en:
Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport.
A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination.
Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the "helicopter" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based.
Road transport was investigated using network analysis, based on the data set "Forest access roads 2013" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account.
Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the "helicopter" category or transport with trucks under 26 tons).
The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland.
The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php)
Input data used:
- Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016).
- NFI forest mask, 10 m resolution (2015)
- Digital elevation model, 10m resolution (based on swissALTI3D 2016)
- Slope map, 10m resolution (based on swissALTI3D 2016)
- Soil suitability map, 10m resolution (based on soil suitability map BFS 2000)
- Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)

en: switzerland forest-accessibility forest wood-extraction wood-harvesting forest-roads economic-efficiency timber-transport

en: Accessibility of the Swiss forest for economic wood extraction (2021)

en:
Resource Title: Data Request "Extraction Method"
    Size: 28660858 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/e57bf80a-9c2b-40d5-8938-5b9dad24549b/download/maperntemethoden_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the most suitable extraction method for wood in the Swiss forest

en:
Resource Title: Data Request "Forest Accessibility"
    Size: 23228715 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/47871f44-7c5c-452e-b755-ff5643abb853/resource/b1a225d8-9db7-4a62-9d6a-224673f88b01/download/mapguete_merge_lv95_cog2.tif
    Description: Raster map (10m resolution) of the overall suitability of the Swiss forest for economic wood extraction and transport

economic-efficiency

display_name: economic-efficiency

forest

display_name: forest

forest-accessibility

display_name: forest-accessibility

forest-roads

display_name: forest-roads

switzerland

display_name: switzerland

timber-transport

display_name: timber-transport

wood-extraction

display_name: wood-extraction

wood-harvesting

display_name: wood-harvesting


$oid: OBSOLETE

en:
A rule-based algorithm [(Schwieder et al., 2022)](https://doi.org/10.1016/j.rse.2021.112795) was used to produce annual maps for 2018–2021 of grassland-management events, i.e. mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite time series. All satellite images were processed with the [FORCE](https://force-eo.readthedocs.io) framework.
The resulting maps provide information on the number and timing of grassland-management events at a spatial resolution of 10 m × 10 m for the whole of Switzerland. For the final maps, permanent grasslands were masked using a variety of land-use layers, according to [Huber et al. (2022)](https://doi.org/10.1002/rse2.298) but replacing the crop mask with the agricultural-use data from the cantons.
We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further tested the ecological relevance of the generated intensity measures in relation to nationwide biodiversity data (see [Weber et al., 2023](https://doi.org/10.1002/rse2.372)).
The webcam-based reference data used for verification was subsequently added on 14.02.2024.

en: remote-sensing land-use landsat management use-intensity grassland mowing sentinel-2

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: Grassland-use intensity maps for Switzerland

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: Readme
    Size: 3433 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/06c9bd5e-ae9c-4c7f-9b29-2849a3aa971b/download/readme.txt
    Description: Metadata and description of the maps and webcam-based reference data.

format: TXT

media_type: text/plain

en:
Resource Title: Grassland-use intensity map 2020
    Size: 2252728445 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/2a301048-a736-442d-980e-852006dc61bb/download/grassland-use_intensity_2020_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2020. See readme file for more details.

format: TIFF

media_type: image/tiff

en:
Resource Title: Preview time of 1st grassland management event 2020
    Size: 2634652 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/eeb08550-52de-4be6-aac9-d8daed43a51f/download/preview_time_of_1st_management_event_2020.png
    Description: Spatial distribution of the timing (day of year; DOY) of the first management event for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the timing of the first event of the year (Weber et al., 2023; IN REVIEW)

format: PNG

media_type: image/png

en:
Resource Title: Webcam-based reference data
    Size: 57563 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/7561f6b0-7e0b-4b99-ad30-bd247546cf3a/download/webcam_reference_data.zip
    Description: Webcam-based reference data from 2020 and 2021 (see readme).

format: ZIP

media_type: application/zip

en:
Resource Title: Preview number of grassland management events 2020
    Size: 2192445 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/58dfd5b4-86d2-434b-932e-8857dcfacdf2/download/preview_number_of_management_events_2020.png
    Description: Spatial distribution of the number of management events for Switzerland and for three zoomed-in regions (a, b, c). The three zoomed-in regions show different grassland-use intensities, which are reflected in the distribution of management frequency (Weber et al., 2023; IN REVIEW)

en:
Resource Title: Grassland-use intensity map 2018
    Size: 2244278154 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/a5da6789-de78-42d5-be38-c1d9daff7cff/download/grassland-use_intensity_2018_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2018. See readme file for more details.

en:
Resource Title: Grassland-use intensity map 2019
    Size: 2202043962 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/fdfed95b-c1c7-4842-9329-896bbbfe1c17/download/grassland-use_intensity_2019_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2019. See readme file for more details.

en:
Resource Title: Grassland-use intensity map 2021
    Size: 2201662465 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/889019e0-7c66-406c-a061-b2e4ab96e5ad/resource/9d8f0f98-b7f9-434a-b711-70e864ec7703/download/grassland-use_intensity_2021_ch_10m_32632_v1_0.tif
    Description: Raster stack with information on the number and timing of grassland-management events (i.e. mowing, grazing) at a spatial resolution of 10 m × 10 m for the whole of Switzerland for 2021. See readme file for more details.

grassland

display_name: grassland

land-use

display_name: land-use

landsat

display_name: landsat

management

display_name: management

mowing

display_name: mowing

remote-sensing

display_name: remote-sensing

use-intensity

display_name: use-intensity


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 stomatal-stringency water-potential water-use-strategy root-distribution

en: Water-use strategies of temperate tree species

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:
This dataset provides distribution data of fungi in Switzerland of the National Data and Information Centre, called  [SwissFungi](https://swissfungi.wsl.ch/en/index.html). SwissFungi is a partner of [InfoSpecies](https://www.infospecies.ch/de/), the network of Swiss data and information centres for [fauna](http://www.cscf.ch/cscf/de/home.html), [flora](https://www.infoflora.ch/en/) and [fungi](https://swissfungi.wsl.ch/en/index.html). One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.
The SwissFungi database currently contains more than 670'000 geo-referenced fungi observations, distributed throughout Switzerland. The oldest observations date back to 1770. A large portion of the records are from the last two decades of the last century to the present day. The database is continuously updated with new fungi records. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from the literature.
The data from the distribution atlas of fungi in Switzerland are available for research and practice (nature conservation projects, environmental impact assessments etc.) and can be obtained via an [application form](https://www.infospecies.ch/de/assets/content/documents/Formular_Datenanfrage20190625.pdf). Please note the tariffs for data requests and submit your request directly to the [InfoSpecies](https://www.infospecies.ch/de/) office. Applications are usually answered within two working weeks. Details on the use of data are regulated in the current guidelines of the national data centers. Please note that the data center SwissFungi is not able to verify all incoming fungal records completely for a correct identification or coordinate errors and therefore cannot guarantee the correctness of the information.
License under [InfoSpecies](https://www.infospecies.ch/de/). Data is free of charge for research projects and available on request.

en: fungi-conservation records-database national-data-center swissfungi fungi biodiversity

en: SwissFungi - Records Database for the Fungi of Switzerland

format: CSV

biodiversity

display_name: biodiversity

fungi

display_name: fungi

fungi-conservation

display_name: fungi-conservation

national-data-center

display_name: national-data-center

records-database

display_name: records-database

swissfungi

display_name: swissfungi


en: The reaction of ozone with bromide in polar regions results in the formation of reactive bromide species with impacts on ozone budget and the oxidative capacity of the lower atmosphere. Here, we present a data investigating the temperature dependence of bromide oxidation by ozone using a coated wall flow tube reactor coated with an aqueous mixture of citric acid and sodium bromide, a proxy for sea salt aerosol in snow or the free troposphere. Thus study shows the effect of of organic species at relatively mild temperatures between the freezing point and eutectic temperature as typical for Earth's cryosphere.

en: snow sea-salt-aerosol antartic polar arctic cryosphere laboratory-study

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: Kinetic experiments on the oxidation of bromide by ozone from 289-245 K.

en:
Resource Title: Experimental Results: Uptake coefficients vs. temperature and ozone concentration
    Size: 1422 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8c77d71e-155b-40ab-a446-ae2dccac9740/resource/af7e17ca-b08b-48d2-8198-621ec0814252/download/dataenivdat.csv
    Description: * Final Data to Figure 3: Uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.
* Final Data to Figure 6: Uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

The average ozone uptake coefficients of the three cycles between the bypass and the flow tube per repeat is taken as the mean uptake coefficient for each experiment. Gamma was corrected for gas phase diffusion limitation following the Cooney–Kim– Davis (CKD) method52 (see supporting material of publication for details).

media_type: text/csv

en:
Resource Title: Experimental results of uptake coefficient vs. temperature and ozone concentration
    Size: 1279 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/8c77d71e-155b-40ab-a446-ae2dccac9740/resource/fd675417-23be-47bb-bcf3-44c3bb2eb572/download/dataenivdat.csv
    Description: Data to Figure 3: Measured uptake coefficients as a function of temperature at 5E12 molecules per cm3 ozone concentration.

Data to Figure 6: Measured  uptake coefficients at different temperatures as a function of gas- phase ozone concentration.

antartic

display_name: antartic

arctic

display_name: arctic

cryosphere

display_name: cryosphere

laboratory-study

display_name: laboratory-study

polar

display_name: polar

sea-salt-aerosol

display_name: sea-salt-aerosol

snow

display_name: snow


en:
This dataset contains all data, on which the following publication below is based.
Paper Citation:
_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._
Please cite this paper together with the citation for the datafile.
Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).
Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.
References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

en: weed-management native-plant non-native-plant herbivory grassland

en: Native and no-native plant interactions in Australian grasslands

envi

en: Environment

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management


en:
The files contain the datasets used to produce Figures 2, 3, and 4 of the manuscript ([doi: 10.1002/2016GL071822](http://dx.doi.org/10.1002/2016GL071822)).
 Manuscript Abstract:
Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

en: sediment-transport erosion mars model snow

en: Energy- and momentum-conserving model of splash entrainment in sand and snow saltation

en:
Resource Title:
    Size: 3626 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/6ee21796-08ad-4069-a4cb-da6c35ffede7/download/figure4a.txt
    Description: Datasets of Figure 4a

en:
Resource Title:
    Size: 3587 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/1f30b883-fc62-4bbf-a8f5-88f716008097/download/figure2.txt
    Description: Datasets of Figure 2

en:
Resource Title:
    Size: 2190 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/82479779-1b20-486f-b4bc-414c6024c25d/download/figure3b.txt
    Description: Datasets of Figure 3b

en:
Resource Title:
    Size: 1434 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/8ab9bafb-62f5-4420-80da-a2a96d22be74/download/figure3a.txt
    Description: Datasets of Figure 3a

en:
Resource Title:
    Size: 2904 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/467b2213-b72a-4578-8c2e-f1181b6a7742/resource/709f4330-9a35-4685-aac8-347067a5e483/download/figure4b.txt
    Description: Datasets of Figure 4b

erosion

display_name: erosion

mars

display_name: mars

model

display_name: model

sediment-transport

display_name: sediment-transport


en:
Starter kit for the TreeMig framework that allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
The starter kit consists of a set of climate, land-use, topography and soil property input data for Switzerland, a script for installing the framework and running the GUI of the framework with the link to the input data, a tutorial covering a range of simulation examples for Switzerland and a transect through Europe, and an associated example simulation environment containing the model executables and other model inputs.

en: spatial-modelling forest species-interaction land-use forest-dynamics r-package bioclimatic-variables treemig forest-model gui species-migration

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: Starter Kit for the TreeMig framework v1 for easy simulation of spatio-temporal forest dynamics

en:
Resource Title: TreeMig Simulation Environment and Input Data
    Size: 1612103870 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5eef16d1-80af-442b-9da2-f64b4fa94671/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en:
Resource Title: TreeMig_Tutorial_2025-05-02.pdf
    Size: 2107648 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/a1dec65a-30ba-4688-90ac-50df5db73d4c/download/treemig_tutorial_2025-05-02.pdf
    Description: Tutorial for using the TreeMig framework; updated

format: PDF

media_type: application/pdf

en:
Resource Title: TreeMig Tutorial
    Size: 2046576 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/8e6ac324-ab2b-40bc-a12f-70960c8f4bd1/download/treemig_tutorial.pdf
    Description: Tutorial for using the TreeMig framework

en:
Resource Title: TreeMig_Tutorial_v2024_12_04.pdf
    Size: 6400462 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/d4c15251-917c-4102-b172-256fecd39161/download/treemig_tutorial_v2024_12_04.pdf
    Description:

en:
Resource Title: TreeMig_Tutorial_v2024_12.pdf
    Size: 3399819 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/5188a2e1-470c-4ed7-83c6-26dc72bd18ab/download/treemig_tutorial_v2024_12.pdf
    Description: Tutorial for using the TreeMig framework; updated

en:
Resource Title: readme_descriptioninputdata.pdf
    Size: 269312 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/3db8ca57-2838-4b26-82a9-9770b75b7096/download/readme_descriptioninputdata.pdf
    Description: Where the environmental and land use input data come from and how they were processed

en:
Resource Title: TreeMig Simulation Environment and Input Data
    Size: 1602386904 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/516d259a-3b10-419c-a033-980bedf6ade1/resource/c2ae78fd-418a-4cdb-a511-0914eb46224f/download/tmenvandinputdata.zip
    Description: The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data.  For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders.  For the first example simulation of the tutorial it contains the
   - the TreeMig executables for MacOS, Linux and Windows
   - simulation control files that define the setup and input files of the simulation (in folder C)
   - species parameters (in folder P)
   - bioclimatic data  (in folder E)
   - folder R for results
   - folder Plots for plots of the simulation results.
   - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

bioclimatic-variables

display_name: bioclimatic-variables

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-model

display_name: forest-model

gui

display_name: gui

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-interaction

display_name: species-interaction

species-migration

display_name: species-migration

treemig

display_name: treemig


en:
This repository contains all observational data sets used for the paper:
Sophia Etzold, Arun K. Bose, Arthur Gessler, Frank Krumm, Katrin Meusburger, Marcus Schaub, Anne Thimonier, Peter Waldner, Roman Zweifel (2026): Decreasing water availability reduces productivity in Swiss forests along an altitudinal gradient, Functional Ecology, https://doi.org/xxxxx.
**Dataset 1**: This dataset contains inventory measurements of individual trees, i.e. species, tree status, DBH (diameter at breast height), height, and BAI (Basal area increment).
**Dataset 2**: This dataset contains plotwise aggregated BAI and NPP data per inventory period, as well as stand and soil properties of the site (N trees, QMD, SDI, meanDBH, foliar N and foliar P, N deposition, LAI, main species) and meteorological parameters (deviation of T, Psum and SWP during vegetation period).
**Dataset 3**: This dataset contains site-specific properties (altitude, age in 2000, main species, Tmean long-term, Psum long-term, soil pH, soil C/N).
**Dataset 4**: This dataset contains annually resolved relative NPP data, based on inventory data (Dataset 2) and annual circumference measurements of individual trees, as well as relative annual Tmax and SWP.

en: carbon-sequestration forest-productivity tree-growth dendrometer drought-stress

envidat

en: EnviDat: the Environmental Data Portal

en: Dataset  Article “Decreasing water availability reduces productivity in Swiss forests along an altitudinal gradient” Etzold et al.

envi

en: Environment

en:
Resource Title: 1_Treedata_Inventory_BAI.csv
    Size: 3816817 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1388bc90-9e07-4a1e-a3a9-144d319e492a/resource/47d47817-4612-44bc-9f36-c1f2195d015b/download/1_treedata_inventory_bai.csv
    Description: #1: Treedata_BAI
Site: Site name
Subplot: Subplot name
Treenr: Tree number
SPECIES: Species name
Start.Year: First Year of Inventory
End.Year: Last Year of Inventory
DBH.tree: Diameter at breast height (1.3m) in [cm]
DBH.class: Category of DBH: 'sub': <12cm, '1':small, '2':medium, '3': large
Height: tree height in [m]
Treestatus: Status of tree: '1': alive, '0': dead
BAIyr: Annual basal area increment of tree in [cm2/yr]

en:
Resource Title: 4_Annual_NPP_plot.csv
    Size: 98038 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1388bc90-9e07-4a1e-a3a9-144d319e492a/resource/24458cd4-2a47-45fb-b201-acfb65b186f1/download/4_annual_npp_plot.csv
    Description: #4: Annual NPP per plot
Site: Site name
Subplot: Subplot name
Year
NPPyr_rel: Annual Net Primary Productivity of the stand in relation to long-term mean in [%]
SWP_rel: Mean soil water potential during vegetation period in relation to long-term mean in [%]
Tmax_rel: Maximum temperature during vegetation period in relation to long-term mean in [%]

en:
Resource Title: 2_Plotdata_Inventory_NPP_BAI.csv
    Size: 65526 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1388bc90-9e07-4a1e-a3a9-144d319e492a/resource/05b47422-7f82-45ce-a545-5c6cb14449e6/download/2_plotdata_inventory_npp_bai.csv
    Description: #2: Plotdata_NPP_BAI
Site: Site name
Subplot: Subplot name
INVYEAR: Assigned Year to Inventory (mean over all plots)
INVNR: Inventory number
Csum.yr.gm2: Carbon uptake by growth in [gC/m2/yr]
BAI.yr.m2ha: Basal area increment in [m2/ha/yr]
Ntrees.ha: Number of trees per ha in [N/ha]
QMD: Quadratic mean diameter of all trees in [cm]
SDI: Reineke's Stand density index [-]
meanDBH_plot: mean DBH of all trees per plot in [cm]
LAI: Leaf area index of plot in [m2/m2]
Ndep: total Nitrogen deposition in [kg N/ha/yr]
foliarN_rel: relative foliar N concentration in [%]
foliarP_rel: relative foliar P concentration in [%]
meanT.veg: mean temperature during vegetation period in [°C]
Psum.veg: mean precipitation sum during vegetation period in [mm]
meanSWP.veg: mean soil water potential during vegetation period in [kPa]
dTemp.veg: annual deviation of mean temperature from long-term mean in [%]
dPsum.veg: annual deviation of precipitation sum from long-term mean in [%]
dSWP.veg: annual deviation of mean soil water potential from long-term mean in [%]

en:
Resource Title: 3_Site_properties.csv
    Size: 1011 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/1388bc90-9e07-4a1e-a3a9-144d319e492a/resource/62395d0d-330e-4d35-a022-ca8a47a501fd/download/3_site_properties.csv
    Description: #3: Site properties
Site: Site name
Altitude: in [m a.s.l.]
Age_in_2000: Estimated stand age in the year 2000 in [years]
Main_species: Dominant species of the stand
meanT_long: long-term (1995-2020) mean temperature during vegetation period in [°C]
Psum_long: long-term (1995-2020) mean precipitation sum during vegetation period in [mm]
soil_CN: C/N ratio of the soil
soil_pH: PH of the soil

carbon-sequestration

display_name: carbon-sequestration

dendrometer

display_name: dendrometer

drought-stress

display_name: drought-stress

forest-productivity

display_name: forest-productivity

tree-growth

display_name: tree-growth


en:
This repository contains data related to an interdisciplinary study on playgrounds, looking at both playground vegetation and the well-being of pre-school children using those playgrounds. This project was funded by and initiated at the Institute for Landscape Planning and Ecology (ILPÖ) of the University of Stuttgart, Germany. Data was collected by ILPÖ. The project was finalised in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The aim of the study was to (1) describe playground vegetation (species richness and diversity at the ground, shrub and tree layers; habitat structure); (2) describe preschool children’s well-being and nature-connectedness; and (3) investigate whether there is a relationship between plant diversity and well-being while exploring potential other predictors of well-being, including children’s and parents’ or carer’s nature-connectedness, greenspace exposure, seasonality, and socio-demographic background.
We sampled ground (-1m height), shrub (1-2m height) and tree (-2m hieght) vegetation of 29 playgrounds of Stuttgart's inner city. Sampling took place between May 25 and July 01, 2021. Ground layer vegetation was sampled in ten one-by-one m2 quadrats per playground, within which we recorded the cover of each species based on the Braun-Blanquet scale. Woody vegetation was exhaustively sampled within the playgrounds and in a surrounding two meters buffer, recording each individual plant. Vegetation cover was visually estimated as a percentage for each vegetation layer, namely the ground, shrub and tree (canopy) layers.
In parallel, we distributed questionnaires to parents and carers to assess the well-being and connectedness-to-nature of preschool children (aged 6 or younger) across the seasons. The questionnaire covered children's (1) use of greenspaces, (2) nature-connectedness, (3) well-being, and (4) socio-demographic variables. Questionnaires were distributed accross all seasons: sampling seasons included autumn (Oct-Nov 2021), winter (Jan-Feb 2022), spring (April-May 2022) and summer (June-July 2022). Ethical approval was granted by the University of Stuttgart Commission on Responsibility in Research (Az. 21-033).

en: seasons urban green-spaces well-being biodiversity

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: Playground biodiversity and preschool children well-being

en:
Resource Title: Plant and playground data.xlsx
    Size: 97321 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/eb12671e-2a17-4acf-b181-a68e40fd1fe5/download/plant-and-playground-data.xlsx
    Description: This file contains the playground and plant diversity data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".
The file is separated in five tabs containing:
(1) the overview of the playgrounds,
(2) the overview of all plant species, with their life-history traits and the diversity indexes per layer,
(3) the tree (canoy) layer abundance of each plant species, measured exhaustively in each playground,
(4) the shrub layer abundance of each plant species, measured exhaustively in each playground, and
(5) the ground layer abundance of each plant species, estimated with the Braun-Blanquet scale in 10 quadrats per playground.

en:
Resource Title: Spielplatz Fragebogen_Englisch.pdf
    Size: 340244 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/b87bc6b7-9aaa-4c86-adfc-52dcf47bcfb4/download/spielplatz-fragebogen_englisch.pdf
    Description: This document includes the English version of the questionnaire administered to carers of pre-school children. This was the original questionnaire, later translated in the 10 most spoken languages in Baden-Württemberg (DE).

en:
Resource Title: Spielplatz Fragebogen_Polnisch.pdf
    Size: 361073 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/024bbf41-00b5-4c84-ba75-28e136050d41/download/spielplatz-fragebogen_polnisch.pdf
    Description: This document includes the Polish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Deutsch.pdf
    Size: 364554 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/deca6461-d9a1-4cf4-8739-480e13432408/download/spielplatz-fragebogen_deutsch.pdf
    Description: This document includes the German version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Ukrainian.pdf
    Size: 1015736 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/1ae17430-7011-40f1-87d5-48f642e997ea/download/spielplatz-fragebogen_ukrainian.pdf
    Description: This document includes the Ukrainian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Well-being.xlsx
    Size: 184576 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/8b624832-b01e-4728-95cc-22644320da26/download/well-being.xlsx
    Description: This file contains the anonymised well-being and nature-connectedness data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".

en:
Resource Title: Spielplatz Fragebogen_Türkisch.pdf
    Size: 346481 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/f49040c1-0140-4b98-8b3a-b8b6be4fd565/download/spielplatz-fragebogen_turkisch.pdf
    Description: This document includes the Turkish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Rumänisch.pdf
    Size: 349716 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/0ac43c39-4a0d-40c2-a544-e2a4e6109213/download/spielplatz-fragebogen_rumanisch.pdf
    Description: This document includes the Romanian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Russisch.pdf
    Size: 357530 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/53481be4-b668-48c6-98df-c58961caf97b/download/spielplatz-fragebogen_russisch.pdf
    Description: This document includes the Russian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Französisch.pdf
    Size: 353495 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/872f9d84-d7a4-498d-9f3e-5851bd9bddfd/download/spielplatz-fragebogen_franzosisch.pdf
    Description: This document includes the French version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Arabisch.pdf
    Size: 397855 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/56c767f8-0b3d-45c3-9209-2bce6dac682f/download/spielplatz-fragebogen_arabisch.pdf
    Description: This document includes the Arabic version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Italienisch.pdf
    Size: 322529 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/6971a33d-2b7d-40d4-8d99-d583aed944d2/download/spielplatz-fragebogen_italienisch.pdf
    Description: This document includes the Italian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Spanisch.pdf
    Size: 345221 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/c57948ab-c230-45c0-a9b2-b60eb3460cfd/download/spielplatz-fragebogen_spanisch.pdf
    Description: This document includes the Spanish of the questionnaire administered to carers of pre-school children.

biodiversity

display_name: biodiversity

green-spaces

display_name: green-spaces

seasons

display_name: seasons

urban

display_name: urban

well-being

display_name: well-being


en:
Summary
* Dataset of daily inflow to Luzzone reservoir in Ticino, Switzerland
* R scripts used to generate return levels for low reservoir inflow, low precipitation, high inflow, and extreme high precipitation based on various methods from extreme value analysis
 Data
The dataset included here is the "natural" reservoir inflow for the Luzzone reservoir.
Additional analyses were conducted on daily total precipitation of 6 meteorological stations (abbreviations: TIOLI, TIOLV, COM, VRN, VLS, ZEV). These precipitation data are freely available for teaching and research from the MeteoSwiss IDAweb portal (https://www.meteoswiss.admin.ch/services-and-publications/service/weather-and-climate-products/data-portal-for-teaching-and-research.html).
 Codes
R scripts used to determine return levels of the data set are included for both extreme high events and low events. The scripts include the following methods for calculating return levels:
* GEV (Generalized Extreme Value)
* GPD and GPDd (Generalized Pareto Distribution including declustered version)
* eGPD (extended Generalized Pareto Distribution)
* MEV (Metastatistical Extreme Value)

en: alpine-precipitation return-periods extreme-values low-flow reservoir-inflow

envidat

en: EnviDat: the Environmental Data Portal

en: Data and Code on Extreme Inflow and Lowflow Analysis for Alpine Reservoirs

envi

en: Environment

en:
Resource Title: R codes for Extreme Values Analysis
    Size: 35946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b138fae4-b287-4af6-b666-ef860ac593ff/resource/6647b3fe-62a5-461b-8b22-be7bcdfb51be/download/r_codes.zip
    Description: Zip file containing R codes for running extreme value analyses for high precipitation and inflow events as well as code for determining return levels of low inflow and low precipitation events

en:
Resource Title: Daily Luzzone Reservoir Inflow 01-01-2000 to 31-12-2019
    Size: 261834 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/b138fae4-b287-4af6-b666-ef860ac593ff/resource/f3b117de-ba26-42dd-b958-e46e826222e4/download/luz.csv
    Description: Daily total water inflow to Luzzone reservoir. Natural inflow (LUZ_inflow_raw) is back-calculated based on daily water level in reservoir (removing hydropower inputs and spills). Linear interpolation between daily values is used to bring all inflow values into positive space (LUZ_inflow_intrp).

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods


en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).
* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.
Note:
* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

en: antarctica reproducibility cryowrf surface-mass-balance blowing-snow

envidat

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

en: Reproducibility dataset for CRYOWRF validation

en:
Resource Title: Scripts_Reproducibility_v2
    Size: 3051205 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/d05a9210-b303-45cc-8f2d-f4292951df2e/download/scripts_reproducibility_v2.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, revised

en:
Resource Title: WRF_27km_NoahMP
    Size: 6657199309 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_NoahMP.zip
    Description: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

en:
Resource Title: Simulation_setup
    Size: 10669 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/79646165-0b4f-4495-b06a-dcd52d403019/download/simulation_setup.zip
    Description: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

en:
Resource Title: Scripts_Reproducibility_v1
    Size: 3227134 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/65815232-fd6a-4d1d-a280-a1ebc1c30375/download/scripts_reproducibility.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

en:
Resource Title: WRF_27km_CRYOWRF
    Size: 28991029248 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_CRYOWRF.zip
    Description: Processed CRYOWRF output used for the analysis and the figures in the paper.

en:
Resource Title: Static_input
    Size: 5034051 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/aa57ffee-2ec1-4561-8673-cf3d03cedeaf/download/static_input.zip
    Description: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance


en: This dataset provides HS, TSS and TS50, TS100, TS150 at the station WFJ2 situated on the Weisfluhjoch research site (2536 m asl). It has been created from merging ENET and IMIS datsets to form a continuous timeseries from 1992- present. ENET is at 1 h resolution whereas IMIS is 30 min. This is a level 2 dataset as defined [here](http://models.slf.ch/p/dataset-processing/).

en: imis snow-height snow-water-equivalent weissfluhjoch enet snow-temperatures

en: WFJ2: Snow measurements from the Weissfluhjoch research site, Davos

enet

display_name: enet

imis

display_name: imis

snow-height

display_name: snow-height

snow-temperatures

display_name: snow-temperatures

snow-water-equivalent

display_name: snow-water-equivalent

weissfluhjoch

display_name: weissfluhjoch


en: This database contains GNSS derived snow water equivalent (SWE), liquid water content (LWC), and snow height (HS)  and reference data collected during the two winter 2018-2020 at 4 sites Weissfluhjoch (2540 m asl, 46°49’47’’ N, 9°48’34’’E), Laret (1515 m asl, . 46°50’2’’N, 9°52’17’’E), Klosters (1200 m asl, 46°51’49’’N, 9°53’17’’E), and Küblis (815 m asl, 46°54’48’’N, 9°46’54’’E).

en: liquid-water-content gps lwc swe gnss snow-water-equivalent snow

envidat

en: EnviDat: the Environmental Data Portal

en: Snow water equivalent measurements with low-cost GNSS receivers along a steep elevation gradient in the East-ern Swiss Alps

en:
Resource Title: Meteo_Kueblis
    Size: 674638 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/398c7a10-d1bf-4fd3-b7a9-8175843077d7/download/kub_meteo.csv
    Description: Snow and meteo data from automatic sensors from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en:
Resource Title: Profiles_WFJ
    Size: 2365 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/8a7318b9-571d-4da9-9686-2330bf0f373a/download/wfj_prof.csv
    Description: Snow profiles data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Meteo_Klosters
    Size: 697178 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/0ba3714e-3caa-47d3-8b8c-c235fc57760e/download/klo_meteo.csv
    Description: Snow and meteo data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: Manual profiles
    Size: 4065671 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/f7ac1de9-3b24-47fa-9f67-cd6560674a18/download/profiles.zip
    Description: Data of the traditional manual profiles for the locations Weissfluhjoch, Klosters and Küblis. For the location of Küblis there are no traditional manual profile data.  We provided the data as both PDF and .CAAML format (See https://niviz.org/  or http://caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS/CAAMLv5_SnowProfileIACS.pdf). Moreover, we added LWC and density profiles when available (all locations).

en:
Resource Title: day_Laret
    Size: 27183 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/3af4ec59-d2ff-425e-ba49-996cd5a85247/download/lar_day.csv
    Description: Daily data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: day_WFJ
    Size: 71919 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/01d5ba5c-4734-43b0-b1cd-68e97e0fd711/download/wfj_day.csv
    Description: Daily data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: day_Klosters
    Size: 28691 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/40726e6f-f175-4033-8df7-526e42cdc266/download/klo_day.csv
    Description: Daily data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: Obs_Kueblis
    Size: 10744 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/ba8b38d2-fcc3-4345-b763-4b618e49836f/download/kub_obs.csv
    Description: Daily observer data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

en:
Resource Title: Prof_Laret
    Size: 3424 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/d18ef060-e61f-4196-82ad-859e3faa1c9b/download/lar_prof.csv
    Description: Profile data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: GNSS_kueblis
    Size: 17196 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/973a7cde-cf6e-484e-8da1-a2da1de4fc49/download/kub_gnss.csv
    Description: GNSS derived SWE, LWC and HS from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-20

en:
Resource Title: GNSS_laret
    Size: 15587 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/0a95d946-3fd0-4d83-bfb9-4fdcb210a0d3/download/lar_gnss.csv
    Description: GNSS derived data for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: Meteo_LAR
    Size: 2994700 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/e582db3a-a0ba-4527-9c2f-ca961562c317/download/lar_meteo.csv
    Description: Snow and meteo data from automatic sensors for Laret at 1510 m a.s.l. (46°50’2’’N, 9°52’17’’E) for the two winter 2018-2020.

en:
Resource Title: GNSS_WFJ
    Size: 54679 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/f791ca79-0c9a-4055-9989-d5176e222935/download/wfj_gnss.csv
    Description: GNSS derived SWE, HS, and LWC for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Obs_Klosters
    Size: 13499 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/9bb74e8a-d19b-49ca-aecf-feed84c3e324/download/klo_obs.csv
    Description: Daily observer data from automatic sensors from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: day_Kueblis
    Size: 28335 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/df76c91e-b71e-4441-a905-31b32b8782fb/download/kub_day.csv
    Description: Daily data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020. These data were processed to daily values from the other data files.

en:
Resource Title: Profiles_Klosters
    Size: 2530 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/dc102dd3-9d9d-4757-9263-9306c6474b5c/download/klo_prof.csv
    Description: Snow profiles data from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-2020.

en:
Resource Title: GNSS_klosters
    Size: 19682 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/bc65a02c-f311-49c7-9007-a8df51a87610/download/klo_gnss.csv
    Description: GNSS derived SWE, LWC and HS from Klosters (1210 m a.s.l. ,46°51’49’’N, 9°53’17’’E) for the two winters 2018-20

en:
Resource Title: Meteo_WFJ
    Size: 2779069 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/be4ca553-12f8-4a2a-94bc-1672dfbac5b9/download/wfj_meteo.csv
    Description: Snow and meteo data from automatic sensors for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Obs_WFJ
    Size: 23691 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/4b796a10-3ab7-42c9-ab1f-3d6218692326/download/wfj_obs.csv
    Description: Daily observer data for the site Weissfluhjoch at 2540 m a.s.l (46°49’47’’ N, 9°48’34’’E) for the two winters 2018-2020.

en:
Resource Title: Webcam images
    Size: 236611230 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/292ddd39-edd8-4df4-8dc7-f79137c6494d/download/pictures_webcam.zip
    Description: Webcam images showing some typical differences in the snow conditions at the four sites (Küblis, Klosters, Laret and Weissfluhjoch) for two time periods (14-18.3.2019 and 27.1-11.2.2020). Both time periods included a precipitation event with partial rain-on–snow occurring at the lower locations.

en:
Resource Title: Profiles_Kueblis
    Size: 1151 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9e303b80-9c88-407c-b926-e8f2f7eb63da/resource/e6d6f714-5f1a-4cc9-9ab1-3cf5417073a7/download/kub_prof.csv
    Description: Snow profiles data from Küblis at 820 m a.s.l. (46°54’48’’N, 9°46’54’’E) for the two winters 2018-2020.

gnss

display_name: gnss

gps

display_name: gps

liquid-water-content

display_name: liquid-water-content

lwc

display_name: lwc

snow

display_name: snow


en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

en: metamorphism ozone brine interface antarctica reaction arctic heterogeneous alpine laboratory-study chemistry snow solution

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: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study

envi

en: Environment

en:
Resource Title: Readme file
    Size: 503143 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/d41fa166-35e9-430f-b96d-a5862556d9cd/download/edebeli_acp_2019__snowbrmet.pdf
    Description: This file shows data, code, and plots.

en:
Resource Title: Matlab Data
    Size: 1008529 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/2cbff0e6-bf62-4476-a533-10cb745520ed/download/edebeli_acp_2020__data.mat
    Description: All data as Matlab mat file

en:
Resource Title: Matlab Script to view and plot data
    Size: 9299 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/b718b5db-b15c-4f88-95a9-ce649b79308a/download/edebeli_acp_2019__snowbrmet.m
    Description:

alpine

display_name: alpine

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

solution

display_name: solution


restoring-grassland-multifunctionality

en:
Please cite this paper together with the citation for the datafile.
Resch, M. C., Schütz, M., Buchmann, N., Frey, B., Graf, U., van der Putten, W. H., Zimmermann, S., Risch, A. C. 2021. Evaluating long-term success in grassland restoration – an ecosystem multifunctionality approach. Ecological Applications 31, e02271.

 Study area
The study was conducted in the Canton of Zurich, Switzerland, in and around two nature reserves Eigental and Altläufe der Glatt (47°27’ to 47°29’ N, 8°37’ to 8°32’ E, 417 to 572 m a.s.l.). All studied grasslands were located with a radius of approximately 4 km. Average monthly temperatures range from 0.7 ± 2.0 °C (January) to 19.0 ± 1.5 °C (July), and monthly precipitation range from 60 ± 42 mm (January) to 118 ± 46 mm (July [maxima]; 1989-2017; MeteoSchweiz 2018). In our study, we focused on semi-dry and semi-wet oligo- to mesotrophic grasslands characterized by high plant species richness and groundwater fluctuations throughout the year (Delarze et al. 2015, see also Resch et al. 2019).
 Experimental design and sampling
A large-scale restoration experiment to expand and reconnect isolated remnants of species-rich grasslands was initiated in the nature reserve Eigental in 1990. Twenty hectares of adjacent intensive grasslands were chosen for restoration. In 1995, three restoration methods of increasing intervention intensities were implemented. The goal of all three methods was to lower the availability of soil nutrients and hence, facilitate ecosystem development towards the targeted nutrient-poor grasslands. These methods were: Harvest only (hay harvest twice a year), Topsoil (removal of the nutrient-rich topsoil), and Topsoil+Propagules (topsoil removal combined with the application of hay from target vegetation). Plant biomass harvest (once a year in late summer/early autumn) commenced in Topsoil and Topsoil+Propagules five years after the soils were removed and is still ongoing today. We measured restoration success by comparing the three restoration methods with intensively managed (Initial) and semi-natural grasslands (Target) 22 years after restoration. Initial grassland sites share the same agricultural history as the restored sites: mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes (Resch et al. 2019). Target sites were the sites from which hay for seeding the Topsoil+Propagules sites was collected. Soil conditions (i.e., soil types, soil texture) were comparable to those found in the restored grasslands (Resch et al. 2019). Additionally, Target sites were selected to represent a variety of semi-natural grasslands, including semi-dry to semi-wet conditions.  In Target grasslands, biomass is harvested once a year in late summer or early autumn. Eleven 5 m x 5 m (25 m2) plots were randomly established in each of the five treatments (in total 55 plots; for a detailed map see Neff et al. 2020). An additional 2 m x 2 m (4 m2) subplot was randomly established at least 2 m away from each 25 m2 plot for destructive sampling. Data sampling took place between June and September 2017.
Vegetation properties
All plant species were identified within the 25 m2 plots (nomenclature: Lauber and Wagner 1996) in mid-June 2017 (in total 250 species). Vegetation structure and plant biomass were assessed diagonally on a transect of 2 m x 10 cm within the 25 m2 plot in early July 2017. We measured the maximum and mean height of the vegetation at the start, middle and end of the transect and calculated the standard deviation of these measures to describe vegetation structural heterogeneity (Schuldt et al. 2019). Thereafter, biomass was clipped on the entire transect to 1 cm height, sorted into five functional groups (graminoids, forbs, legumes, litter, and woody species), dried at 60 °C for 48 h, and weighed (Meyer et al. 2015).
 Aboveground arthropods
Aboveground arthropods were sampled at two locations in each 25 m2 plot in early July 2017 (see also Neff et al. 2020). Briefly, two cylindrical baskets (50 cm diameter, 67 cm height; woven fabric) were thrown simultaneously from outside the plot into two opposite corners. A closable mosquito mesh sleeve was mounted to the top of the baskets and an integrated metal ring at the bottom was fixed to the ground with metal stakes to assure that insects could not escape. A suction sampler (Vortis, Burkhard Manufacturing Co. Ltd., Hertfordshire, England) was then inserted into one of the baskets through the opening of the sleeve and the plot was “vacuumed" twice for 105 seconds with a 30 seconds break. The collected animals were immediately transferred into 70% ethanol. Arthropods were sorted and assigned to 23 taxonomic groups. Holometabolic larvae were lumped into one category while hemimetabolic larvae were grouped separately from adults in the respective taxonomic rank. We used mean values of individuals per plot for total abundance. Aboveground arthropod richness was defined by the number of different taxa to lowest taxonomic level (in total 23 taxa). All taxa were assigned to one of five trophic levels: 1) primary producers, 2) primary consumers, 3) secondary consumers, 4) tertiary consumers, and 5) quaternary consumers.
 Belowground fauna
Sampling of all belowground fauna took place in mid-July 2017. Earthworms were sampled in two 30 cm x 30 cm x 20 cm soil monoliths at two opposite corners of the 25 m2 plot (opposite to aboveground arthropod sampling). The excavated soil monolith was broken by hand, all earthworms collected and immediately transferred in a 4% formaldehyde solution. Thereafter, earthworm individuals were identified to species level (in total 10 taxa; Christian and Zicsi 1999) and species assigned to three functional groups (Bouché 1977).
To assess soil arthropod communities, we randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) in each 4 m2 subplot with a slide hammer corer lined with a plastic sleeve (AMS Samplers, American Falls, Idaho, USA). Soil arthropods were extracted using Berlese-Tullgren funnels (3 mm mesh), starting the day of sampling and lasting 14 days. Individuals were stored in 70% ethanol. Soil arthropods were assigned to 41 taxonomic groups and 4 feeding types. Holometabolic and hemimetabolic larvae were treated as previously described for aboveground arthropods. Belowground arthropod richness refers to the 41 taxonomic groups.
For soil nematode sampling, we randomly collected eight soil cores of 2.2 cm diameter (Giddings Machine Company, Windsor, CO, USA) within each 4 m2 subplot to a depth of 12 cm. The eight cores were combined, gently homogenized, placed in coolers, kept at 4 °C and transported to the laboratory at NIOO in Wageningen (NL) within one week after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink 1960) and prepared for morphological identification and quantification as described by Resch et al. (2019). Nematodes were identified to family level (39 taxa) according to Bongers (1988), assigned to 17 functional groups, 5 feeding types and 5 colonizer-persister (C-P) classes (Yeates et al. 1993, Bongers 1990, Resch et al. 2019).
We randomly collected two more soil cores (2.2 cm diameter x 12 cm depth) within each 4 m2 subplot to determine soil microbial communities. Again, the soil cores were combined, homogenized, placed in coolers and transported to the laboratory at WSL in Birmensdorf (Switzerland) where the metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNeasy PowerMax Soil Kit (Quiagen, Hilden, NRW, GER) according to the manufacturer`s instructions. PCR amplification of the V3-V4 region of the prokaryotic small-subunit (16S) and the ribosomal internal transcribed spacer region (ITS2) of eukaryotes was performed with 1 ng of template DNA utilizing PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates and pooled. The pooled amplicons were sent to the Genome Quebec Innovation Centre (Montreal, QC, Canada) for barcoding using the Fluidigm Access Array technology (Fluidigm) and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA). Quality filtering, clustering into operational taxonomic units (OTUs) and taxonomic assignment were performed as described by Frey et al. (2016) and Adamczyk et al. (2019). We used a customised pipeline largely based on UPARSE (Edgar 2013) implemented in USEARCH v. 9.2 (Edgar 2010). After discarding singletons of dereplicated sequences, clustering into OTUs with 97% sequence similarity was performed (Edgar 2013). Quality-filtered reads were mapped on the filtered set of centroid sequences. Taxonomic classification of prokaryotic and fungal sequences was conducted querying against most recent versions of SILVA (v.132, Quast et al. 2013) and UNITE (v.8, Nilsson et al. 2018). Only taxonomic assignments with confidence rankings equal or higher than 0.8 were accepted (assignments below 0.8 set to unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as eukaryotic OTUs assigned other than fungi were removed prior to data analysis. In addition, prokaryotic and fungal datasets were filtered to discard singletons and doubletons. Thereafter, OTU abundance matrices were rarefied to the lowest number of sequences per community, to normalize the total number of reads and achieve parity between samples (Prokaryota: 29,843 reads; Fungi: 26,690 reads). Finally, prokaryotic and fungal observed richness (number of OTUs) were estimated (Prokaryota: 14,010 OTUs; Fungi: 5,813 OTUs). For prokaryotes, we distinguished five and for fungi six functional types based on lowest taxonomic resolution (Nguyen et al. 2016, Tedersoo et al. 2014).  Belowground taxon richness was defined by the total number of earthworm, arthropod, nematode, fungi, and prokaryote taxa assigned to lowest taxonomic level. Finally, all belowground taxa were assigned to the same five trophic levels as the aboveground arthropods.
 Soil chemical and physical properties, soil nitrogen mineralization
We randomly collected three 5 cm diameter x 12 cm depth soil samples in each 4 m2 subplot with a slide hammer corer (AMS Samplers, American Falls, Idaho, USA), pooled them and then made two subsamples. One was field-fresh and stored at 3 °C until analysis, the other was dried for 48 h at 60 °C and passed through a 4 mm mesh. From the dried sample, we measured soil pH potentiometrically in 0.01 M CaCl2 (soil:solution ratio=1:2; 30 minutes equilibration time). Total and organic carbon content were measured on fine-ground samples (≤ 0.5 mm) by dry combustion using a CN analyzer NC 2500 (CE Instruments, Wigan, United Kingdom). Inorganic carbon of samples with a pH - 6.5 was removed with acid vapor prior to analysis of organic carbon (Walthert et al. 2010). We calculated total soil carbon (C) storage after correcting its content for soil depth, stone content and density of fine earth (see below). Exchangeable cations were determined on another 5 g dry soil sample with 50 mL unbuffered 1 M NH4Cl solution (soil:solution ratio=1:10, end-over-end shaker for 1.5 hours) and measured by an ICP-OES (Optima 7300 DV, Perkin-Elmer, Waltham, Massachusetts, USA). Thereafter, cation exchange capacity (CEC) was calculated as the sum of exchangeable cations and protons (and expressed as mmolc per 1 kg soil) and used to describe nutrient retention capacity in our plots. Concentrations of exchangeable protons were calculated as the difference between total and Al-induced exchangeable acidity as determined by the KCl-method (Thomas 1982).
Ammonium (NH4+) and nitrate (NO3−) were extracted from a 20 g fresh subsample with 80 mL 1M KCl for 1.5 hours on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnemühle FineArt GmbH, Dassel, Germany). NH4+ concentrations were determined colorimetrically by automated flow injection analysis (FIAS 300, Perkin-Elmer, Waltham, Massachusetts, USA). NO3− concentrations were measured colorimetrically according to Norman and Stucki (1981). Potential soil net nitrogen (N) mineralization was assessed during an 8-week incubation period under controlled moisture (60% of field capacity), temperature (20 °C) and light conditions (dark) in the laboratory. We weighed duplicate samples of fresh soil equivalent to 8 g dry soil (24 h at 104 °C) into 50 mL Falcon tubes. Soil samples were extracted for NH4+ and NO3− at the beginning and after eight weeks as described above. Soil net N mineralization was calculated as the difference between the inorganic nitrogen (NH4+ and NO3−) before and after the incubation (Hart et al. 1994), corrected for the total incubation time and represented per day values expressed as mg N kg-1 soil d-1.
To assess soil physical properties, we randomly collected one undisturbed soil core per 4 m2 subplot (5 cm diameter, 12 cm depth) in a steel cylinder that fit into the slide hammer (AMS Samplers, American Falls, Idaho, USA). The cylinder was capped in the field to avoid disturbance. We then measured field capacity in the laboratory. For this purpose, the cylinder and soil therein were saturated in a water bath and drained on a sand/silt-bed with a suction corresponding to 60 cm hydrostatic head. The moist soil was dried at 105 °C to constant weight. Field capacity was calculated by dividing the mass of water by the total mass of wet soil contained at 60 cm hydrostatic head and used to describe water holding capacity. Thereafter, samples were passed through a 4 mm mesh. Fine-earth and skeleton fractions were weighed separately to assess bulk soil density (fine-earth plus skeleton), density of fine earth, and proportion of skeleton. Particle density was determined with the pycnometer method (Blake and Hartge 1986), and total porosity and proportion of fine pores were calculated (Danielson and Sutherland 1986). Clay, silt, and sand contents were quantified with the sediment method (Gee and Bauder 1986).
Surface and soil temperature (12 cm depth, water-resistant digital pocket thermometer; IP65, H-B Instrument, Trappe, Pennsylvania, USA) as well as volumetric soil moisture content (12 cm depth, time domain reflectometry; Field-Scout TDR 300, Spectrum Technologies, Aurora, Illinois, USA) were measured at five random locations within the 4 m2 subplots every month from June to September. We calculated the standard deviation of each temperature and moisture measure over four months to describe seasonal variations. Slope inclination was determined at plot-level via GPS measurements (GPS 1200, Leica Geosystem, Heerbrugg, Switzerland) and categorized into slope gradient classes according to FAO standards (1990). Thickness of the topsoil horizon (equivalent to Ah or Aa horizon) was determined at one soil monolith (30 x 30 x 30 cm3) per 4 m2 subplot in cm and rounded to next integer.
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en: bacteria nematodes plants soil-biodiversity fungi biodiversity mineralization grassland ecosystem-multifunctionality restoration

en: Restoring grassland multifunctionality

title_for_slug: restoring-grassland-multifunctionality

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en:
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en:
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bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

ecosystem-multifunctionality

display_name: ecosystem-multifunctionality

fungi

display_name: fungi

grassland

display_name: grassland

mineralization

display_name: mineralization

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil-biodiversity

display_name: soil-biodiversity


en:
In fall 2019, a new set of climate change scenarios has been released for
Switzerland, the CH2018 dataset (www.climate-scenarios.ch). The data are
provided at daily resolution. We produced from the CH2018 dataset a new
set of climate change scenarios temporally downscaled at hourly resolution.
In addition, we extended this dataset integrating the meteorological stations
from the Inter-Cantonal Measurement and Information System (IMIS) network,
an alpine network of automatic meteorological stations operated by the WSL
Institute for Snow and Avalanche Research SLF.
The extension to the IMIS network is obtained using a Quantile Mapping approach
in order to perform a spatial transfer of the CH2018 scenarios from the location
of the  MeteoSwiss stations to the location of the IMIS stations. The temporal
downscaling is performed using an enhanced Delta-Change approach. This approach
is based on objective criteria for assessing the quality of the determined delta
and downscaled time series. In addition, this method also fixes a flaw of common
quantile mapping methods (such as used in the CH2018 dataset for spatial downscaling)
related to the decrease of correlation between different variables. The idea behind
the delta change approach is to take the main seasonal signal (and mean) from
climate change scenarios at daily resolution and to map it to a historical time series
at hourly resolution in order to modify the historical time series. The obtained time
series exhibit the same seasonal signal as the original climate change time series,
while it keeps the sub-daily cycle from the historical time series.
The applied methods (Quantile Mapping and Delta-Change) have limitations in
correctly representing statistically extreme events and changes in the frequency
of discontinuous events such as precipitation. In addition, the sub-daily cycle in
the data is inherited from the historical time series, so there is no information
of the climate change signal in this sub-daily cycle. A careful reading of the paper
accompanying the dataset is necessary to understand the limitations and scope of
application of this new dataset.
This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode).

en: switzerland temporal-downscaling delta-change climate-change-scenarios quantile-mapping meteoswiss imis alpine-regions

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: Dataset for: Climate change scenarios at hourly time-step over Switzerland from an enhanced temporal downscaling approach

alpine-regions

display_name: alpine-regions

climate-change-scenarios

display_name: climate-change-scenarios

delta-change

display_name: delta-change

imis

display_name: imis

meteoswiss

display_name: meteoswiss

quantile-mapping

display_name: quantile-mapping

switzerland

display_name: switzerland

temporal-downscaling

display_name: temporal-downscaling