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.

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

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

format: HTML

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


$oid: OBSOLETE

en:
This dataset contains the input data generated for the pseudo-global warming (PGW) experiments used in the study of the March 2022 Antarctic heatwave with the CRYOWRF model. It includes:
- PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for past and  future storyline experiments.
- Model configuration files required to reproduce the CRYOWRF simulations.
These resources allow researchers to reproduce the experimental setup and generate model outputs consistent with the results presented in the study.

en: heatwave atmospheric-rivers era5 antarctica cmip6 event-attribution extreme-events climate-change

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Storylines of the March 2022 heatwave event at Concordia - East Antarctica

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: CRYOWRF_ANT_20220315_ConfigFiles.tar
    Size: 912259096 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/7f77d116-cd3b-4eec-a6d6-061b0d7b43f6/download/cryowrf_ant_20220315_configfiles.tar
    Description: Model configuration files required to reproduce the CRYOWRF simulations over Antarctica.

en:
Resource Title: PGW_deltas.tar
    Size: 3701853962 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/79b7c457-e689-49bd-8330-29b0508d2b2c/resource/9936c23c-dc86-4eaa-8a6f-5a49cffb338c/download/pgw_deltas.tar
    Description: PGW delta fields derived from CMIP6 simulations, used to perturb ERA5 reanalysis data for future storyline experiments.

antarctica

display_name: antarctica

atmospheric-rivers

display_name: atmospheric-rivers

climate-change

display_name: climate-change

event-attribution

display_name: event-attribution

extreme-events

display_name: extreme-events

heatwave

display_name: heatwave


en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.
The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).
In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

en: hydrologic-and-hydrodynamic-modelling climate-change perialpine-lakes lake-level-regulation switzerland

en: Lake climate change scenarios CH2018

en:
Resource Title: Lake water level scenarios CH2018
    Size: 128937984 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/b461ac74-3c51-4c96-9602-6200405f7ef4/download/lake_water_level_scenarios_ch2018.xls
    Description: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

format: XLS

en:
Resource Title: Lake outflow scenarios CH2018
    Size: 129406464 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/5d653540-4338-4d0f-bad3-4d083584964a/download/lake_outflow_scenarios_ch2018.xls
    Description: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
Resource Title: Lake characteristics
    Size: 668782 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/1c350a5c-5297-43ad-ae2f-f093b5f4bfa3/resource/469b12d3-8184-4ce1-a2c8-881a5b81db3e/download/lake_characteristics.xlsx
    Description: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland


historical-vegetation-height-model-nfi

en:
The main datasets available are 4 nationwide **Digital Surface Models (DSMs)** and corresponding **Vegetation Height Models (VHMs)** with a spatial resolution of 1 m.
The Vegetation Height Models are calculated by subtraction of a Digital Terrain Model (swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs were derived by image matching of **scanned historical images** (panchromatic 8-bit) acquired with a RC10 frame camera, in the context of the swisswide image acquisition campaigns of swisstopo.
Nationwide products could be generated for the **four epochs**
 1979-1985 / 1985-1991 / 1990-1998 / 1998-2006.
Additional information about successful image matching vs. interpolation of pixels and about the year of image acquisition are available in the corresponding files (**matched_area_xxxx_xxxx_binay.tif** and **meta_acquisition_year_xxxx_xxxx.json**, respectively).
To separate vegetation from non-vegetation areas a mask derived from a combination of information of the Topographic landscape model - TLM (swisstopo) and a NDVI layer was used and is supplied as **"TLM_mask.tif"**
Due to the occurrence of unrealistic vegetation height values caused by the failure of the image matching process (mainly overexposed images and clouds or very steep rocky terrain), pixel values - 60 m were set to NoData and - 0 m to 0.
All datasets are available in the Reference System **LV95 (EPSG: 2056) LN02 (EPSG: 5728)** and share the common **extent definition** (xmin ymin xmax ymax): 2480000 1070000 2840000 1300000

en: vhm historical forest photogrammetry nfi dsm

en: Historical Vegetation Height Model NFI

title_for_slug: historical-vegetation-height-model-nfi

en:
Resource Title: 1979-1985 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1979-1985_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1998-2006 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1998-2006_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1990-1998 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1990-1998_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: readme.txt
    Size: 2045 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d16d27e5-b239-4909-b914-1b0b5337dab3/resource/f6cabeaa-bf7c-4141-bea9-af99d3224487/download/readme.txt
    Description: Description of available data

format: TXT

media_type: text/plain

en:
Resource Title: 1985-1991 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1985-1991_vegetation_height_model_nfi%2F
    Description:

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm


en:
Nuclear microsatellite markers and genotype data for _Trichopria ddrosophilae_
This data set comprises (i) the characteristics of a set of 21 species-specific nuclear microsatellites for PCR amplification in _Trichopria drosophilae_ (ii) and genotype data for samples collected in southern Switzerland (Canton of Ticino), with few reference samples from Canton of Vaud, southern Germany, and northern Italy (lab-reared population).
Markers were developed by Ecogenics GmbH, Balgach (Switzerland), using MiSeq Nano 2x250 v2 format (on a mix of 10 individuals). Multiplex PCR assays for multilocus genotyping were established by Ecological Genetics (WSL Birmensdorf), and population genetic analyses are found in Gugerli et al., Agrarforschung Schweiz 2019.

en: drosophila-suzukii trichopria-drosophilae switzerland biological-control nuclear-microsatellite-markers population-genetics simple-sequence-repeats multilocus-genotypes

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: EnviDat: the Environmental Data Portal

en: Nuclear microsatellite markers for Trichopria drosophilae, parasitoid wasp on Drosophila suzukii

envi

en: Environment

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-multilocus-genotype_dataset
    Size: 100131 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9998d313-6c9a-4abc-b83b-a5b0c31c07cb/download/trichopriadrosophilae_nucmicrosat_genotypes.csv
    Description: Multilocus genotypes (biallelic coding for 21 nuclear microsatellites) of Trichopria drosophilae described in Gugerli et al. Agrarforschung Schweiz 2019. Missing data denoted as '999'. Population codes (PopNo) are the following: 1, Vezia; 3, Contone ; 5, Davesco; 6, Corteglia; 7, Mezzana; 8, Stabio; 9, Gordola; 10, Sementina; 12, Brusata di Novazzano; 14, Monteggio; 16, Giubiasco; 17, ComoBP; 18, VD; 19, Weil_D; 20, Dossenheim; 21, BioPlanet_Como. Coordinates (CoordCH_E, CoordCH_N) refer to the Swiss coordinates system CH1903.

format: CSV

media_type: text/csv

en:
Resource Title: Trichopria-drosophilae_nuclear-microsatellite-markers_characteristics
    Size: 6134 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a69b5f91-0e30-45ba-9d42-06db76b549c4/resource/9bd01ee4-8334-4d38-b64e-806fc839fa8c/download/trichopriadrosophilae_nucmicrosat_seqinfo.csv
    Description: Table comprising all pertinent information for multiplex PCRs of species-specific nuclear microsatellite makers for Trichopria drosophilae, comprising all 21 newly developed markers, details on full sequences with GenBank accession numbers, primer sequences (including labeling and pig-tails), and repeat motives. PCRs with respective annealing temperatures (AnnealingTemp) refer to Type-It Multiplex PCR Kit (Qiagen, Hilden, Germany).

biological-control

display_name: biological-control

drosophila-suzukii

display_name: drosophila-suzukii

multilocus-genotypes

display_name: multilocus-genotypes

nuclear-microsatellite-markers

display_name: nuclear-microsatellite-markers

population-genetics

display_name: population-genetics

simple-sequence-repeats

display_name: simple-sequence-repeats

trichopria-drosophilae

display_name: trichopria-drosophilae


en:
Table of content: 1. Frequency of early concepts; 2. Frequency of additional concepts; 3. Use of any early concept; 4. Use of any additional concept, 5. Planning steps; 6. Protocol.
The present dataset is part of the published scientific paper entitled “Landscape ecological concepts in planning: review of recent developments” (Hersperger et al., 2021). The goal of this research was to review recent publications to assess the use of landscape ecological concepts in planning. Specifically, we address the following research questions: Q1. Landscape ecological concepts: What are they? How frequently are they mentioned in current research? Q2. How are landscape ecological concepts integrated in landscape planning?
We analysed all empirical and overview papers that have been published in four key academic journals in the field of landscape ecology and landscape planning in the years 2015–2019 (n = 1918). Four key journals in the field of landscape ecology were selected to conduct the analysis, respectively Landscape Ecology (LE), Landscape Online (LO), Current Landscape Ecology Reports (CLER), and Landscape and Urban Planning (LUP). The title, abstract and keywords of all papers were read in order to identify landscape ecological concepts. Then, all 1918 papers went through a keyword search to identify the use of early and additional concepts. We used the “pdfsearch” package in R programming language and searched for singular and plural forms and different variations of the concepts (see Supplementary material 1, Table A). As a result, we provided four outputs:
  1. Frequency of early concepts. This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.
  2. Frequency of additional concepts. This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.
  3. Use of any early concept. This data provides the total number of times each article used any early concept (Q1).
This data was used to produce the Figure 3a at the original publication.
  4. Use of any additional concept. This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.
To address the second question (Q2), the title, abstract and keywords of the papers included in our sample (n=1918 articles) were screened to identify papers that might show how landscape ecological concepts are integrated into planning. We selected 52 empirical papers (see Supplementary material – 4 Integration of landscape ecological concepts into planning), and we provided two outputs:
  5. Planning steps.  This data provides the number of times landscape ecological concepts were addressed in each
planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the
original publication.
  6. Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the
data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the
paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning
steps described above?

en: resilience green-infrastructure landscape-planning multifunctionality planning socio-ecological-system landscape-ecology sense-of-place pdfsearch landscape-services literature-review decision-making landscape-perception ecosystem-services

en: The usage of landscape ecological concepts in the planning literature

en:
Resource Title: 2. Frequency of additional concepts.
    Size: 1187545 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/7ae0ec68-0675-4d2b-a5d2-51d08e153f99/download/2-frequency_of_additional_concept.csv
    Description: This data provides the total number of times each article used each additional concept (Q1). This data was used to produce the Figure 2b at the original publication.

en:
Resource Title: 3. Use of any early concept.
    Size: 157296 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/21b7a6f8-9f37-4ddb-b8fa-b17f25428996/download/3.-use_of_any_early_concept.csv
    Description: This data provides the total number of times each article used any early concept (Q1). This data was used to produce the Figure 3a at the original publication.

en:
Resource Title: 4. Use of any additional concept.
    Size: 146949 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/070af529-0b2d-4ead-b0d8-86aaf15afd04/download/4.-use_of_any_additional_concept.csv
    Description: This data provides the total number of times each article used any additional concept (Q1). This data was used to produce the Figure 3b at the original publication.

en:
Resource Title: 1. Frequency of early concepts.
    Size: 1002570 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/3b4f848b-5dc5-4f24-96b3-09778c0a8655/download/1.-frequency_of_early_concepts.csv
    Description:  This data provides the total number of times each article used each early concept (Q1). This data was used to produce the Figure 2a at the original publication.

en:
Resource Title: 6. Protocol
    Size: 91483 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/8675307f-37dc-4062-b990-3202634a5dbc/download/6_protocol.xlsx
    Description: Protocol for assessing the integration of landscape ecological concepts into planning. To systematically collect the data, we used this protocol which addressed the following questions: (a) which type of planning is addressed by the paper? (b) to which planning level does the paper refer to? (c) which concepts are integrated in any of the planning steps described above?

en:
Resource Title: 5. Planning steps.
    Size: 3898 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/61f83301-e7aa-4374-a4bd-7fbf35fb12ff/resource/f456f712-f67c-40d0-9f6a-7e18f2746ce4/download/5.-planning_steps.csv
    Description: This data provides the number of times landscape ecological concepts were addressed in each planning steps in 52 empirical papers analysed in detail (Q2). This data was used to produce the Figure 4 at the original publication.

decision-making

display_name: decision-making

ecosystem-services

display_name: ecosystem-services

green-infrastructure

display_name: green-infrastructure

landscape-ecology

display_name: landscape-ecology

landscape-perception

display_name: landscape-perception

landscape-planning

display_name: landscape-planning

landscape-services

display_name: landscape-services

literature-review

display_name: literature-review

multifunctionality

display_name: multifunctionality

pdfsearch

display_name: pdfsearch

planning

display_name: planning

resilience

display_name: resilience

sense-of-place

display_name: sense-of-place

socio-ecological-system

display_name: socio-ecological-system


en: This dataset includes gridded data on snow depth (m), snow water equivalent (mm), runoff from snow melt (mm) and snow cover fraction for Swtzerland. The data is spanning the water years 2016-2022 at a high spatial resolution of 250 m. Data are stored as daily results.

en: snow-depth-distribution snow-melt oshd snow-cover-fraction seasonal-snow-data

en: Seasonal snow data for Switzerland OSHD - FSM2sohd

oshd

display_name: oshd

seasonal-snow-data

display_name: seasonal-snow-data

snow-cover-fraction

display_name: snow-cover-fraction

snow-depth-distribution

display_name: snow-depth-distribution

snow-melt

display_name: snow-melt


wind-lidar-davos-wolfgang

en: Scanning wind Lidar from Meteoswiss was installed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577) and measured from 200 m above ground to 8100 m. The time resolution is up to 5 seconds. The Lidar was measuring wind profiles but also performed plan position indicator (PPI) and range height indicator (RHI) scans.

en: wolfgangpass profiles raclets lidar wind

envidat

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

en: EnviDat: the Environmental Data Portal

en: Wind LIDAR Davos Wolfgang

title_for_slug: wind-lidar-davos-wolfgang

format: ZIP

lidar

display_name: lidar

profiles

display_name: profiles

raclets

display_name: raclets

wind

display_name: wind

wolfgangpass

display_name: wolfgangpass


soil-respiration-exclosure-experiment

en:
Location of data collection
The Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (- 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume - 60% of the biomass in short-grass compared to - 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, - 5 g).
Experimental design
We selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil.
!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!
Data collection
In-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged.
Please acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli

en: ungulates subalpine grassland soil-respiration grazing

en: Soil respiration - exclosure experiment

title_for_slug: soil-respiration-exclosure-experiment

envi

en: Environment

grassland

display_name: grassland

grazing

display_name: grazing

soil-respiration

display_name: soil-respiration

subalpine

display_name: subalpine

ungulates

display_name: ungulates


en:
The dataset includes spatially aggregated canopy temperature measurements (°C) of one to two tree crowns obtained using infrared (IR) point sensors.
The dataset was quality screened using a multi-step outlier detection procedure based on Median Absolute Deviation (MAD) statistics within a defined analysis period (= 1 year).
**Three complementary quality-control checks were applied**:
1\. Global MAD screening – detects observations that strongly deviate from the overall distribution of each individual sensor time series.
2\. Local spike detection – identifies short-term anomalous spikes within each sensor time series using rolling median and rolling MAD statistics.
3\. Cross-sensor consistency screening – compares measurements across all sensors recorded at the same timestamp to identify extreme deviations relative to the network-wide median behaviour.
Each observation received individual QC flags for all three checks, followed by a combined final quality flag. Observations passing all criteria were labelled as `good`, while flagged observations were labelled as `outlier` if considered suspect, or as `bad` if associated with known sensor drifts. Observations labelled as `outlier` may still represent physically plausible values, while observations labelled as `bad` should not be considered for further analysis. All observations were retained in the exported dataset for traceability.

en: pfynwald pinus-sylvestris ir-sensor vpdrought irrigation heat-stress transpiration cooling

en: Pfynwald VPDrought experiment canopy temperature parameter

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2024.zip
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    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/966309dc-3bf5-4bbc-9964-6af79bf294fd/download/pfynwald_vpdrought_canopy_temperature_1min_2024.zip
    Description:

media_type: application/zip

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Size: 50905903 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/3ed284f7-5ca4-4b25-9441-00722b92e58d/download/pfynwald_vpdrought_canopy_temperature_1min_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Size: 5833672 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/66747b91-d345-4e98-97c7-9d7b3ce92266/download/pfynwald_vpdrought_canopy_temperature_10min_2025.zip
    Description:

en:
Resource Title: pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Size: 5872908 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a585bca2-a5e2-4810-b9a8-e831fdc7aebd/resource/212221fb-14a0-4157-97e9-1670e221959d/download/pfynwald_vpdrought_canopy_temperature_10min_2024.zip
    Description:

cooling

display_name: cooling

heat-stress

display_name: heat-stress

ir-sensor

display_name: ir-sensor

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

transpiration

display_name: transpiration

vpdrought

display_name: vpdrought


en:
Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland.
The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of
* Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground)
* Digital Elevation Model (grid resolution 2 m) obtained via UAV
* Orthophoto (5 cm resolution) obtained via UAV
* Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL)
* StoneNode v1.0 raw data stream for equipped rocks.
Further information is found in
* A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/
*  P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/

en: rockfall sensor-stream stonenodedata rockfall-experiments deposition-points dem induced-rockfall natural-hazards rockfall-runout stonenode

en: Induced Rockfall Dataset (Small Rock Experimental Campaign), Tschamut, Grisons, Switzerland

en:
Resource Title: Induced Rockfall Data, Tschamut, GR
    Size: 83833546 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/3be3d9f6-cf12-4dbc-bdf1-80e101fb47f7/download/2018_rf_tschamut.7z
    Description: __ Induced Rockfall Experimental Data, Tschamut, GR, Switzerland__

The archive contains site specific geographical data as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally availabe are the StoneNode v1.0 sensor streams for the equipped rocks.

The _OverviewFigures_ file serves as quick representation of the included data. It also contains the overview table for the rock masses in order to set the dimensions accordingly in RAMMS::ROCKFALL.

The archive contains the following folders:
<\ul>
* DEM: ArcGIS compatible DEM Tschamut_DEM_2m (grid resolution of  2 m) as well as the .asc grid used in RAMMS::ROCKFALL simulations
* _DepositionPoints_: containing two folders _RF Tschamut Frozen_ and _RF Tschamut WET_ containing each a shapefile with the complete deposition data of each series as well as deposition shapfiles for each rock shape.
* _DigitizedRocks_: Digitized point clouds of the used rocks as used for RAMMS::ROCKFALL simulations (.pts files) (dimensions have to be checked).
* _Orthofoto_: Orthophoto of the experimental site obtained via UAV with 5 cm resolution.

en:
Resource Title: StoneNode v1.0 Data for equipped experimental Runs.
    Size: 6899716 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/c80b0561-d5f8-4bd6-97e7-ec5a15bfd84e/download/experimentalruns_sensorstreams.7z
    Description: Corresponding StoneNode v1.0 data streams belonging to the deposition points.

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata


en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).
We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.
This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.
Koordinate System: CH1903+ LV95 LN02

en: natural-hazard satellite avalanche hazard-mapping snow

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: EnviDat: the Environmental Data Portal

en: SPOT6 Avalanche outlines 24 January 2018

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
This dataset contains all data on which the following publication below is based.
Paper Citation:
Risch Anita C., Zimmermann, Stefan, Moser, Barbara, Schütz, Martin, Hagedorn, Frank, Firn, Jennifer, Fay, Philip A., Adler, Peter B., Biederman, Lori A., Blair, John M., Borer, Elizabeth T., Broadbent, Arthur A.D., Brown, Cynthia S., Cadotte, Marc W., Caldeira, Maria C., Davies, Kendi F., di Virgilio, Augustina, Eisenhauer, Nico, Eskelinen, Anu, Knops, Johannes M.H., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Prober, Suzanne M., Seabloom, Eric W., Siebert, Julia, Silveira, Maria L. , Speziale, Karina L., Stevens, Carly J., Tognetti, Pedro M., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties. Global Change Biology
Please cite this paper together with the citation for the datafile.
We assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000).

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

en: Anthropogenic change and soil net N mineralization

envi

en: Environment

ammonification

display_name: ammonification

climate

display_name: climate

fertilization

display_name: fertilization

global-change

display_name: global-change

grassland

display_name: grassland

herbivore

display_name: herbivore

mineralization

display_name: mineralization

nitrification

display_name: nitrification

nitrogen

display_name: nitrogen

nutrient-network

display_name: nutrient-network

soil

display_name: soil


en: The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017.

en: ice-layers weissfluhjoch snow-temperature water-front snowmicropen snow-stratigraphy

en: WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack

en:
Resource Title: README
    Size: 476 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2bf03a26-ee90-4e13-8ed0-63fbfada5733/resource/55d88599-ae7a-4ba6-af25-9544893de2be/download/readme.txt
    Description:

en:
Resource Title: WFJ_ICE_LAYERS dataset
    Size: 4289873 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2bf03a26-ee90-4e13-8ed0-63fbfada5733/resource/06794e9d-cbac-4a14-9d3b-a06f7f6c2061/download/wfj_ice_layers_dataset.zip
    Description:

ice-layers

display_name: ice-layers

snow-stratigraphy

display_name: snow-stratigraphy

snow-temperature

display_name: snow-temperature

snowmicropen

display_name: snowmicropen

water-front

display_name: water-front

weissfluhjoch

display_name: weissfluhjoch


en:
Overview
The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.
 Experimental Setup
Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).
 Data
Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.

en: Alpine3D simulations of future climate scenarios CH2014

en:
Resource Title: Aare input
    Size: 360212 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/c8696023-5622-481d-952a-13f88c35e9fe/resource/ad886f54-bc18-4972-9fd0-db9bda3f7dd5/download/aare_input.tar.bz2
    Description: Grid input data for the 'Aare' CH2014 simulation.

en:
Resource Title: Graubunden input
    Size: 1208440 bytes
    Format: application/x-tar
    URL: https://www.envidat.ch/dataset/c8696023-5622-481d-952a-13f88c35e9fe/resource/41555ebb-435b-40a3-b338-826e1c3172e3/download/graubunden_input.tar.bz2
    Description: Grid input data for the 'Graubunden' CH2014 simulation.

en:
Resource Title: CH2014 REPORT
    Size: 0
    Format: No Info
    URL: http://ch2014-impacts.ch/
    Description: CH2014-Impacts: Toward Quantitative Scenarios of Climate Change Impacts in Switzerland

The CH2014-Impacts report presents the results of a concerted effort of 15 Swiss research institutions to describe impacts of climate change in Switzerland quantitatively. This dataset contributes to the Crosphere/Snowcover section.

en:
Resource Title: Dataset
    Size: 35433480192 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/12/ch2014/
    Description: Datasets are grouped under experiment "Aare" and "Graubunden".Data is also made available in netCDF format. A range of tools are available to [read netCDF](http://www.unidata.ucar.edu/software/netcdf/software.html).

climate-change

display_name: climate-change

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent


vegetation-height-model-sentinel-nfi

en: Countrywide vegetation height models (VHM) were generated for Switzerland based on Copernicus Sentinel-2 imagery and the digital terrain model (DTM) swissALTI3D from the Swiss Federal Office of Topography swisstopo. A Convolutional Neural Network (CNN) model was trained to estimate the maximum vegetation height at the spatial resolution of the Sentinel-2 pixel of 10 m. Vegetation heights from the spatially higher-resolved VHM Lidar NFI were used as reference data for the CNN training. Within the framework of the Swiss National Forest Inventory (NFI), the VHMs were modelled annually based on available Sentinel-2 imagery from May – September of the respective year. Further details on the creation of the VHM Sentinel NFI can be found in the paper Jiang et al. (2023, https://doi.org/10.1016/j.srs.2023.100099). Contains modified Copernicus Sentinel data.

en: nfi vegetation-height cnn switzerland forest sentinel-2 remote-sensing

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: EnviDat: the Environmental Data Portal

en: Vegetation Height Model Sentinel NFI

title_for_slug: vegetation-height-model-sentinel-nfi

en:
Resource Title: VHM_Sentinel_NFI_2019
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    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/1320cdac-5544-47d8-acaf-983fd88744a4/download/landesforstinventar-vegetationshoehenmodell_sentinel_2019_2056.tif
    Description:

format: TIFF

media_type: image/tiff

en:
Resource Title: VHM_Sentinel_NFI_2025
    Size: 789365244 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/cd9f3543-87a3-4eb5-ab05-a4388a7967c4/download/landesforstinventar-vegetationshoehenmodell_sentinel_2025_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2021
    Size: 793778198 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/8fc7f306-c788-4b1c-9a17-8dfe946c9681/download/landesforstinventar-vegetationshoehenmodell_sentinel_2021_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2024
    Size: 799033995 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/284e4292-df10-4227-85b5-1fc7024def5b/download/landesforstinventar-vegetationshoehenmodell_sentinel_2024_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2022
    Size: 794990349 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/12ed6aff-aeed-45f4-aed3-81e17797a8da/download/landesforstinventar-vegetationshoehenmodell_sentinel_2022_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2020
    Size: 793832708 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/f0496550-ac9a-4dfd-bfea-68e601e9f3f7/download/landesforstinventar-vegetationshoehenmodell_sentinel_2020_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2023
    Size: 794605160 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/c57585ec-51da-4aeb-bf90-c5598e14d3c6/download/landesforstinventar-vegetationshoehenmodell_sentinel_2023_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2018
    Size: 791849627 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/6f9a20f7-78bf-4cc5-b734-c52d63bbfd0a/download/landesforstinventar-vegetationshoehenmodell_sentinel_2018_2056.tif
    Description:

en:
Resource Title: VHM_Sentinel_NFI_2017
    Size: 791212333 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/3b1cae17-fc7a-4722-95da-92d3be869273/resource/771519e8-6435-463c-a2cb-57031ee25861/download/landesforstinventar-vegetationshoehenmodell_sentinel_2017_2056.tif
    Description:

cnn

display_name: cnn

forest

display_name: forest

nfi

display_name: nfi

remote-sensing

display_name: remote-sensing

switzerland

display_name: switzerland

vegetation-height

display_name: vegetation-height


bats-in-beaver-systems

en:
This dataset contains processed bat acoustic data collected to evaluate the ecological impacts of beaver-engineered ponds on bat species richness, activity, and feeding activity. It includes nightly activity and feeding call counts identified to species or species group level, site and treatment information (beaver pond vs. control areas along the same stream), and associated environmental covariates such as deadwood volume, arthropod abundance, and vegetation structure.
Methods: Bats were recorded using passive acoustic detectors placed at paired beaver-influenced and control sites. The resulting data was processed in the software Batscope. Arthropod abundance was estimated using flight-interception traps. The amount of deadwood and vegetation cover was measured in the field. Canopy cover and canopy heterogeneity were modelled from GIS models.
Temporal and Spatial Coverage:
Data were collected from eight sites in Switzerland between June and July 2022, each site sampled for 16 nights.

en: flying-arthropods wetland habitat-heterogeneity nature-conservation castor deadwood beaver ecosystem-engineer chiroptera

en: Bats in beaver systems

title_for_slug: bats-in-beaver-systems

envi

en: Environment

en:
Resource Title: site_info.csv
    Size: 4452 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/0a4317c7-3251-4c37-8519-26f542ed56a5/download/site_info.csv
    Description: site_info contains columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"location" (sampling location row within site),
"sample_nr" (sampling number within location)

en:
Resource Title: bats_raw_values_overview.R
    Size: 8975 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/f7d9750d-6dcd-4fa9-856e-c810d08c9708/download/bats_raw_values_overview.r
    Description: bats_raw_values_overview to produce raw value summaries and tables

format: OCTET

en:
Resource Title: gewichtungsfaktor.csv
    Size: 9392 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/b3f59232-46fa-4068-ad06-15947d042c16/download/gewichtungsfaktor.csv
    Description: gewichtungsfaktor with columns
"Project" (sampling site),
"Treatment" (sampling location within site, with levels ctrl for Control and pool for Pool),
"date" (sampling date),
"gew" (weighting factor to standardize night length)

en:
Resource Title: bat_guilds.CSV
    Size: 2607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/9dbe3429-5669-4b2c-a83c-a643411b06b5/download/bat_guilds.csv
    Description: bat_guilds with columns
"SP" (identification level),
"EndGuilde" (information on feeding guild)

en:
Resource Title: bats_biodiv.day.csv
    Size: 16681 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/56b11b90-7932-434b-a089-f3ff14b3f7d7/download/bats_biodiv.day.csv
    Description: bats_biodiv.day with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"date" (sampling date),
"month" (sampling month),
"feeding" (number of feeding buzzes summed per 5 minutes and identification level), "abundance" (sequences per 5 minutes and identification level),
"richness" (species richness),
"richness_feeding" (species richness of feeding bats)

en:
Resource Title: README.txt
    Size: 6009 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/03d87d3e-c9f0-4e53-b1fc-531dd2087e8f/download/readme.txt
    Description: README text file providing context for the data. Please do not hesitate to contact us if you have any questions

en:
Resource Title: dead_wood.csv
    Size: 40298 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/3985310a-835b-4fdf-a66e-5ec0a92ab490/download/dead_wood.csv
    Description: dead_wood for deadwood with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"type" (deadwood type),
"height_length" (the height or lenghth of a piece of deadwood in m),
"DBH_diamlarge" (diameter at breast height or diameter of larger end if lying in m),
"diamsmall (diameter of smaller end if lying in m",
"volume" (calculated volume in m3)

en:
Resource Title: bats_age.R
    Size: 6554 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/0e7ad52e-0545-4eec-98bc-ee80e4d27a90/download/bats_age.r
    Description: R script bats_age to test the beaver pool age effect on bat richness, activity and feeding activity

en:
Resource Title: bats_glmm.R
    Size: 44503 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/ba5c25fd-9c4b-480f-8f89-29449bbddfd7/download/bats_glmm.r
    Description: R script bats_glmm to test the influence of beavers on bat richness, activity and feeding activity

en:
Resource Title: arthropods_flying.csv
    Size: 1822 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/22214e46-c662-4398-91da-197fa844c656/download/arthropods_flying.csv
    Description: arthropods_flying the arthropod abundance with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"month" (sampling month),
"abundance" (number of flying arthropods)

en:
Resource Title: bats_pool_size.R
    Size: 7169 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/664b4516-22a3-4509-bec6-ccbd57f4ee8c/download/bats_pool_size.r
    Description: R script bats_pool_size to test the beaver pool size on bat richness, activity and feeding activity

en:
Resource Title: bats.environment.xlsx
    Size: 10844 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/ad5c3240-15c9-4330-9677-9786ef447662/download/bats.environment.xlsx
    Description: bats.environment with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"canopy" (modelled tree canopy cover, averaged across radius of 100 m, unitless),
"structure_ruggedness" (mean ruggedness of the total vertical structure > 3 m, averaged across radius of 100 m, unitless), "vegetation_ruggedness" (mean ruggedness of the canopy > 3 m, later called canopy_heterogenneity, averaged across radius of 100 m, unitless),
"pool_size" (maximum width of beaver pool in m),
"area_deadwood_monitoring" (total area of deadwood moonitoring in m3),
"age" (beaver presence in years)

en:
Resource Title: vegetation_characteristics.csv
    Size: 2769 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/f60cdb2f-d4bc-454a-9fed-058c86234b5e/download/vegetation_characteristics.csv
    Description: vegetation_characteristics data on vegetation_cover and cumulative_cover with columns "laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"Vegetation_cover" (estimated vegetation cover over 5x1 m plot in %),
"Cumulative cover" (summed up cover over tree, shrub and herb layer in %),
"Cumulative cover trees" (tree cover level, higher than 3 metres in %),

en:
Resource Title: bats_data_exploration_Figure_nighly.R
    Size: 65739 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/d59bb90b-29b3-4908-a692-17fdd8e79486/download/bats_data_exploration_figure_nighly.r
    Description: R script bats_data_exploration_Figure_nighly to explore the data and display nightly species richness, activity and feeding activity

en:
Resource Title: bats_biodiv.day.guilds.csv
    Size: 53549 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/78d66f28-1f5a-43f9-8cfe-e5edf12055d8/download/bats_biodiv.day.guilds.csv
    Description: bats_biodiv.day.guilds with columns
"laufnummer" (unique identifier per sampling point),
"site" (sampling site),
"sample" (sampling location within site),
"community" (species group),
"date" (sampling date),
"month" (sampling month),
"guild" (which feeding guild information),
"feeding" (number of feeding buzzes summed per 5 minutes and identification level), "abundance" (sequences per 5 minutes and identification level),
"richness" (species richness),
"richness_feeding" (species richness of feeding bats)

en:
Resource Title: data_bats.xlsx
    Size: 7453297 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/bab1affd-1f46-41bd-b405-364af91da886/download/data_bats.xlsx
    Description: Raw data data_bats with columns:
“Categories” (empty or "feeding", indicating that call sequence contains feeding buzz)
“Sequence” (sequence number)
“Timestamp” (recording time)
“Temperature” (temperature recorded by batlogger in degree celcius)
“Serial” (serial number of bat logger)
“Duration” (duration of call sequence in seconds)
“Call.Count” (call count number, how many calls could be detected)
“Verification.1” (bat sequence verification)
“Notes” (remarks for identification)
“treatment” (treatment ctrl = Control and Pool)
“slot” (slot number, 4 slots, two in June, two in July)
“Laufnummer” (unique identifier per sampling point)

en:
Resource Title: bats_data_cleaning.R
    Size: 28317 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/9c5e13fb-5c1a-4990-af1d-576832120846/download/bats_data_cleaning.r
    Description: R script bats_data_cleaning to clean the raw data

en:
Resource Title: sampling dates.xlsx
    Size: 10360 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/6f9bce17-7b4b-4176-a3b8-8a32a0475b60/download/sampling-dates.xlsx
    Description: For the time information about the research data, created (2022-09-23 to 2022-09-23) refers to the GIS data, collected (2022-06-13 to 2022-07-31) to the field sampling. Details can be found in the csv “sampling_dates”.

sampling_dates with columns
"site" (sampling site),
"bats_1" (first period of bat survey in June),
"bats_2" (second period of bat survey in June),
"bats_3" (first period of bat survey in July),
"bats_4" (second period of bat survey in July),
"flying_arthropods_1" (arthropod sampling in June),
"flying_arthropods_2" (arthropod sampling in July),
"deadwood survey" (date of deadwood survey),
"vegetation survey" (date of vegetation survey)

en:
Resource Title: bats_SEM.R
    Size: 69411 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/a7d16ee7-974d-42e4-a16c-36351a0ee09c/resource/d682ac4b-8266-4fc8-ad06-0cbc03709b47/download/bats_sem.r
    Description: R script bats_SEM to test the influence of the beaver on bat richness, activity and feeding activity through feeding and habitat heterogeneity

beaver

display_name: beaver

castor

display_name: castor

chiroptera

display_name: chiroptera

deadwood

display_name: deadwood

ecosystem-engineer

display_name: ecosystem-engineer

flying-arthropods

display_name: flying-arthropods

habitat-heterogeneity

display_name: habitat-heterogeneity

nature-conservation

display_name: nature-conservation

wetland

display_name: wetland


en: The dataset contains seven environmental layers (average annual temperature, aridity [annual precipitation divided by annual potential evapotranspiration], frost change frequency, precipitation in the driest quarter, mean diurnal temperature range, and precipitation seasonality) modified from CHELSA (https://chelsa-climate.org/) and three soil layers (soil organic matter content, pH water, and clay content) modified from SoilGrids (https://soilgrids.org/).

en: precipitation ground-temperature soil sdms aridity frost-change-velocity

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: EnviDat: the Environmental Data Portal

en: Environmental layers for SDM simulations (GDPlants)

envi

en: Environment

en:
Resource Title: CLYPPT_M_sl1_1km_ll_preped.tif
    Size: 200847715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/4fd1317c-6869-4ada-8e7b-f10f7d154ca8/download/clyppt_m_sl1_1km_ll_preped.tif
    Description: Soil clay content modified from SoilGrids

en:
Resource Title: CHELSA_FCF_1979-2013_V1.2_preped.tif
    Size: 142268147 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/473d3b79-6926-4409-b047-6c418c1eb450/download/chelsa_fcf_1979-2013_v1.2_preped.tif
    Description: Frost change frequency modified from CHELSA

en:
Resource Title: CHELSA_bio10_02_preped.tif
    Size: 170864899 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/09b74779-e536-46fd-9b22-cd02e121f9b6/download/chelsa_bio10_02_preped.tif
    Description: Mean diurnal range modified from CHELSA

en:
Resource Title: aridity_transformed.tif
    Size: 1004802161 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/332b3970-b592-4a5f-a24d-5d4ff6ede9cf/download/aridity_tranformed.tif
    Description:

en:
Resource Title: ORCDRC_M_sl1_1km_ll_tranformed.tif
    Size: 380997791 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/561e7b40-585a-4b0c-afe3-930791ea37ec/download/orcdrc_m_sl1_1km_ll_tranformed.tif
    Description: Soil organic carbon content modified from SoilGrids

en:
Resource Title: CHELSA_bio10_15_preped.tif
    Size: 235427681 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/d37b7265-9729-48da-9543-30db55d6a72d/download/chelsa_bio10_15_preped.tif
    Description: Precipitation seasonality from CHELSA

en:
Resource Title: PHIHOX_M_sl1_1km_ll_preped.tif
    Size: 187284692 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/4381dafd-effe-4a3b-8498-ccb3f0eb95c4/download/phihox_m_sl1_1km_ll_preped.tif
    Description: Soil pH modified from SoilGrids

en:
Resource Title: CHELSA_bio10_01_preped.tif
    Size: 265375925 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/eeb36514-fe36-4b7f-aae3-5ff64984b2de/download/chelsa_bio10_01_preped.tif
    Description: Mean annual temperature modified from CHELSA

en:
Resource Title: CHELSA_bio10_17_tranformed.tif
    Size: 295725568 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/7758e97b-7bf0-42d5-8587-2d88f82180e8/resource/b896d859-ff77-46d4-9e8f-dc87f9b1e88f/download/chelsa_bio10_17_tranformed.tif
    Description: Precipitation of driest quarter modified from CHELSA

aridity

display_name: aridity

frost-change-velocity

display_name: frost-change-velocity

ground-temperature

display_name: ground-temperature

precipitation

display_name: precipitation

sdms

display_name: sdms

soil

display_name: soil


en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.
The data set contains for each site:
* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)
* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)
Input files for SNOWPACK model:
* .sno: snow profile at the end of winter
* .smet: meteorological data measured by weather stations in the area
For more details see  Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

en: winter-tourism snow-farming snow-conservation snow snowpack terrestrial-laser-scanning

en: Snowfarming data set Davos and Martell 2015

en:
Resource Title: Fluela .sno
    Size: 1919 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/f31e7520-2624-4628-a7a9-bb0bcbeea876/download/fluela_1schicht_40cm_lwc3.sno
    Description: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

en:
Resource Title: HS Martell spring 2015
    Size: 2332516 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/558c33f7-ce57-45b8-a339-f617be015e96/download/20150519_martell_hs.txt
    Description: Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en:
Resource Title: Martell .smet
    Size: 827214 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/5c4a89bc-c16a-4c37-92e6-183a50438fae/download/meteo_martell.smet
    Description: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

en:
Resource Title: Martell .sno
    Size: 1761 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/bd5861f8-f17c-4133-9ff2-c8526e67804e/download/martell_1schicht_lwc3.sno
    Description: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

en:
Resource Title: Fluela .smet
    Size: 889965 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/7e360bad-ec83-4675-802e-05dc7a701a27/download/haufen_vwcor_shade.smet
    Description: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

en:
Resource Title: HS Fluela spring 2015
    Size: 1702059 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/a0aef820-34e4-490a-9271-a12646f37b67/download/20150429_fluela_hs.txt
    Description: Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

en:
Resource Title: HS Fluela autumn 2015
    Size: 1720506 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/47f70f9b-63df-44aa-836c-02a46bbf4f6b/download/20151008_fluela_hs.txt
    Description: Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

en:
Resource Title: HS Martell autumn 2015
    Size: 2412003 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/640b09be-3b86-492e-aba2-449329969989/resource/0d16510c-f1d4-4de2-86f7-b5ef2fb0bd0f/download/20151028_martell_hs.txt
    Description: Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

snow

display_name: snow

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism


en:
Long-term phenological data in alpine regions are often limited to a few locations and thus, little is known about climate-change induced plant phenological shifts above the treeline. Because plant growth initiation in seasonally snow-covered regions is largely driven by snowmelt timing and local temperature, it is essential to simultaneously track phenological shifts, snowmelt, and near-ground temperatures. In this study, we make use of ultrasonic snow height sensors installed at climate stations in the Swiss Alps to reveal phenological advance of grassland ecosystems and relate them to climatic changes over 25 years (1998 – 2023). When snow is absent, these snow height sensors additionally provide information on plant growth at a uniquely fine temporal scale. Daily temperatures and snow- / plant height values, annual phenological- and melt-out dates were derived from IMIS climate station data (doi.org/10.16904/envidat.406). We observed an advance of green-up by -2.4 days/decade coinciding with strong warming of up to +0.8°C/decade. Although the timing of melt-out has not changed significantly over the study period in this focal region, phenological responses to early melt-out years varied due to differing influences of photoperiodic and thermal constraints, which were not equally important across elevations and communities. Phenological shifts of alpine grasslands are thus likely to become even more pronounced if melt-out timing advances in the future as predicted.
This repository relates to the publication Zehnder et al. (2025). Snow height sensors reveal phenological advance in alpine grasslands. Global Change Biology. accepted. The model data and code that support our findings are deposited in this repository.

en: phenology climate monitoring long-term grassland ultrasonic snowmelt snow alpine imis

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: EnviDat: the Environmental Data Portal

en: IMIS Phenology Data Since 1998

envi

en: Environment

en:
Resource Title: 5_method_plots.Rmd
    Size: 14013 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/91df036c-3904-4c7b-84de-355012cbbad9/download/5_method_plots.rmd
    Description:  Generates the methods-related figures used in the publication.

en:
Resource Title: pheno_params.csv
    Size: 417970 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/1a1b4c9a-2fe8-471f-8c36-616d5fd17738/download/pheno_params.csv
    Description: Contains annual phenological variables and phenofit outputs, sorted, ordered and renamed according with the readme in this repository

en:
Resource Title: snow3.png
    Size: 12808 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/afa71796-2a2e-4b7b-9885-d2a0fa47ed31/download/snow3.png
    Description: Snow3.png and grass.png are needed for plotting the methods plot in 5_methods_plots.Rmd

format: PNG

media_type: image/png

en:
Resource Title: 1_phenofit.R
    Size: 14137 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/08e70804-eed7-4a7c-8ad8-1a28c85deb2d/download/1_phenofit.r
    Description: implements the phenofit method. Note: This script is computationally intensive and may take a while to run. We recommend using the temporary data created from it (i.e. starting from 2_temperature.R). For a better description of the phenofit R package and the different methods to determine the SOG, see Kong et al. (2022): https://doi.org/10.1111/2041-210X.13870

en:
Resource Title: 3_models.Rmd
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    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/3799ac14-e0c6-4651-a18f-bc507ebb87d2/download/3_models.rmd
    Description:  Documents and reproduces the statistical models used in the analysis.

en:
Resource Title: 0_readme.Rmd
    Size: 7952 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/89105a24-c1b0-457f-8ad4-deb0a91e2aee/download/0_readme.rmd
    Description: Is the readme that documents all data and code in this repository

en:
Resource Title: grass.png
    Size: 30676 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/c190e750-7951-4434-b3e1-325bca7a6ddc/download/grass.png
    Description: Snow3.png and grass.png are needed for plotting the methods plot in 5_methods_plots.Rmd

en:
Resource Title: phenofit_outputlist.rds
    Size: 132907 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/95fca3e1-8f8f-4b1b-bc53-9c9778462b67/download/phenofit_outputlist.rds
    Description: Temporary data. Contains annual unfiltered output of phenofit (i.e. the variable names are in line with the phenofit documentation), including all curve parametrization variables for plotting and additional variables, which are not necessarily used in the analysis.

en:
Resource Title: 2_temperature.R
    Size: 23036 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/19951a82-e3bf-4650-bc36-dbe502dff703/download/2_temperature.r
    Description: Contains temperature-related calculations.

en:
Resource Title: IMIS_daily.csv
    Size: 198550707 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/4d2df843-22cf-46a4-84bb-a5eb09e6d1e0/download/imis_daily.csv
    Description: Contains daily climate station data including daily median temperatures, snow depth, plant height, and annual melt-out timings.

en:
Resource Title: phenostations.csv
    Size: 463262 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/210f372a-6bf4-42ce-aadc-6751e00c2a74/download/phenostations.csv
    Description: Contains filtered annual phenological data from 40 IMIS stations suitable and used for phenological analysis

en:
Resource Title: 4_functions.R
    Size: 8508 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/57a701f9-40be-4068-9ae6-b2a101e8d802/download/4_functions.r
    Description: Contains custom functions required for the scripts; this file must be sourced before running other scripts.

en:
Resource Title: station_info.csv
    Size: 14695 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/1e867868-1e64-4ec6-9788-aaa7ab9fd561/download/station_info.csv
    Description: Contains IMIS station location data

en:
Resource Title: all_stations.csv
    Size: 1351408 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/53a457eb-0915-43d1-98ec-a11b4963b6ff/resource/2f390316-91a2-4600-a188-b6c1045065c1/download/all_stations.csv
    Description: Contains unfiltered annual phenological, temperature and snow-climatic data for all IMIS stations.

alpine

display_name: alpine

climate

display_name: climate

grassland

display_name: grassland

imis

display_name: imis

long-term

display_name: long-term

monitoring

display_name: monitoring

phenology

display_name: phenology

snowmelt

display_name: snowmelt

ultrasonic

display_name: ultrasonic


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.

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

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: EnviDat: the Environmental Data Portal

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

en:
Resource Title: Snowmask 2015
    Size: 6736562 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/89c08602-142c-4fdb-9c76-3993a9d0dbfc/download/2015snowmask.zip
    Description:

en:
Resource Title: DEM 2016
    Size: 73447711 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/787f969b-71db-4ec9-967b-7e0198dd9d71/download/2016dem.zip
    Description: Digital Elevation Modell 2016

en:
Resource Title: Gletschboden test site
    Size: 352578 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/645e45ec-fc90-432c-a29e-d1d79781d5b2/download/dischma_neu.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: DEM 2014
    Size: 76297946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/299a98ef-94e5-4bdd-912f-24b347d20da6/download/2014dem.zip
    Description: Digital Elevation Modell 2014

en:
Resource Title: DEM 2015
    Size: 85474333 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/9d19c582-76ca-45df-b032-46d8346f45be/download/2015dem.zip
    Description: Digital Elevation Modell 2015

en:
Resource Title: Snowmask 2016
    Size: 1979860 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/2b54670d-74e9-4ea5-8fcd-4ea98ad26ed6/download/2016snowmask.zip
    Description:

en:
Resource Title: Snowmask 2014
    Size: 2069460 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/5a5b22eb-a0ae-4552-a7b3-34631c3ae998/download/2014snowmask.zip
    Description:

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

tls

display_name: tls


envidat-supports-open-science

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.
License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

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

en: EnviDat Supports Open Science

title_for_slug: envidat-supports-open-science

envi

en: Environment

envidat

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl


en:
This dataset contains the data used  and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is
 Avalanche size estimates
* the 10 pictures depicting avalanches
* the survey results from the 170 participants
 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs
 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas
The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

en: remote-sensing reliability avalanche-size-estimation avalanche-mapping avalanche

en: Data reliability study: avalanche size estimates and outlines

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing


en:
The list gives the clearly identifiable plant species from Schinz (1775). Die Reise auf den Uetliberg. Verlag des Waysenhauses, Zürich). Several species given in Schinz (1775) are not identifiable to the species level and are not included in the list. Similarly, *Vicia pisiformis*, Erbsenartige Wicke, given by Schinz (1775) is probably a misidentification and also not included in the list.
Latin plant species name Schinz 1775: Latin plant name (if) given by Schinz (1775); na: not available
German plant species name Schinz 1775: German plant name given by Schinz (1775)
Latin plant species name Info Flora 2024: Latin plant name according to www.infoflora.ch in 2024
German plant species name Info Flora 2024: German plant name according to www.infoflora.ch in 2024
Plant species still occurring in 2020: Plant species given in Schinz (1775) still occurring at the Uetliberg in 2020 (Zürcherische Botanische Gesellschaft. 2020. Flora des Kanton Zürich. Haupt, Bern); occurrence of *Thesium alpinum*, Alpen-Bergflachs, according to floristic knowledge of Rolf Holderegger and Michèle Büttner; 1: still occurring; 0: no longer occurring / extinct.

en: flora-change plant-species uetliberg occurrence zurich

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: Plant species list from 1775 and 2020 for Uetliberg Zürich

flora-change

display_name: flora-change

occurrence

display_name: occurrence

plant-species

display_name: plant-species

uetliberg

display_name: uetliberg

zurich

display_name: zurich


en: The data includes (1) amphibian occurrence data (2017-2019) for ten species across the cantons of Aargau and Zürich gathered from the Coordination Center for the Protection of Amphibians and Reptiles of Switzerland (http://www.karch.ch), (2) amphibian whole-life cycle environmental predictors (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related), and (3) local urban "green" and "grey" landcover data which can be used to identify opportunities for Blue-Green Infrastructure (through green or grey transitions) in support of regional landscape connectivity.

en: urban-spatial-planning integrated-modelling human-dominated-landscapes circuit-theory ecological-corridors biodiversity

envidat

en: EnviDat: the Environmental Data Portal

en: Amphibian and urban-rural landscape data Swiss Lowlands

en:
Resource Title: Amphibian species specific landscape resistance maps.
    Size: 51864736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/acaac64b-3ebe-4e97-ae24-a35736dfa1d5/download/resistance.zip
    Description: For each amphibian species we used the weighted average Ensemble model suitability map and converted it to a resistance map using an exponential decay function following (Duflot et al., 2018) using the species-specific mpa threshold previously computed (Preau et al., 2020). The function assigns a resistance value of 1,000 when habitat suitability equals zero, and a value of one when habitat suitability is greater than or equal to the binarization threshold. The exponential shape strengthens the barrier effect of less favorable areas.

en:
Resource Title: Binarized "green" and "grey" landcover data (Cantons of Aargau and Zürich)
    Size: 531399 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/5752ef42-b6cc-4365-bb61-288dfa3d5d95/download/urban_green_grey.zip
    Description: "Green" landcover refers to lawns and vegetated urban surfaces such as, for example private gardens, public parks, cemeteries, green stripes along roadsides, etc. While "grey" landcover refers to impervious grounds such as roads, troittoirs, other impervious. Binarized maps, 30x30m resolution.

en:
Resource Title: Amphibian whole life cycle predictors - 10m resolution
    Size: 734915785 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/26ceef50-633c-469b-970d-cd6e453e9500/download/amphibian_predictors_sdms.zip
    Description: Amphibian whole life cycle predictors include 6 variable types:
(1)	Topographic – slope [°]: derived from the Swiss Topographical Landscape model (swissTLM 3D 2015) at 2 m resolution (elevation uncertainty ± 0.5m) and, subsequently, aggregated to a median value;
(2)	Hydrologic: two predictors including nearest distance to water [m] (all water-related objects and rasterized lotic, lentic and reedbeds from the regional cadastral maps – AV: Daten der Amtliche Vermessung) and runoff coefficient [C] (between 0 and 1 relating amount of runoff to amount of precipitation, mapped AV: Daten der Amtliche Vermessung data against literature values for different land covers);
(3)	Edaphic – soil moisture variability (not available): can gathered from the spatial modelling of Ecological Indicator Values in Switzerland (Descombes et al., 2020) and resampled from 100m to 10m;
(4)	Vegetation: we calculated the median and standard deviation of the Normalized Difference Vegetation Index (NDVI) from all available cloud free Sentinel-2 pixels available between April and October for the years 2016 to 2019 (Drusch et al., 2012) and the median vegetation height [m] (not available) can gathered from Ginzler and Hobi (2015);
(5)	Land-use derived: includes three predictors, grassland density [grassland/cell] (not available) - can be gathered from Pazur et al. (2021), total grasslands area evaluated using a spatial weight matrix and a 250m neighborhood radius around each cell; urbanization [buildings/cell] – average building density for a 250m neighborhood around each cell based on the AV: Daten der Amtliche Vermessung ; and traffic intensity [vehicles/day] – average daily vehicle count (Nationales Personenverkehrsmodells);
(6)	Movement-ecology related: includes three predictors of proximity – nearest forest distance [m]; nearest rock-gravel and sandy area (RGS) distance [m] and nearest road distance [m] (considering any road type) – all calculated based on the AV: Daten der Amtliche Vermessung maps.

en:
Resource Title: Amphibian breeding sites of national importance - cantons of Aargau and Zürich
    Size: 39808424 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/fd5b1fe3-bdf9-4095-816a-edaf22178df2/download/breeding_sites_raster_30m.asc
    Description: Amphibian breeding sites of national importance (focal nodes) in the cantons of Aargau and Zürich, 30x30 m resolution, binarised ascii format.

format: pgp-keys

en:
Resource Title: Amphibian monitoring data
    Size: 310101 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8197fa13-272f-4ab0-b8fa-061269b079b6/resource/ce42d731-4b85-4da0-b356-35deb8f80607/download/amphibian_presence_2017_2019.csv
    Description: Processed amphibian occurrence data (2017-2019) in the cantons of Aargau and Zürich. The dataset includes information for the following species:  _Alytes obstetricans_,_Bombina variegata_, _Bufo bufo_, _Hyla arborea_, _Ichtyosaura alpestris_, _Lissotriton helveticus_, _Lissotriton vulgaris_, _Rana temporaria_, _Salamandra salamandra_, and _Triturus cristatus_.

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

human-dominated-landscapes

display_name: human-dominated-landscapes

integrated-modelling

display_name: integrated-modelling

urban-spatial-planning

display_name: urban-spatial-planning


en:
This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL.
Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level.
EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues.
EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services.
For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster.
Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research.
_License_: This poster is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse this poster in any way you want, for any purposes and without restrictions.

en: open-data open-science hpc reproducibility jupyter-notebooks open-source research-data-management

en: Open Science Support at the Swiss Federal Research Institute WSL. The EnviDat Concept

envi

en: Environment

hpc

display_name: hpc

jupyter-notebooks

display_name: jupyter-notebooks

open-data

display_name: open-data

open-science

display_name: open-science

open-source

display_name: open-source

reproducibility

display_name: reproducibility

research-data-management

display_name: research-data-management