zone and the development-restricted zone (The development-optimized zone and the development-prohibited zone are excluded);
Builtup_13_15 is the built-up land expansion from 2013 to 2015;
Builtup_13_18 is the built-up land expansion from 2013 to 2018;
Builtup_13_20 is the built-up land expansion from 2013 to 2020;
Dis2water is the Euclidean distance from the town to the nearest waterbody;
Slope is the the average slope within the town;
GDP is the average GDP in 2010 within the town;
Pop is the average population in 2010 within the town;
Road is the average population in 2010 within the town;
Dis2city is the Euclidean distance from the town to the nearest prefectural city centre;
Nei_Arable, Nei_Forest, and Nei_Built.up are the area of arable land, forest land, and built-up land neighbouring town i in 2010.

Method: we used the propensity score matching to compare the changes in the amount of built-up land in the towns of the development-prioritised zone with the matched towns of the development-restricted zone. Additionally, we used three evaluation intervals (2013–2015, 2013–2018 and 2013–2020) to evaluate temporal variation in the causal effect of the MFOZ on built-up land expansion.

built-up-land-change

display_name: built-up-land-change

causality

display_name: causality

fujian-province

display_name: fujian-province

propensity-score-matching

display_name: propensity-score-matching

selection-bias

display_name: selection-bias

the-major-function-oriented-zone

display_name: the-major-function-oriented-zone

educ

en: Education, culture and sport

en: Causal effect of MFOZ


maintainer: Zhao

en: urban-land-use planning land-dynamics driving-factors austin

en: Potential driving factors of urban transformations of Austin over 25 years

en: In this study, the Austin metropolitan area, Texas, U.S., one of the fastest urban transformations and transformations regions, is selected to test the hypothesis that spatial planning and policies are important factors of urban transformations. Despite ample previous work in understanding the interactions between human and urban form transformation at specific areas, the actual interventions and outcomes of planning and policies (e.g., ‘smart growth’) on urban forms have been poorly measured. In this study, the potential influencing factors of urban transformations of Austin over 25 years were selected and collected.

austin

display_name: austin

driving-factors

display_name: driving-factors

land-dynamics

display_name: land-dynamics

planning

display_name: planning

urban-land-use

display_name: urban-land-use


en: ramms avalanche modelling impact-pressure hazard-mapping release

en: Scenario 30 years without forest

en:
PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

en: Scenario 100 years with forest

en: Scenario 10 years without forest

en: Scenario 100 years without forest

en: Scenario 10years with Forest

en: Extent of the canton of Grisons

media_type: application/json

format: JSON

en: Scenario 300 years with forest

en: Scenario 30 years with forest

en: Scenario 300 years without forest

en:
We developed a workflow to generate Large Scale Hazard Simulations for avalanches based on digital elevation models and information on the protective function of the forest. This datasets contains the potential avalanche release areas (PRA) as polygons, the simulation outputs (maximum pressure, maximum flow velocity and maximum flow height) as .tif rasters and the outlines of the simulated avalanches (polygon) for the entire area of the canton of Grisons (7105 km2). The simulations are performed for the scenarios wit return periods of 10, 30, 100 and 300 years, once with (FOR) and once without (NoFor) taking the effect of the forest into account.

The details can be found in this publication:

Bühler, Y., Bebi, P., Christen, M., Margreth, S., Stoffel, L., Stoffel, A., Marty, C., Schmucki, G., Caviezel, A., Kühne, R., Wohlwend, S., and Bartelt, P.: Automated avalanche hazard indication mapping on state wide scale, Nat. Hazards Earth Syst. Sci. Discuss., 2022, 1-22, 10.5194/nhess-2022-11, 2022.

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

impact-pressure

display_name: impact-pressure

modelling

display_name: modelling

ramms

display_name: ramms

release

display_name: release

en: Large Scale Hazard Indication Simulations for avalanches, canton of Grisons


maintainer: Martin Schneebeli

en: depth-hoar snow-cast new-snow 3d-model weak-layer rounded-snow snow 3d-print

en: Snow models in STL-format

en: The zipped file contains all data described in the file 3d_snow_models_metadata. The stl-files should be ready for additive manufacturing.

en: Description of snowtypes, filenames and other metadata

en: This file contains information about the stl-files of the different snow models. Snowtype (Schneeart), International Snow Classification, preview picture, notes about the origin of the snow, filename of the stl-data, and physical size of the model are given.

en: The dataset contains several snow models in the Standard Tesselated Geometry File Format (stl) for 3D visualization, printing and additive manufacturing. Different snow types are available (new snow, rounded snow, depth hoar, buried surface hoar, graupel).

depth-hoar

display_name: depth-hoar

new-snow

display_name: new-snow

rounded-snow

display_name: rounded-snow

snow

display_name: snow

snow-cast

display_name: snow-cast

weak-layer

display_name: weak-layer

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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.