volume-of-dead-wood

title_for_slug: volume-of-dead-wood

en:
Volume of stemwood with bark of all dead trees and shrubs (standing and lying) starting at 12 cm dbh. Unlike this theme , the "Amount of deadwood according to the method of NFI3" includes all lying deadwood starting at 7 cm in diameter.

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

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

main-tree-species

display_name: main-tree-species

mechanical-strength-of-wood

display_name: mechanical-strength-of-wood

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

tree-state-standing-lying

display_name: tree-state-standing-lying

volume-of-dead-wood

display_name: volume-of-dead-wood

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: Volume of dead wood


maintainer: Frank Hagedorn

en: nitrogen phosphorus fertilization soil-temperature beech zero-tension-lysimeters seasons nutrient-fluxes dissolved-organic-phosphorus forest-topsoil

state: active

type: dataset

format: XLS

en:
Data on dissolved organic and inorganic phosphorus and nitrogen concentrations in leachates and their corresponding
fluxes from the litter layer, the Oe/Oa horizon, and the A horizon of two German beech forest sites.
Leachate samples were taken in April 2018, July 2018, October 2018, Feb./Mar. 2019, and July 2019
with zero-tension lysimeters after artificial irrigation. Soil samples were taken in July 2019.
For more details please refer to the publication.

beech

display_name: beech

dissolved-organic-phosphorus

display_name: dissolved-organic-phosphorus

fertilization

display_name: fertilization

forest-topsoil

display_name: forest-topsoil

nitrogen

display_name: nitrogen

nutrient-fluxes

display_name: nutrient-fluxes

phosphorus

display_name: phosphorus

seasons

display_name: seasons

soil-temperature

display_name: soil-temperature

zero-tension-lysimeters

display_name: zero-tension-lysimeters

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

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.

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: Phosphorus and nitrogen leaching from beech forest soils


data-broedlin-cnp

maintainer: EnviDat Support

title_for_slug: data-broedlin-cnp

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

en: Data Broedlin-CNP-Release

en: Raw data of C-N-P mobilization experiment from Oi, Oe/Oa, and A horizons of beech forest soils along a nutrient availability gradient.

en: Data Broedlin-CNP

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

carbon

display_name: carbon

dissolved-organic-matter

display_name: dissolved-organic-matter

drying-rewetting

display_name: drying-rewetting

forest

display_name: forest

mineralization

display_name: mineralization

soil

display_name: soil

stoichiometry

display_name: stoichiometry

en: Data Broedlin CNP


maintainer: Elisabeth Hafner

en: avalanche avalanche-hazard-mapping validation snow satellite

en: Satellite Avalanche Mapping Validation data and data description

media_type: application/zip

en: 14 shapefiles to be used only together with the data description also provided as a pdf.

format: ZIP

en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).

Coordinate system: CH1903+_LV95

The generation of this dataset is described in detail in:

Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

satellite

display_name: satellite

snow

display_name: snow

validation

display_name: validation

en: Satellite avalanche mapping validation data


maintainer: Giulia Mazzotti

en: forest-structure snow-energy-balance forest-snow snow-modelling snow-distribution

en: Snow depth data forest sites

en: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en: Canopy data

en: Includes all canopy structure metrics computed at all surveyed locations

en: Coordinates data

en: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en: Meteo data to drive FSM2 model

en: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

mimetype: application/zip

en: Grid point nomenclature

en: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.  Each point marks the location of snow depth measurements and co-located canopy structure parameters.

en: Snow depth data open sites

en: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en:
This dataset contains all snow, canopy and meteorological data presented and used in the publication: Mazzotti, G., Essery, R., Moeser, D. & Jonas T. (2020) 'Resolving spatial variability of forest snow using an energy-balance model with a 1-layer canopy'. Water Resources Research, https://doi.org/10.1029/2019WR026129.
This publication must be cited when using this dataset.

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling

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: Snow depth, canopy structure and meterorological datasets from the Davos area, Switzerland, Winters 2012/13-2014/15, used for high-resolution forest snow modelling


tree-diameter-and-height-inventory-lwf

title_for_slug: tree-diameter-and-height-inventory-lwf

en: tree-growth lwf swiss-forest-lab long-term-forest-ecosystem-research icp-forests

en: Data Request

format: SERVICE

en:
Tree circumference, height, height to crown base measurements, mortality, decay class and removal assessment on LWF plots

 Purpose:

Assessment of tree and forest growth

 Manual Citation:

 * Matthias Dobbertin, Christian Hug, 1999: Vorläufige Feld-Aufnahmeanleitung für die BHU- und Höhen-Inventur auf LWF-Flächen (V1.0), Langfristige Waldökosystem-Forschung, Eidg. Forschungsanstalt WSL, Birmensdorf, 18 S.

 * Christian Hug, Matthias Dobbertin, Chris Nussbaumer, Yves Stettler, 2010: Provisorische Aufnahmeanleitung für die Brusthöhenumfang- und Höheninventur auf LWF-Flächen. Langfristige Waldökosystem-Forschung, Eidg. Forschungsanstalt WSL, Birmensdorf, 29 S.

 * Christian Hug, Chris Nussbaumer, Yves Stettler, 2014: Aufnahmeanleitung für die Brusthöhenumfang und Höheninventur auf LWF-Flächen. Langfristige Waldökosystem-Forschung, Eidg. Forschungsanstalt WSL, Birmensdorf, 36 S.

 * Dobbertin M, Neumann M, 2016: Part V: Tree Growth. 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, 17 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Etzold S, Waldner P, Thimonier A, Schmitt M, Dobbertin M (2014) Tree growth in Swiss forests between 1995 and 2010 in relation to climate and stand conditions: Recent disturbances matter. Forest Ecology and Management, 311: 41-55. [doi: 10.1016/j.foreco.2013.05.040](http://dx.doi.org/10.1016/j.foreco.2013.05.040)

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

lwf

display_name: lwf

swiss-forest-lab

display_name: swiss-forest-lab

tree-growth

display_name: tree-growth

educ

en: Education, culture and sport

en: Tree Diameter and Height Inventory LWF


en: forest-monitoring maps anthropic-disturbances natural-disturbances neophytes

en:
Some models has been refined. Here are the updated raster.
Pixel values represent the proability of presence for a given species. 0 = absent, 1 = 100% of presence

en: neophytes risk map ticino

format: GeoTIFF

en:
943 disturbances in the forest of southern Switzerland have been visited and characterized with various general and specific parameters and the presence absence of woody neophyte species has also been recorded.
A Generalized linear regression modelling approach with a binomial family (link function “logit”) was then used to analyse the effects of these parameters on the presence/absence of the six most widespread neophyte species separately (i.e Ailanthus altissima, Buddleja davidii, R. pseudoacacia, Paulownia tomentosa, Prunus laurocerasus, Trachycarpus fortunei).

The best model for every species have been used to predict the risk of invasion on a 25 X 25m grid of 1’773’603 million of points covering the entire forest area under 1’500 m a.s.l. Predictions over this new set of points have been computed with the predict function (v4.2.1; R core Team, 2023) and using the best select model for every neophyte species. The resulting prediction are available as a raster tiff.
These presence probability risk maps for the forest area of the entire canton Ticino provide a practical tool to be used in combination with the waldmonitoring.ch data allowing to efficiently monitor the spread of woody neophyte species in new disturbances in the forest.

anthropic-disturbances

display_name: anthropic-disturbances

forest-monitoring

display_name: forest-monitoring

maps

display_name: maps

natural-disturbances

display_name: natural-disturbances

neophytes

display_name: neophytes

en: Presence probability risk maps neophyte Ticino


en: municipality switzerland participation survey energy-transition

media_type: text/csv

format: CSV

media_type: application/pdf

format: PDF

en: The dataset contains data from a survey, which was conducted in a periurban region close to Berne, Switzerland. The survey was conducted in Fall 2018 and contained opinion questions about the energy transition. Additionally, spatial data was collected using a PPGIS. While the opinion data is included in the data set, the spatial data is not. For more explanation, please consider the information sheet, the related publications or to contact the authors.

energy-transition

display_name: energy-transition

municipality

display_name: municipality

participation

display_name: participation

survey

display_name: survey

switzerland

display_name: switzerland

en: Implementing the energy transition at municipal level in Switzerland: A regional survey


en: snow-cover vertical-wind-motion saltation snow-depth boundary-layer-winds

en: Data Compilation

en: Compressed TXT files

en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.

Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion

en: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations


maintainer: M. Carol Resch

en: nematodes long-term-experiment diversity topsoil-removal grassland vegetation restoration

en: Plant community composition (plant species)

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-252: Plant abundance per species (in total 252 plant species) expressed as cover percentage estimation according to van der Maarel (vdM 1979; 7 classes: 1-7); nomenclature according to Lauber & Wagner (1996)

en: Nematode colonizer-persister classes

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001
CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001
CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990
CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

en: Nematode families

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

column 3-41: Nematode abundance (individuals per 100g dry soil) per family; nomenclature according to Bongers 1988

en: Nematode feeding types

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

en: Nemadotes and vegetation

en:
Plot: Plot ID combining treatment code and plot number (in total 55 plots)

Treatment: Three restoration treatments and two reference treatments. Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands

X: X-Coordinate

Y: Y-Coordinate

Ri.veg: Total number of plant species

Div.veg: Shannon diversity of plant species

Ri.nem: Total number of nematode families

Div.nem: Shannon diversity of nematode families

abund: Total nematode abundance (individuals per 100g dry soil)

MI: Maturity index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI: Plant parasite index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

PPI.MI: Plant parasite to Maturity index according to Bongers, van der Meulen, & Korthals 1997; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

CI: Channel index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

EI: Enrichment index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

SI: Structure index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)

He.a: Herbivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

He.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ba.a: Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Fu.a: Fungivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.a: Omnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Ca.a: Carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014

Om.Ca.a	Sum of omnivorous and carnivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014
CP1.a: C-P (colonizer-persister) class 1 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to enrichment indicators according to Ferris, Bongers, & de Goede 2001

CP2.a: C-P (colonizer-persister) class 2 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990; equivalent to stress indicators according to Ferris, Bongers, & de Goede 2001

CP3.a: C-P (colonizer-persister) class 3 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP4.a: C-P (colonizer-persister) class 4 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP5.a: C-P (colonizer-persister) class 5 nematode abundance (individuals per 100g dry soil); C-P classification according to Bongers 1990

CP3-5.a: Sum of C-P3, C-P4 and C-P5 nematode abundance (individuals per 100g dry soil) equivalent to structure indicators according to Ferris, Bongers, & de Goede 2001

protect.sp.pro: plant species categorized into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002)

tar.sp: Number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species)

Indi.moist: Plant indicator values for soil moisture according to Landolt et al. 2010

Indi.nutri: Plant indicator values for soil nutrients according to Landolt et al. 2010

Management: level of mowing and manuring frequency (35-40 kg N ha-1 application-1); intensity1 = mowing once and no manure; intensity2 = 2-3 times mowing and no manure; intensity3 = 2-3 times mowing and manuring; intensity4 = 4-5 times mowing and manuring

Tillage: last time of tillage

Land.use.history: for Initial plots = recent agricultural use; for all restored sites = agricultural use before restoration
Mowing	earliest date of biomass harvesting (excluding “Initial”) based on contracts between farmers and the Nature Protection Agency of Zurich

Soil.type: based on soil mapping survey 1991 (before restoration)

Soil.texture: determined by the sediment method (Gee & Bauder 1986) and classified into soil textural classes according to FAO (1990)

pH: soil pH (CaCl2)

Slope: slope gradient classes according to FAO (1990; %)

en: Coordinates of one research plot were wrong. This was corrected in the current version of the file.

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

Paper Citation:
 > Resch, M.C., Schütz, M., Graf, U., Wagenaar, R., van der Putten, W.H., Risch, A.C. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56: 1782-1793.

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

 Methods
 Study area and experimental settings
The study was conducted in a nature reserve (Eigental: 47° 27’ to 47° 29’ N, 8° 37’ E, 461 to 507 m a.s.l.) that is located on the Swiss Central plateau close to Zurich airport (Canton Zurich, Switzerland). The mean annual temperature in this area ranges from 8.9 to 10.6 °C, mean annual precipitation from 910 to 1260 mm [10-year average (2007-2017); MeteoSchweiz, 2018]. The main soil types are calcaric to gleyic Cambisol and Gleysols. The reserve was established in 1967 to protect small remnants of oligotrophic semi-natural grasslands (roughly 12 ha). The plant community can be characterized as Molinion and Mesobromion (semi-wet to semi-dry), depending on the site-specific groundwater level and slope inclination (Delarze, Gonseth, Eggenberg, & Vust, 2015). These remnants represent species-rich islands in an otherwise intensively managed agricultural landscape. Semi-natural grasslands covered an area of 60,000 ha in the Canton Zurich in 1939, however, by 2005 only roughly 600 ha remained (Baudirektion Kanton Zürich, 2007). In 1990, the government of Canton Zurich decided to enlarge the nature reserve Eigental. The goal was to incorporate eleven patches of 20 ha adjacent intensively farmed land and transform these patches into semi-natural grasslands. The patches had a different agricultural history, ranging from permanent (no tillage for >50 years) to temporary grassland (as part of crop rotation; last tillage <5 years). On all freshly integrated patches fertilization was stopped in 1992 and from then on biomass was harvested three times a year and removed. After 5 years without noticeable effects on vegetation composition, the Nature Conservation Agency of Canton Zurich decided to increase the restoration efforts. In 1995, a large-scale experiment was initialized to evaluate if certain treatments can facilitate restoration within a reasonable timeframe of 5 to 10 years after treatment implementation.
The three restoration treatments used were:
i. “Harvest only”: Plots are being mowed two to three times a year and the biomass is removed.
ii. “Topsoil”: Topsoil was removed to a depth of 10 to 20 cm, depending on the depth of the O and A horizon, in four randomly selected areas within each of the eleven patches in late autumn 1995. The size of each topsoil removal area depended on individual patch size and was between 2700 and 7000 m2.
iii. “Topsoil+Propagules”: Propagules from target vegetation were added on half of the area where topsoil was removed, using fresh, seed-containing hay originating from a mixture of semi-dry to semi-wet species-rich grasslands of local provenance (within a radius of 7 km). Hay applications were conducted twice in 1995 and 1996. Repeated applications were chosen to account for the low quantity of available plant material per transfer, since area ratio between receptor and donor sites was roughly 1:1. In addition, hand-collected propagules from 15 selected target species of regional provenance (within a radius of 30 km) were equally applied in 1996 and 1997.
“Topsoil” and “Topsoil+Propagules” plots are mowed once a year, and the biomass is removed. Mowing on these plots started five years after the treatment was implemented.
Eleven permanent plots of 5 m x 5 m were randomly established in each treatment to monitor the vegetation development. The experiment was complemented with 11 control plots that represent the initial state of intensively managed grasslands, further referred to as “Initial”, and 11 control plots that represent the targeted state of donor sites for “Topsoil+Propagules”, further referred to as “Target”. Consequently, the experiment consists of 55 plots (5 treatments x 11 replicates). Management of intensively used grasslands includes mowing and fertilizing (manure) between two to five times a year, as well as different tillage regimes (no tillage for >50 years; last time of tillage <5 years).

 Nematode and plant sampling
Soil nematodes were sampled in 2 m x 2 m plots, randomly established at least 2 m away from the vegetation plots. We collected eight soil cores with a 2.2 cm diameter soil core sampler (Giddings Machine Company, Windsor, CO, USA) to a depth of 12 cm (representing the majority of the plant rooting system) in each plot at the beginning of July 2017. The eight cores within each replicate plot were combined, gently homogenized, placed in coolers and transported to the laboratory of NIOO in Wageningen, the Netherlands, within one week. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink, 1960) and concentrated, resulting in 6 mL nematode solution. The nematode solution was subdivided into three subsamples, two for morphological identification and quantification, and one for molecular work (not used in this study). For morphological identification and quantification, nematodes were heat-killed at 90 °C and fixed in 4 % formaldehyde solution (final volume 10 mL per subsample). All nematodes in 1 mL of formaldehyde solution were counted, and a minimum of 150 individuals per 1 mL sample (or all if less nematodes were present) were identified to family level using Bongers (1988). We then extrapolated the numbers of each nematode taxa identified to the entire sample and expressed them per 100 g dry soil for further analyses.
We calculated number of nematode taxa and Shannon diversity and assessed nematode community composition. In addition, we classified the nematode taxa into feeding types (herbivores, bacterivores, fungivores, omni-carnivores), structural and functional guilds (Table S4). Structural guilds assign nematode taxa according to life-history traits into five colonizer-persister (C-P) classes, ranging from one (early colonizers of new resources) to five (persisters in undisturbed habitats; Bongers 1990). C-P classes can be categorized as indicators for nutrient-enriched (C-P1), stressed (C-P2) and structured (C-P3 + C-P4 + C-P5) soil conditions (Ferris, Bongers, & de Goede, 2001). Functional guilds assign nematode taxa according to their C-P classification combined with their feeding habits (Ferris, Bongers, & de Goede, 2001). Based on the structural and functional guild classification we calculated five additional indices to assess soil nutrient status, disturbance and food web characteristics using NINJA (Sieriebriennikov, Ferris, & de Goede, 2014). 1) The Maturity index indicates the degree of different environmental perturbations (e.g., tillage, nutrient enrichment, pollution) and is used to monitor colonization and subsequent succession after disturbances (Bongers, 1990). 2) The ratio between the Plant Parasite (C-P of herbivorous nematodes only) to Maturity index is used to monitor the recovery of disturbed habitats incorporating information of life-history traits for all feeding types (Bongers, van der Meulen, & Korthals, 1997). 3) The Enrichment index indicates nutrient-enriched soils and agricultural management practices (Ferris, Bongers, & de Goede, 2001). 4) The Structure index provides information about the succession stage of the soil food web and therefore correlates with the degree of maturity of an ecosystem (Ferris, Bongers, & de Goede, 2001). 5) The Channel index provides information about the predominant decomposition pathways, where higher values stand for a higher proportion of energy transformed through the slow fungal decomposition channel (Ferris, Bongers, & de Goede, 2001). In addition, the Structure and Enrichment indices can be displayed in a biplot where nematode assemblages are plotted along a structure (x-axis) and enrichment (y-axis) trajectory (increasing index values). Each biplot quadrat reflects different levels of disturbance, soil nutrient pools and decomposition pathways (Ferris, Bongers, & de Goede, 2001).
The plant surveys were conducted on the 25 m2 permanent plots in June 2017. Plant species cover was visually assessed according to the semi-quantitative cover-abundance scale of Braun-Blanquet (1964; nomenclature: Lauber & Wagner, 1996). We calculated number of species and Shannon diversity, and assessed plant community composition. We also counted the number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species) and categorized plant species into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002). Furthermore, we calculated indicator values for soil moisture and soil nutrients for each species according to Landolt et al. (2010).

 References
Baudirektion Kanton Zürich (2007). 10 Jahre Naturschutz-Gesamtkonzept für den Kanton Zürich 1995-2005 – Stand der Umsetzung. Zürich: Baudirektion Kanton Zürich.
Bongers, T. (1988). De nematoden van Nederland. Utrecht: Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging.
Bongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia, 83, 14-19. doi:10.1007/BF00324627
Bongers, T., van der Meulen, H., & Korthals, G. (1997). Inverse relationship between the nematode maturity index and plant parasite index under enriched nutrient conditions. Applied Soil Ecology, 6, 195-199. doi:10.1016/S0929-1393(96)00136-9
Braun-Blanquet, J. (1964). Pflanzensoziologie, Grundzüge der Vegetationskunde (3rd ed.). Wien: Springer.
Delarze, R., Gonseth, Y., Eggenberg, S., & Vust, M. (2015). Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten (3rd ed.). Bern: Ott.
Ferris, H., Bongers, T., & de Goede, R.G.M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 13-29. doi:10.1016/S0929-1393(01)00152-4
Landolt, E., Bäumler, B., Erhardt, A., Hegg, O., Klötzli, F., Lämmler, W., … Wohlgemuth, T. (2010). Flora indicativa. Ecological indicator values and biological attributes of the Flora of Switzerland and the Alps (2nd ed.). Bern: Haupt.
Lauber, K., & Wagner, G. (1996). Flora Helvetica. Flora der Schweiz. Bern: Haupt.
MeteoSchweiz (2018). Klimabulletin Jahr 2017, Zürich: MeteoSchweiz.
Moser, D., Gygax, A., Bäumler, B., Wyler, N., & Palese, R. (2002) Rote Liste der gefährteten Farn- und Blütenpflanzen der Schweiz. Bern: BUWAL.
Oostenbrink, M. (1960). Estimating nematode populations by some selected methods. In N.J. Sasser & W.R. Jenkins (Eds.), Nematology (pp. 85-101). Chapel Hill: University of North Carolina Press.
Sieriebriennikov, B., Ferris, H., & de Goede, R.G.M (2014). NINJA: An automated calculation system for nematode-based biological monitoring. European Journal of Soil Biology, 61, 90-93. doi:10.1016/j.ejsobi.2014.02.004

diversity

display_name: diversity

grassland

display_name: grassland

long-term-experiment

display_name: long-term-experiment

nematodes

display_name: nematodes

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

vegetation

display_name: vegetation

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: Grassland restoration: nematodes and plant communities


en: discharge hydrology model climate-change-impact water-temperature

en: Data access

en:
This work presents the first extensive study of climate change impacts on rivers temperature in Switzerland. Results show that even for low emissions scenarios, water temperature increase will lead to adverse effect for both ecosystems and socioeconomic sectors (such as nuclear plant cooling) throughout the 21st century. For high emissions scenarios, the effect will be worsen. This study also shows that water warming in summer will be more important in Alpine regions than in lowlands.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

climate-change-impact

display_name: climate-change-impact

discharge

display_name: discharge

hydrology

display_name: hydrology

model

display_name: model

water-temperature

display_name: water-temperature

educ

en: Education, culture and sport

en: Dataset for: Future water temperature of rivers in Switzerland under climate change investigated with physics-based models


en: evaporation soil-moisture net-radiation evapotranspiration ecohydrology

en: R data file containing gridded net radiation and soil moisture values

en:
Net radiation (W/m2), variable name: NetRadiation, source: Viviroli et al., 2009, spatial resolution: 500 m,
temporal resolution: daily, year 2004, extent: Switzerland.

Soil moisture saturation (-), variable name: SoilMositure, source: simulations from the hydrological model PREVAH,
Brunner et al., 2019; Speich et al., 2015; Orth et al., 2015; Zappa et al., 2003, spatial resolution: 500 m, temporal
resolution: daily, year 2004, extent: Switzerland.

The R command to load the data:
load(“500m_SM_NetRad_2004_for_HESS_raster.RData”)

en: simple R script to load the data and generate sample plots

en: R data set containing R raster objects with 500m gridded daily modeled soil moisture and net radiation covering Switzerland for the year 2004.

ecohydrology

display_name: ecohydrology

evaporation

display_name: evaporation

evapotranspiration

display_name: evapotranspiration

net-radiation

display_name: net-radiation

soil-moisture

display_name: soil-moisture

en: daily 500m gridded net radiation and soil moisture for Switzerland, 2004


maintainer: Michael Lehning

en: Data Source

en: Coordinates of Grid Points

en: Description

en: Full Data Description

mimetype: application/pdf

en: Hourly Gridded Wind Power Time Series

en:
This dataset consist of simulated hourly power production from an Enercon E82 Turbine at 100 m hub-height. It describes the hourly power output a 1MW turbine would produce in each 0.01° grid cell for the years 2016 and 2017.

100 m wind speed data was taken from the COSMO-1 model (Consortium for Small-scale Modeling 2017), which has a 0.01° horizontal resolution. The domain covered is the whole of Switzerland, with the exclusion of lakes. As such, the number of 0.01◦ pixels within Switzerland amounts to 48657.
Conversion to power output was done based on the power curve of the Enercon E82 Turbine. As power output is lower at altitude due to lower air density, we corrected for this effect as described in (Kruyt et al. 2017).

Please cite the following paper in connection with the dataset:

Paper Citation:
 > _Bert Kruyt, Jérôme Dujardin, and Michael Lehning: Improvement of wind power assessment in complex terrain: The case of COSMO-1 in the Swiss Alps, Front. Energy Res., [doi:10.3389/fenrg.2018.00102] (https://doi.org/10.3389/fenrg.2018.00102)_

mountain-wind-potential

display_name: mountain-wind-potential

topography

display_name: topography

wind-energy

display_name: wind-energy

en: Dataset on Cosmo-1 based Energy Potential in Swiss Alps


lwf-lageren-long-term-research-site

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

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

en: LWF plot Lägeren. Photo: Peter Waldner, 2019

en:
![alt text](https://www.envidat.ch/dataset/b763c4e1-2de3-4e8f-9bb7-2ca533624060/resource/b6e747c6-7a85-43e0-958b-3522f370bbad/download/lwf_laegeren.jpg "LWF Lägeren")

This research site is located on the southern slope of the Lägern, which forms the eastern most part of the Jura mountains, within a managed mixed deciduous forest. The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and currently part of the following national networks:

* National Air Pollution Monitoring Network ([NABEL](https://www.empa.ch/web/s503/nabel))
* [TreeNet](https://treenet.info/switzerland/laegeren): The biological drought and growth indicator network
* Long-term Forest Ecosystem Research ([LWF](https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf/sites/laegeren.html))
* [Swiss FluxNet](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

The site measurements are jointly run by the Swiss Federal Laboratories for Materials Science and Technology ([EMPA](https://www.empa.ch)), the groups [Grassland Sciences](https://www.gl.ethz.ch) and [Land-Climate Dynamics](https://iac.ethz.ch/group/land-climate-dynamics.html) from the Swiss Federal Institute of Technology Zurich, the unit [Soil Science & Biogeochemistry](https://www.geo.uzh.ch/en/units/2b.html) from the University of Zurich, and the Swiss Federal Research Institute ([WSL](https://www.wsl.ch)).

LWF Plot Lägeren

- Community: Wettingen / canton AG
- Date of installation: 1.05.2012
- Size of the plot: 1.34 ha
- Altitude: 643 - 718 m
- Mean slope: 37 %
- Geology (in German): Kettenjura; Jura: Malm, Molassehangschutt
- Soil types (WSL) : calcareous brown soil, chromic luvisol, mixed rendzina
- Woodland association after Ellenberg and Klötzli's classification (1972): Galio odoratio-Fagetum typicum bis - Pulmonario-Fagetum typicum
- Main tree species: fagus sylvatica
- Management system: high forest
- Silvicultural system: forest reserve
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 72.18 cm
- Number of trees BHD >= 12 cm (2011): 503
- Maximum tree age: picea abies: 120-170 years, fagus sylvatica: ca. 150 years

forest

display_name: forest

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-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab

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 Lägeren long-term research site


en: toposcale cordex cryosphere downscaling rcm

en: TopoCLIM v1.0

en: Archive of Github repository as of 10 June 2021 including license and documentation and examples.

en: Github link to TopoCLIM project

en:
Model code and documentation for the downscaling model TopoCLIM which provides methods to downscale climate timeseries from CORDEX RCM data. This scheme specifically addresses the need for hillslope scale atmospheric forcing timeseries for modeling the local impact of regional climate change projections on the land surface in complex terrain. The method has a global scope and is able to generate the full suite of model forcing variables required for hydrological and land surface modeling at hourly timesteps.

A working example is provided in this code archive but for full running of the scheme TopoSCALE is required https://doi.org/10.5194/gmd-7-387-2014 with code available at https://github.com/joelfiddes/tscaleV2. Standard library dependencies are given in the python requirements.txt of the archive with installation instructions in the README.md.

License GPL v.3

cordex

display_name: cordex

cryosphere

display_name: cryosphere

downscaling

display_name: downscaling

rcm

display_name: rcm

toposcale

display_name: toposcale

educ

en: Education, culture and sport

en: TopoCLIM v1.0 code


en: marine america occurrences fish caribbean

en: Fish observations of Greater Caribbean and Tropical East Pacific

en:
combined and cleaned occurrences of marine fish species of the Greater Caribbean and Tropical East Pacific.

Data were obtain from the following sources in 2019/2020:
https://gbif.org
https://idigbio.org
https://biogeodb.stri.si.edu/sftep/en/pages
https://biogeodb.stri.si.edu/caribbean/en/pages

america

display_name: america

caribbean

display_name: caribbean

fish

display_name: fish

marine

display_name: marine

occurrences

display_name: occurrences

en: marine fish occurrences of Tropical America


en: avalanche switzerland consistency avalanche-danger danger-description avalanche-bulletin avalanche-forecast

en:
The data contains the following information:
- districtId - the ID of the danger region
- validFromDate - the date and time when the forecast was published
- problem - whether the danger refers to dry or wet conditions as a major avalanche problem
- dangerlevel - the issued danger level
- danger_description_dt - the German danger description describing the major avalanche problem

en: The data set contains the danger descriptions (German) of the avalanche forecasts published at 5 pm between 27-Nov-2012 and 13-Feb-2020.

avalanche

display_name: avalanche

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger

display_name: avalanche-danger

avalanche-forecast

display_name: avalanche-forecast

consistency

display_name: consistency

danger-description

display_name: danger-description

switzerland

display_name: switzerland

en: How is avalanche danger described in textual descriptions in avalanche forecasts in Switzerland?


en: cosmo-wrf high-resolution meteoswiss numerical-simulation complex-terrain

en: WPSrun

en: Scripts to run the WRF pre-processing (WPS) for COSMO-WRF simulation (see Section 5 in COSMOWRFdocumentation.pdf)

en: WPSSetup

en: Scripts that need to be changed to compile WPS (see COSMOWRFdocumentation.pdf, Section 4)

en: StaticData

en:
Scripts to process geographical/static data (see Section 3 in COSMOWRFdocumentation.pdf).
- ascii_to_bin_landuse.f90
- ascii_to_bin_soiltype.f90
- ascii_to_bin_topo_wgs84_ws2sf1.f90
- see_slopes.ncl
- soiltype_writing.py
- toposmooth_wgs84_cosmobound.ncl
- write_geogrid.o

en: WRFrun

en: Scripts to run COSMO-WRF simulation (see Section 6 in COSMOWRFdocumentation.pdf)

en: Postprocessing

en: Postprocessing scripts to map WRF output on swiss coordinates (see Section 7 in COSMOWRFdocumentation.pdf)

en: MeteorologicalData

en: Scripts to process meteorological data (see Section 2 in COSMOWRFdocumentation.pdf).

en: COSMO-WRF documentation v1.0

en:
Gerber, Franziska; Sharma, Varun (2018). Running COSMO-WRF on very-high resolution over complex terrain. EnviDat. doi:10.16904/envidat.35

Documentation about the procedure to run COSMO-WRF

en: This is a technical documentation of the procedure to run the Weather Research and Forecasting (WRF) model over complex alpine terrain using Consortium for Small-Scale Modeling (COSMO) reanalysis by the Federal Office of Meteorology and Climatology (MeteoSwiss) as initial and boundary conditions (COMSO-WRF). The setup is adapted for very high resolution simulations based on COSMO-2 (2.2 km resolution) reanalysis. This document gives an overview over steps to setup COSMO-WRF and adaptations needed to run COSMO-WRF. Additionally, the calculation of precipitation rate at a horizontal plane and remapping COSMO-WRF output on Swiss coordinates are documented.

complex-terrain

display_name: complex-terrain

cosmo-wrf

display_name: cosmo-wrf

high-resolution

display_name: high-resolution

meteoswiss

display_name: meteoswiss

numerical-simulation

display_name: numerical-simulation

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: raised-bog vegetation-survey long-term-biodiversity-monitoring observer-error inter-observer-difference flood-plain dry-grassland pseudoturnover ecological-indicator-value fen

en: Boch et al. 2022 Applied Vegetation Science - Raw species list and file used for lmer

en: The dataset was used for the paper Boch S, Küchler H, Küchler M, Bedolla A, Ecker KT, Graf UH, Moser T, Holderegger R, Bergamini A (2022) Observer-driven pseudoturnover in vegetation monitoring is context dependent but does not affect ecological inference. Applied Vegetation Science.

en:
This dataset was used to analyze the inter-observer error (i.e. pseudoturnover) in vegetation surveys for the publication Boch S, Küchler H, Küchler M, Bedolla A, Ecker KT, Graf UH, Moser T, Holderegger R, Bergamini A (2022) Observer-driven pseudoturnover in vegetation monitoring is context dependent but does not affect ecological inference. Applied Vegetation Science.
In the framework of the project "Monitoring the effectiveness of habitat conservation in Switzerland", we double-surveyed a total of 224 plots that were marked once in the field and then sampled by two observers independently on the same day. Both observers conducted full vegetation surveys, recording all vascular plant species, their cover, and additional plot information. We then calculated mean ecological indicator values and pseudoturnover.
The excel file contains two sheets:
1) Raw species lists of the 224 plots conducted by two different observers. Woody species are distinguished in three layers: H (herb layer; woody species <0.5 m in height), S (shrub layer; woody species 0.5–3 m in height) and T (tree layer; woody species >3 m in height). "cf." indicates uncertain identification, "aggr." indicates that the plant was identified only to the aggregate level. Cover was estimated for each species using a modified Braun-Blanquet scale (r ≙ <0.1%, + ≙ 0.1% to <1%, 1 ≙ 1% to <5%, 2 ≙ 5% to <25%, 3 ≙ 25% to <50%, 4 ≙ 50% to <75%, 5 ≙ 75% to <100%).
2) File used for the linear mixed effects model.

dry-grassland

display_name: dry-grassland

ecological-indicator-value

display_name: ecological-indicator-value

fen

display_name: fen

flood-plain

display_name: flood-plain

inter-observer-difference

display_name: inter-observer-difference

long-term-biodiversity-monitoring

display_name: long-term-biodiversity-monitoring

observer-error

display_name: observer-error

pseudoturnover

display_name: pseudoturnover

raised-bog

display_name: raised-bog

vegetation-survey

display_name: vegetation-survey

educ

en: Education, culture and sport

en: Observer-driven pseudoturnover in vegetation surveys


phosphatase-leaching

title_for_slug: phosphatase-leaching

en: phosphomonoesterase-activity phosphate dissolved-organic-phosphorus forest-topsoil phoshporus-forms

en:
Data on phosphomonoesterase activity in forest topsoil leachates and soil extracts as well as P forms in the leachate.
Leachate samples were taken in Feb./Mar. and July 2019 with zero-tension lysimeters at two sites in Germany
of contrasting phosphorus availability from the litter, the Oe/Oa, and the A horizon in beech forest.
Soil samples were taken in July 2020. For methods see publication.

en:
Data on phosphomonoesterase activity in forest topsoil leachates and soil extracts as well as P forms in the leachate.
Leachate samples were taken in Feb./Mar. and July 2019 with zero-tension lysimeters at two sites in Germany
of contrasting phosphorus availability from the litter, the Oe/Oa, and the A horizon in beech forest.
Soil samples were taken in July 2019. For methods see publication.

dissolved-organic-phosphorus

display_name: dissolved-organic-phosphorus

forest-topsoil

display_name: forest-topsoil

phoshporus-forms

display_name: phoshporus-forms

phosphate

display_name: phosphate

phosphomonoesterase-activity

display_name: phosphomonoesterase-activity

en: Phosphatase leaching


maintainer: Mathias Bavay

en: air-pressure wind-direction snow-depth shortwave-radiation dew-point-temperature treeline precipitation-sum relative-humidity soil-temperature air-temperature wind-speed stillberg

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en: The Davos Stillberg meteorological data (Stillberg_meteo_v1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en:
 Background information
The Stillberg ecological treeline research site is located in the transition zone between the relatively humid climate of the Northern Alps and the continental climate of the Central Alps. In 1975, 92,000 seedlings of the high-elevation conifer species *Larix decidua* Mill. (European larch), *Pinus cembra* L. (Cembran pine), and *Pinus mugo* ssp. *uncinata* (DC.) Domin (mountain pine) were systematically planted across an area of 5 hectares along an elevation gradient of about 150 metres, with the aim to develop ecologically, technically, and economically sustainable afforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Alongside the ecological long-term monitoring of the afforestation, several meteorological stations have recorded local meteorological conditions at the Stillberg research site. Here, we provide the Davos Stillberg meteorological timeseries of five stations from 1975 (01-01-1975), the year of the afforestation establishment, until the end of the year 2022 (31-12-2022).

 Station description
The five meteorological stations were all installed at the same location (46°46′25.015″N 9°52′01.792″E) at 2090 m a.s.l., in the lower part of the afforestation area. In general, the five stations were operated sequentially (Stillberg_meteo_metadata_stations_v1.csv). However, there are some overlapping time periods when more than one station was operated in parallel. The stations have recorded environmental parameters, such as air and soil temperature, dew point temperature, air pressure, relative humidity, wind direction and velocity, radiation, precipitation, and snow depth (Stillberg_meteo_metadata_parameters_v1.csv). The meteorological measurements were recorded hourly from 1975 until 1996 and have been recorded in 10-minute intervals since 1997.

 Data description
We processed the Davos Stillberg meteorological timeseries with the MeteoIO meteorological data pre-processing library (Bavay & Egger, 2014). Data files are provided for each station and quality level separately and named according to the station (see ‘Stillberg_meteo_metadata_stations_v1.csv’). From the raw data in their original formats, we generated three data quality levels: raw standardized (folder ‘raw_standardized’), edited (folder ‘raw_edited’) and filtered (folder ‘filtered’). The processing level is indicated in the headers of the data files. The whole processing protocol is described in a set of human-readable configuration files that are used by MeteoIO to generate the required data quality levels. This improves long-term reproducibility (Bavay et al., 2022), as the data could be regenerated in the future, even using a completely different software, to account for additional data points or to introduce new data corrections. The first quality level (raw standardized) is generated by parsing the original data files and interpreting them in order to convert all data points to a common format and meteorological parameter naming scheme, while excluding unreadable or duplicated data lines. The generated data files are derivatives of CSV files, with a standardised header that contains the metadata that are necessary to interpret and use the data (use metadata) and to populate a data index (search metadata). The latter is a textual implementation of the Attribute Convention for Data Discovery (ACDD) metadata standard (Attribute Convention for Data Discovery 1-3, 2022). The second quality level (edited) builds on the raw data by performing low-level data editing, such as removing some data periods that are known to be unusable (often based on maintenance records or anecdotal evidence) or applying undocumented calibration factors (for example, when there seems to be an obvious offset on a measured parameter for a period between two documented maintenance operations). The third quality level is generated by applying statistical filters on the data (per station and per meteorological parameter) to exclude presumably wrong values. We did not perform gap filling, as no single strategy could be relied upon that would work best for all possible data usage scenarios.

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

treeline

display_name: treeline

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

en: Long-term meteorological station Stillberg, Davos, Switzerland at 2090 m a.s.l.


total-stem-number

title_for_slug: total-stem-number

en:
Number of stems of all living and dead trees and shrubs starting at 12 cm dbh.

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

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

degree-of-damage

display_name: degree-of-damage

economic-region

display_name: economic-region

giants

display_name: giants

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

main-tree-species

display_name: main-tree-species

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

total-stem-number

display_name: total-stem-number

tree-state-alive-dead

display_name: tree-state-alive-dead

tree-status

display_name: tree-status

envidat

en: EnviDat: the Environmental Data Portal

en: Total stem number


en: shortwave-radiation outgoing longwave-radiation weissfluhjoch incoming

en: Metadata

en: Processing doc

en: DATA ACCESS

en: Parameter file

media_type: text/plain

format: TXT

mimetype: text/plain

en:
Corrected incoming and outgoing shortwave and longwave 2 min radiation measurements at the Weissfluhjoch summit, Davos, 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.

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

weissfluhjoch

display_name: weissfluhjoch

envidat

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

en: ASRB_WFJ: Shortwave and longwave radiation measurements (2 min) at the Weissfluhjoch research site, Davos


seilaplan

title_for_slug: seilaplan

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

en: Seilaplan QGis Plugin v2.0

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

License: GNU, General Public License, Version 2 or newer.

Literature:
Bont, L., & Heinimann, H. R. (2012). Optimum geometric layout of a single cable road. European journal of forest research, 131(5), 1439-1448.

cable-planning

display_name: cable-planning

cable-yarding

display_name: cable-yarding

catenary-load-path

display_name: catenary-load-path

python

display_name: python

qgis

display_name: qgis

software

display_name: software

steep-terrain-harvesting

display_name: steep-terrain-harvesting

educ

en: Education, culture and sport

en: Seilaplan


en: meteo-station snow-height shortwave-radiation gemstock longwave-radiation

en:
Meteo data at Gemsstock [Level 2 dataset](http://models.slf.ch/p/dataset-processing/).

fields      = timestamp TSS HS VW DW VW_MAX OSWR ISWR ILWR RECORD AUX_VOLTAGE LOGGER_VOLTAGE LW_SENSOR_TEMP VENTILATION_FLAG OLWR

en: Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.

gemstock

display_name: gemstock

meteo-station

display_name: meteo-station

snow-height

display_name: snow-height

en: GEM2: Meteorological and snow station at Gemsstock (3021 m asl), Canton Uri, Switzerland


full-content-of-wsl-fauna-database

title_for_slug: full-content-of-wsl-fauna-database

en: invertebarates collections arthropods wsl database

en: Updated export with semicolon-delimited columns instead of comma delimited

en: Complete dataset of all projects and data collected in WSL Fauna Database

en:
Query executed to retrieve the complete dataset from WSL Fauna Database
FIDO_global_extract 2023-03-08_16-27-28 WSL-AllData-AllTaxa.sql compressed in zip-archive

en: Complete extract of Fauna Database of WSL, containing all projects and all taxa. Meant as exchange and citation platform for sharing the data with the national data centre 'Centre Suisse de la Cartographie de la Fauna (CSCF)', and Info Fauna.

arthropods

display_name: arthropods

collections

display_name: collections

database

display_name: database

invertebarates

display_name: invertebarates

wsl

display_name: wsl

envidat

en: EnviDat: the Environmental Data Portal

en: Full content of WSL Fauna Database


soil-matrix-chemistry-lwf

title_for_slug: soil-matrix-chemistry-lwf

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

en: Data Request

en:
Assessment of several chemical soil parameters at the beginning of the monitoring campaign. Most parameters were determined accordung to the manual of ICP-Integrated-Monitoring. The parameters were analysed for all genetic horizons in soil pits and additionally for fixed layers in the Intensive-Monitoring-Plots. In heterogeneous LWF-plots, several soil pits were analysed in order to assess the soil variability of the plot. The manual (in German) for soil sampling and soil analyses is available in www: http://e-collection.ethbib.ethz.ch/view/eth:25622?q=walthert. The results and data of the first soil survey are available (in German) in www: http://e-collection.ethbib.ethz.ch/view/eth:26275?q=walthert.

 Purpose:

The chemical characterisation of soil matrix down to the paraent material is realised with data from soil pits. The monitoring of the soil matrix in a frequency of roundly 15 years is effected with soil samples from Intensiv-Monitoring-Plots. For soil monitoring, pooled samples with 16 replicats are used down to a depth of 80 cm. The date of the second soil survey is not yet fixed.

 Manual Citation:

 * Walthert L, Lüscher P, Luster J, Peter B (2002) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Aufnahmeanleitung zur ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 269: 56 p. [10.3929/ethz-a-004375470](https://doi.org/10.3929/ethz-a-004375470)

 Paper Citation:

 * Walthert L, Blaser P, Lüscher P, Luster J, Zimmermann S (2003) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Ergebnisse der ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 276: 340 p.

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

soil-chemistry

display_name: soil-chemistry

soil-matrix

display_name: soil-matrix

swiss-forest-lab

display_name: swiss-forest-lab

envidat

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

en: Soil matrix chemistry LWF


en: vegetation-structure chiroptera habitat-modelling forest-management echolocation

en: R scripts for all analyses

en: Complete set of field data and LiDAR data including bat activity measurements

en: Variable description_20220411.csv

en: Description of all variables given in the file 'Felddaten_2020-02-14_Guilde.csv'

en: Habitat shift caused by human impact on vegetation structure poses a great threat to species which are special- ized on unique habitats. Single layered beech forests, the main foraging habitat of Greater Mouse-eared Bats (My- otis myotis), are threatened by recent changes in forest structure. After this species suffered considerable popula- tion losses until the 1970s, their roosts in buildings are strictly protected. However, some populations are still de- clining. Thus, the spatial identification of suitable foraging habitat would be essential to ensure conservation pol- icy. The aim of this study was (a) to verify the relevance of forest structural variables for the activity of M. myotis and (b) to evaluate the potential of LiDAR (Light Detection and Ranging) in predicting suitable foraging habitat of the species. We systematically sampled bat activity in forests close to 18 maternity roosts in Switzerland and applied a generalized linear mixed model (GLMM) to fit the activity data to forest structure variables recorded in the field and derived from LiDAR. We found that suitable forest foraging habitat is defined by single layered for- est, dense canopy, no shrub layer and a free flight space. Most importantly, this key foraging habitat can be well predicted by airborne LiDAR data. This allows for the first time to create nationwide prediction maps of potential foraging habitats of this species to inform conservation management. This method has a special significance for endangered species with large spatial use, whose key resources are hard to identify and widely distributed across the landscape.

chiroptera

display_name: chiroptera

echolocation

display_name: echolocation

forest-management

display_name: forest-management

habitat-modelling

display_name: habitat-modelling

vegetation-structure

display_name: vegetation-structure

educ

en: Education, culture and sport

en: LiDAR metrics predict suitable forest foraging areas of endangered Mouse-eared bats (Myotis myotis)


en: gis photovoltaic bioenergy complementarity biomethane

en: Supplementary Information

en: Supplementary Information with regards to how the solar and biomass resources were calculated for the paper. Electricity yields of PV depending on various variables

en: Manure monthly resolution

en: This gives details on how calculation were made to estimate the monthly distribution of manure produced in Switzerland.

en:
Base data for quantitites of manure and agricultural residues available in Switzerland aggregated per municipalities and provided yearly and monthly.

Method:
The biomass considered in this study consists of agricultural residues arising according to current practice, i.e. mainly manure and some crop by-products. Availability was calculated following the method of (Burg et al., 2018)   based on the updated national agricultural inventory (FSO, 2018). The animal manure potential considered here represents the total annually collected amount, i.e. generated amount after subtracting losses from grazing. With regard to crop by-products, only a small percentage of the theoretical potential was considered to be available since most crop by-products cannot be readily collected today (Burg et al., 2018). The potential biogas production used in the present study was calculated analogously as in Burg et al. (2018) based on a specific biogas yield from fresh biomass. The additional potential of co-substrates from industrial or municipal organic wastes was not considered here.
Bsed on G1G22 (Municipalities in 2022) according to BFS

References:
Burg, V., Bowman, G., Erni, M., Lemm, R., Thees, O., 2018a. Analyzing the potential of domestic biomass resources for the energy transition in Switzerland. Biomass and Bioenergy 111, 60-69. https://doi.org/https://doi.org/10.1016/j.biombioe.2018.02.007
FSO, 2018. Individual data from the agricultural structure survey STRU. Federal statistical office FSO, Bern.

en: Additional references

en: Additional references to an article

en:
Additional references to the article:
Linking solar and biomass resources to generate renewable en-ergy: can we find local complementarities in the agricultural setting?
Gillianne Bowman, Thierry Huber, Vanessa Burg
Energies, https://www.mdpi.com/1996-1073/16/3/1486

Today, the energy transition is underway to tackle the problems of climate change and energy sufficiency. For this transition to succeed, it is essential to use all available re-newable energy resources most efficiently. However, renewable energies often bring high volatility that needs to be balanced. One solution is to combine the use of different renewable sources to increase the overall energy output or reduce its environmental impact. Here, we estimate the agricultural solar and biomass resources at the local level in Switzerland, considering their spatial and temporal variability using Geographic In-formation Systems. We then identify the technologies that could allow synergies or complementarities. Overall, the technical agricultural resources potential is ~15 PJ/annus biogas yield from residual biomass and ~10 TWh/a electricity from solar installed on roofs (equivalent to ~36 PJ/a). Anaerobic digestion, combined heat & power plant, Raw manure separation, Biomethane upgrading, Power to X, Electrolysis, Chill generation and Pho-tovoltaic on biogas facilities could foster complementarity in the system if resources are pooled within the agricultural setting. Temporal complementarity at the farm scale can only lead to partial autarchy. The possible benefits from these complementarities should be better identified, particulary in looking looking at the economic viability of such systems.

bioenergy

display_name: bioenergy

biomethane

display_name: biomethane

complementarity

display_name: complementarity

gis

display_name: gis

photovoltaic

display_name: photovoltaic

en: Linking solar and biomass resources to generate renewable energy: can we find local complementarities in the agricultural setting?


litterfall-lwf

title_for_slug: litterfall-lwf

en: nutrient-content icp-forests branches fruit-production swiss-forest-lab litterfall long-term-forest-ecosystem-research foliage-production

en: Data Request

en:
Litterfall is a key parameter in the biogeochemical cycle of forest ecosystems, linking the tree part to the soil compartment. Litterfall has been collected on 15 LWF plots using 10 traps that are emptied every 4 to 8 weeks since 1996 or later. Both the biomass of the litter and its chemical content (including heavy metals) are measured, in order to quantify the annual return of nutrients and organic matter to the soil. Furthermore, the analysis of the temporal pattern of litterfall production gives insight into possible effects of anthropogenic and natural factors (e.g. severe drought) on the ecosystem and the vitality of the forest stand, provides information on the phenological development of the stand, and, in particular, allows mast years to be identified. At 7 broadleaved sites, litterfall was also used to estimate the leaf area index (LAI) of the forest stand.

 Purpose:

To quantify the annual return of nutrients and organic matter to the soil.

 Manual Citation:

 * Thimonier, A., Brang, P., Ottiger, A., 1997. Kapitel C5. Streufall, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-18.

 * Ukonmaanaho L., Pitman R, Bastrup-Birk A, Breda N, Rautio P, 2016: Part XIII: Sampling and Analysis of Litterfall. 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 for Forests Ecosystems, Eberswalde, Germany, 14 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Thimonier A, Sedivy I, Schleppi P (2010) Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods. European Journal of Forest Research, 129 (4): 543-562. [doi: 10.1007/s10342-009-0353-8](http://doi.org/10.1007/s10342-009-0353-8 )

branches

display_name: branches

foliage-production

display_name: foliage-production

fruit-production

display_name: fruit-production

litterfall

display_name: litterfall

nutrient-content

display_name: nutrient-content

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: Litterfall LWF


en: snow snow-avalanche crack-propagation snow-mechanics experiment

en: Supplementary material

en:
 Supplementary material to the publication Bergfeld et al 2021
- description of the reverse crack
- additional snowpack parameters derived from the SMP measurements

en: Crack speed and Touchdown distance data

en:
Data is stored as netcdf files as python/xarray Datasets.
Datasets are self-explaining and contain the necessary information and metadata.
Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

en: DIC Data

en:
Data contains the displacement, strain, velocity and acceleration fields measured during the crack propagation process in our three example Propagation Saw Tests (PSTs). Data is stored as netcdf files as python/xarray Datasets. Datasets are self-explaining and contain the necessary metadata (field notes on the PSTs, camera settings, Digital Image Corrrelation parameters, preprocessing parameters).

Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

en: Videos

en: The videos are .mp4 exports of the raw files (reduced 50 times in time)

en: Videos of crack propagation

en: The videos show the cracking process in three example Propagation Saw Tests (flat field). The upper panel shows strain on top of the recorded movie frames. The second row shows vertical (*w*, blue line) and horizontal (*u*, orange line) displacement fields. The third and fourth row show the first and second time derivatives, namely the velocity and acceleration field.

en:
This data set includes material and results described in the related research article:

Bergfeld, B., van Herwijnen, A., Reuter, B., Bobillier, G., Dual, J., and Schweizer, J.: Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2020-360, in review, 2021.

 Context:
In order to study crack propagation in weak snowpack layers in great detail, we recorded Propagation Saw Test (PST) experiments using a high-speed camera and applied digital image correlation (DIC) to derive displacement and strain fields in the slab, weak layer, and substrate. We demonstrated the versatility and accuracy of the DIC method by showing measurements from three PST experiments, resulting in slab fracture, crack arrest and full propagation in the related publication.
 Content:
- Supplementary material for related publication
- Ilustrative videos showing crack propagation
- High-speed recordings of the Experiments
(the raw .cine files are available upon request)
Processed Data containing:
  - displacement, velocity and acceleration fields for the three PSTs
  - speed and touchdown dataset

crack-propagation

display_name: crack-propagation

experiment

display_name: experiment

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics

educ

en: Education, culture and sport

en: Dataset for "Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography"


en: antwerp flying-arthropods zurich chiroptera urban-biodiversity urbanisation nocturnal-fauna paris

en: Bats Insects Sites dataset

en: Tab-delimited data file containing data analysed. First row is column header. Column headers are described in tab-delimited file 'Variable_description.txt"

en: BIOVEINS raw bat data.csv

en: Raw bat identification data from which the analysis data were derived

en: Variable description

en: Tab-delimited file containing names and description of data contained in the tab-delimited data file 'BatsInsectsSites_Date.txt'.

en: BIOVEINS raw bat explanatory data.csv

en: Explanation for column headers in file 'BIOVEINS raw bat data.csv'

en: Animal biodiversity in cities is generally expected to be uniformly reduced, but recent studies show that this is modulated by the composition and configuration of Urban Green Areas (UGAs). UGAs represent a heterogeneous network of vegetated spaces in urban settings that have repeatedly shown to support a significant part of native diurnal animal biodiversity. However, nocturnal taxa have so far been understudied, constraining our understanding of the role of UGAs on maintaining ecological connectivity and enhancing overall biodiversity. We present a well-replicated multi-city study on the factors driving bat and nocturnal insect biodiversity in three European cities. To achieve this, we sampled bats with ultrasound recorders and flying insects with light traps during the summer of 2018. Results showed a greater abundance and diversity of bats and nocturnal insects in the city of Zurich, followed by Antwerp and Paris. We identified artificial lighting in the UGA to lower bat diversity by probably filtering out light-sensitive species. We also found a negative correlation between both bat activity and diversity and insect abundance, suggesting a top-down control. An in-depth analysis of the Zurich data revealed divergent responses of the nocturnal fauna to landscape variables, while pointing out a bottom-up control of insect diversity on bats. Thus, to effectively preserve biodiversity in urban environments, UGAs management decisions should take into account the combined ecological needs of bats and nocturnal insects and consider the specific spatial topology of UGAs in each city.

antwerp

display_name: antwerp

chiroptera

display_name: chiroptera

flying-arthropods

display_name: flying-arthropods

nocturnal-fauna

display_name: nocturnal-fauna

paris

display_name: paris

urban-biodiversity

display_name: urban-biodiversity

urbanisation

display_name: urbanisation

zurich

display_name: zurich

envidat

en: EnviDat: the Environmental Data Portal

en: Bats and nocturnal insects in urban green areas


maintainer: Frank Techel

en: verification avalanche-bulletin avalanche-forecasting avalanche-danger-level avalanche-forecast

en: D_QC for forecasting seasons 2001/2002 until 2019/2020.

en: D_QC for forecasting seasons 2020/2021 - 2022/2023.

en:
The data set contains the re-analyzed (or quality-checked) regional avalanche danger levels (D_QC) for Switzerland.

D_QC relates to dry-snow avalanche conditions only. Measuring the avalanche danger level D is not possible; forecast, nowcast, and hindcast assessments of D are judgments by humans interpreting data. However, combining several pieces of information indicating the same D, it can be expected that it is more likely that D_QC represents the avalanche conditions well.

For the **forecasting seasons 2001/2002 until 2019/2020**, the approach to obtain D_QC is described in detail in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

For the **forecasting seasons 2020/2021 and later**, D_QC is derived using the following approach:
1. *Combination of forecast (D_forecast) and nowcast (D_nowcast)*: If there was only one assessment available by an observer after a day in the field for a region, and if D_forecast = D_nowcast --> D_QC = D_forecast.
2. *Combination of several nowcast assessments (D_nowcast)*: If two (or more) observers agreed (or majority opinion) in their (independent) assessments of D_nowcast after a day in the field in the same warning region. --> D_QC = D_nowcast.
3. *Hindcast analysis (D_hindcast)*: In Switzerland, avalanche forecasters re-evaluate all situations when D = 4 (high) or D = 5 (very high) were either forecast, should have been forecast, or when forecasters discussed given one of these two levels but had not given them. Generally, two forecasters assess each situation. In these cases, D_QC = D_hindcast. The hindcast analysis, only available since the forecasting season 2020/2021, replaces what was step (2) in Appendix A of [Pérez-Guillén et. al. (2022)](https://nhess.copernicus.org/articles/22/2031/2022/nhess-22-2031-2022.html).

All other cases - ties in case of (1) or (2), no new information from the warning region in question, or if no D_hindcast was available - are not considered quality-checked, and are, thus, not contained in the data set.

In addition to D_QC, the file contains information on the elevation and aspect, where D_QC likely prevails.
- The indicated elevation is the mean of the respective elevations in (1), (2), or (3). At danger level 1 (low), when no elevation is indicated in the Swiss forecast, a value of 1500 m is set.
- For the four cardinal aspects N, E, S, and W, a value of 1 means that there was agreement that D was reached in this aspect and a value of 0 means that there was agreement that D was not reached in this aspect. Intermediate values correspondingly mark disagreements in the assessments.

avalanche-bulletin

display_name: avalanche-bulletin

avalanche-danger-level

display_name: avalanche-danger-level

avalanche-forecast

display_name: avalanche-forecast

avalanche-forecasting

display_name: avalanche-forecasting

verification

display_name: verification

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: Re-analyzed regional avalanche danger levels in Switzerland


radar-wind-profiler-davos-wolfgang

maintainer: Maxim Hervo

title_for_slug: radar-wind-profiler-davos-wolfgang

en: raclets wind-speed wind-direction wolfgangpass radar

en: Radar Wind Profiler Data

en: A Vaisala Lap3000 was installed at Davos Wolfgang to record wind profiles. The time format is number of days fom January 0, 0000 in UTC with a 10 minute resolution.

en: The RADAR wind profiler from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 2171 m above sea level to 11079 m, with a temporal resolution of 10 minutes.

raclets

display_name: raclets

radar

display_name: radar

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed

wolfgangpass

display_name: wolfgangpass

educ

en: Education, culture and sport

en: RADAR Wind profiler Davos Wolfgang


mass-of-needles-or-leaves-of-live-trees

title_for_slug: mass-of-needles-or-leaves-of-live-trees

en:
Dry weight (mass) of the needles and leaves of the living trees and shrubs starting at 12 cm dbh.

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

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

mass-of-needles-or-leaves-of-live-trees

display_name: mass-of-needles-or-leaves-of-live-trees

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

en: Mass of needles or leaves of live trees


en: drought litterfall heat soil-matric-potential forest fruit-abortion beech pollen mast

en: LWF beech litterfall and pollen, and environmental parameters

en: Parameters for the LWF beech plots Bettlachstock, Lausanne and Schänis. Fruit biomass, leaf biomass and pollen are present as percentage of highest annual value measured per plot. Environmental parameters precipitation sums, mean temperatures and soil matric potentials in four soil depths are present as deviations from longterm mean for the seasons spring (April and May) and summer (June and July).

en:
This dataset contains the parameters used in the statistical analyses for the manuscript SREP-19-40170-T, submitted in Scientific Reports. This study is part of the WSL Drought Initiative 2018 (C3 - Analysis of the beech litterfall of the drought year 2018).

Data originate from the Long-term Forest Ecosystem Research Programme LWF (litterfall, soil matric potential, deposition (precipitation) and meteo (temperature)), and from the Swiss Federal Office of Meteorology and Climatology MeteoSwiss (pollen).

Datafile:

 _LWF_beech_plots_litterfall_pollen.xlsx_

1. Sheet _extreme_weather_: values used for analysis of weather conditions in strongest mast years compared to years with fruit abortion.

2. Sheet _weather_and_resource_allocation_: values used for analysis of weather impacts on mast occurrence and resource allocation models.

beech

display_name: beech

drought

display_name: drought

forest

display_name: forest

fruit-abortion

display_name: fruit-abortion

heat

display_name: heat

litterfall

display_name: litterfall

mast

display_name: mast

pollen

display_name: pollen

soil-matric-potential

display_name: soil-matric-potential

en: Litterfall and pollen data of three LWF beech plots


lwf-isone-long-term-research-site

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

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

en: LWF plot Isone. Photo: Anne Thimonier Rickenmann, 2011

en: Isone Meteorological Data LWF

en:
![alt text](https://www.envidat.ch/dataset/f4b44f60-4eed-471f-a09e-749a0f5f0683/resource/cb8e84ea-ad8b-476e-be32-e02a927d2449/download/lwf_isone.jpg "LWF Isone")

LWF Plot Isone

- Community: Isone / canton TI
- Date of installation: 5 September 1995
- Size of the plot: 2 ha
- Altitude (m): 1181-1259
- Mean slope: 58%
- Geology (in German): Untergrund: Südalpin, präpermisches Grundgebirge, Ceneri Zone; schiefriger Biotitplagioklasgneis - Oberfläche: Quartär; Moräne, Hängeschutt-.
- Provisional soil type (WSL) : Humic Cambisol
- Woodland association after EK72: 4: Luzulo niveae-Fagetum dryopteridetosum
- Main tree species: Fagus sylvatica
- Management system: former coppice
- Silvicultural system: unmanaged
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 37.4 cm
- Number of trees BHD >= 12 cm (2011): 1254
- Maximum tree age: Fagus sylvatica uneven-aged - 70-85-100 yr

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

envidat

en: EnviDat: the Environmental Data Portal

en: LWF Isone long-term research site


en:
Volume of stemwood with bark of all trees and shrubs starting at 12 cm dbh removed from the forest between two inventories due to damage that occurred, in this case windthrow, and not due to silvicultural 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).  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)_

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

economic-region

display_name: economic-region

production-region

display_name: production-region

salvage-logging-due-to-wind

display_name: salvage-logging-due-to-wind

envidat

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

en: Salvage logging due to wind