de: Dieser Datensatz umfasst die Unternehmen im Thurgau, welche im Handelsregister des Zefix (Zentraler Firmenindex) registriert sind. Zefix ist ein öffentlich zugängliches Angebot des Eidgenössischen Amtes für das Handelsregister (EHRA). Es bietet die Daten des Zentralregisters über verschiedene Zugänge an: Zefix-Webapplikation ([https://www.zefix.admin.ch/](https://www.zefix.admin.ch/))Zefix REST API ([https://www.zefix.admin.ch/ZefixPublicREST](https://www.zefix.admin.ch/ZefixPublicREST))Zefix Mobile App ([https://www.zefixapp.ch/](https://www.zefixapp.ch/)) Linked Data in LINDAS ([https://lindas.admin.ch/](https://lindas.admin.ch/))Über Zefix können die Daten aller im Handelsregister eingetragenen Rechtseinheiten sowie die täglichen Handelsregisterpublikationen im SHAB (Schweizerisches Handelsamtsblatt, [https://www.shab.ch/](https://www.shab.ch/)) abgerufen werden. Der hier angebotene Datensatz enthält tagesaktuelle Kerndaten der aktiven, im Handelsregister eingetragenen Rechtseinheiten, wie Firma/Name, Sitz und Domiziladresse.Der Datensatz wird über den Linked Data Service LINDAS bezogen. Anschliessend werden die Adressen mit dem aktuellen Stand des Gebäude- und Wohnungsregisters (GWR) abgeglichen und die entsprechenden Koordinaten zugewiesenEs ist zu beachten, dass die Koordinaten nur dann zugeordnet werden, wenn eine eindeutige Zuordnung über das GWR möglich ist. Ist keine eindeutige Zuordnung möglich, so werden keine Koordinaten angegeben.Auch andere Kantone veröffentlichen die Daten des jeweiligen Handelsregisters:[Kanton Basel-Stadt](https://data.bs.ch/explore/dataset/100330/information/?disjunctive.company_type_de&disjunctive.municipality&disjunctive.plz&disjunctive.locality&disjunctive.address&sort=company_legal_name): Hier können auch die Handelsregisterauszüge aller Kantone heruntergeladen werden.[Kanton Basel-Land](https://data.bl.ch/explore/dataset/12480/information/?disjunctive.firmensitz&disjunctive.firmensitz_bezirk&disjunctive.rechtsform&disjunctive.noga_abschnitt&disjunctive.noga_abteilung&disjunctive.lokalisierungsmethode&sort=firmensitz_code)

de: handelsregister unternehmensstruktur firmenindex zefix lindas linked-data standort koordinaten amtsblatt firma firmenkonkurs unternehmen gwr gebaude wohnung

kanton-thurgau

de: Der Kanton Thurgau veröffentlicht hier schrittweise OGD-Datensätze der kantonalen Verwaltung.

de: Kanton Thurgau

en: Canton of Thurgau

fr: Canton de Thurgovie

it: Cantone di Turgovia

de: kanton-thurgau

value: TG-Kt DCAT Harvester

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (csv)

de: csv

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (json)

de: json

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (fgb)

de: fgb

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (geojson)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (gpx)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (jsonl)

de: jsonl

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (kml)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (ov2)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (parquet)

de: parquet

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (rdfxml)

de: rdfxml

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (jsonld)

de: jsonld

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (turtle)

de: turtle

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (n3)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (shp)

de: Handelsregister Kanton Thurgau: Firmen mit Rechtsform und Standort (xls)


$oid: OBSOLETE

en:
This dataset represents the data shown in the Figures 2 - 7 of Walthert et al. (2024): Coordination between degree of isohydricity and depth of root water uptake in temperate tree species. Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2024.174346). A detailed methodical description of the data can be found in the Methods section of the paper.
Abstract
In an increasingly dry environment, it is crucial to understand how tree species use soil water and cope with drought. However, there is still a knowledge gap regarding the relationships between species-specific stomatal behaviour, spatial root distribution, and root water uptake (RWU) dynamics.
Our study aimed to investigate above- and below-ground aspects of water use during soil drying periods in four temperate tree species that differ in stomatal behaviour: two isohydric tracheid-bearing conifers, Scots pine and Norway spruce, and two more anisohydric deciduous species, the diffuse-porous European beech, and the ring-porous Downy oak. From 2015 to 2020, soil-tree-atmosphere-continuum parameters were measured for each species in monospecific forests where trees had no access to groundwater. The hourly time series included data on air temperature, vapour pressure deficit, soil water potential, soil hydraulic conductivity, and RWU to a depth of 2 m. Analysis of drought responses included data on stem radius, leaf water potential, estimated osmotically active compounds, and drought damage.
Our study reveals an inherent coordination between stomatal regulation, fine root distribution and water uptake. Compared to conifers, the more anisohydric water use of oak and beech was associated with less strict stomatal closure, greater investment in deep roots, four times higher maximum RWU, a shift of RWU to deeper soil layers as the topsoil dried, and a more pronounced soil drying below 1 m depth. Soil hydraulic conductivity started to limit RWU when values fell below 10-3 to 10-5 cm/d, depending on the soil. As drought progressed, oak and beech may also have benefited from their leaf osmoregulatory capacity, but at the cost of xylem embolism with around 50% loss of hydraulic conductivity when soil water potential dropped below -1.25 MPa. Consideration of species-specific water use is crucial for forest management and vegetation modelling to improve forest resilience to drought.

en: anisohydric water-potential water-use-strategy root-distribution stomatal-stringency

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: Water-use strategies of temperate tree species

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

format: XLS

anisohydric

display_name: anisohydric

root-distribution

display_name: root-distribution

stomatal-stringency

display_name: stomatal-stringency

water-potential

display_name: water-potential

water-use-strategy

display_name: water-use-strategy


en:
Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes
From 22-Jun-2020 to 26-Jun-2020, we sampled five sites comprising one low, two intermediate and two high-elevation sites per catchment (Fig. 1a). We visited two catchments per day—one in the morning and one in the afternoon—for a total of ten catchments. All samples per catchment were collected within a maximum four-hour period by three groups of samplers. The intermediate and high-elevation sites were situated along two tributaries leading into the low-elevation site of the river. We used three filters for each relative elevation class and filtered 60 L per relative elevation class. We sampled 30 L per tributary for a combined volume of 60 L at the intermediate and high-elevation sites. In total, 180 L were sampled in total per catchment. A filtration device composed of either the Athena® peristaltic pump (Proactive Environmental Products LLC; 1 L/min nominal flow) or the Subspace® underwater peristaltic pump (Subspace Pictures; 1 L/min nominal flow), combined with a VigiDNA® 0.2 µM cross-flow filtration capsule (VigiDNA, SPYGEN) was used in order to filter a large water volume. We used a finer mesh than the recommended VigiDNA® 0.45 µM cross-flow filtration capsule to maximise the capture of biological material since mountain water does not transport high quantities of sediments. For each filtration capsule, we used disposable sterile tubing. At the end of each filtration, we emptied the water inside the capsules, replaced it with 80 ml of CL1 conservation buffer (SPYGEN), and stored it at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Goldberg et al. 2016; Valentini et al. 2016). Each water sample was processed using disposable gloves and single-use filtration equipment. We used two primer sets targeting vertebrates (Vert01, forward: − TTAGATACCCCACTATGC, reverse: − TAGAACAGGCTCCTCTAG, mean marker length: 97 bp) and spermatophytes (g-h/Sper01, forward: − GGGCAATCCTGAGCCAA, reverse: CCATTGAGTCTCTGCACCTATC, mean marker length: 48 bp). Though both primers are relatively broad with low species-level resolution, we selected them as the goal was to minimise cost and effort and maximise the identification of a broad range of taxa which can represent the species assemblages of the region. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

en: environmental-dna spermatophytes sper01 edna switzerland vertebrates vert01 freshwater

en: Environmental DNA Freshwater Switzerland VaudCatchment Modipl 2020

edna

display_name: edna

environmental-dna

display_name: environmental-dna

freshwater

display_name: freshwater

spermatophytes

display_name: spermatophytes

switzerland

display_name: switzerland

vertebrates

display_name: vertebrates


en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2020)
In October 2020 we chose 16 sites from the 2020 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. All sites were located on the continental shelf (26–170 m depth), except one on the upper slope with a depth of 1045 m. To perform eDNA sampling, we collected water samples at 15 sites (Figure 1a). At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http:
//metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: teleo atlantic-region fish-composition edna dna-metabarcoding chondrichthyes bay-biscay actinopterygii

en: Environmental DNA Marine France Evhoe 2020

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

dna-metabarcoding

display_name: dna-metabarcoding

fish-composition

display_name: fish-composition

teleo

display_name: teleo


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

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

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:
Fish taxonomic, functional and phylogenetic composition variations recovered from eDNA metabarcoding along the coast of Curacao
In February 2020, we collected a total of 20 water samples, from 10 stations, with two filtration replicates per station, in the two investigated coastal areas. Each station consisted of a transect of 2 km at an overall constant distance from the coast. We recorded the GPS coordinates at the start and end of the transect, which we used to map the transect positions. We conducted eDNA sampling by using a filtration device composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 L/min), a VigiDNA® 0.20 μM cross-flow filtration capsule (SPYGEN, le Bourget du Lac, France) and disposable sterile tubing for each filtration capsule. We performed two filtration replicates in parallel on each side of a boat, at each station, for 30 min corresponding to a volume of ~30 L of water filtered by each capsule. At the end of each filtration, the water inside the capsules was emptied, and we filled the capsules with 80 ml of CL1 Conservation buffer (SPYGEN, le Bourget du Lac, France) and stored at room temperature. We followed a strict contamination control protocol in both field and laboratory stages (Valentini et al., 2016). Each water sample processing included the use of disposable gloves and single-use filtration equipment to avoid any risk of contamination. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).

en: curacao marine fish edna fish-composition caribbean-region coral-reefs teleo environmental-dna

en: Environmental DNA Marine Curacao 2020

caribbean-region

display_name: caribbean-region

coral-reefs

display_name: coral-reefs

curacao

display_name: curacao

edna

display_name: edna

environmental-dna

display_name: environmental-dna

fish

display_name: fish

marine

display_name: marine


en:
This dataset contains Community Land Model 5 (CLM5) simulation output over the spatial extent of Switzerland at different resolutions and based on a range of input datasets. It further contains land-use surface data used for the CLM5-simulations.
**Detailed description of the CLM5  simulation setup and the various input datasets  can be found in the accompanying publication: https://doi.org/10.5194/egusphere-2023-1832.**
 CLM5 simulation output
This dataset includes gridded CLM5 simulations of snow depth, gross primary productivity (GPP) and evapotranspiration at different resolutions ( 1km, 0.25° and 0.5°) and based on a range of input datasets over the spatial extent of Switzerland (see folder *gridded_CLM5_simulations*). Additionally, point-scale CLM5 simulations of snow depth and snow-water-equivalent at 36 snow-station locations (see folder *point_scale_CLM5_simulations*) are included. Latitude, longitude and elevation for these station locations can be found in table A1 of the above-mentioned publication. All simulation output spans from 01/01/2015 - 31/12/2019.
Included CLM5 simulation results are based on 3 different meteorological forcing datasets:
* Clim_CRU: standard global dataset, we used the recent state-of-the-art standrd global dataset CRU-JRA (https://catalogue.ceda.ac.uk/uuid/aed8e269513f446fb1b5d2512bb387ad)
* Clim_CRU*: ClimCRU upraded by downscaling temperature data using a temperature lapse rate of -6.5K/1000m and a high-resolution DEM
* Clim_OSHD: highest level of detail, meteorological forcing generated according to methods developed by the Operational Snow Hydrological Service (OSHD), at 1km spatial and 1hour temporal resolution-/li-
 Land-use surface data
This dataset further includes forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution (see folder *surface_landuse_datasets*). For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR), which includes a higher level of detail and is based on a more up-to-date land use datase, are provided. More details on these two datasets can be found in the above-mentioned publication.

en: evapotranspiration oshd land-use land-cover snow high-resolution clm5 forest-productivity snow-simulation

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: Multi-resolution CLM5 simulations across Switzerland

en:
Resource Title: gridded_CLM5_simulations.zip
    Size: 1275381556 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/2a1eed91-e1dd-41dd-993f-8533051685b9/download/gridded_clm5_simulations.zip
    Description: 12 gridded CLM5 simulations over the spatial extent of Switzerland:
- 1km, 0.25deg, 0.5deg
- 3 different meteorological forcings (Clim_CRU, CLIM_CRU*, CLIM_OSHD)
- 2 different land use forcings
each with the following outputs:
- daily snow depth (file SNOW_DEPTH.nc)
- monthly summed gross primary production (file FPSN_MONTH_SUM.nc)
- monthly summed evapotranspiration (file QFLX_EVAP_TOT_MONTH_SUM.nc).
Temporal extent of all simulations: 01/01/2015 - 31/12/2020.

format: ZIP

en:
Resource Title: surface_landuse_datasets.zip
    Size: 127856024 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/bb64e97d-c86d-491a-8671-b3f010812344/download/surface_landuse_datasets.zip
    Description: Forcing land surface datasets used for the CLM5 simulations at 1km, 0.25° and 0.5° resolution. For the 1km resolution both the standard global (LU_Gl) and the high-resolution dataset (LU_HR) are provided.

en:
Resource Title: point_scale_CLM5_simulations.zip
    Size: 4515857 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/5c9bd5b4-baf0-4aa3-83c0-0864f9275f4e/resource/7e90ee76-d274-4add-8f66-d7f75c1f3621/download/point_scale_clm5_simulations.zip
    Description: Point-scale CLM5 simulation output of snow depth and snow water equivalent for 9 different simulation scenarios, each performed at 36 snow station locations across Switzerland. Please have a look at table A1 in the appendix of the linked publication for coordinates of the stations. Additional information on the setup, and the differences between simulation setups can also be found in the linked publication.

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow

display_name: snow

snow-simulation

display_name: snow-simulation


snow-height-classification-dataset

en:
Snow Height Classification dataset provides manually annotated snow height data that can be used for development and evaluation of automatic snow height classification approaches.
A subset of 20 IMIS stations which span different locations and elevations and vary in underlying surface (e.g., vegetation, bare ground, glacier, etc.) were selected and manually annotated with binary two-class ground truth information regarding snow height data:
 * **Class 0 - Snow** - the surface is covered by snow
 * **Class 1 - No Snow** - the surface is snow-free (e.g., vegetation, soil, rocks, etc.)
Data has been annotated with the help of domain experts. It should be mentioned that annotating historical data is problematic, as there is no way of checking whether there really was snow at the station or not. This means that assessing the presence of snow with the help of information from other sensors should be considered a best effort approach.
Besides the annotated snow height data, the dataset also contains additional data which are relevant to reproduce results in the following repository:
[https://gitlabext.wsl.ch/jan.svoboda/snow-height-classification](https://gitlabext.wsl.ch/jan.svoboda/snow-height-classification)
Any further use of the data has to comply with the CC BY-NC license:
[https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)

en: snow-height machine-learning imis snow-depth deep-learning

en: Snow Height Classification Dataset

title_for_slug: snow-height-classification-dataset

envi

en: Environment

en:
Resource Title: snow-height-classification-dataset.zip
    Size: 5658619412 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.512/snow-height-classification-dataset.zip
    Description:

media_type: application/zip

en:
Resource Title: Data Access
    Size: 21474836480 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.512%2Fsnow-height-classification-dataset%2F
    Description:

deep-learning

display_name: deep-learning

imis

display_name: imis

machine-learning

display_name: machine-learning

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height


root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald
Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring
Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest
Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

en: fine-root-traits ingrowth-cores drought belowground-biomass soil-coring

en: Root-traits

title_for_slug: root-traits

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring


en: Urbanization poses threats and opportunities for the biodiversity of wild bees. A main gap relates to the food preferences of wild bees in urban ecosystems, which usually harbour large numbers of plant species, particularly at the larval stage. This data sets describes the larval food of four wild bee species (i.e. Chelostoma florisomne, Hylaeus communis, Osmica bicornis and Osmia cornuta) and three genera (i.e. Chelostoma sp., Hylaeus sp, and Osmia sp.) common in urban areas in five different European cities (i.e. Antwerp, Paris, Poznan, Tartu and Zurich). This data results from a European-level study aimed at understanding the effects of urbanization on biodiversity across different cities and citiscapes, and a Swiss project aimed at understanding the effects of urban ecosystems in wild bee feeding behaviour. Wild bees were sampled using standardized trap-nests in 80 sites (32 in Zurich and 12 in each of the remaining cities), selected following a double gradient of available habitat at local and landscape scales. Larval pollen was obtained from the bee nests and identified using DNA metabarconding. The data provides the plant composition at the species or genus level of the different bee nests of the studied species in the studied sites of the five European cities. For Hylaeus communis, this is the first study in reporting larval food composition.

en: paris osmia-cornuta urban-ecology plant-pollinator-interactions poznan antwerp dna-metabarcoding trap-nest cavity-nesting-bees hylaeus-communis osmia-bicornis chelostoma-florisomne tartu zurich

en: Larval food composition of four wild bee species in five European cities

en:
Resource Title: Larval food composition
    Size: 222187 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/281173e2-361c-4953-8267-20ac6cf61588/resource/549272fe-1219-4eaf-bb06-4e0d130662a6/download/21092021_responses_metabarcoding_clean.csv
    Description:

en:
Resource Title: Information on the study sites
    Size: 14688 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/281173e2-361c-4953-8267-20ac6cf61588/resource/8c2661c3-d559-4820-98e7-e0d3ce3c4f0b/download/16072024_study_sties.csv
    Description: For each site, IDs, city, coordinates, structure where trapnest was attahced and height of the trapnest is provided

en:
Resource Title: Explanation data variables
    Size: 4090 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/281173e2-361c-4953-8267-20ac6cf61588/resource/a1a07896-7189-46b7-9fb7-c10e4f06d6c4/download/readme.csv
    Description:

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich


en:
This dataset includes the FORTRAN code of the FSM2trans model version used in the paper: Quéno et al., Snow redistribution in an intermediate-complexity snow hydrology modelling framework, The Cryosphere, 2024.
The FSM2trans code is derived from the FSM2 model (Essery et al., 2015) and its variant FSM2oshd (Mott et al., 2023). In this model, we implemented and adapted the snowdrift model SnowTran-3D (Liston et al., 2007) and the avalanching model SnowSlide (Bernhardt and Schulz, 2010).
This dataset does not include the processing scripts to prepare meteorological input data for the model, provided as bin files.

en: avalanche snowpack source-code snowdrift snow-modelling

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: FSM2trans code

en:
Resource Title: namelist.zip
    Size: 1490 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/b59836a9-e725-4276-92d2-d3e17efc0966/download/namelist.zip
    Description:

en:
Resource Title: code.zip
    Size: 90894 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/2f7b6697-4863-4ab8-8975-11603ba6dd5e/download/code.zip
    Description:

en:
Resource Title: README.txt
    Size: 957 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d2398461-752f-4984-a944-2e565ed0c1ce/resource/7446d1e9-634a-4da1-b7ef-7ffc28ea61c4/download/readme.txt
    Description:

format: TXT

media_type: text/plain

avalanche

display_name: avalanche

snow-modelling

display_name: snow-modelling

snowdrift

display_name: snowdrift

snowpack

display_name: snowpack

source-code

display_name: source-code


en:
The data was generated during a landscape experiment performed on 69 plots in Sihlwald forest between 2016 and 2019. Branch bundles of different sizes consisting of beech branches were exposed in the forest for one year to be colonized by saproxylic beetles and later reared for one year in emergence traps. All beetles emerging from the branches were collected. Overall 244 branch bundles are included and we found 66 beetles species (23511 individuals) of which 43 were classified as saproxylic (20873 individuals).
 Species data (2 tables)
Two community matrices (including abundance): one for saproxylic beetles and one for all beetles. Beetles were classfied as saproxylic following an extended list of the list reported in Schmidl & Bussler (2004).
 Model data (1 table)
*Response variables*
Species richness and abundance of (saproxylic) beetles.
*Branch bundles*
Branch bundles consisted of 1, 3, 6 or 12 branches and each bundle size was installed at each of the 69 plots. The bundles consisted of standardized freshly cut beech branches (Fagus sylvatica) with a length of 80 cm and a diameter between 3 and 6 cm. Total surface and volume of each bundle is reported.
*Tree on which the bundle was installed*
Information on the tree to which the bundles were attached (tree species, dbh, distance and azimut from the plot center).
*Temperature and light availability*
Temperature (plot level) and light availability (bundle level) were calculated.
*Deadwood availability in the landscape*
Based on a map of lying dead wood, dead wood amount and isolation were calculated for concentric circles with a radius ranging from 20 to 200 m (in 10 m steps) around each branch bundle.
 Variable descriptions (1 table)

en: habitat-heterogeneity sloss colonisation habitat-availability conservation forest-management saproxylic-beetles dead-wood biodiversity

en: Beetle communities reared from beech branches and associated forest and environmental variables

envi

en: Environment

en:
Resource Title: Forest and environmental variables
    Size: 158262 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/66dbaff5-2b06-4e82-9f92-9e40d298f938/download/data_branch_bundles.csv
    Description: Data on the branch bundle, forest and environmental variables

en:
Resource Title: Community matrix (saproxylic beetles)
    Size: 23120 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/1873211d-631c-493e-a998-103395d5de43/download/abundance_saproxylics.csv
    Description: Abundances of saproxylic beetle species for each branch bundle

en:
Resource Title: Community matrix (all beetles)
    Size: 34872 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/30938085-43a4-43f0-bdde-2f57dd557064/download/abundance_all_beetles.csv
    Description: Abundances of all beetle species for each branch bundle

en:
Resource Title: Variable description
    Size: 3005 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/bdc548f5-00b1-4d6b-9b97-13d9016002e4/resource/8113973a-149d-4514-8b03-11201870881c/download/variable_description.csv
    Description: Detailed description of the forest and environmental variables

biodiversity

display_name: biodiversity

colonisation

display_name: colonisation

conservation

display_name: conservation

dead-wood

display_name: dead-wood

forest-management

display_name: forest-management

habitat-availability

display_name: habitat-availability

habitat-heterogeneity

display_name: habitat-heterogeneity

saproxylic-beetles

display_name: saproxylic-beetles

sloss

display_name: sloss


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

en: Environmental layers for SDM simulations (GDPlants)

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

format: TIFF

media_type: image/tiff

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: 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

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: 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_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: 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

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:
This dataset contains all data and R codes (R Development Core Team, https://www.R-project.org) used in the following publication: Donati GFA, Parravicini V, Leprieur F, Hagen O, Gaboriau T, Heine C, Kulbicki M, Rolland J, Salamin N, Albouy C, Pellissier L. "A process-based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted by Ecography in August 2019. When using this data and R scripts the above publication should be cited.
The interaction of habitat dynamics with species dispersal abilities could generate gradients
in species diversity and prevalence of life-history and ecological traits, when the latter are associated with dispersal potential. In this dataset, we use a spatial mechanistic model of speciation, extinction and dispersal, constrained by a dispersal parameter. This model allows to simulate the interplay between reef habitat dynamics over the past 140 million years and dispersal, shaping lineage diversification history and global assemblage composition of over 6000 tropical reef fish species. Global trait distribution data of tropical reef fish are used to evaluate the congruence between simulations and observations.

en: biodiversity reef-fish traits ecology dispersal

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: Simulated and observed prevalence of dispersal-related traits in tropical reef fish assemblages worldwide

envi

en: Environment

en:
Resource Title: Coral reef grid cells (shape, dbf, etc. files)
    Size: 12441 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/7b6a4981-0f00-432c-9ed8-502c43126613/download/grid_4326_files.zip
    Description: Grid cells of 5 × 5°, corresponding to circa 555 × 555 km at the Equator (see Parravicini et al. 2013, Leprieur et al. 2016)

Parravicini, V. et al. 2013. Global patterns and predictors of tropi- cal reef  sh species richness. – Ecography 36: 1254–1262.

Leprieur, F. et al. 2016. Plate tectonics drive tropical reef biodiver- sity dynamics. – Nat. Commun. 7: 11461.

en:
Resource Title:
    Size: 17762 bytes
    Format: application/x-r-data
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/95d1d60f-7dc9-4c51-992e-baaca842c296/download/cong_sim_obs_trait_prop.rdata
    Description: Input for spatial congruence test overlap between proportions of low and high  dispersal and observed low- and high- dispersal-related traits in assemblages (30-50% threshold). see Table 2.

en:
Resource Title: Main text figures
    Size: 15475 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/c0870690-1143-4ac8-957a-2bfd2d6c96e3/download/donati_et_al_dispersal_global_prevalence_traits_figures_main_text.r
    Description: R Script used for figures in main text in: Donati et al. 2019: "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019.

en:
Resource Title: Global species distribution of tropical reef fish species
    Size: 3224423 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/f554c199-621c-4c60-9566-e3ae1d9479b0/download/fishnet_gaspar_code.csv
    Description: Each species corresponds to a "Gaspar_code" gathered from the General Approach to Species Abundance Relationships (GASPAR) database (Kulbicki et al. 2013, Parravicini et al. 2013) and is linked to a specific Fishned ID corresponding to a specific Latitude and Longitude.

en:
Resource Title: Global simulated distribution of species under a range of dispersal parameter values
    Size: 30514436 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/471350ea-cbf8-409e-a8cc-55a84fe4a8cd/download/matrix_sim_sprichness.txt
    Description: Global distribution of simulated species richness under a range of dispersal parameter values d
d ∈ [1.75°: 5.45°].

en:
Resource Title: Simulated rates of speciation and extinction under a range of dispersal parameters.
    Size: 8135 bytes
    Format: application/x-rds
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/3b9df6ee-3cc3-4760-a51c-8241db1fa78c/download/rates.rds
    Description: Simulated rates of speciation and extinction under a range of dispersal parameters. Net diversification rates are calculated from the difference between speciation and extinction rates. This data allows the creation of Figure A4 in Supporting information, Appendix 1.

en:
Resource Title: Tropical reef fish trait data
    Size: 428195 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/a5227230-5514-4bdc-b81d-b38d5aaea5cb/download/sp_ecological_trait_data.csv
    Description: Species trait (i.e. adult body size, home range mobility behaviour, circadian activity and schooling) data gathered from the General Approach to Species Abundance Relationships (GASPAR) database (Kulbicki et al. 2013, Parravicini et al. 2013).

Kulbicki, M. et al. 2013. Global biogeography of reef  shes: a hier- archical quantitative delineation of regions. – PLoS One 8: e81847.

Parravicini, V. et al. 2013. Global patterns and predictors of tropi- cal reef  sh species richness. – Ecography 36: 1254–1262.

To complement the trait data with Pelagic Larval Duration information refer to the following publication:

Luiz, Osmar J., et al. "Adult and larval traits as determinants of geographic range size among tropical reef fishes." Proceedings of the National Academy of Sciences 110.41 (2013): 16498-16502.

In Donati et al. "A process-based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography in August 2019, we used the PLD gathered from Luiz et al. 2013 as described in the methods - section "Species trait data".

en:
Resource Title: Functions used in R scripts in: Donati et al. 2019 "A process-based-model supports an association between  # dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019
    Size: 8444 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/eed003d7-c661-42ab-bafb-c2fd2290d94e/download/donati_et_al_dispersal_global_prevalence_traits_functions.r
    Description: Functions for Figures illustrated in Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019.

en:
Resource Title: Input for the Global distribution maps for proportions of species richness for (a) simulated dispersal parameter value (b) observed dispersal-related traits
    Size: 45638 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/2115cb5b-7557-4897-8892-f109a15eb0c1/download/grid_pl_sim_obs_trait_prop_cong.csv
    Description: Geographic distribution data (species richness and proportions of high/low dispersal-related traits) on predominantly low dispersing and high dispersing species expected based on the simulations, and those where low- and high- dispersal related traits values are observed for the five investigated traits.

en:
Resource Title: Global coast files from https://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html
    Size: 566907 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/a14c6b25-180d-42d8-a863-e13574487a03/download/coast_files.zip
    Description: Global coast files from https://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html used in the Figures

en:
Resource Title: Donati et al. main script
    Size: 9040 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/e00d3cf8-4845-4de0-8eb6-33243506c274/download/donati_et_al_dispersal_global_prevalence_traits_main.r
    Description: Main script used in : Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages"
accepted in Ecography, August 2019

en:
Resource Title: Dispersal parameter value d per simulation
    Size: 124575 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/f895d8b6-3eff-4479-892b-8cc86b476a22/download/d_param_sim.txt
    Description: Dispersal parameter value d per simulation starting with a minimum dispersal value, where each species is able to colonise each adjacent cell, and ending with the value of d for which all the extant habitats, including the most remote Pacific islands, have been colonised (d ∈ [1.75°: 5.45°]).

en:
Resource Title: Supplementary material Appendix 1 Figures
    Size: 26270 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/6b06ad48-bd85-47a8-b478-0850b6def1a4/resource/2946e2c8-9f5c-4ed8-bce2-13069fcb6faf/download/donati_et_al_dispersal_global_prevalence_traits_figures_supp_mat.r
    Description: Supplementary material Appendix 1 Figures illustrated in Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages". accepted in Ecography, August 2019

dispersal

display_name: dispersal

ecology

display_name: ecology

reef-fish

display_name: reef-fish

traits

display_name: traits


en:
We conducted consecutive loading-relaxation experiments at low strain rates to study the viscoplastic behavior of the intact ice matrix in snow. The experiments were conducted using a micro-compression stage within the X-ray tomography scanner in the SLF cold laboratory.
Next, to evaluate the experiments, a novel, implicit solution of a transient scalar model was developed to estimate the stress exponent and time scales in the effective creep relation (Glen's law). The result reveals that, for the first time, a transition in the exponent in Glen's law depends on geometrical grain size. A cross-over of stress exponent $n=1.9$ for fine grains to $n=4.4$ for coarse grains is interpreted as a transition from grain boundary sliding to dislocation creep.
The dataset includes compression force data from 11 experiments and corresponding 3D image data from tomography scans.

en: microstructure x-ray-tomography snow-mechanics slow-snow-compression-experiments ice

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: A grain-size driven transition in the deformation mechanism in slow snow compression

en:
Resource Title: README
    Size: 2225 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2fbce191-4283-4b68-aa4c-ad90723146ed/resource/a23d3947-513f-47dc-aba2-a56fd8b4afcf/download/readme.txt
    Description: README file gives an overview of the organization of the data

en:
Resource Title: slow snow compression experiments
    Size: 96297572 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2fbce191-4283-4b68-aa4c-ad90723146ed/resource/faca29b9-a95f-4f86-a3f9-1bf7faedab29/download/2023_slow_snow_compression_paper_envidat.zip
    Description: Compression experiments, X-ray images and with supplemented README file

ice

display_name: ice

microstructure

display_name: microstructure

slow-snow-compression-experiments

display_name: slow-snow-compression-experiments

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography


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

envidat

en: EnviDat: the Environmental Data Portal

en: Lake climate change scenarios CH2018

envi

en: Environment

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.

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.

climate-change

display_name: climate-change

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


en:
Background information
The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Long-term monitoring of the large-scale high-elevation afforestation has generated data about tree growth, survival, and vitality. In addition, detailed characteristics of the microsite conditions of the research were conducted. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone.
 Experiment description
The Stillberg afforestation experiment was established in 1975 by planting 92,000 seedlings of *Larix decidua*, *Pinus cembra* and *Pinus mugo* ssp. *uncinata* in the alpine treeline ecotone. The afforestation site is located on a northeast-facing slope with steep, topographically highly structured terrain and covers elevations from 2075 to 2230 m a.s.l. The afforestation site was divided into 4052 square plots of 3.5 × 3.5 m, arranged in a regular species-alternating pattern over the whole area. Each plot contained 25 trees of one species (1350 plots per species), and the seedlings were systematically planted 70 cm apart. The trees have been monitored since 1975. Specifically, tree mortality was assessed annually from 1975 until 1995 and has been documented every ten years since then, with surveys in 2005 and 2015 (the next survey is due in 2025). Height of the surviving trees was measured in 1975, 1979, 1982, 1985, 1990, 1995, 2005, and 2015. In 1995, 2005, and 2015, drivers of tree vitality were assessed for a subset of trees per plot. Additionally, an extensive set of environmental parameters characterizing microsite conditions of the afforestation area were recorded before and after the planting of the trees.
 Data description
The five datasets from the afforestation experiment comprise ecological and environmental data from the main afforestation experiment in five datasets with accompanying metadata (Stillberg_afforestation_all_metadata.xlsx). All data and metadata files are bundled in a ZIP-file (Stillberg_afforestation_v1.zip). In particular, a first dataset contains environmental data characterising microsite conditions of the 4000 plots with regard to soil, topography, vegetation and microclimatic conditions (Stillberg_afforestation_plot_data_v1.csv; Stillberg_afforestation_plot_metadata_v1.csv. In each plot, the natural tree regeneration was assessed by counting seedings of several tree species in 2005 and 2015 (Stillberg_afforestation_regeneration_data_v1.csv; Stillberg_afforestation_regeneration_metadata_v1.csv). Furthermore, specific information about each of the 92’000 planted trees of the tree species is available (Stillberg_afforestation_tree_parameter_data_v1.csv; Stillberg_afforestation_tree_parameter_metadata_v1.csv). Survival data for each of the 92’000 individual trees can be found in a separate dataset (Stillberg_afforestation_tree_survival_data_v1.csv; Stillberg_afforestation_tree_survival_metadata_v1.csv). Tree growth and vitality parameters are available for all trees from 1995, and for subsets of trees for 2005 and 2015 (Stillberg_afforestation_tree_measurements_data_v1.csv; Stillberg_afforestation_tree_measurements_metadata_v1.csv).

en: afforestation stillberg long-term-experiment mountain-forest treeline

en: Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline


en: This repository contains PMCMx-UF model outputs used for the paper: D. Patoulias K. Florou S. N. Pandis and A. Nenes: New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale, Geophysical Research Letters,  in review, 2023.

en: modeling cloud-droplets pmcamx-uf total-number nucleation

en: Dataset for the publication New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale

cloud-droplets

display_name: cloud-droplets

modeling

display_name: modeling

nucleation

display_name: nucleation

pmcamx-uf

display_name: pmcamx-uf

total-number

display_name: total-number


en:
Data and scripts of publication:
Madleina Gerecke, Oskar Hagen, Janine Bolliger, Anna M. Hersperger, Felix Kienast, Bronwyn Price, Loïc Pellissier (2019) Assessing potential landscape service trade-offs driven by urbanization in Switzerland. Palgrave communications.
Contains land use projections for Switzerland and scripts and data for these projections as well as the calculation of landscape services.
Data Folder:
Contains sub-folder with the data necessary for this study (provided were no copyright issues, otherwise placeholders with descriptions), and folders where produced data may be stored
Scripts Folder:
Contains scripts organized into subfolders depending on their purpose
Note: Some abbreviations within the scripts and data are derived from German words and not English.

en: switzerland modeling land-use-change urbanization landscape-services land-use statistical-model

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: Land use projections and services for Switzerland

en:
Resource Title: Scripts for Assessing potential landscape service trade-offs driven by urbanization in Switzerland
    Size: 72256 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c259ac71-37ea-477e-94b0-c463cc195304/resource/062e679c-5d1b-4733-8d91-4caca049816f/download/scripts.zip
    Description: Scripts ordered by their main purpose within sequential folders in this ReadMe marked with ##

Within the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with #

## 00_Function Scripts ##
# Functions.r
Script containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS

# Service_functions.R
Script containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters

## 01_Data Preparation ##
# A_AS_raster_preparation.R
Preparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all "construction sites" for calibrating the models
For model projection starting point (2009) and for service calculations (all ASCH years) the "other" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells
Creation of water & mountainous area raster that stayed stable throughout the projections
Creation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other

# B_Factors_preparation.R
Preparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk

# B_Predictors_preparation.R
Preparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)

# B_Regions_preparation.R
Preparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region

# C_Pred_proj.R
Projecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; more detailed extrapolation of temperature (based on data for all stations that matched between the temp table we used for the calibration period and the projections from CS2M, and then making a spatial interpolation for all years based on the interpolation of temperature for all years per station)

## 02_Model calibration ##
# A_Bioreg_pred_corr.R
Calculating correlation between the predictors for each bioregion and land use category, Output are those with too high correlation so that one predictor can be removed from transitions were both predictors occur

# A_trans_numbers_bioreg.R
Calculate transition numbers for each bioregion to decide which transitions to primarily consider

# B_Bioreg_ext_eval.R
Calculating TSS based on the external evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 85-97, evaluation data: 97-09)

# B_Bioreg_int_eval.R
Calculating TSS based on the internal evaluation for the bioregion transitions that happened often enough to try to model them (calibration data: 70%, evaluation data: 30%)

# C_Bioreg_TSS_analysis.R
Extracting TSS numbers from internal and external evaluation, calculating mean and median for each transition for each region for each evaluation method and saving as csv per region to be able to select only the transitions with high enough model performance

# D_Bioreg_Models_for_prediction.R
Calibration of the models that were then used to project land use transitions into the future; calibrated separately for each bioregion

# E_Residuals_trans_models.R
Calculation of Moran's I statistics to analyze the residuals of the land use transition models

## 03_Projections ##
# A_Bioreg_Projections_run.R
Master script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step

## 04_Service calculation ##
# A_Bioreg_as_services.R
Calculate services per bioregion for years 1985, 1997, 2009

# A_Service_calculation_bioregions.R
Extracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; can be run for swiss wide projections or regional ones

## 05_Analysis ##
# A_Bioreg_ASCH_development.R
Extracting the occurrence of each category per region for all runs (first part), then for ASCH years, and then plotting them nicely; only works for regional projections

# A_Bioreg_Predictors_importanceD2.R
Calculating D2 for each transition and each considered predictor from bivariate models to get value of importance

# B_Bioreg_Pred_imp_analysis.R
Using calculated D2 to sort Predictors according to their importance for each transition

# A_Bioreg_Spatial_results_analysis.R
Plotting randomly sampled runs for ASCH and services to analyses their spatial development

# A_Bioreg_Transition_numbers_check_v1.R
Analyzing the frequency for all transitions for all regions and producing the point plots for each transition separately

# A_Bioreg_Transition_numbers_check_v2.R
Analyzing percentage and numbers of all transitions but plotting them per region and originating ASCH category

# B_Transition_Analysis.R
Further Analysis of transition numbers

# A_Service_analysis.R
Plotting of the service development for bioregions in several ways for analyzing

en:
Resource Title: Data for Assessing potential landscape service trade-offs driven by urbanization in Switzerland
    Size: 4119284 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c259ac71-37ea-477e-94b0-c463cc195304/resource/3f13ea3a-3dd2-48a3-98a1-284b565b2c2d/download/data.zip
    Description: The provided folder structure follows the set up of the scripts.
Data is only provided when it has been fully produced by us, otherwise dummies are given.
For data that will be produced by one of the scripts, no dummies are given.
The folders may contain sub-folders, which would be filled if the scripts were all run

## 00_Analysis_Data
Data produced throughout the process of the calibration and projection that is later needed for analysis

## 01_Raw_Data
Primary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation

## 02_Prepared_Data
Data that will be prepared for further use by scripts are put in here
Additionally it contains the parameter sheets for the transition predictors that we compiled

## 03_Model_Data
# Model outputs
Folder were the projection models statistics will be saved
# Models
Folder into which the actual transition models will be saved
# Residuals
Folder into which data on models residuals will be saved for future use

## 04_Projected_Data
The output of the projections will be saved into this folder

## 05_Service_Data
Any service calculations will be saved in here

## 06_Results_Analysis
Any Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

statistical-model

display_name: statistical-model

urbanization

display_name: urbanization


en:
Background information
The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Over almost fifty years, research at the Stillberg site combined long-term monitoring of the large-scale high-elevation afforestation with experimental manipulations simulating global change impacts. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone across different compartments and scales, from individual trees, non-tree vegetation and soils to whole ecosystems, in the context of global change resulting in more than 150 publications.
 Dataset generation
We compiled a comprehensive list of scientific publications covering research at the Stillberg research site by conducting searches in the literature databases Web of Science and Google Scholar, as well as in the Digital Object Repository of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL (DORA). We compiled all publications about the afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, the G-TREE experiment, as well as other studies related to the Stillberg research site.
 Data description
The Stillberg bibliography (Stillberg_bibliography_data_v1.csv) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals. Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title. The bibliography is described in a metadata file (Stillberg_bibliography_metadata_v1.csv). The bibliography along with the metadata file are provided in a ZIP-folder (Stillberg_bibliography_v1.zip).

en: mountain-ecology treeline-ecosystems stillberg long-term-experiment literature-review

envidat

en: EnviDat: the Environmental Data Portal

en: Bibliography of the long-term treeline research site Stillberg, Switzerland

literature-review

display_name: literature-review

mountain-ecology

display_name: mountain-ecology

treeline-ecosystems

display_name: treeline-ecosystems


en: Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017.

en: environmental-gradients herbivores-communities community-indices functional-traits elevation alps plant-herbivore-interactions

en: Above- and below-ground herbivore communities along elevation

envi

en: Environment

en:
Resource Title: Nematode surveys
    Size: 13302 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/b564230b-cfea-4587-84b7-06fe299995af/download/nematode_surveys.txt
    Description: Surveys of soil nematode along elevation

en:
Resource Title: Plant traits
    Size: 25166 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/6da02cea-6955-4d5d-b389-85e24cda8a93/download/plant_traits.txt
    Description: Plant functional traits (SLA, LDMC, carbon and nitrogen content, punch strenght; averaged by species)

en:
Resource Title: Study sites
    Size: 1120 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/5f605109-b59f-40cd-aa3f-804623828d36/download/study_sites.txt
    Description: Coordinates and elevation of the study sites

en:
Resource Title: Orthoptera traits
    Size: 3646 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/083b639b-9a30-4d58-bb15-2e6965c72271/download/orthoptera_traits.txt
    Description: Orthoptera functional traits (incisive mandibular strength averaged by species)

en:
Resource Title: Vegetion surveys
    Size: 115943 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/a2f466e2-1eb8-4436-a0cb-8dd3387243bd/download/vegetation_surveys.txt
    Description: Species inventories of plants

en:
Resource Title: Orthoptera surveys
    Size: 17366 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2e5114d6-4dee-4dc9-8bf7-434425af15a7/resource/f877bfcd-df8c-4059-bdca-0176154eeb02/download/orthoptera_surveys.txt
    Description: Species inventories of Orthoptera

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions


en:
Background information
The Stillberg ecological treeline research site is located in the transition zone between the relatively humid climate of the Northern Alps and the continental climate of the Central Alps. In 1975, 92,000 seedlings of the high-elevation conifer species *Larix decidua* Mill. (European larch), *Pinus cembra* L. (Cembran pine), and *Pinus mugo* ssp. *uncinata* (DC.) Domin (mountain pine) were systematically planted across an area of 5 hectares along an elevation gradient of about 150 metres, with the aim to develop ecologically, technically, and economically sustainable afforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Alongside the ecological long-term monitoring of the afforestation, several meteorological stations have recorded local meteorological conditions at the Stillberg research site. Here, we provide the Davos Stillberg meteorological timeseries of five stations from 1975 (01-01-1975), the year of the afforestation establishment, until the end of the year 2022 (31-12-2022).
  Station description
The five meteorological stations were all installed at the same location (46°46′25.015″N 9°52′01.792″E) at 2090 m a.s.l., in the lower part of the afforestation area. In general, the five stations were operated sequentially (Stillberg_meteo_metadata_stations_v1.csv). However, there are some overlapping time periods when more than one station was operated in parallel. The stations have recorded environmental parameters, such as air and soil temperature, dew point temperature, air pressure, relative humidity, wind direction and velocity, radiation, precipitation, and snow depth (Stillberg_meteo_metadata_parameters_v1.csv). The meteorological measurements were recorded hourly from 1975 until 1996 and have been recorded in 10-minute intervals since 1997.
 Data description
We processed the Davos Stillberg meteorological timeseries with the MeteoIO meteorological data pre-processing library (Bavay & Egger, 2014). Data files are provided for each station and quality level separately and named according to the station (see ‘Stillberg_meteo_metadata_stations_v1.csv’). From the raw data in their original formats, we generated three data quality levels: raw standardized (folder ‘raw_standardized’), edited (folder ‘raw_edited’) and filtered (folder ‘filtered’). The processing level is indicated in the headers of the data files. The whole processing protocol is described in a set of human-readable configuration files that are used by MeteoIO to generate the required data quality levels. This improves long-term reproducibility (Bavay et al., 2022), as the data could be regenerated in the future, even using a completely different software, to account for additional data points or to introduce new data corrections. The first quality level (raw standardized) is generated by parsing the original data files and interpreting them in order to convert all data points to a common format and meteorological parameter naming scheme, while excluding unreadable or duplicated data lines. The generated data files are derivatives of CSV files, with a standardised header that contains the metadata that are necessary to interpret and use the data (use metadata) and to populate a data index (search metadata). The latter is a textual implementation of the Attribute Convention for Data Discovery (ACDD) metadata standard (Attribute Convention for Data Discovery 1-3, 2022). The second quality level (edited) builds on the raw data by performing low-level data editing, such as removing some data periods that are known to be unusable (often based on maintenance records or anecdotal evidence) or applying undocumented calibration factors (for example, when there seems to be an obvious offset on a measured parameter for a period between two documented maintenance operations). The third quality level is generated by applying statistical filters on the data (per station and per meteorological parameter) to exclude presumably wrong values. We did not perform gap filling, as no single strategy could be relied upon that would work best for all possible data usage scenarios.

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

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

en:
Resource Title: Stillberg_meteo_v1.1.zip
    Size: 137597369 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/e29d869c-bb1e-422a-bb6a-93738ac15539/download/stillberg_meteo_v1.1.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v1.1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

en:
Resource Title: Stillberg_meteo_v2.0.zip
    Size: 256217522 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/78cb26bb-7d1d-4dce-a0a9-04082c984033/download/stillberg_meteo_v2.0.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v2.0.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological resea...

en:
Resource Title: Stillberg_meteo_v1
    Size: 69344042 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/64667eef-ac6d-416c-b05b-1bbd9850fe18/resource/590394ac-fb28-4033-8edf-42245f219cce/download/stillberg_meteo_v1.zip
    Description: The Davos Stillberg meteorological data (Stillberg_meteo_v1.zip) consists of timeseries from five meteorological stations operated at the Stillberg treeline ecological research site. Metadata are provided in the folder 'Stillberg_meteo_metadata' and the data in the folder 'Stillberg_meteo_data' with subfolders for the three quality levels 'raw_standardized', ‘raw_edited’, and ‘filtered’.

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

treeline

display_name: treeline

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed


en:
License: GPL-v2
The R script presents an advanced sampling approach for monitoring biodiversity on agricultural land by combining multiple objectives and integrating environmental and geographic space.
The example demonstrates the first-stage selection of squares (km2) in the ALL-EMA sampling design using modern sampling techniques such as unequal probability sampling with fixed sample size, balanced sampling, stratified balancing and geographic spreading. Sampling is done with unequal probabilities and weights defined by power allocation to give equal weight to extrapolations to the total agricultural area of Switzerland and two stratifications of predefined interest (regions and agricultural production zones). Calibration is used to limit the distribution of the sampling weights. The sample sizes are almost fixed within the strata and evenly distributed across the years of a temporal rotation plan, which is favourable for the organisation of the field survey. Sampling also ensures an optimal (annual) distribution across geographic space, including altitude. Despite the complexity of the sampling, estimation based on probability theory is straightforward.
Ecker, K.T., Meier, E.S. & Tillé, Y. 2023. Integrating spatial and ecological information into comprehensive biodiversity monitoring on agricultural land. Environmental Monitoring and Assessment 195.

en: multi-stage balanced-sampling unequal-probability habitat vegetation

envidat

en: EnviDat: the Environmental Data Portal

en: R script and input data for "ALL-EMA sampling design"

en:
Resource Title: R script
    Size: 10670 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/0b303fb7-17fc-4910-af8f-dbee54c0d093/resource/2fa8e0c9-acbb-4a25-bb8e-79c76908a3b7/download/sample_selection_s1.r
    Description:

en:
Resource Title: data
    Size: 22605 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/0b303fb7-17fc-4910-af8f-dbee54c0d093/resource/89264e93-545c-4794-b6eb-46247ec92310/download/s0.csv
    Description:

balanced-sampling

display_name: balanced-sampling

habitat

display_name: habitat

multi-stage

display_name: multi-stage

unequal-probability

display_name: unequal-probability

vegetation

display_name: vegetation


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

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

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

envi

en: Environment

en:
Resource Title: Coordinates data
    Size: 70111 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/a3df4cb0-7f75-46e5-ae50-ffc0c2fa2a7a/download/coordinates_data.xlsx
    Description: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en:
Resource Title: Grid point nomenclature
    Size: 16191 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/af731be9-f29a-4ff3-89a4-d7c042cde321/download/grid_point_nomenclature.xlsx
    Description: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.   Each point marks the location of snow depth measurements and co-located canopy structure parameters.

en:
Resource Title: Snow depth data forest sites
    Size: 326390 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/4a465ad6-8cc2-440b-b211-a4b68b37adde/download/hs_data_forest.xlsx
    Description: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en:
Resource Title: Meteo data to drive FSM2 model
    Size: 730523 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/f03a1a6e-261c-4d63-b516-e722ebb0ca8d/download/meteo_data.zip
    Description: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

en:
Resource Title: Snow depth data open sites
    Size: 18865 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/cf970b76-a538-4b2b-b478-d8458dbec9cf/download/hs_data_open.xlsx
    Description: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en:
Resource Title: Canopy data
    Size: 383962 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5369a1d1-dbdd-4397-8409-8b7105b79e8b/resource/11c64977-4469-4786-93e1-d8f0a897bbc9/download/canopy_data.xlsx
    Description: Includes all canopy structure metrics computed at all surveyed locations

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling


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

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

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

en:
Resource Title: Daily-Snowmelt.Lysimeter-solute-and-isotope-database_Version1
    Size: 3017002 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/d234a921-9000-4ffc-b723-a663d390b9f8/resource/db3801e0-1b14-4290-ab6a-3f1148e9e0ed/download/envidat-daily.isotope.solute.database.alptal-ch-18.07.2019_level02.xlsx
    Description: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution.  10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
Resource Title: Daily-Snowmelt.Lysimeter-solute-and-isotope-database_Version2
    Size: 42211381 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/d234a921-9000-4ffc-b723-a663d390b9f8/resource/cb7620a7-6854-4dd9-b11d-290395d64f4b/download/lysimeterdatabase.alptal-ch_27062019_level02.xlsx
    Description: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution.  10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes


en:
This dataset contain measurements of solute and stable water isotopes in stream water and precipitation in the Alp catchment and two of its tributaries (between 2015 -2018) . The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.  The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (precipitation rates, discharge) at daily intervals from several sampling locations.
An updated version of the isotope dataset is available here: https://www.doi.org/10.16904/envidat.242

en: precipitation spatially-distributed-sampling stable-water-isotopes geochemical-solutes stream-water

envidat

en: EnviDat: the Environmental Data Portal

en: Daily data of solute and stable water isotopes in stream water and precipitation in the Alp catchment, Central Switzerland

en:
Resource Title: Daily-solute-and-isotope-database_Version_2
    Size: 3017011 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/53f4e1d8-506e-403d-b874-e294c6e8b2eb/resource/2a929c69-5e6e-4c10-a284-08798e5354f7/download/envidat-daily.isotope.solute.database.alptal-ch-18.07.2019_level02.xlsx
    Description: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added. Date: 18.07.2019

en:
Resource Title: Daily-solute-and-isotope-database_Version1
    Size: 3080831 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/53f4e1d8-506e-403d-b874-e294c6e8b2eb/resource/7ae45f32-4411-4ad9-ac84-fd8f28dfc933/download/01.daily.isotope.solute.database.alptal-ch-13.05.2019_envidat.xlsx
    Description: The dataset contains daily measurements of volumes, isotopes and solutes of stream water as well as precipitation measured several locations; meteorological variables are added.

geochemical-solutes

display_name: geochemical-solutes

precipitation

display_name: precipitation

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stream-water

display_name: stream-water