en: swiss-forest-lab long-term-forest-ecosystem-research icp-forests nitrogen base-cations atmospheric-deposition acidity

en:
Throughfall (precipitation under forest canopy) is a major pathway in forest nutrient cycling, and its quantification is necessary to establish both water and nutrient budgets. Furthermore, parallel sampling of throughfall and precipitation in the open field (bulk precipitation), together with assumptions about the canopy exchange processes (uptake and leaching of nutrients), allow the atmospheric deposition of nutrients and pollutants to be quantifed. Bulk precipitation and throughfall have been sampled since 1994 or later on 15 LWF plots using 3 (in the open) and 16 (in the forest) funnel-type precipitation collectors. These collectors are replaced by 1 (open area) and 4 (forest stand) snow buckets in winter on plots with abundant precipitation in the form of snow. The length of sampling intervals is usually 14 days.

 Purpose:

To assess a major flux of the water and nutrient budget in forests, and to quantify the atmospheric deposition of nitrogen, sulphur and other nutrients. Atmospheric deposition is one of the key factors in the causal chain between emission of air pollutants and acidifying or eutrophying effects in forest ecosystems.

 Manual Citation:

 * Thimonier, A., Brang, P., Wenger, K., 1997. Kapitel C4. Atmosphärische Deposition: Freiland- und Bestandesniederschläge, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-48.

 * Clarke N, Žlindra D, Ulrich E, Mosello R, Derome J, Derome K, König N, Lövblad G, Draaijers GPJ, Hansen K, Thimonier A, Waldner P, 2016: Part XIV: Sampling and Analysis of Deposition. 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,  32  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Thimonier A, Schmitt M, Waldner P, Rihm B (2005) Atmospheric deposition on Swiss Long-term Forest Ecosystem Research (LWF) plots. Environmental Monitoring and Assessment, 104: 81-118. [doi: 10.1007/s10661-005-1605-9](http://doi.org/10.1007/s10661-005-1605-9)

 * Thimonier A, Kosonen Z, Braun S, Rihm B, Schleppi P, Schmitt M, Seitler E, Waldner P, Thöni L (2019) Total deposition of nitrogen in Swiss forests: Comparison of assessment methods and evaluation of changes over two decades. Atmospheric Environment, 198: 335-350. [doi: 10.1016/j.atmosenv.2018.10.051](http://doi.org/10.1016/j.atmosenv.2018.10.051)

acidity

display_name: acidity

atmospheric-deposition

display_name: atmospheric-deposition

base-cations

display_name: base-cations

nitrogen

display_name: nitrogen

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: Atmospheric deposition (throughfall and bulk deposition) LWF


maintainer: Sebastian Schlögl

en: stable-boundary-layer atmosphere turbulent-sensible-heat-fluxes atmospheric-turbulence snow

state: active

type: dataset

en: Turbulence data AA00

media_type: application/zip

en: sensor in 25 m height

format: ZIP

mimetype: application/zip

en: Turbulence data GR00

en: sensor in 1 m height

en: Turbulence data WFJ07

en: upper sensor

en: Turbulence data PM07

en: NWW

en: Turbulence data WFJ11

en: sensor in 0.2 m height

en: lower sensor

en: SEE

en: sensor in 2 m height

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

snow

display_name: snow

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

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.

en: How do stability corrections perform in the stable boundary layer over snow?


en: dsm photogrammetry ground-classification drone-data uav

en: Geodata and Ground Classification Wolfgang Arelen

en: Original RGB images and generated products.

format: GeoTIFF

en: We conducted two drone flights with the Wingtra and DJI Phantom 4 RTK drones in Davos Wolfgang Arelen, on 25.08.2021. The data was processed with the Agisoft Metashape Professional Software.The Wingtra point cloud was further processed to derive a ground classification in individual LASTools and Terrasolid workflows.

drone-data

display_name: drone-data

dsm

display_name: dsm

ground-classification

display_name: ground-classification

photogrammetry

display_name: photogrammetry

uav

display_name: uav

envidat

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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.

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Photogrammetric Drone Data and derived Ground Classification Wolfgang Arelen


en: wind-disturbance damaged-wood chablis wood-market bois-endommage scieries stockage-humide wet-storage marche-du-bois sawmills

en: Impact des événements météorologiques extrêmes sur l'économie forestière suisse: le point de vue des scieries

format: XLS

en:
Extreme events impact on the Swiss forest economy: the sawmill perspective

Supplementary Information
This survey aimed at answering three main questions: (i) What are the Swiss sawmills challenges and actions taken after a large storm/windthrow?, (ii) How do these challenges and actions vary across sawmill size and location?, and (iii) is adaptation from the sawmills to extreme events possible, with regards to wood type, products and required infrastructure?

Informations supplémentaires
Cette enquête visait à répondre à trois questions principales : (i) Quels sont les défis et les mesures prises par les scieries suisses après une grosse tempête ou un coup de vent ? (ii) Comment ces défis et ces mesures varient-ils selon la taille et l'emplacement de la scierie ? et (iii) l'adaptation des scieries aux événements extrêmes est-elle possible, en ce qui concerne le type de bois, les produits et l'infrastructure requise ?

Ziel dieser Umfrage war die Beantwortung von drei Hauptfragen: (i) Welche
s sind die Herausforderungen und Massnahmen der Schweizer Sägewerke nach einem grossen Sturm/Windwurf?, (ii) Wie unterscheiden sich diese Herausforderungen und Massnahmen je nach Grösse und Standort des Sägewerks? und (iii) Ist eine Anpassung der Sägewerke an Extremereignisse möglich, in Bezug auf Holzart, Produkte und erforderliche Infrastruktur?

bois-endommage

display_name: bois-endommage

chablis

display_name: chablis

damaged-wood

display_name: damaged-wood

marche-du-bois

display_name: marche-du-bois

sawmills

display_name: sawmills

scieries

display_name: scieries

stockage-humide

display_name: stockage-humide

wet-storage

display_name: wet-storage

wind-disturbance

display_name: wind-disturbance

wood-market

display_name: wood-market


en: wild-bee gardens species-composition functional-diversity community-assembly functional composition environmental-heterogeneity garden niche ground-beetles allotments allotment trait ground-beetle diversity species urban-ecology functional-traits bettergarden wild-bees bettergardens ecology urbanization niche-breadth

en: Urban carabid and bee species city of Zurich Switzerland

media_type: text/plain

en: Carabid beetle and wild bee occurrences in the city of Zurich, Switzerland, from the years (project) 2009 (BiodiverCity), 2011 (ENHANCE) and 2016 (BetterGardens).

format: TXT

en: Arthropod-databank query used to access data.

format: SERVICE

en:
Carabid beetle and wild bee occurrences in the city of Zurich, Switzerland.

Dataset available upon request (An agreement between the data provider and the data recipient is necessary).

allotment

display_name: allotment

allotments

display_name: allotments

bettergarden

display_name: bettergarden

bettergardens

display_name: bettergardens

community-assembly

display_name: community-assembly

composition

display_name: composition

diversity

display_name: diversity

ecology

display_name: ecology

environmental-heterogeneity

display_name: environmental-heterogeneity

functional

display_name: functional

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

garden

display_name: garden

gardens

display_name: gardens

ground-beetle

display_name: ground-beetle

ground-beetles

display_name: ground-beetles

niche

display_name: niche

niche-breadth

display_name: niche-breadth

species

display_name: species

species-composition

display_name: species-composition

trait

display_name: trait

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

wild-bee

display_name: wild-bee

wild-bees

display_name: wild-bees

en: The origin of urban communities: from the regional species pool to community assemblages in city


en: tree-ring-width dendrochronology stable-isotopes long-term-forest-ecosystem-research dominant-trees icp-forests swiss-forest-lab

en: Data Request

en:
Two stem core samples of 10 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 10 pre-dominant or dominant trees.

 Purpose:

N and C stable isotope signals

 Paper Citation:

 * Tomlinson, G., Siegwolf, R.T.W., Buchmann, N., Schleppi, P., Waldner, P., Weber, P., 2014. The mobility of nitrogen across tree-rings of Norway spruce (Picea abies L.) and the effect of extraction method on tree-ring d15N and d13C values. Rapid Commun. Mass Spectrom. 28, 1258-1264.

dendrochronology

display_name: dendrochronology

dominant-trees

display_name: dominant-trees

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

stable-isotopes

display_name: stable-isotopes

swiss-forest-lab

display_name: swiss-forest-lab

tree-ring-width

display_name: tree-ring-width

educ

en: Education, culture and sport

en: Dendrochronological analyses of tree core samples (IsoN) adjacent to LWF sites


maintainer: Armin Sigmund

en: backward-trajectories isotopic-distillation antarctica stable-water-isotopes snow-sublimation evaporation lagrangian-analysis

en: Data

en: Modeled data including the data shown in the figures of the related research article

en: Python scripts for data visualization

en: Scripts for generating the figures of the related research article and generating the data files (csv) from the model output

en: Model code

en: Model Sublimation and Model Air Parcel (python scripts)

en: Readme

en: Meta data

en:
 Summary

This data set contains Python programming code and modeled data discussed in a related research article. We developed a simple isotope model to study the drivers of the particularly depleted vapour isotopic composition measured on the ship of the Antarctic Circumnavigation Expedition close to the outlet of the Mertz glacier, East Antarctica, in the 6-day period from 27 January 2017 to 1 February 2017. The model considers the stable water isotopologues H2(16O), H2(18O), and HD(16O). It uses data from the ERA5 reanalysis product with a spatial resolution of 0.25° x 0.25° (Hersbach et al., 2018) and 10-day backward trajectories for the location of the ship, published by Thurnherr et al. (2020a). Our data set includes the model code, Python scripts for visualizing the results, and data produced by the model including the results shown in the figures of the related research article. Here, we summarize the most important model characteristics while further details can be found in the readme.txt file and the related research article including its supporting information.

 Main model characteristics

The modeling approach consists of two steps called *Model Sublimation* and *Model Air Parcel*. The former estimates the isotopic compositions of the snow and sublimation flux across the Antarctic Ice Sheet using an Eulerian frame of reference while the latter models the vapour isotopic composition and specific humidity along air parcel trajectories using a Lagrangian frame of reference. The isotope effects of most phase changes are represented by equilibrium fractionation. Only for ocean evaporation, kinetic fractionation is additionally taken into account (original Craig-Gordon formula). For snow sublimation, two assumptions are tested: *Run E* assumes that sublimation is associated with equilibrium fractionation while *Run N* assumes that sublimation occurs without isotopic fractionation.

 Model Sublimation
Model Sublimation uses a simple one-dimensional mass-balance approach in each grid cell, considering snow accumulation due to snowfall and vapour deposition and snow ablation due to sublimation. The snowpack is represented by 100 layers of equal thickness (e.g., 1 cm) and density (350 kg m-3). The isotopic composition of snowfall is parameterized by generalizing a site-specific, empirical relationship between the daily mean air temperature and snowfall isotopic composition. In the case of vapour deposition, Model Sublimation assumes equilibrium fractionation and estimates the isotopic composition of the atmospheric vapour as the average value for two idealized situations: (i) locally sourced vapour which has the same isotopic composition as the sublimation flux; (ii) non-locally sourced vapour in isotopic equilibrium with snowfall. Model Sublimation is run with a time step of 1 h, independently of Model Air Parcel.

 Model Air Parcel
Every hour, an ensemble of trajectories arrives at different heights in the ABL above the ship. For each of these trajectories, we consider an air parcel with a constant volume of 1 x 1 x 1 m3. The air parcels are initialized at the first suitable time when the trajectories are located in the ABL, either over the ice-free ocean in conditions of evaporation or over snow (Antarctic Ice Sheet or sea ice). Subsequently, the masses of the water isotopologues in the air parcels are simulated with a time step of 3 h, considering vapour uptake or removal due to the moisture flux at the snow or liquid ocean surface (only if the parcel is in the ABL) and cloud/precipitation formation (if the saturation specific humidity is reached). Sea ice is taken into account in a very simplified way. We represent the sea ice by grid cells with a sea-ice cover of more than 90% and assume the isotopic composition of the sublimation flux to be identical to that in the nearest grid cell of the Antarctic Ice Sheet. The isotopic composition of the sublimation flux is taken from Model Sublimation whereas the isotopic composition of the vapour deposition flux (over snow) and condensation flux (over ice-free ocean) is simulated assuming an isotopic equilibrium with the air parcel. Isotope effects of cloud/precipitation formation are represented using the classic Rayleigh distillation model with equilibrium fractionation, where the cloud water is assumed to precipitate immediately after formation.

 References

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horanyi, A., Munoz Sabater, J.,... others (2018). *ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)*. doi: 10.24381/cds.bd0915c6

Thurnherr, I., Wernli, H., & Aemisegger, F. (2020a). *10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017*. Zenodo. doi: 10.5281/zenodo.4031705

antarctica

display_name: antarctica

backward-trajectories

display_name: backward-trajectories

evaporation

display_name: evaporation

isotopic-distillation

display_name: isotopic-distillation

lagrangian-analysis

display_name: lagrangian-analysis

snow-sublimation

display_name: snow-sublimation

stable-water-isotopes

display_name: stable-water-isotopes

envidat

en: EnviDat: the Environmental Data Portal

en: Modeled Isotopic Composition of Water Vapour Along Air Parcel Trajectories in the Antarctic


foliar-analyses-lwf

title_for_slug: foliar-analyses-lwf

en: swiss-forest-lab foliar-analyses long-term-forest-ecosystem-research tree-nutrition icp-forests

en:
Foliage has been sampled every two years since 1995/1997 on 5-6 trees of the main species on all LWF plots. Concentrations of macronutrients (N, P, K, Ca, Mg, S), carbon (C) and micronutrients are determined on leaves and current and previous year needles. The dry mass of 100 leaves or 1000 needles is determined as well.

 Purpose:

To assess the nutrient status of the forest stands and detect possible deficiencies or imbalances, which are often indicative of processes at the ecosystem level.

 Manual Citation:

 * Brang, P., Hug, C., Thimonier, A., Zehnder, U., 1997. Kapitel D1.5 Nährstoffversorgung von Nadeln und Blättern, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-12.

 * Rautio P, Fürst A, Stefan K, Raitio H, Bartels U, 2016: Part XII: Sampling and Analysis of Needles and Leaves. 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,  19  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)

 Paper Citation:

 * Thimonier A, Graf Pannatier E, Schmitt M, Waldner P, Walthert L, Schleppi P, Dobbertin M, Kräuchi N (2010) Does exceeding the critical loads for nitrogen alter nitrate leaching, the nutrient status of trees and their crown condition at Swiss Long-term Forest Ecosystem Research (LWF) sites?. European Journal of Forest Research, 129 (3): 443-461. [doi: 10.1007/s10342-009-0328-9](http://doi.org/10.1007/s10342-009-0328-9)

foliar-analyses

display_name: foliar-analyses

tree-nutrition

display_name: tree-nutrition

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: Foliar analyses LWF


en: magerrasen dry-grasslands sentinel milieux-naturels fens typoch distribution-models schweiz bogs remote-sensing fettwiesen lebensraum trockenrasen lebensraumkarte flachmoore

en: Map for TypoCH 2.3.1 (Molinion)

en:
Probability of occurrence for *Molinion* (TypoCH 2.3.1) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.5.3 (Cynosurion)

en:
Probability of occurrence for *Cynosurion* (TypoCH 4.5.3) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en:
Countrywide ensemble maps of the 20 grassland habitat types

(1) Median predicted probability of occurrence

(2) Standard deviation of predicted probability of occurrence

(3) Presence/Absence map

en: Map of the most likely grassland habitat type

en:
Final combined map of the most likely grassland habitat type (i.e., after regional corrections) at 10x10 m resolution

Coordinate System: CH1903+_LV95

Value:	    TypoCH     Name
1:           2.2.1       *Magnocaricion* + *Cladetium*
2:           2.2.2       *Caricion fuscae*
3:	 2.2.3	*Caricion davallianae*
4:	 2.3.1	*Molinion	*
5:	 2.3.2/3	*Calthion* + *Filipendulion*
6:	 2.4.1	*Sphagnion magellanici *
7:	 4.0.2	Re-seeded and heavy fertilized grassland/Kunstrasen
8:	 4.2.1/2/3	*Stipo-Poion*, *Xerobromion*, *Diplachnion*
9:	 4.2.4	*Mesobromion *
10:	 4.3.1	*Seslerion*
11:	 4.3.2/4	*Caricion firmae* + *Elynion*
12:	 4.3.3	*Caricion ferrugineae*
13:	 4.3.5	*Nardion*
14:	 4.3.6	*Festucion variae*
15:	 4.3.7	*Caricion curvulae*
16:	 4.5.1	*Arrhenatherion*
17:	 4.5.2	*Polygono-Trisetion*
18:	 4.5.3	*Cynosurion*
19: 4.5.4	*Poion alpinae*
20: 	 4.6	Fallow grassland/Grasbrachen

en: Map for TypoCH 2.3.2/3 (Calthion + Filipendulion)

en:
Probability of occurrence for *Calthion* (TypoCH 2.3.2) and *Filipendulion* (TypoCH 2.3.3) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.2.4 (Mesobromion)

en:
Probability of occurrence for *Mesobromion* (TypoCH 4.2.4) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en:
Map of the second most likely grassland habitat type at 10x10 m resolution; Coordinate System: CH1903+_LV95

Value:	 TypoCH  Name
1:  2.2.1  *Magnocaricion* + *Cladetium*
2:  2.2.2  *Caricion fuscae*
3:	 2.2.3	*Caricion davallianae*
4:	 2.3.1	*Molinion	*
5:	 2.3.2/3	*Calthion* + *Filipendulion*
6:	 2.4.1	*Sphagnion magellanici *
7:	 4.0.2	Re-seeded and heavy fertilized grassland/Kunstrasen
8:	 4.2.1/2/3	*Stipo-Poion*, *Xerobromion*, *Diplachnion*
9:	 4.2.4	*Mesobromion *
10:	 4.3.1	*Seslerion*
11:	 4.3.2/4	*Caricion firmae* + *Elynion*
12:	 4.3.3	*Caricion ferrugineae*
13:	 4.3.5	*Nardion*
14:	 4.3.6	*Festucion variae*
15:	 4.3.7	*Caricion curvulae*
16:	 4.5.1	*Arrhenatherion*
17:	 4.5.2	*Polygono-Trisetion*
18:	 4.5.3	*Cynosurion*
19: 4.5.4	*Poion alpinae*
20: 	 4.6	Fallow grassland/Grasbrachen

en: Map for TypoCH 4.3.1 (Seslerion)

en:
Probability of occurrence for *Seslerion* (TypoCH 4.3.1) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 2.2.3 (Caricion davallianae)

en:
Probability of occurrence for *Caricion davallianae* (TypoCH 2.2.3) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.2.1/2/3 (Stipo-Poion/Cirsio-Brachypodion/Xerobromion)

en:
Probability of occurrence for *Stipo Poion* (TypoCH 4.2.1.1), *Cirsio-Brachypodion* (TypoCH 4.2.1.2), *Xerobromion* (TypoCH 4.2.2) and *Diplachnion* (TypoCH 4.2.3) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.3.7 (Caricion curvulae)

en:
Probability of occurrence for *Caricion curvulae* (TypoCH 4.3.7) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.3.5 (Nardion)

en:
Probability of occurrence for *Nardion* (TypoCH 4.3.5) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Overview: individual grassland habitats in the combined map

media_type: application/pdf

en:
Overview of the occurrence of the individual habitat types in the combined map (M1F):

For each grassland habitat type, its predicted occurrence is shown per elevation, slope, aspect and biogeographic region.

format: PDF

en: Map for TypoCH 4.5.1 (Arrhenatherion)

en:
Probability of occurrence for *Arrhenatherion* (TypoCH 4.5.1) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.6 (Fallow/Abandoned grassland)

en:
Probability of occurrence for fallow/abandoned grasslands (TypoCH 4.6) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: List of modelled grassland habitat types

en:
List of the 20 grassland habitat types modelled

Attributes: TypoCH, Modelled, Latin, Français, Deutsch, Italiano, English

en: Map for TypoCH 4.5.2 (Polygono-Trisetion)

en:
Probability of occurrence for *Polygono-Trisetion* (TypoCH 4.5.2) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 2.3.2/4 (Caricion firmae + Elynion)

en:
Probability of occurrence for *Caricion firmae* (TypoCH 4.3.2) and *Elynion* (TypoCH 4.3.4) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.3.3 (Caricion ferrugineae)

en:
Probability of occurrence for *Caricion ferrugineae* (TypoCH 4.3.3) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.5.4 (Poion alpinae)

en:
Probability of occurrence for *Poion alpinae* (TypoCH 4.5.4) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 2.4.1 (Sphagnion magellanici)

en:
Probability of occurrence for *Sphagnion magellanici* (TypoCH 2.4.1) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 2.2.1 (Magnocaricion + Cladietum)

en:
Probability of occurrence for *Magnocaricion* and *Cladietum* (TypoCH 2.2.1) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 4.3.6 (Festucion variae)

en:
Probability of occurrence for *Festucion variae* (TypoCH 4.3.6) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en: Map for TypoCH 2.2.2 (Caricion fuscae)

en:
Probability of occurrence for *Caricion fuscae* (TypoCH 2.2.2) as predicted by the ensemble models

Values: 0-1000 corresponding to probabilities of occurrence from 0-1

Coordinate System: CH1903+_LV95

Spatial resolution: 10x10m

Remarks: No masking applied to remove non-grassland areas such as forested areas, etc.

en:
We modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances according to the Swiss habitat typology (TypoCH; Delarze et al. 2015) at 10x10 m resolution across Switzerland. The 20 grassland habitat types belong to the following habitat groups: fens, wet meadows, raised bogs, re-seeded and heavy fertilized grasslands, dry grasslands, nutrient-poor alpine and subalpine grasslands, nutrient-rich pastures and meadows as well as fallow grasslands.

We followed a two-step approach:

(1) Ensemble models provide **distribution maps of the 20 individual grassland habitat types**, using training data from various sources. Predictors were Copernicus Sentinel satellite imagery and variables describing climate, soil and topography. The performance of these maps was assessed with the True Skill Statistics and split‐sampling of the data.

Available maps for each grassland habitat: (1) *Map of the median of predicted probability of occurrence*; (2) *Map of the standard deviation of the predicted probability of occurrence* (available upon request); (3) *Binary presence/absence map* (available upon request). For an overview, see *Overview: Maps of the individual grassland habitats*.

(2) **Combined maps**: The individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys.

Available combined maps: Map of the most likely habitat type (M1F; after regional corrections); Map of the second most likely habitat type (M2); Map of the most likely habitat type without regional corrections (available upon request); Map of the weighted median of the predicted probability of occurrence for the most/second most likely habitat type, respectively (available upon request); map of the ratio of the probabilities of occurrence of the most and second most likely habitat types (available upon request)

bogs

display_name: bogs

distribution-models

display_name: distribution-models

dry-grasslands

display_name: dry-grasslands

fens

display_name: fens

fettwiesen

display_name: fettwiesen

flachmoore

display_name: flachmoore

lebensraum

display_name: lebensraum

lebensraumkarte

display_name: lebensraumkarte

magerrasen

display_name: magerrasen

milieux-naturels

display_name: milieux-naturels

remote-sensing

display_name: remote-sensing

en: Distribution maps of permanent grassland habitats for Switzerland


maintainer: EnviDat Support

en: nfi-photos visual-attractiveness adults-and-teenagers online-questionnaire-survey perception-of-ecosystem-services

en: Dataset in csv-format

media_type: text/csv

format: CSV

mimetype: text/csv

en: Questionnaire French

en: Codebook to SPSS-file

mimetype: application/pdf

en: Questionnaire German

en: SPSS-Dataset

en: Questionnaire Italian

en: This questionnaire survey was conducted as an online survey and aimed at investigating the relationship between physical forest characteristics, visual attractiveness of forest and the perception of ecological and cultural ecosystem services in urban forests. Each participant was shown 6 photos out of a pool of 50 photos taken from the Swiss National Forest Inventory (NFI) database. Physical forest characteristics were derived from the photos. The study was conducted as part of the "WaMos meets LFI" (WML) project.

adults-and-teenagers

display_name: adults-and-teenagers

nfi-photos

display_name: nfi-photos

online-questionnaire-survey

display_name: online-questionnaire-survey

perception-of-ecosystem-services

display_name: perception-of-ecosystem-services

visual-attractiveness

display_name: visual-attractiveness

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Relationship between physical forest characteristics, visual attractiveness and perception of ecosystem services in urban forests


snow-drift-station-flowcapt

maintainer: Benjamin Walter

title_for_slug: snow-drift-station-flowcapt

en: flowcapt raclets acoustic-mass-flux wind-speed snowdrift snow-blowing

en: maximum mass flux

en: The data file contains the maximum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: minimum mass flux

en: The data file contains the minimum mass flux of 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: average wind speed

en: The data file contains the average wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: avergaged mass flux

en: Average mass flux of 10 min measurement interval. The Cycle duration is 1 min which includes 6 s observation and 54 s stand-by. The time is given in UTC+1.

en: minimum wind spees

en: The data file contains the minimum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6s observations and 54 s stand-by. The time is given in UTC+1.

en: maximum wind speed

en: The data file contains the maximum wind speed in 10 minute intervalls. The duration of one cycle was 1 min and contained 6 s observations and 54 s stand-by. The time is given in UTC+1.

en: The FlowCapt is an ultra-robust instrument measuring solid particle acoustic mass - flux intensities (g m‾ ² s‾ ¹) and wind speeds (m s‾ ¹). It was deployed at Gotschnagrat (LON: 46.859 LAT: 9.849). The vertical tube with a length of 1 m monitors snowdrift and snow-blowing; and is mounted at a height between 0.1 an 1.1 m above snow surface. The time within each data set is given in UTC+1.

acoustic-mass-flux

display_name: acoustic-mass-flux

flowcapt

display_name: flowcapt

raclets

display_name: raclets

snow-blowing

display_name: snow-blowing

snowdrift

display_name: snowdrift

wind-speed

display_name: wind-speed

en: Snow Drift Station - Flowcapt


en: rcm cryosphere software downscaling toposcale cordex

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.

cordex

display_name: cordex

cryosphere

display_name: cryosphere

downscaling

display_name: downscaling

rcm

display_name: rcm

software

display_name: software

toposcale

display_name: toposcale

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: TopoCLIM v1.1 code


en: picea-abies insect-outbreaks windthrow castanea-sativa pinus-sylvestris national-forest-inventory disturbance tree-recruitment switzerland drought vegetation-shift

en: Site Information

en:
File containing the information on parameters of the 5521 National forest inventory sites recorded during the NFI2 and NFI4.

CLNR = Number of site in the National Forest Inventory
INVNR = Information on which National Forest Inventory
Elevation = Elevation above sea level
Perc_Conifers = Proportional contribution of Conifer species to the total basal area of a site
DominantTreeSp = Dominant tree taxa of a site as defined by maximum basal area contribution
DMGTYP = Type of damage observed between NFI2 and NFI4 (up to four observations possible)
DMGYEAR = In case a DMGTYPE event was observed here is the corresponding year marked.
BioReg = Biogeographic region of the site
Ggrob = NaiS site type (Potential natural forest vegetation of a site)
DisturbanceType = Type of disturbance recorded on the site between NFI2 and NFI4.

en: R-Scripts for Figures and Data tables

en:
This archive contains the R-Scripts to reproduce the Figures 2-4, S1-S4 and the data tables S4-S10 in the associated publication.

Scherrer, D., Ascoli, D., Conedera, M., Fischer, C., Maringer, J., Moser, B., . . . T., W. (2021). Canopy disturbances catalyse tree species shifts in Swiss forests. Ecosystems, in revision.

en: ReadMe

en: A detailed description of the data.

en: Species-specific biomass per NFI site

en:
File containing the information about taxa-specific basal area, sapling density and polestage density for the different National Forest Inventory sites during NFI2 (1993-1995) and NFI4 (2009-2017).

INVNR = Information on which National Forest Inventory
CLNR = Number of site in the National Forest Inventory
Species = Information on the species
BA = basal area per hectare
Sapling = Sapling (< 4 cm DBH) density as stems per hectare
Polestage = Polestage (DBH 4 - 11.9 cm) density as stems per hectare

en:
The files refer to the data used in Scherrer et al. (2021) "Canopy disturbances catalyse tree species shifts in Swiss forests" in _Ecosystems_.

The two data files contain information about site factors (e.g. disturbance events, dominant tree species, elevation) and species-specific biomass of 5521 plots of the Swiss National Forest Inventory visited during the second (NFI2 1993-1995) and fourth (NFI4 2009-2017) inventory.
In addition, we provide all the R-scripts necessary to reproduce the Figures and data tables of the related publication.

For more detailed information about the data files please check the ReadMe.docx file.

castanea-sativa

display_name: castanea-sativa

disturbance

display_name: disturbance

drought

display_name: drought

insect-outbreaks

display_name: insect-outbreaks

national-forest-inventory

display_name: national-forest-inventory

picea-abies

display_name: picea-abies

pinus-sylvestris

display_name: pinus-sylvestris

switzerland

display_name: switzerland

tree-recruitment

display_name: tree-recruitment

vegetation-shift

display_name: vegetation-shift

windthrow

display_name: windthrow

en: Effects of canopy disturbance on Swiss forests


en: snow-avalanche experiment snow-mechanics dynamic-crack-propagation crack-propagation propagation-saw-test

en: SNOWPACK modelling

en: The snow cover model SNOWPACK (version 3.60) was used to simulate the evolving snow stratigraphy at our field site. The model was driven with data from an automatic weather station which was located 100m next to the field site (FLS_bunker_snowpack.smet). The SNOWPACK initiation file (FLS_bunker_snowpack.ini) contains the selected model parameters that result in the modeled snow stratigraphy (FLS_bunker_snowpack.pro).

en: Snowpack data and crack propagation characteristics

en: Snowpack data includes the elastic modulus (stiffness properties) of the slab, the elastic modulus of the weak layer, and the specific fracture energy of the weak layer determined with a homogeneous and a layered slab model. During crack propagation, we measured the crack speed, touchdown distance, crack arrest length and energy dissipation due to compaction and dynamic fracture.

en: Videos of crack propagation

en: The videos show the cracking process in the 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: Sustained crack propagation index

en: Index of self-sustained crack propagation SSP (ssp_measured.xlsx) with time. The self-sustained crack propagation index SSP was also modelled for simulated snow stratigraphy (ssp_modelled.xlsx) using crack speed and critical cut length parameterizations from Heierli (2005) and Richter et al. (2019), respectively.

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

Bergfeld, B., van Herwijnen A., Bobillier, G., Rosendahl P., Weißgraeber P., Adam V., Dual, J., and Schweizer, J.: Temporal evolution of crack propagation characteristics in a weak snowpack layer: conditions of crack arrest and
sustained propagation, Natural Hazards and Earth System Sciences, 23, 293-315, https://doi.org/10.5194/nhess-23-293-2023, 2023.

We performed a series of propagation saw test experiments, up to ten meters long, over a period of 10 weeks and analyzed these using digital image correlation techniques. We derived the elastic modulus of the slab, the elastic modulus of the weak layer and the specific fracture energy of the weak layer with a homogeneous and a layered slab model. During crack propagation, we measured crack speed, touchdown distance and the energy dissipation due to compaction and dynamic fracture. Our data set provides unique insight and valuable data to validate models.

crack-propagation

display_name: crack-propagation

dynamic-crack-propagation

display_name: dynamic-crack-propagation

experiment

display_name: experiment

propagation-saw-test

display_name: propagation-saw-test

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics

en: Time series data on dynamic crack propagation in long propagation saw tests


en: ecological-indicator-values landolt plants soil-mapping ecological-maps switzerland soil-moisture soil-ph

en: Description

en: Description of the predictors provided in this dataset

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


mortality

title_for_slug: mortality

en:
Volume of stemwood with bark of all trees and shrubs starting at 12 cm dbh that died or disappeared between two inventories, but were not cut. *In the calculation no D7/tree height data were used. The values calculated like this have not been corrected for bias, but allow for cantons or forest districts a more robust estimation of changes and could thus be better interpreted.

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

canton

display_name: canton

mortality-star

display_name: mortality-star

ownership

display_name: ownership

en: Mortality*


en: topography cryowrf antarctica wrf landuse

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

en: REMA topography and AntarcticaLC2000 for WRF


en: species-richness bryophytes nature-conservation vascular-plants habitat-area extinction-debt habitat-fragmentation wetlands

en: Wetlands of the canton of Zürich (Switzerland): Data on species richness and recent and historic area and connectivity of 55 fens.

en:
The data provided in the Excel sheet contain the following information for 55 wetlands of the canton of Zürich (Switzerland):
-Species richness data for vascular plants and bryophytes classified as follows: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species.
-Area of all wetlands in 1850, 1900, 1950 and 2000
-Wetland area within buffers with 2km radius with the center of the wetland as starting point
-Mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.

en:
This dataset includes data on species richness of vascular plants and bryophytes in 55 wetlands of the canton of Zürich (Switzerland) as well as recent and historic data on the area and connectivity of these 55 wetlands and was used for the paper Jamin A., Peintinger M., Gimmi U., Holderegger R., Bergamini A. (2020) Evidence for a possible extinction debt in Swiss wetland specialist plants. Ecology and Evolution.
Species richness data are available for vascular plants and bryophytes. The field survey was carried out between June 5 and August 10, 2012. The survey covered all wetland (fen) types in the canton of Zürich. For data collection, at least half a day per wetland was spent searching for species. Within each wetland all different vegetation types were covered until no new species were found to get as complete species lists as possible. In the Excel file information on species richness of the following groups is provided: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species. Specialist vascular plant species included all characteristic species listed in Appendix 1a of the wetland inventory of Switzerland (BUWAL, 1990).
Based on the data of Gimmi et al. (2011), the area of all wetlands in 1850, 1900, 1950 and 2000 were determined as well as the wetland area within buffers 2km in radius with the center of the wetland as starting point. These data are also provided in the Excel sheet.
Moreover, for each wetland mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants were calculated and are provided in Excel sheet. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.

bryophytes

display_name: bryophytes

extinction-debt

display_name: extinction-debt

habitat-area

display_name: habitat-area

habitat-fragmentation

display_name: habitat-fragmentation

nature-conservation

display_name: nature-conservation

species-richness

display_name: species-richness

vascular-plants

display_name: vascular-plants

wetlands

display_name: wetlands


en: meteo-station ground-temperature depth-of-snowfall swiss-alps climate-change-impact

en: GenPSUm

en:
GenPSUm contains Files to get the complete precipitation set:

1. MeteoData.ini: Ini file for MeteoIO to get the met. input data. It has to be run two times, to get prec. Data from Imis 	stations and from ANETZ regressions.

2 GenPSUM.ini: Inifile for Snowpack (in research mode), to get winter precipitation calculated by snowpack out of the snow hight measurements.
	In:_sno contain the soil profils for the station
	In_met contains the meterological input data. It's from the data base and MeteoData.ini is used to get it.

3. The folder R_programms contains the R sripts to generate the precipitation data set, it reads in IMIS, ANETZ and SNOWPACK precipi and makes one complet data set out of it. (it contains the function- script plus a script to use the function)

en: SNOWPACK climate change simulation files

en: This folder contains SNOWPACK INI-files for snowpack, soil profiles, and input data for climate change modeling.

en: R-Script

en: The Folder R- Script contains, the R files to create the Climate Change input and the Data for the WFJ- Modeling.

en: Precipitation datasets

en:
This folder contains 16 ideal precipitation data sets for IMIS stations.

*Updated documentation 24 August 2020:*

1. Datasets have been filtered for unphysical values using a MeteoIO min/max tool, however spikes still exist that pass this filter yet appear to be outliers, no further manual filtering was applied.
2. Data prior to 2009 can have large data gaps in certain stations. This is documented in the accompanying publication and was not used for simulations.
3. GUT2 was erroneously filtered during summer periods. This does not affect published snow modelling results but summer (Jun-Oct) values of 8.25 should not be used and filtered prior to use. This affects 4759 summer values or 1.2% of the time-series.

en:
This dataset includes all data and simulation files presented in the publication: Bender et al. 2020. Changes in climatology, snow cover and ground temperatures at high alpine locations, DOI: 10.3389/feart.2020.00100.

This includes:

* meteorological forcing,
* climate change timeries and
* simulation files together with
* snow depth
* ground temperature

Please refer to the following publication for further details which should be cited when using this dataset:

Bender et al. 2020. Changes in climatology, snow cover and ground temperatures at high alpine locations, DOI: 10.3389/feart.2020.00100.

climate-change-impact

display_name: climate-change-impact

depth-of-snowfall

display_name: depth-of-snowfall

ground-temperature

display_name: ground-temperature

meteo-station

display_name: meteo-station

swiss-alps

display_name: swiss-alps

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Changes in climatology, snow cover and ground temperatures at high alpine locations in Switzerland (Bender et al. 2020)


ect-and-rb-data-switzerland

title_for_slug: ect-and-rb-data-switzerland

en: slope-stability stability-test ect snow-stability rutschblock

en: data set (update)

en:
This is the same data set as uploaded originally, except for the following three additional columns, which are required to replicate the respective classification of ECT results: *depthCriteriaDecisive_ectStabOrig*, *depthCriteriaDecisive_ectStabWinkler*, *depthCriteriaDecisive_ectStabNew*. These columns have the following values:
- 1 if the depth criteria as defined in the paper was decisive for rating the ECT result with stability class 4
- 0 if the depth of the fracture plane was not decisive for the stability classification

In addition, the stability class has been recoded for:
- *ectStabOrig* from [1, 2] to [1, 4]
- *ectStabWinkler* from [1, 2, 3] --> [1, 2.5, 4]
to be fully in line with the stability classes used in the paper.

en: data set

en:
The data set contains the following information. For details, refer to the publication:
Variables
- unique identifier for the snow pit location (profileID)
- unique identifier for the ECT stability test (stabTestID)
- ECT stability classifications
-- orginal (ectStabOrig)
-- Winkler and Schweizer (ectStabWinkler)
-- new (ectStabNew)
- ECT results
-- lowest number of taps (ectScoreMin) for the decisive propagation
-- propagation
- slope stability information (slopeStability 0 = stable, 1 = unstable)
- RB stability class
- forecast avalanche danger level (forecastDangerLevel)

en: The data set contains the data used in the publication "On snow stability interpretation of Extended Column Test results" by Techel et. al. (2020), published in Natural Hazards Earth System Sciences.

ect

display_name: ect

rutschblock

display_name: rutschblock

slope-stability

display_name: slope-stability

snow-stability

display_name: snow-stability

stability-test

display_name: stability-test

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: ECT and RB data Switzerland


high-resolution-climate-data-for-europe

title_for_slug: high-resolution-climate-data-for-europe

en: cordex daily-climate maximum-temperature eur11 minimum-temperature precipitation air-temperature europe

en: Data Access

en: CHELSA EUR11 Technical Documentation

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.

The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation

en: High resolution climate data for Europe


maintainer: Axel Volkwein

en: mass-movements experiments field-tests trajectory field-test natural-hazards rockfall experiment field-data

en: Jumps and impacts

en: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

en: Overview of all tests

en:
This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en: Block trajectories recorded from local positioning system

en: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.

An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.

The dataset contains all data that were gathered through above field campaign.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

trajectory

display_name: trajectory

educ

en: Education, culture and sport

en: Repetitive trajectory testing in Tschamut 2014


swiss-canopy-crane-ii-research-site

title_for_slug: swiss-canopy-crane-ii-research-site

en: swiss-forest-lab climate-change drought forest ecosystem-functions infrastructure damage-of-tree

en: Link to website

en: Research site metadata

en: Swiss Canopy Crane II

en:
![alt text](https://www.envidat.ch/dataset/fc69e369-eee9-42ab-8486-d2c38cff317d/resource/68fa7065-de32-4343-aa26-71094c5254ae/download/sccii.jpg "Swiss Canopy Crane II")

This research site is located near Hölstein in Canton Basel-Landschaft in a mature temperate forest that harbours more than 400 trees from 14 different species. The 1.6 ha site is equipped with the latest infrastructure, including 60 automated point dendrometers, automated soil respiration chambers, 72 ceramic suction cups at various locations and depths across the site, and a range of automated environmental sensors in the soil, the forest floor and in the canopy. A key piece of infrastructure is the new Swiss Canopy Crane II (SCC II), a 50 m tall crane with a 50 m jib that provides canopy access to 250 trees from 12 different species.

climate-change

display_name: climate-change

damage-of-tree

display_name: damage-of-tree

drought

display_name: drought

ecosystem-functions

display_name: ecosystem-functions

forest

display_name: forest

infrastructure

display_name: infrastructure

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: Swiss Canopy Crane II research site


maintainer: Rebecca Mott

en: riegl-vz6000 patchy-snow-covers terrestrial-laser-scanning tls snow-ablation-rates

en: Snowmask 2014

en: Digital Elevation Modell 2014

en: Snowmask 2016

en: Digital Elevation Modell 2015

en: Snowmask 2015

en: Gletschboden test site

en: Digital Elevation Modell 2016

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


en: strategic-planning governance planning-efficacy land-use-planning analytical-hierarchy-process

en: The present content is part of the published paper Palka, G., Oliveira, E., Pagliarin, S., & Hersperger, A. M. (2021). Strategic spatial planning and efficacy: an analytic hierarchy process (AHP) approach in Lyon and Copenhagen. European planning studies, 29(6), 1174-1192. It contains the jupyter notebook and sample data to compute Analytical Hierarchy Process, and a report on its use.

analytical-hierarchy-process

display_name: analytical-hierarchy-process

governance

display_name: governance

land-use-planning

display_name: land-use-planning

planning-efficacy

display_name: planning-efficacy

strategic-planning

display_name: strategic-planning

educ

en: Education, culture and sport

en: Planning efficacy computation based on AHP


maintainer: Jana von Freyberg

en: snowmelt-lysimeter solutes snowmelt-rate snowpack-outflow stable-water-isotopes

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

envidat

en: EnviDat: the Environmental Data Portal

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


en: avalanche-fatalities number-of-dead-persons number-of-caught-persons avalanche-accidents avalanche-accident-statistics

en: Fatal avalanche accidents in Switzerland since 1995-1996

en:
Attention: this data is not updated after 2022 anymore.
This data collection contains information concerning all accidents by snow avalanches causing at least one fatality in Switzerland. The data set commences on 01/10/1995. After the completion of a hydrological year, the new data is added.
The following information is provided:
 * avalanche identifier
 * date of the accident
 * accuracy of the date in range of days before and after
 * canton
 * name of the locality
 * start zone of the avalanche
  * coordinates (Swiss coordinate system, approximately in middle of start zone)
  * accuracy of the coordinates in meters
 * elevation (in meteres above sea level, app. in middle of start zone)
 * slope aspect (main orientation of start zone)
 * slope inclination (in degree, steepest point within start zone)
 * number of dead persons
 * number of caught persons
 * number of fully buried persons
 * forecasted avalanche danger level
 * activity/location of the accident party at the time of the incident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

number-of-caught-persons

display_name: number-of-caught-persons

number-of-dead-persons

display_name: number-of-dead-persons

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-height snow-depth parallel-measurements snow-onset-and-disappearance-dates climate-indicators

en: ReadMe

en: File containing information about variables used in this data set

en: snow climate indicators

en: Snow climate indicators derived from parallel manual snow measurements

en: Sdur

en: Potential sunshine duration during MA and mean snow disappearance dates for a selection of station pairs.

en: Data set consisting of snow climate indicators derived from parallel manual snow measurements in Switzerland.

climate-indicators

display_name: climate-indicators

parallel-measurements

display_name: parallel-measurements

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height

snow-onset-and-disappearance-dates

display_name: snow-onset-and-disappearance-dates


irkis-soil-moisture-measurements-davos

maintainer: Nander Wever

title_for_slug: irkis-soil-moisture-measurements-davos

en: davos meteo-station soil-moisture dischma-catchment meteorological-measurements

en: IRKIS soil moisture data (zip file)

en: Compressed archive (zip) containing soil moisture measurements, as well as meteorological measurements and interpolated meteorological time series.

en:
Meteorological and soil moisture measurements from soil moisture stations installed from October 2010 - October 2013 in the area surrounding Davos, in particular in the Dischma catchment.

There are in total 7 stations: 1202, 1203, 1204, 1205, 222, 333 and SLF2. For each of the stations, there is a:

* vwc_[stn].smet: containing the soil moisture measurements

* station_[stn].smet: in-situ measured meteorlogical parameters. Note, the quality of these measurements for stations 1202, 1203, 1204 and 1205 is very low, with data gaps. Use this data with care. For stations 222, 333 and SLF2, data quality is high and only the default cautiousness should be applied.

* interpolatedmeteo_[stn].smet contains per stations a dataset derived by interpolating from several stations in the Davos area to the stations location. This dataset was generated from the output of the Alpine3D model, of which simulations are presented in the Wever et al. (2017) manuscript.

At the soil moisture measurement sites, Decagon 10HS sensors were installed, at 10, 30, 50, 80 and 120 cm depth. Per depth 2 sensors were installed, labelled A and B in the datafiles. Note that at stations 1203, 1204 and 1205, sensors were only installed at 10, 30 and 50 cm depth.

The files follow the SMET format: https://models.slf.ch/docserver/meteoio/SMET_specifications.pdf and metadata for the stations can be found in the header of the smet files.

Please cite the Wever et al. (2017) reference when using this data in publications.

For a more detailed description, please refer to: Wever, N., Comola, F., Bavay, M., and Lehning, M.: Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment, Hydrol. Earth Syst. Sci., 21, 4053-4071, https://doi.org/10.5194/hess-21-4053-2017, 2017.

davos

display_name: davos

dischma-catchment

display_name: dischma-catchment

meteo-station

display_name: meteo-station

meteorological-measurements

display_name: meteorological-measurements

soil-moisture

display_name: soil-moisture

educ

en: Education, culture and sport

en: IRKIS Soil moisture measurements Davos


en: raster-processing qgis-plugin swiss-geodata open-source seilaplan cable-yarding digital-planning digital-elevation-model geoinformation-system geodata-processing

en: DHM-Kacheln zusammenfügen

en: View video on youtube!

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to Seilaplan website: https://seilaplan.wsl.ch

***************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

envidat

en: EnviDat: the Environmental Data Portal

en: Seilaplan Tutorial: Merge DTM tiles


lwf-chironico-long-term-research-site

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

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

en: LWF plot Chironico. Photo: Anne Thimonier Rickenmann, 2019

en: Chironico Meteorological Data LWF

en:
![alt text](https://www.envidat.ch/dataset/67e14643-c7f2-4190-ae6e-c8c94f1c5f01/resource/1d23d53f-8572-47eb-b466-88dd8ad244c9/download/lwf_chironico.jpg "LWF Chironico")

LWF Plot Chironico

- Community: Chironico / canton TI
- Date of installation: 29 August 1995
- Size of the plot: 2 ha
- Altitude: 1342-1387 m
- Mean slope: 35%
- Geology (in German): Untergrund: Penninikum; Paragneisse u. Glimmerschiefer - Oberfläche: Quartär; karbonatfreie Moräne, Hängeschutt
- Provisional soil type (WSL) : Distric Cambisol
- Woodland association after EK72: 47: Calamagrostio villosae-Abietetum
- Main tree species: Picea abies
- Management system: high forest
- Silvicultural system: group selection
- Top-height diameter (quadratic average diameter of the 100 thickest trees per ha): 54.1 cm
- Number of trees BHD >= 12 cm (2011): 750
- Maximum tree age: Picea abies: 160-180 yr - Abies alba: 140-160 yr

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

forest

display_name: forest

infrastructure

display_name: infrastructure

lwf

display_name: lwf

meteorological-data

display_name: meteorological-data

plot

display_name: plot

swiss-forest-lab

display_name: swiss-forest-lab

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 Chironico long-term research site


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

en: Data plot of the forest station (LEB)

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

en: Site photo of the forest station (LEB)

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

mimetype: image/jpeg

en: Forest station data (LEB)

en: Data file.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for one meteorological station in Lens in Switzerland which is located within a natural coniferous forest with Scots pine (_Pinus sylvestris_; 150-170 yrs)) as dominant tree species. The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Lens is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind-speed

display_name: wind-speed

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


tree-ring-laser-ablation-data

maintainer: Paula Ballikaya

title_for_slug: tree-ring-laser-ablation-data

en: dendrochronology dendrochemistry tree-rings air-pollution laser-ablation

en: Laser ablation data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.

In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.

Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Tree-ring laser ablation data


en:
Sum of stem cross-section areas of all dead trees in a stand at a height of 1.3 m (dbh measurement height) recorded according to the NFI1 method.

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

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

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: Basal area of dead wood NFI1


maintainer: Ueli Reber

en: policy-analysis text-corpus bgb biodiversity environmental--policy policy-documents switzerland

en: Replication files

en:
 Introduction

The ZIP file contains all data and code to replicate the analyses reported in the following paper.

Reber, U., Fischer, M., Ingold, K., Kienast, F., Hersperger, A. M., Grütter, R., & Benz, R. (2022). Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics. *Policy Sciences*. [https://doi.org/10.1007/s11077-022-09456-4](https://doi.org/10.1007/s11077-022-09456-4)

If you use any of the material included in this repository, please refer to the paper. If you use (parts of) the text corpus, please also refer to the sources used for its compilation listed below. The content of the texts may not be changed.

 Data folder

The data folder contains the following files.

* _corpus.parquet_: Text corpus of Swiss policy documents
* _dict_de.csv_: Biodiversity dictionary (German)
* _dict_fr.csv_: Biodiversity dictionary (French)
* _dict_it.csv_: Biodiversity dictionary (Italian)
* _topic_labels.csv_: labels/codes for policy sectors
* _topics.csv_: labels/codes for policy sectors

The corpus and the dictionary were compiled by the authors specifically for this project. The labels/codes for policy sectors are based on the [coding scheme](http://ws-old.parlament.ch/affairs/topics) of the Swiss Parliament.

 Text corpus

The text corpus consists of 439,984 Swiss policy documents in German, French, and Italian from 1999 to 2018. The corpus was compiled from the following source between 2020-10-01 and 2021-01-31.

* Transcripts and parliamentary businesses (e.g. questions, motions, parliamentary initiatives) via the [Web Services (WS)](https://www.parlament.ch/de/%C3%BCber-das-parlament/fakten-und-zahlen/open-data-web-services) provided by the Swiss Parliament
* The official compilation of federal legislation ("Amtliche Sammlung", AS) via [opendata.swiss](https://opendata.swiss/de/dataset/official-compilation-of-federal-legislation-bs-as-1947-2018) provided by the Swiss Federal Archives (SFA)
* The federal gazette ("Bundesblatt") via [fedlex.admin.ch](https://www.fedlex.admin.ch/de/fga/index)
* Decisions of federal courts via [entscheidsuche.ch (ES)](https://entscheidsuche.ch/)

The corpus is stored in a single data frame to use with R saved as [PARQUET](https://parquet.apache.org/) file (corpus.parquet). The data frame has the following structure.

* _text_id_: Unique identifier for each text (source information as prefix, e.g. "t_")
* _doc_type_: Document type (see coding scheme below)
* _branch_: Government branche (1 legislative, 2 executive, 3 judicative)
* _stage_: Stage of policy process (1 drafting, 2 introduction, 3 interpretation)
* _year_: Year of publication
* _topic_: Policy sector (coding scheme in separate file in data folder)
* _lang_: Language (de, fr, it)
* _text_: Text

The following list contains the coding scheme for the doc_type variable.

* 101: Federal gazette // Draft for public consultation ("Vernehmlassungsverfahren")
* 102: Federal gazette // Explanation of draft for parliament ("Botschaft")
* 103: Federal gazette // Strategy, action plan
* 104: Federal gazette // Federal council decree ("Bundesratsbeschluss")
* 105: Federal gazette // (Simple) Federal decree ("(Einfacher) Bundesbeschluss")
* 106: Federal gazette // General decree ("Allgemeinverfügung")
* 107: Federal gazette // Treaty ("Übereinkommen")
* 108: Federal gazette // Treaty ("Abkommen")
* 109: Federal gazette // Draft for parliament ("Entwurf")
* 110: Federal gazette // Report ("Bericht")
* 111: Federal gazette // Report of parliamentary comission ("Bericht")
* 112: Federal gazette // Report of federal council ("Bericht")
* 201: Parl. businesses // Submitted text
* 202: Parl. businesses // Reason text
* 203: Parl. businesses // Federal council response
* 204: Parl. businesses // Initial situation
* 205: Parl. businesses // Proceedings
* 301: Parl. transcripts // Speech of MP
* 302: Parl. transcripts // Speech of federal council
* 401: Federal legislation // Legal text of the official compilation (law, ordinances, etc.)
* 501: Court decisions // Federal Supreme Court
* 502: Court decisions // Federal Criminal Court
* 503: Court decisions // Federal Administrative Court

 Code folder

The code folder contains all R code for the analyses. The files are numbered chronologically.

* _1_classifier_training.R_: Training of classifiers for classification of policy sectors
* _2_classifier_application.R_: Classification of documents in corpus
* _3_dictionary_application.R_: Biodiversity indexing of documents in corpus
* _4_stm_truncation.R_: Truncation of indexed documents to keep only relevant parts
* _5_stm_translation.R_: Translation of FR and IT documents to DE
* _6_stm_model.R_: Preprocesssing and structural topic model
* _7_plots.R_: Plots and numbers as included in the paper

The code/functions folder contains custom functions used in the scripts, e.g. to support topic model interpretation.

Package versions and setup details are noted in the code files.

 Contact

Please direct any questions to Ueli Reber (ueli.reber@eawag.ch).

bgb

display_name: bgb

biodiversity

display_name: biodiversity

environmental--policy

display_name: environmental--policy

policy-analysis

display_name: policy-analysis

policy-documents

display_name: policy-documents

switzerland

display_name: switzerland

text-corpus

display_name: text-corpus

en: Replication files for "Integrating biodiversity: A longitudinal and cross-sectoral analysis of Swiss politics"


automatic-detection-of-avalanches

maintainer: Matthias Heck

title_for_slug: automatic-detection-of-avalanches

en: snow avalanche-activity monitoring hidden-markov-model seismic

en: Results and Scripts

en: This zip package contains the classification results, coherence results, reference data set, python scripts used for the classification and the start and end times for the pre-processed continuous seismic data. A further readme file is also include for more detailed information.

en: This dataset contains the results obtained by an automatic classification using hidden Markov models of a continuous seismic dataset. To avoid long computational times, we reduced the seismic data using pre-processing step. The start and end times of the windows used for the classification are also included in this dataset. Furthermore, an avalanche reference data set is included and the python scripts used to perform the processing steps and the classification.

avalanche-activity

display_name: avalanche-activity

hidden-markov-model

display_name: hidden-markov-model

monitoring

display_name: monitoring

seismic

display_name: seismic

snow

display_name: snow

en: Automatic detection of avalanches


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: machine-learning monitoring avalanche seismic localization

en:
This tar file contains classification results for two seismic geophone arrays deployed above Davos, Switzerland. The of the first array located at the Dischma Valley was used to automatically identify all seismic events produced by avalanches, whereas the classification perfomed at the second array located at the Wannengrat field site was used to identify airplanes and earthquakes.
Furthermore, this tar file also contains the median back-azimuth of all classified events at the Dischma field site.

mimetype: application/x-tar

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

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

en: Automatic Classification of Avalanches


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

en: Manually observed snow profiles

en: Manually observed snow profiles as csv-files containing depth [cm], thickness [cm], density [kg m-3], hand hardness, first grain type, second grain type, first grain size [mm], and second grain size [mm] of each layer.

en: Extracted data

en: Extracted data contain validation and results published in Richter et al. (2019).

en: SNOWPACK simulations

en: This dataset contains all SNOWPACK simulations, including input files, setup and output files.

en: README

en: README file explaining data structure and content

mimetype: text/plain

en: Stability tests

en: Stability tests including csv-files with CT, ECT and PST experiments for each year and each field site.

en:
To validate the critical crack length as implemented in the snow cover model SNOWPACK, PST experiments were conducted for three winter seasons (2015-2017) at two field site above Davos, Switzerland. This dataset contains manually observed snow profiles and stability tests. Furthermore, corresponding SNOWPACK simulations are included.
These data were analyzed and results were published in Richter et al. (2019).

Please refer to the Readme file for further details on the data.

These data are the basis of the following publication:
Richter, B., Schweizer, J., Rotach, M. W., and van Herwijnen, A.: Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK, The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, 2019.

avalanche-forecast

display_name: avalanche-forecast

snow-stability-evaluation

display_name: snow-stability-evaluation

snowpack

display_name: snowpack

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Validating and improving the critical crack length in SNOWPACK


en:
Sum of stem cross-section areas at a height of 1.3 m (dbh measurement height) of all living and dead trees and shrubs starting at 12 cm dbh recorded according to the NFI1 method. In NFI1 only those dead trees were recorded whose wood could still be exploited.

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

economic-region

display_name: economic-region

main-tree-species

display_name: main-tree-species

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

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: Total basal area NFI1