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

en: Site photo of the forest station (NAB)

en: Site photo of the forest station from the side.

en: Forest station data (NAB)

en: Data file.

en: Field station data (NAF)

en: Data plot of the forest station (NAB)

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

en: Site aerial photo (Nationalpark)

en: Site aerial photo from both Nationalpark stations. Source: Google. 2016. Site aerial photo from both Nationalpark stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Site photo of the field station (NAF)

en: Site photo of the field station form the side.

en: Data plot of the field station (NAF)

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Nationalpark in Switzerland where one station is located within a natural coniferous forest stand (NAB) with mountain pine (_Pinus mugo_; 210 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NAF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Nationalpark is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: EnviDat Support

en: large-eddy-simulations turbulence eddy-covariance-measurements micro-rain-radar blowing-snow antarctica meteorological-data drifting-snow mass-flux

state: active

type: dataset

en: Simulation data for a situation with significant snow transport

en: Data from two LES-LSM simulations called Drift_1 and Drift_2, which reproduce the conditions observed at the S17 site on 11th January 2019, 00:40 to 00:50 UTC.

format: SERVICE

en: Measurement data from micro-meteorological station

en: Automatic in-situ measurements of micro-meteorology and snow transport

en: Readme

media_type: text/plain

en: Meta data

format: TXT

en: Measurement data from snow particle counter at MRR site

en: Near-surface observations of drifting snow from a Snow Particle Counter (SPC) installed at the location of the Micro Rain Radar.

en: Source code of the large-eddy simulations coupled with a Lagrangian stochastic model (LES-LSM), available on GitLab.

en: Measurement data from Micro Rain Radar (MRR)

en: Remote sensing data of blowing snow from a Micro Rain Radar (MRR).

en: Simulation data for a situation with negligible snow transport

en: Results from two LES-LSM simulations called NoDrift_1 and NoDrift_2, which reproduce the conditions observed at the S17 site on 12th January 2019, 05:40 to 05:50 UTC.

en:
This dataset contains measurement and simulation data. The measurements characterize the standard meteorology, turbulence, and snow transport at the S17 site near Syowa Station in East Antarctica during an expedition in austral summer 2018/2019. Large-eddy simulations with sublimating particles provide additional insight into the latent and sensible heat exchange between snow and air in two example situations observed at the S17 site.

A part of the measurement data was recorded by an automatic measurement station from 10th January 2019 to 26th January 2019. This measurement station was equipped with standard meteorological sensors, a three-dimensional ultrasonic anemometer, an open-path infrared gas analyzer, a snow particle counter, an infrared radiometer for measurements of the surface temperature, and a sonic ranging sensor measuring changes in snow surface elevation.

At a horizontal distance of approximately 500 m, a Micro Rain Radar (MRR) was installed in a tilted configuration with an elevation angle of 7° for remote sensing of blowing snow between 25th December 2018 and 24th January 2019. In addition, near-surface in-situ measurements of snow transport were performed at the location of the MRR by deploying a snow particle counter from 27th December 2018 to 24th January 2019.

The simulations cover a 18 x 18 x 6 m³ domain and reproduce the steady-state conditions during a 10-min interval with significant snow transport and another 10-min interval with negligible snow transport. We provide the model source code and the post-processed simulation data, i.e., horizontally averaged quantities as a function of height and time.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

drifting-snow

display_name: drifting-snow

eddy-covariance-measurements

display_name: eddy-covariance-measurements

large-eddy-simulations

display_name: large-eddy-simulations

mass-flux

display_name: mass-flux

meteorological-data

display_name: meteorological-data

micro-rain-radar

display_name: micro-rain-radar

turbulence

display_name: turbulence

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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.

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Meteorology and snow transport at S17 near Syowa, Antarctica, in austral summer 2018/2019


maintainer: Markus Schlegel

en: monitoring air-sampling spore-dispersal edna metabarcoding

en: Data files and analysis scripts (Version 1)

media_type: application/zip

en: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.

format: ZIP

mimetype: application/zip

en:
Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of fungi* (Schlegel et al. 2023, submitted).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were underrepresented in the air.
The contents of the dataset (ZIP archive):
* All analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.

air-sampling

display_name: air-sampling

edna

display_name: edna

metabarcoding

display_name: metabarcoding

monitoring

display_name: monitoring

spore-dispersal

display_name: spore-dispersal

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Supporting information for case study on the application of spore sampling for the monitoring of fungi


en: snow-water-equivalent meteodat-gmbh gcos snow wagital

en:
Total water reserves of the snow cover [mio m3] for Wägital catchment, Switzerland, for reference date April 1. Data is separated in 2 elevation zones 900m-1500m asl and 1500m-2300m asl. Time period 1943-2023, status 2023-04-17.

Funded currently or in the past by:

- Federal Office of Meteorology and Climatology MeteoSwiss in the context of GCOS Switzerland
- Meteodat GmbH
- Institute of Geography, University of Zurich
- WSL Institute for Snow and Avalanche Research SLF
- Institute of Geography, ETH Zurich (IAC ETH Zurich)
- AG Kraftwerk Wägital (AXPO and EWZ)

See also https://www.meteodat.ch/waegital.html

gcos

display_name: gcos

meteodat-gmbh

display_name: meteodat-gmbh

snow

display_name: snow

snow-water-equivalent

display_name: snow-water-equivalent

wagital

display_name: wagital

en: Snow water equivalent for reference date April 1 for Wägital catchment, starting 1943


en: occupancy-models conservation landscape amphibians wetlands

en: Model code, description

media_type: text/html

en: This is the output of the R markdown file that provides JAGS model code and describes how to format the provided data and fit the dynamic occupancy models described in the associated publication, for a quick overview.

format: HTML

en: Original raw data

en: This file contains the original raw monitoring data as provided by the canton of Aargau. Access is restricted and only considered upon request and in consultation with the canton of Aargau.

format: XLS

en: Observation data

media_type: text/csv

en: This file contains detection/non-detection data for the 12 amphibian species between 1999 and 2019 for 3 annual visits. Detectable denotes whether or not a visit j was made to pond i in year t. ObservedID gives a unique ID for the observer collecting the data during visit j to pond i in year t.

format: CSV

en: Readme

media_type: application/pdf

en: Description of methods and datasets.

format: PDF

en: Covariate data 1

en: This file contains covariate data that does not change over time for 856 ponds: the region the pond is in, whether the pond is old or new (constructed since 1991), elevation, water surface area, fluctuations of the water table (yes, no), the percent forest cover in 100m radius around the pond, the area or large (>6m wide) roads in 1km radius around the pond.

en: Covariate data 2

en: This file contains covariate data that changes over time for 856 ponds in 21 years (long format): whether or not a pond exists in year _t_, the age of constructed ponds in year _t_, structural connectivity of the pond in year _t_.

en: Model code

en: This R markdown file contains all code and descriptions necessary to load and format the provided data and to fit the dynamic occupancy models described in the associated publication, including JAGS code for the fitted models.

en:
In the canton of Aargau, hundreds of new ponds have been constructed since the 1990s to benefit declining amphibian populations. This dataset consists of monitoring data for all 12 pond-breeding amphibian species in the canton of Aargau from 1999 to 2019 in 856 ponds, and environmental variables that describe the ponds and the landscape surrounding the ponds. Species observation data is detection/non-detection data from repeat visits during survey years, during which all potentially suitable ponds in an area were surveyed. Environmental variables describing the ponds are whether the pond has been newly constructed since 1991 or not, pond age (if constructed), elevation a.s.l., the water surface area, and whether the water table fluctuates or not. Environmental variables describing the surroundings of the ponds are the percent area of forest within a circular buffer of radius 100m around the pond, the area of large (width ≥6m) roads within a circular buffer of radius 1km around the pond, and structural connectivity.

The canton of Aargau is the owner of the monitoring data; the original datafile is only disclosed upon request and in consultation with the canton of Aargau.

The edited dataset contains cleaned observation data for the 12 amphibian species, as well as compiled and edited covariate data and code to fit dynamic occupancy models.

amphibians

display_name: amphibians

conservation

display_name: conservation

landscape

display_name: landscape

occupancy-models

display_name: occupancy-models

wetlands

display_name: wetlands

en: Amphibian observation and pond data (Aargau, Switzerland)


en: snow-distribution forest-structure airborne-laser-scanning canopy-height snow-depth

en: Terrain elevation maps

en: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

mimetype: text/plain

en: Snow depth maps

en: Snow depth maps from two snow-on flights at each of the three field areas Davos (March 20th and 31st 2017), Engadien (March 20th and 31st, 2017) and Grand Mesa (February 8th and 16th, 2017)

en: Canopy height maps

en: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

en:
This dataset includes snow depth, canopy height and terrain elevation maps of forest stands in the Grisons (CH) and at Grand Mesa (CO,USA) derived from airborne lidar. Data were acquired i) within a pilot mission of NASA's Airborne Snow Observatory in the Swiss Alps in March 2017 and ii) during NASA’s SnowEx campaign at Grand Mesa in February 2017. Snow depth maps are available for two dates separated by approx.1 week, and include an area of ca. 0.5km2 for each of the three sites Davos, Engadine and Grand Mesa.
All data were presented and analyzed in the publication 'Revisiting Snow Cover Variability and Canopy Structure within Forest Stands: Insights from Airborne Lidar Data' (Mazzotti et al., 2019, WRR, doi: 10.1029/2019WR024898). This publication must be cited when using this dataset.

Paper Citation:
 > _Giulia Mazzotti; William Ryan Currier; Jeffrey S. Deems; Justin M. Pflug; Jessica D. Lundquist; Tobias Jonas (2019). Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resources Research, 55, 6198– 6216, [doi: 10.1029/2019WR024898](https://doi.org/10.1029/2019WR024898)._

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: ALS-based snow depth and canopy height maps from flights in 2017 (Grisons, CH and Grand Mesa, CO)


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: raclets disdrometer precipitation visibility hydrometeors

en: Disdrometer Data Gotschnagrat

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility


en: shortwave-radiation outgoing weissfluhjoch incoming longwave-radiation

en: Metadata

mimetype: application/pdf

en: Processing doc

en: DATA ACCESS

en: Parameter file

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

 References
1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019.
2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf.

incoming

display_name: incoming

longwave-radiation

display_name: longwave-radiation

outgoing

display_name: outgoing

shortwave-radiation

display_name: shortwave-radiation

weissfluhjoch

display_name: weissfluhjoch

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


photogrammetric-drone-data-gruenbodeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

en: photogrammetry drone-data snow-depth-mapping dsm orthophoto wingtra uav

en: Data Access

en:
- ortho (3 cm/25 mm resolution)
- DSM (10 cm resolution)
- HS (10 cm resolution)
- RGB images
- Agisoft Metashape Project Report

All products are also available as a cloud optimized geotiff.

en:
We conducted various drone flights at Grüenbödeli near Davos with the Sony RX1R II mounted on a Wingtra drone during 2020/21/22. The data was processed with the Agisoft Metashape Professional Software.
The following products are available for download:
- DSM 10cm resolution
- Orthomosaic 3cm/25mm resolution
- Snow Raster 10cm resolution
- original RGB images

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Grüenbödeli


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

en: Documentation

en: This data documentation is outdated and has been replaced with an updated version (see description).

mimetype: application/msword

en: Dataset V1

en: This dataset is outdated and has been replaced with an updated version (see description).

format: GDB

en: Site photo

en: This site photo is outdated and has been replaced with an updated version (see description).

en:
 Important
This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland." The entry can be found under this link <https://www.envidat.ch/dataset/afforestation-stillberg> and with this DOI 10.16904/envidat.397.

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

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Long-term treeline research dataset at Stillberg, Davos


en: national-dishes latent-semantic-analysis food-preferences agro-food-trade food-taste-similarity

en: National dishes, migration data and data for bilateral food trade flows

en:
The data include information on national dishes, migration data and data for bilateral food
trade flows for 5 years as well as importer and exporter GDP, population, distance between
most populated cities, bilateral information on Preferential Trade Agreements, common
official primary langauge, common colonizer post-1945, colonial relationship for overall
171 countries. The final data set contains 145,350 observations (29,070 country pairs for
5 years)

en: information on ingredients of national dishes

en: shows information of ingredients of all national dishes of 171 countries and their names

en: dyadic food similarity measures, pairwise similarity and dissimilarity (chord diagram)

en:
The figures show the distribution of two dyadic food tastes similarity measures on the base of
the national dishes: (i) the Manhattan distance and the (ii) latent semantic analysis. The chord diagram
shows the results for country pairs with most and less similarity on basis of the LSA-approach.

en: The data described in this article were collected daily over the period 4 June 2018 to 23 August 2018 and contains information of several data sources. The database includes information on national recipes and their ingredients for 171 countries, measures for food taste similarities between all 171 countries as well as bilateral migration and agro-food trade data for 5 years. The database can be used for analyzing e.g., the relation between food preferences and international trade or food preferences and health outcomes (e.g., obesity) across countries.

agro-food-trade

display_name: agro-food-trade

food-preferences

display_name: food-preferences

food-taste-similarity

display_name: food-taste-similarity

latent-semantic-analysis

display_name: latent-semantic-analysis

national-dishes

display_name: national-dishes

en: Data of national dishes, their similarity and trade flows


en: relative-humidity growing-degree-days temperature precipitation solar-radiation growing-season-length soil-water-balance

en: CHELSA-BIOCLIM+ Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA-BIOCLIM+

en: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.

format: GeoTIFF

en: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.

growing-degree-days

display_name: growing-degree-days

growing-season-length

display_name: growing-season-length

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

soil-water-balance

display_name: soil-water-balance

solar-radiation

display_name: solar-radiation

temperature

display_name: temperature

en: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution


maintainer: Matthias Haeni

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

en: Site aerial photo (Bettlachstock)

en: Site aerial photo from both Bettlachstock stations. Source: Google. 2016. Site aerial photo from both Bettlachstock stations. Retrieved November 11, 2016, from https://www.google.ch/maps

mimetype: image/jpeg

en: Data plot of the forest station (BTB)

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

en: Field station data (BTF)

en: Data file.

mimetype: text/csv

en: Site photo of the field station (BTF)

en: Site photo of the field station from the side.

en: Data plot of the field station (BTF)

en: Site photo of the forest station (BTB)

en: Site photo of the forest station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Bettlachstock in Switzerland where one station is located within a natural mixed forest stand (BTB) with European beech (_Fagus sylvatica_; 170-190 yrs), European silver fir (_Abies alba_; 190 yrs) and Norway spruce (_Picea abies_; 200 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, BTF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Bettlachstock is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

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


maintainer: Lyu

en: species-distribution-model species-occurrence species-range-map fagales species-richness pinales

en: Species range maps of species in Fagales and Pinales (with enough occurrences)

en: species_map.zip includes species 1690 range maps generated based on the integrated method described in Lyu et al., (2022). File names with (polygon) indicate that this map is only generated by polygon mapping, as there are not enough occurrences for SDMs.

en: Occurrence maps for species of Fagales and Pinales with few records

en: Point_buffer.zip includes 267 occurrence maps of species that do not have enough occurrence data for polygon mapping.

en:
This database contains 1957 distribution maps of species from Fagales and Pinales constructed based on a method integrating polygon mapping and SDMs (Lyu et al., 2022).
To construct the maps, we first collected occurrence data from 48 different sources. According to the number of occurrences after data cleaning, three kinds of maps are constructed: (1) For species with more than 20 occurrences, we performed SDM and polygon mapping described in Lyu et al. (2022) and select the integration of the two layers as the distribution range; (2) For species with more than 4 but less than 20 occurrences, we only use polygon mapping to draw the distribution range; (3) For species with less than 4 occurrences, a 20-km buffer was generated around the occurrences as the distribution range. The maps were manually checked and evaluated (see Note S3 and Table S9 in Lyu et al., 2022 for details).

fagales

display_name: fagales

pinales

display_name: pinales

species-distribution-model

display_name: species-distribution-model

species-occurrence

display_name: species-occurrence

species-range-map

display_name: species-range-map

species-richness

display_name: species-richness

en: Species distribution maps of Fagales and Pinales (GDPlants)


regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

label: Link zur Detailbeschreibung

label: geocat.ch permalink

fr: Lien vers la distribution des données

de: Link für Datenbezug

en: Link for data download

it: Link per le fonti dei dati

fr: Lien vers le WMS

de: Link zum WMS

en: Link to WMS

it: Link verso WMS

format: WMS

protocol: WWW:DOWNLOAD:INTERLIS 1 (ITF)

fr: L'OFAC peut déterminer des alignements en vue d'assurer la libre disposition des terrains nécessaires à des installations d'aéroports existantes ou futures. Les alignements doivent satisfaire aux exigences de l'exécution finale prévisible de ces travaux et tenir compte des impératifs de l'aménagement du territoire et de la protection de l'environnement. Ils peuvent être limités en hauteur. A l'intérieur des alignements, toute transformation d'une construction et toute autre mesure contraire au but de l'alignement sont interdites. Font exception à cette règle les mesures destinées à assurer l'entretien ou à prévenir des dangers ou des effets dommageables. Jusqu'à présent, l'OFAC n'a pas fait usage de cet instrument. Il n'existe donc ni données ni modèle minimal de géodonnées pour ce jeu de données. Le jeu de métadonnées sert uniquement à décrire la couche correspondante du «Feature Service» pour les données de la Confédération dans les applications cantonales du cadastre RDPPF.

de: Das BAZL kann Baulinien zur Sicherung bestehender oder künftiger Flughafenanlagen festlegen. Die Baulinien müssen dem voraussichtlichen Endausbau entsprechen und der Raumplanung sowie dem Umweltschutz Rechnung tragen. Sie können vertikal begrenzt werden. Innerhalb der Baulinien dürfen keine baulichen Veränderungen oder sonstigen Vorkehren getroffen werden, die dem Zweck der Baulinie widersprechen. Ausgenommen sind Vorkehren, die dem Unterhalt oder der Beseitigung von Gefahren und schädlichen Einwirkungen dienen. Das BAZL hat bisher von diesem Instrument keinen Gebrauch gemacht. Es existieren deshalb keine Inhalte und kein Minimales Geodatenmodell zu diesem Datensatz. Der Metadatensatz dient einzig der Beschreibung des «Feature Service» zur entsprechenden Ebene in den kantonalen ÖREB-Katastern.

en: The FOCA can specify building lines to safeguard existing or future airport installations. The building lines must correspond to the intended final version and take account of spatial planning and environmental protection considerations. They can be limited vertically. No constructional changes or other measures that contradict the purpose of the building line may be implemented within building lines. This excludes maintenance or measures to eliminate hazards and damaging effects. The FOCA has not yet made use of this tool. As a result, no content and no minimal geodata model are available for this data set. The metadata set serves solely as a description of the Feature Service for the corresponding level in the cantonal PLR-cadastre.

it: L'UFAC può determinare allineamenti per assicurare impianti aeroportuali esistenti o futuri. Gli allineamenti devono corrispondere allo stato finale prevedibile delle opere e tener conto della pianificazione del territorio e della protezione dell'ambiente. Possono essere delimitati verticalmente. Entro gli allineamenti non può essere eseguita alcuna trasformazione edilizia o altro intervento contrari al loro scopo. Sono eccettuati i provvedimenti di manutenzione o per l'eliminazione di pericoli e di immissioni nocive. Fino ad oggi, l'UFAC non ha fatto ricorso a questo strumento; pertanto non esistono né dati né un modello minimo di geodati su questo livello d'informazione. I metadati hanno per unico scopo la descrizione del «Feature Service» del rispettivo livello nei catasti cantonali RDPP.

spatial: Schweiz

bundesamt-fur-zivilluftfahrt-bazl

fr: Office fédéral de l'aviation civile OFAC

de: Bundesamt für Zivilluftfahrt BAZL

en: Federal Office of Civil Aviation FOCA

it: Ufficio federale dell’aviazione civile UFAC

fr: L’Office fédéral de l’aviation civile (OFAC) est l’organe compétent en matière de politique aéronautique et de surveillance de l'aviation civile suisse. Placé sous l’autorité du Département fédéral de l’environnement, des transports, de l’énergie et de la communication (DETEC), l’OFAC veille à ce que l’aviation civile suisse bénéficie d’un niveau de sécurité élevé et suive un développement durable.

de: Das Bundesamt für Zivilluftfahrt (BAZL) ist für die Luftfahrtentwicklung und die Aufsicht über die zivile Luftfahrt in der Schweiz zuständig. Das BAZL gehört zum Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK) und ist dafür verantwortlich, dass die Zivilluftfahrt in der Schweiz ein hohes Sicherheitsniveau aufweist und eine nachhaltige Entwicklung verfolgt.

en: The Federal Office of Civil Aviation (FOCA) is responsible for aviation development and the supervision of civil aviation activities in Switzerland. The FOCA is part of the Federal Department of the Environment, Transport, Energy and Communications (DETEC) and is charged with ensuring that the high safety standards in civil aviation in Switzerland are maintained, and with pursuing a policy of sustainable development.

it: L’Ufficio federale dell’aviazione civile (UFAC), che fa parte del Dipartimento federale dell’ambiente, dei trasporti, dell’energia e delle comunicazioni (DATEC), è responsabile dell’evoluzione nel settore aeronautico e della sorveglianza sull’aviazione civile in Svizzera. Esso garantisce uno standard di sicurezza elevato e promuove il principio dello sviluppo sostenibile nell’aviazione civile elvetica.

political_level: confederation

value: BAZL - Geocat Harvester

fr: Alignements des installations aéroportuaires V2.0 RDPPF

de: Baulinien Flughafenanlagen V2.0 OeREB

en: Building lines for airports V2.0 PLR

it: Allineamenti per gli impianti aeroportuali V2.0 RDPP


label: Link zu Detailbeschreibung

fr: Zone clairement délimitée dont les terrains sont réservés en vue de futures installations aéroportuaires. Représentation des parcelles sur un plan à grande échelle. Les modifications de construction contraires à cette affectation ne sont pas admises. Durée limitée à une période de cinq ans prorogeable de trois ans au plus. Base légale (LA, art. 37n, al. 1): «En vue d’assurer la libre disposition des terrains nécessaires à des installations d’aéroport, l’Office fédéral peut, d’office ou sur requête de l’exploitant de l’aérodrome, du canton ou de la commune déterminer des zones réservées dont le périmètre est bien délimité. …»

de: Genau bezeichnetes Gebiet, in dem die Grundstücke für künftige Flughafenanlagen freizuhalten sind. Parzellenscharfe Darstellung mit einer Linie auf einem grossmassstäblichen Plan. Bauliche Veränderungen, die diesem Zweck widersprechen sind nicht gestattet. Befristete Wirkung von maximal 5 Jahren, mögliche Verlängerung um höchstens 3 Jahre. Rechtsgrundlage (LFG Art. 37n Abs. 1): «Das Bundesamt kann von Amtes wegen oder auf Antrag des Flugplatzhalters, des Kantons oder der Gemeinde für genau bezeichnete Gebiete Projektierungszonen festlegen, um Grundstücke für künftige Flughafenanlagen freizuhalten. …»

en: Designated area in which the land must be kept free for future airport installations. Plot-specific representation with a line on a large-scale plan. Constructional changes that contradict this purpose are not permitted. Limited effect of five years maximum, with a potential extension of up to three years. Legal basis (CAA Art. 37n Para. 1): “By virtue of its office or at the request of the airport owner, the canton or the local authority, the Federal Office can specify project planning zones for designated areas in order to keep land free for future airport installations ...”

it: Zona riservata determinata per impianti aeroportuali futuri. Rappresentazione che mette in evidenza le parcelle mediante linee su una carta a grande scala. Nelle zone riservate non possono essere eseguite trasformazioni edilizie contrarie al loro scopo. Durata: massimo cinque anni con possibile proroga di tre anni al massimo. Base giuridica (legge federale sulla navigazione aerea, LNA, art. 37n, cpv. 1): «L’UFAC può, d’ufficio o su proposta dell’esercente dell’aerodromo, del Cantone o del Comune, determinare zone riservate in regioni esattamente delimitate, per riservare i fondi necessari a costruzioni e impianti aeroportuali futuri. …»

fr: Zones réservées des installations aéroportuaires modification V2.0 RDPPF

de: Projektierungszonen Flughafenanlagen Aenderung V2.0 OeREB

en: Reserved zones for airport installations modification V2.0 PLR

it: Zone riservate per gli impianti aeroportuali modifica V2.0 RDPP


en: soil fungi grassland plants soil-chemistry soil-biology topsoil-removal nematodes bacteria restoration biodiversity soil-biodiversity

en: Networks

en:
Treatment	Treatment groups; Y.4-18 = restored grasslands; Initial = intensively managed grasslands; Target = species-rich semi-wet to semi-dry grasslands
Correlation	non-parametric Spearman rank correlations
Vertex.1+2	Comparison between network components; N.pool = total soil nitrogen pool [kg ha-1 12 cm-1]; Corg.pool = soil organic carbon pool [kg ha-1 12 cm-1], pH = soil pH [CaCl2]; BD = bulk density [g cm-3]; FC = field capacity [%]
	PCoA 1 + 2 biotic communities [Veg = vegetation; Nem = nematoda; Fun = fungi; Prok = prokaryota]
Type	Interactions type; A.A = abiotic.abiotic; A.B = abiotic.biotic; B.B = biotic.biotic

en: Vegetation data

en:
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)
column I-LW	Plant abundance per species (in total 327 plant species) expressed as cover percentage estimation according to van der Maarel (vdM 1979; 7 classes: 1-7); nomenclature according to Lauber & Wagner (1996)

en: Nematode data

en:
Sample.data
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)

Taxonomy
ASV.ID	unit number.letter code per amplicon sequence variant (in total 904)
Taxonomic rank	Phylum, Class, Order, Family, Genus, Species

Abundance
columns	Plot.ID (see Sample.data)
rows	ASV.ID (see Taxonomy)

en: Soil properties

en:
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)
N.pool	Soil nitrogen pool (June 2017); corrected for bulk density and 12 cm sampling depth [kg ha-1 12cm-1]
Corg.pool	Soil organic carbon pool (June 2017); corrected for bulk density and 12 cm sampling depth [kg ha-1 12cm-1]
pH	soil pH [CaCl2]
BD	Bulk density [g cm-3]
FC	Field capacity [%]
Veg.1	principle coordinate axis 1 (vegetation)
Veg.1	principle coordinate axis 2 (vegetation)
Nem.1	principle coordinate axis 1 (nematoda)
Nem.2	principle coordinate axis 2 (nematoda)
Fun.1	principle coordinate axis 1 (fungi)
Fun.2	principle coordinate axis 2 (fungi)
Prok.1	principle coordinate axis 1 (prokaryota)
Prok.2	principle coordinate axis 2 (prokaryota)
Veg.H	Shannon diversity (vegetation)
Nem.H	Shannon diversity (nematoda)
Fun.H	Shannon diversity (fungi)
Prok.H	Shannon diversity (prokaryota)

en: Fungi data

en:
Sample.data
Plot.ID	consecutive numbers for plots (in total 36 plots)
Treatment	One restoration treatment and two reference treatments. Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Initial=intensively managed grasslands; Target= species-rich semi-wet to semi-dry grasslands
treat.yr	Treatment abbreviation. For restored grasslands: Treatment abbreviation + time since restoration; Initial + Target = NA
yr.trt	year when topsoil was removed; Initial + Target = NA
Age	time since restoration (sampling year 2018 - yr.trt); Initial + Target = NA
Age.class	restored sites of similar age grouped into four age classes. Y.4 = Year 3+4 (recently restored); Y.18 = Year 17+19 (mid-term); Y.24 = Year 23+25 (long-term); Y.30 = Year 27+32 (long-term); Initial + Target = NA
Cluster	clustered spatial arrangment of sites in the field (see Supporting Information Fig. S1)
Site	clustered spatial arrangment (replicates) of plots per site (see Supporting Information Fig. S1)

Taxonomy
OTU.ID	consecutive numbers for operational taxonomic units (OTUe 1-7794)
Taxonomic rank	Domain, Phylum, Class, Order, Family, Genus, Species

Abundance
columns	Plot.ID (see Sample.data)
rows	OTU.ID (see Taxonomy)

en: Distance to target results

en:
Community	biotic community (vegetation, nematoda, fungi, prokaryota)
Treatment	Treatment groups; Y.4-30= restored grasslands (time since restoration); Initial=intensively managed grasslands (I)
Comparison	within- or between-community Bray-Curtis dissimilarity distance comparison
Label	within-community distances of initial/restored grasslands: treatment abbreviation; between-communities distances of initial/restored-to-target grasslands: treatment abbreviation plus Target (T; species-rich grasslands)
mean	Mean distance to Target (6 plots per treatment group)
sd	Standard deviation of distances to Target (6 plots per treatment group)

en: Ecosystem coupling_interactions

en:
Treatment	Treatment groups; Y.4-18 = restored grasslands; Initial = intensively managed grasslands; Target = species-rich semi-wet to semi-dry grasslands
Type	Interactions type; A.A = abiotic.abiotic; A.B = abiotic.biotic; B.B = biotic.biotic
Correlation	non-parametric Spearman rank correlations between biotic and abiotic parameters (ecological interactions)

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

Paper Citation:

_Resch, M.C., Schütz, M., Ochoa-Hueso, R., Buchmann, N., Frey, B., Graf, U., van der Putten, W.H., Zimmermann, S., Risch, A.C. (in review). Long-term recovery of above- and belowground interactions in restored grassland after topsoil removal and seed addition. Journal of Applied Ecology_

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

Study area and experimental design
The study was conducted in and around two nature reserves, Eigental and Altläufe der Glatt, which were located approximately 5 km apart (47°27´ to 47°29´ N, 8°37´ to 8°32´ E, 417 to 572 m a.s.l., Canton of Zurich, Switzerland; Figure S1 and S2, Table S1). Mean annual temperature and precipitation are 9.8 ± 0.6 °C and 990 ± 168 mm (Kloten climate station 1988-2018; MeteoSchweiz, 2019). TFor this study, we used a space-for-time approach based on eight restoration sites that were between 3 and 32 years old. We measured recovery and restoration success by comparing the restored grasslands with intensively managed and semi-natural grasslands. Using a space-for-time approach requires high similarities in historical properties of the site, such as soil conditions and management regimes, to assure that temporal processes are appropriately represented by spatial patterns (Walker et al., 2010). This was the case in our study. The restored sites had similar soil conditions (i.e., soil type, structure, water availability) as the targeted semi-natural grasslands, while they shared the same agricultural legacy with intensively managed grasslands, i.e., biomass harvest and fertilization (manure and/or slurry) three to five times a year as well as tillage. We randomly established three 5 m x 5 m (25-m2) plots for plant identification and three 2 m x 2 m (4-m2) subplots for soil biotic and abiotic data collection at least 2 m away from the 25-m2 plots in each restoration site. Sites of similar age were grouped into four age classes: Y.4 (3 & 4 years after restoration), Y.18 (17 & 19 years), Y.24 (23 & 25 years), and Y.30 (27 & 32 years). Six intensively managed (Initial) and six semi-natural grassland (Target) sites complemented the experimental set-up, for a total of 36 plots. All plots were sampled under similar conditions, i.e., day of the year, air temperature, soil moisture, and time since last rain event, in June/July 2017 (intensively managed and semi-natural plots) and 2018 (restored plots).

Collection of plants and selected soil biota data
Plant species cover (in %) was visually estimated in each 25-m2 plot in mid-June (Braun-Blanquet, 1964; nomenclature: Lauber & Wagner, 1996). We calculated Shannon diversity and assessed plant community structure. We included soil microbial (fungi, procaryotes) and nematodes in our study as they represent the majority of soil biotic diversity and abundance (Bardgett & van der Putten, 2014), cover various trophic levels of the soil food web (Bongers & Ferris, 1999), and play key roles in soil functioning and ecosystem processes (Bardgett & van der Putten, 2014). In particular, soil nematodes were found to be well suited belowground indicators to evaluate recovery/development after restoration (e.g. Frouz, et al. 2008; Kardol et al., 2009; Resch et al., 2019). We randomly collected ten soil cores (2.2 cm diameter x 12 cm depths; sampler from Giddings Machine Company, Windsor, USA) in the 4-m2 subplots to assess soil nematode and microbial (fungal, prokaryotic) diversities and community structures. For soil nematodes, eight of the soil cores were combined and gently homogenized, placed in coolers and stored at 4 °C and transported to the laboratory (Netherlands Institute of Ecology, NIOO, Wageningen, Netherlands) within three days after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriators (Oostenbrink, 1960). After extraction, each sample was divided into three subsamples, two for molecular identification and one to determine nematode abundance (see Resch et al., 2019). For the molecular work, two subsamples were stored in 70% ethanol (final volume 10 mL each) and transported to the laboratory at the Swiss Federal Research Institute WSL (Birmensdorf, Switzerland). Each subsample was reduced to roughly 200 μL by centrifugation and removal of the supernatant. The remaining ethanol was vaporized (65 °C for 3 h). Thereafter, 180 μL ATL buffer solution (Qiagen, Hilden, Germany) was immediately added and samples were stored at 4 °C until further processing. From these samples, nematode metagenomic DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer`s protocol, except for the incubation step which was run at 56 °C for 4 h. PCR amplification of the V6-V8 region of the eukaryotic small-subunit (18S) was performed with 7.5 μL of genomic DNA template (ca. 1 ng/μL) in 25 μL reactions containing 5 μL PCR reaction buffer, 2.5 mM MgCL2, 0.2 mM dNTPs, 0.8 μM of each primer (NemF: Sapkota & Nicolaisen, 2015; 18Sr2b: Porazinska et al., 2009), 0.5 μL BSA, and 0.25 μL GoTaq G2 Hot Start Polymerase (Promega Corporation, Madison, USA). Amplification was using an initial DNA denaturation step of 95 °C for 2 min, followed by 35 cycles at 94 °C for 40 sec, 58 °C for 40 sec, 72 °C for 1 min, and a final elongation step at 72 °C for 10 min. Filtering, dereplication, sample inference, chimera identification, and merging of paired-end reads was implemented using the DADA2 pipeline (v.1.12; Callahan et al., 2016) to finally assign amplicon sequence variants (ASVs) as taxonomic units.
We combined and homogenized the remaining two soil cores to assess soil microbes, placed them in coolers (4 °C) and transported them to the laboratory at WSL. Metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNAeasy PowerMax Soil Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol. PCR amplification of the V3-V4 region of the small-subunit (16S) of prokaryotes (i.e., bacteria and archaea) and the ribosomal internal transcribed spacer region (ITS2) of fungi was performed with 1 ng of template DNA using PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates, pooled and 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, USA). Quality filtering, clustering into operational taxonomic units (OTUs, 97% similarity cutoffs) and taxonomic assignment were performed as previously described (Resch et al., 2021).Taxonomic classification of nematode, prokaryotic and fungal sequences was conducted querying against the most recent versions of PR2 (v.4.11.1; Guillou et al., 2013), SILVA (v.132; Quast et al., 2013), and UNITE (v.8; Nilsson et al., 2019) reference sequence databases. Taxonomic assignment cutoffs were set to confidence rankings ≥ 0.8 (below ranked as unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as OTUs or ASVs assigned to other than Fungi or Nematoda were manually removed prior to data analysis. The three datasets were filtered to discard singletons and doubletons. Taxonomic abundance matrices were rarefied to the lowest number of sequences per community to achieve parity of the total number of reads between samples (Prokaryotes: 10,929 reads; Fungi: 18,337 reads; Nematodes: 6,662 reads). We calculated Shannon diversity and assessed community structures for soil nematodes, prokaryotes and fungi based on their relative abundances of ASV or OTU at the taxon level.

Collection of soil physical and chemical properties
We randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) per 4-m2 subplot using a steel cylinder that fit into the soil corer. The cylinders were capped to avoid disturbance during transport and used to measure field capacity, rock content and fine earth density as previously described (Resch et al., 2021). We randomly collected another three soil cores (5 cm diameter, 12 cm depths) in each 4-m2 subplot to determine soil chemical properties. The cores were pooled, dried at 60 °C for 48 h and passed through a 2 mm sieve. We measured soil pH (CaCl2) on dried samples, total nitrogen (N) and organic carbon (C) concentration on dried and fine-ground samples (≤ 0.5 mm; for details see Resch et al., 2021). We calculated total N and organic C pools after correcting its concentration for soil depth, rock content and fine earth density.

bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

fungi

display_name: fungi

grassland

display_name: grassland

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil

display_name: soil

soil-biodiversity

display_name: soil-biodiversity

soil-biology

display_name: soil-biology

soil-chemistry

display_name: soil-chemistry

topsoil-removal

display_name: topsoil-removal

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Long-term recovery of above-and belowground interactions in restored grasslands


regi

en: Regions and cities

envi

en: Environment

de: gewasserschutz grundwasser hydrologie

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: zeigt die nutzbaren Grundwasservorkommen, die oberirdischen Gewässer und Uferbereiche, die mittleren Grundwasserspiegel und die Mächtigkeit des Grundwassers.

spatial: Kanton Luzern

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

political_level: canton

value: LU-Kt - Geocat Harvester

de: Grundwasservorkommen


regi

de: Regionen und Städte

de: oreb flugplatz zonenplan luftfahrt luftfahrthindernis flughafen zivilluftverkehr luftverkehr sicherheit bgdi-bundesgeodaten-infrastruktur

en: Link for data download

en: Link to WMS

fr: Une zone de sécurité doit être établie pour chaque aéroport. Pour les installations de navigation aérienne et les trajectoires de vol, l’OFAC décide dans chaque cas si une zone de sécurité est nécessaire. Le cadastre des surfaces de limitation d’obstacles est déterminant pour établir les zones de sécurité. Elles sont représentées dans un plan de zone indiquant les restrictions de la propriété en surface et en hauteur. Le plan des zones de sécurité approuvé entre en force par sa publication dans les organes officiels cantonaux et constitue une restriction de droit public apportée à la propriété foncière.

de: Für jeden Flughafen ist eine Sicherheitszone zu errichten, welche den Luftraum vor Hindernissen schützt. Das BAZL entscheidet im Einzelfall, ob für Flugsicherungsanlagen und Flugwege eine Sicherheitszone erforderlich ist. Für die Festsetzung der Sicherheitszonen sind die Hindernisbegrenzungsflächen-Kataster massgebend. Die Sicherheitszone wird in einem Zonenplan dargestellt, aus dem die Eigentumsbeschränkungen nach Fläche und Höhe ersichtlich sind. Die genehmigten Sicherheitszonenpläne werden mit ihrer Veröffentlichung in den kantonalen Publikationsorganen verbindlich und stellen eine öffentlich-rechtliche Eigentumsbeschränkung dar.

en: For each airport, a security zone is to be established, which protects the airspace from obstacles. The FOCA will decide in each case whether a safety zone is necessary for air navigation equipment and flight paths. Authoritative for the establishment of safety zones is the cadastre of obstacle limitation surfaces. The safety zones are represented in a zone map, where the restrictions of property rights on area and height are shown. The approved security zone plans are binding upon publication in the cantonal publications and constitute a public property restriction.

it: Per ogni aeroporto deve essere fissata una zona di sicurezza volta a proteggere lo spazio aereo da ostacoli. L’UFAC decide caso per caso se è necessario fissare una zona di sicurezza per gli impianti della navigazione aerea e le traiettorie di volo. Per la delimitazione delle zone di sicurezza è determinante il catasto delle superfici di limitazione degli ostacoli. La zona di sicurezza è illustrata in un piano di zona che indica le restrizioni della proprietà in superficie e in altezza. I piani delle zone di sicurezza approvati diventano vincolanti con la pubblicazione negli organi cantonali ufficiali e rappresentano una restrizione di diritto pubblico della proprietà.

bundesamt-fur-zivilluftfahrt-bazl

en: Federal Office of Civil Aviation FOCA

en: The Federal Office of Civil Aviation (FOCA) is responsible for aviation development and the supervision of civil aviation activities in Switzerland. The FOCA is part of the Federal Department of the Environment, Transport, Energy and Communications (DETEC) and is charged with ensuring that the high safety standards in civil aviation in Switzerland are maintained, and with pursuing a policy of sustainable development.

fr: Plan de la zone de sécurité modification V2.0 RDPPF

de: Sicherheitszonenplan Aenderung V2.0 OeREB

en: Safety zone plan modification V2.0 PLR

it: Piano delle zone di sicurezza modifica V2.0 RDPP


schutzinventar-kultur

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

title_for_slug: schutzinventar-kultur

fr: isos zone geodonnees-de-base

de: isos zone geobasisdaten

en: isos zone official-geodata

it: isos zona geodati-di-base

label: Web GIS Client des Kanton Uri. Die Daten können direkt via dem Portal in den unterschiedlichsten Datenformaten heruntergeladen werden.

fr: WMS-Dienst des Kanton Uri

de: WMS-Dienst des Kanton Uri

en: WMS-Dienst des Kanton Uri

it: WMS-Dienst des Kanton Uri

fr: WFS-Dienst des Kanton Uri

de: WFS-Dienst des Kanton Uri

en: WFS-Dienst des Kanton Uri

it: WFS-Dienst des Kanton Uri

format: WFS

fr: Der Datensatz zeigt die schutzwürdigen Objekte (Gebiete, Einzelobjekte) im Bereich Kultur. Das Kantonale Schutzinventar hat gemäss kNHG Art. 17 hinweisenden Charakter. Es ist nicht abschliessend und wird laufend nachgeführt. Rechtsverbindliche Angaben sind bei der Fachstelle Heimatschutz und Denkmalpflege erhältlich. Die Archäologischen Zonen sind nicht Bestandteil des Schutzinventars und werden lediglich zur Information aufgeführt. Für die Anzeige des vollständigen Schutzinventars müssen noch die beiden Layer "Schutzinventar: Natur" und "Schutzinventar: Landschaft" dazugeladen werden. Link zu den Inventarlisten des Kantons Uri

spatial: Canton of Uri (UR)

geoinformation-kanton-uri

de: Lisag AG, Geoinformation Kanton Uri

de: Die Lisag AG bewirtschaftet das geografische Informationssystem des Kantons Uri (GIS Uri), ist die verantwortliche Stelle für den ÖREB-Kataster Uri und zudem zuständig für die Durchführung der amtlichen Vermessung auf Urner Kantonsgebiet.

value: Uri-Kt - Geocat Harvester

fr: Schutzinventar Kultur

de: Schutzinventar Kultur

en: Schutzinventar Kultur

it: Schutzinventar Kultur


regi

fr: Régions et villes

it: Regioni e città

envi

fr: Environnement

de: Umwelt

it: Ambiente

de: oreb flugplatz luftfahrt belasteter-standort flughafen altlast umweltuberwachung boden bgdi-bundesgeodaten-infrastruktur

fr: Lien vers la distribution des données

de: Link für Datenbezug

it: Link per le fonti dei dati

fr: Lien vers le WMS

de: Link zum WMS

it: Link verso WMS

fr: Cadastre public des sites pollués dans le périmètre des aérodromes civils. Le cadastre renseigne dans la mesure du possible sur l’emplacement, le type et la quantité de déchets présents sur le site, sur la période de stockage des déchets et sur les investigations et les mesures de protection de l’environnement déjà réalisées. On distingue entre les types de sites suivants: aires d’exploitation, lieux d’accident et sites de stockage.

de: Öffentlich zugänglicher Kataster der belasteten Standorte im Perimeter der zivilen Flugplätze. Der Kataster gibt unter anderem Auskunft über die Lage, die Art und Menge der an den Standort gelangten Abfälle, den Ablagerungszeitraum, sowie durchgeführte Untersuchungen und Massnahmen. Unterschieden werden folgende Standorttypen: Betriebsstandort, Unfallstandort und Ablagerungsstandort.

en: Public register of contaminated sites within the perimeter of civil aerodromes. This includes information about the location, type and quantity of waste, the period of deposition, as well as conducted studies and measures. The following types of sites can be distinguished: operating site, accident site and deposition site.

it: Catasti pubblici dei siti inquinati nel perimetro degli aerodromi civili. Il catasto informa, tra l’altro, sull’ubicazione, sul tipo e la quantità di rifiuti presenti sul sito, sui tempi di deposito, sulle verifiche effettuate e le misure adottate. Si distingue tra i seguenti tipi di siti: aree d’impresa, luoghi d’incidente, siti di stoccaggio.

bundesamt-fur-zivilluftfahrt-bazl

de: Bundesamt für Zivilluftfahrt BAZL

de: Das Bundesamt für Zivilluftfahrt (BAZL) ist für die Luftfahrtentwicklung und die Aufsicht über die zivile Luftfahrt in der Schweiz zuständig. Das BAZL gehört zum Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK) und ist dafür verantwortlich, dass die Zivilluftfahrt in der Schweiz ein hohes Sicherheitsniveau aufweist und eine nachhaltige Entwicklung verfolgt.

fr: Cadastre des sites pollués – domaine des aérodromes civils (CSP OFAC) V2.0 RDPPF

de: Kataster der belasteten Standorte im Bereich der zivilen Flugplätze (KbS BAZL) V2.0 OeREB

en: Cadastre of contaminated sites on civil aerodromes (CCS FOCA) V2.0 PLR

it: Catasto dei siti inquinati nel settore degli aeroporti civili (CSIN UFAC) V2.0 RDPP


regi

de: Regionen und Städte

en: Regions and cities

de: oreb flugplatz zonenplan luftfahrt luftfahrthindernis flughafen zivilluftverkehr sicherheit luftverkehr bgdi-bundesgeodaten-infrastruktur

de: Für jeden Flughafen ist eine Sicherheitszone zu errichten, welche den Luftraum vor Hindernissen schützt. Das BAZL entscheidet im Einzelfall, ob für Flugsicherungsanlagen und Flugwege eine Sicherheitszone erforderlich ist. Für die Festsetzung der Sicherheitszonen sind die Hindernisbegrenzungsflächen-Kataster massgebend. Die Sicherheitszone wird in einem Zonenplan dargestellt, aus dem die Eigentumsbeschränkungen nach Fläche und Höhe ersichtlich sind. Die genehmigten Sicherheitszonenpläne werden mit ihrer Veröffentlichung in den kantonalen Publikationsorganen verbindlich und stellen eine öffentlich-rechtliche Eigentumsbeschränkung dar.

fr: Office fédéral de l'aviation civile OFAC

it: Ufficio federale dell’aviazione civile UFAC

fr: L’Office fédéral de l’aviation civile (OFAC) est l’organe compétent en matière de politique aéronautique et de surveillance de l'aviation civile suisse. Placé sous l’autorité du Département fédéral de l’environnement, des transports, de l’énergie et de la communication (DETEC), l’OFAC veille à ce que l’aviation civile suisse bénéficie d’un niveau de sécurité élevé et suive un développement durable.

it: L’Ufficio federale dell’aviazione civile (UFAC), che fa parte del Dipartimento federale dell’ambiente, dei trasporti, dell’energia e delle comunicazioni (DATEC), è responsabile dell’evoluzione nel settore aeronautico e della sorveglianza sull’aviazione civile in Svizzera. Esso garantisce uno standard di sicurezza elevato e promuove il principio dello sviluppo sostenibile nell’aviazione civile elvetica.

fr: Plan de la zone de sécurité V2.0 RDPPF

de: Sicherheitszonenplan V2.0 OeREB

en: Safety zone plan V2.0 PLR

it: Piano delle zone di sicurezza V2.0 RDPP


tranquillity-map

envi

en: Environment

title_for_slug: tranquillity-map

fr: Service WMS-IFDG, couche "Carte Tranquillité"

de: WMS-BGDI Dienst, Layer "Tranquillity Map"

en: WMS-FSDI service, layer "Tranquillity Map"

it: Servizio WMS-IFDG, strato "Mappa Tranquillità"

fr: Service WMTS-IFDG, couche , Layer "Tranquillity Map"

de: WMTS-BGDI Dienst, Layer "Tranquillity Map"

en: WMTS-FSDI service, layer "Tranquillity Map"

it: Servizio WMTS-IFDG, strato "Mappa Tranquillità"

format: WMTS

fr: Map (Preview) Aperçu map.geo.admin.ch

de: Map (Preview) Vorschau map.geo.admin.ch

en: Map (Preview)  map.geo.admin.ch

it: Map (Preview) Previsione map.geo.admin.ch

de: Link zum Datenbezug

en: Link for download

protocol: WWW:DOWNLOAD:Cloud Optimized GeoTIFF

de: Download Cloud Optimized GeoTIFF

format: cloud optimized geotiff

fr: Fondation suisse pour la protection et l'aménagement du paysage

de: Stiftung Landschaftsschutz Schweiz

en: Stiftung Landschaftsschutz Schweiz

it: Fondazione svizzera per la tutela del paesaggio

fr: La «Tranquillity map du Plateau suisse» ou «Carte de quiétude» montre où l’on trouve sur le Plateau, à proximité des grandes agglomérations, des paysages comportant peu d’infrastructures et peu exposées au bruit qui se prêtent à la détente dans le calme. Pour créer cette carte, la région biogéographique du Plateau a été divisée selon une trame de 100 x 100 mètres. Un calcul prenant en compte différents facteurs positifs et négatifs qui influent sur le calme et la détente par les biais visuel et auditif a produit une valeur de quiétude pour chaque cellule de la grille.

de: Die «Tranquillity Map des Schweizer Mittellands» zeigt auf, wo es im Schweizer Mittelland in der Nähe grosser Siedlungen naturnahe und wenig lärmbelastete Gebiete gibt, die sich für die ruhige Erholung eignen. Dazu wurde die biogeographische Region Mittelland in ein Raster von 100 x 100 m Zellengrösse eingeteilt. Durch die Berechnung verschiedener positiver und negativer Faktoren, die über Augen bzw. Ohren das Ruhe- und Erholungserlebnis beeinflussen, wurde pro Rasterzelle ein «Tranquillity»-Wert errechnet.

en: The "Tranquillity Map of the Swiss Plateau" illustrates where areas of near-natural character and low noise pollution still exist near large settlements within the Swiss Plateau. These areas are suitable for quiet recreation. To create the map, the biogeographical region of the Central Plateau was divided into a grid of 100 x 100 m cell size. By calculating various positive and negative factors that influence the experience of tranquillity and recreation through eyes and ears respectively, a "tranquillity" value was calculated for each grid cell.

it: La “Tranquillity map dell'Altopiano centrale svizzero” mostra dove si trovano aree pressoché naturali e poco rumorose nell'Altopiano, in prossimità di grandi insediamenti, adatte a uno svago di carattere tranquillo. A tale scopo, la regione biogeografica dell'Altopiano centrale è stata suddivisa in una griglia di celle di 100 x 100 metri. Calcolando vari fattori positivi e negativi che influenzano l'esperienza della tranquillità e dello svago, sia a livello visuale che a livello acustico, è stato calcolato un valore di "tranquillità" per ciascuna di queste celle.

name: Bundesamt für Umwelt / Abteilung Biodiversität und Landschaft

bundesamt-fur-umwelt-bafu

fr: Office fédéral de l'environnement OFEV

de: Bundesamt für Umwelt BAFU

en: Federal Office for the Environment FOEN

it: Ufficio federale dell'ambiente UFAM

fr: L’autorité compétente pour les questions environnementales. Il est à ce titre chargé de gérer les ressources naturelles selon les principes du développement durable et de protéger l’homme contre les dangers naturels et l’environnement contre les pollutions.

de: Die Fachbehörde für die Umwelt. Es ist zuständig für die nachhaltige Nutzung der natürlichen Ressourcen sowie für den Schutz des Menschen vor Naturgefahren und den Schutz der Umwelt vor übermässigen Belastungen.

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

it: Il servizio specializzato in materia ambientale, è competente per quanto riguarda l'utilizzazione sostenibile delle risorse naturali, la protezione delle persone dai pericoli naturali e dell'ambiente da un inquinamento eccessivo.

value: BAFU - Geocat Harvester

fr: Tranquillity map

de: Tranquillity Map

en: Tranquillity Map

it: Tranquillity map


en: reef-fish dispersal ecology biodiversity traits

en: 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

en: 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: 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

en: 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: Global species distribution of tropical reef fish species

en: 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: Input for the Global distribution maps for proportions of species richness for (a) simulated dispersal parameter value (b) observed dispersal-related traits

en: 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: Main text figures

en: 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: Global coast files from https://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html used in the Figures

en: Donati et al. main script

en:
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: Coral reef grid cells (shape, dbf, etc. files)

en:
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: Global simulated distribution of species under a range of dispersal parameter values

en:
Global distribution of simulated species richness under a range of dispersal parameter values d
d ∈ [1.75°: 5.45°].

en: 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: 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: Tropical reef fish trait data

en:
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:
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.

dispersal

display_name: dispersal

ecology

display_name: ecology

reef-fish

display_name: reef-fish

traits

display_name: traits

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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.

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


tranquillity-gebiete

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: tranquillity-gebiete

de: umwelt lebensraume-und-biotope schutzgebiete erholungsanlage gewasserraum bgdi-bundesgeodaten-infrastruktur ruhe

label: Stiftung Landschaftsschutz Schweiz

fr: Service WMS-IFDG, couche "Zones tranquil"

de: WMS-BGDI Dienst, Layer "Tranquillity Gebiete"

en: WMS-FSDI service, layer "Tranquillity Areas"

it: Servizio WMS-IFDG, strato "Zone tranquille"

fr: Service WMTS-IFDG, couche , Layer "Zones tranquil"

de: WMTS-BGDI Dienst, Layer "Tranquillity Gebiete"

en: WMTS-FSDI service, layer "Tranquillity Areas"

it: Servizio WMTS-IFDG, strato "Zone tranquille"

fr: RESTful API de geo.admin.ch

de: RESTful API von geo.admin.ch

en: RESTful API from geo.admin.ch

it: RESTful API da geo.admin.ch

format: API

en: Map (Preview)  map.geo.admin.ch

fr: Lien vers la distribution des données

en: Link for download

it: Link per le fonti dei dati

protocol: WWW:DOWNLOAD:ESRI File Geodatabase FileGDB (GDB)

de: Download ESRI File Geodatabase FileGDB (GDB)

de: ESRI File Geodatabase FileGDB (GDB)

protocol: WWW:DOWNLOAD:OGC Geopackage (GPKG)

de: Download OGC Geopackage (GPKG)

de: OGC Geopackage (GPKG)

format: GPKG

protocol: WWW:DOWNLOAD:ESRI Shapefile (SHP)

de: Download ESRI Shapefile (SHP)

de: ESRI Shapefile (SHP)

fr: Sur la base de la «Carte de quiétude du Plateau suisse», certaines zones particulièrement propices à la détente ont été identifiées à partir des valeurs de quiétude calculées. Pour ce faire, des surfaces ont été sélectionnées qui, sur au moins 500 cellules de grille contiguës (soit 5 km²), ne sont pas inférieures à un certain indice de "quiétude". Cette méthode a permis de distinguer pour le Plateau suisse, 53 zones d’une certaine étendue qui se prêtent à la détente dans le calme.

de: Ausgehend von der «Tranquillity Map des Schweizer Mittellands» wurden aus den berechneten «Tranquillity»-Werten bestimmte Erholungsgebiete abgeleitet. Dazu wurden Flächen selektiert, die über mindestens 500 zusammenhängende Rasterzellen hinweg (5 km²) einen bestimmten «Tranquillity»-Index nicht unterschreiten. Durch dieses Verfahren konnten für das Schweizer Mittelland 53 grossräumige Gebiete abgeleitet werden, die sich für die ruhige Erholung eignen.

en: Based on the "Tranquillity Map of the Swiss Plateau" and its calculated "tranquillity" values, certain recreational areas were derived. For this purpose, areas that did not fall below a certain "tranquillity" index over at least 500 contiguous grid cells (5 km²) were selected. Using this procedure, 53 large-scale areas could be derived for the Swiss Plateau that are suitable for quiet recreation.

it: Sulla base della “Tranquillity map dell'Altopiano centrale svizzero”, sulla base dei valori di "tranquillità" calcolati, sono state ricavate alcune aree ricreative tranquille. A tale scopo, sono state selezionate le aree il cui indice di "tranquillità" non scende al di sotto di un certo valore su almeno 500 celle contigue (che corrispondono a 5 km²). Con questa procedura è stato possibile ricavare 53 aree per l'Altopiano svizzero adatte a uno svago di carattere tranquillo.

bundesamt-fur-umwelt-bafu

en: Federal Office for the Environment FOEN

en: The federal environmental authority. It is responsible for ensuring that natural resources are used sustainably, that the public is protected against natural hazards, and that the environment is protected from unacceptable adverse impacts.

fr: Zones de quiétude

de: Tranquillity Gebiete

en: Tranquillity Areas

it: Aree tranquille


de: betreibung auskunfte

de: xls

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (xls)

license: CC BY

de: rdfxml

media_type: application/rdf+xml

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (rdfxml)

format: RDF XML

de: parquet

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (parquet)

de: csv

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (csv)

de: jsonld

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (jsonld)

format: JSON-LD

de: turtle

media_type: text/turtle

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (turtle)

format: RDF Turtle

de: fgb

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (fgb)

format: octet-stream

de: jsonl

media_type: application/json

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (jsonl)

format: JSON

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (n3)

de: json

de: Auskünfte Betreibungsregister Stadt St.Gallen (2005-2018) (json)

de: Anzahl der Betreibungsregisterauskünfte der Stadt St.Gallen (2005-2018)

auskunfte

display_name: auskunfte

betreibung

display_name: betreibung

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze

stadt-st-gallen

fr: Ville de Saint-Gall

de: Stadt St.Gallen

en: City of St.Gallen

it: Città di San Gallo

fr: Avec une population de 80 000 habitants, Saint-Gall, huitième ville de Suisse, est la métropole économique, politique, sociale et culturelle de la Suisse orientale. Ses 1400 ans d'histoire se mêlent à la créativité urbaine, à une économie innovante et à un paysage préservé.

en: With a population of 80,000, St.Gallen, Switzerland’s eighth largest city, is the economic, political, social and cultural metropolis of eastern Switzerland. Its 1400 years of history blend with urban creativity, an innovative economy and an unspoilt landscape.

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.

it: Con una popolazione di 80.000 abitanti, San Gallo, l'ottava città più grande della Svizzera, è la metropoli economica, politica, sociale e culturale della Svizzera orientale. I suoi 1400 anni di storia si fondono con la creatività urbana, un'economia innovativa e un paesaggio incontaminato.

political_level: commune

value: DCAT Harvester Stadt St. Gallen


de: budget rechnung funktionen haushalt

de: rdfxml

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (rdfxml)

de: xls

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (xls)

de: csv

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (csv)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (n3)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (turtle)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (json)

de: parquet

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (parquet)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (jsonl)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (jsonld)

de: Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung (fgb)

de: Der Datensatz zeigt das Budget 2021 der Stadt St.Gallen nach Funktionaler Gliederung. Ebenfalls enthalten sind die Rechnung 2019, das Budget 2020, sowie die Abweichung zum Budget 2021. Eine klickbare Visualisierung des Budgets finden Sie im Tab "Klickbares Budget"

budget

display_name: budget

funktionen

display_name: funktionen

haushalt

display_name: haushalt

rechnung

display_name: rechnung


de: umweltbelastung co2 energy-hackdays material sektor entsorgung

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (csv)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (rdfxml)

de: fgb

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (fgb)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (parquet)

de: jsonld

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (jsonld)

de: json

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (json)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (xls)

de: jsonl

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (jsonl)

de: turtle

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (turtle)

de: Material- und Energieflüsse Schweiz und St.Gallen (EMPA MATCH) Synthese 2020 Entsorgungswege (Tonnen & CO2eq) (n3)

de: Der Datensatz zeigt die Material- und Energieflüsse der Entsorgungswege der Schweiz aus dem MatCH Synthesebericht der Eidgenössische Materialprüfungs- und Forschungsanstalt (EMPA), in dem u.a. die Umweltbelastung (Tonnen & CO2) der Wirtschaftssektoren berechnet wird.Der Datensatz wurde aus dem Synthesebericht 2018 erstellt und für die Energy Hackdays 2021 aufbereitet. Daraus entstand eine Anwendung zum Thema "Klimaneutrale Städte". Mehr Infos dazu: https://hack.opendata.ch/project/745Mehr Infos zum Projekt MatCH und zu den verschiedenen Berichten finden Sie unter folgenden Ressourcen:MatCH Projekt InformationenBericht - Synthesis: The Swiss EconomyBericht - Building sector Bericht - Mobility sectorBericht - Production and consumption sector

energy-hackdays

display_name: energy-hackdays

entsorgung

display_name: entsorgung

material

display_name: material

sektor

display_name: sektor

umweltbelastung

display_name: umweltbelastung

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

envi

de: Umwelt

tran

fr: Transports

de: Verkehr

en: Transport

stadt-st-gallen

de: St.Gallen, die achtgrösste Stadt der Schweiz, ist mit 80'000 Einwohnern die wirtschaftliche, politische, soziale und kulturelle Metropole der Ostschweiz. Ihre 1400-jährige Geschichte verbindet sich mit urbaner Kreativität, einer innovativen Wirtschaft und einer intakten Landschaft.


en: urban-compactness nature-conservation land-use-and-cover-change urban-morphology forest-gain topography urban-sprawl built-up-classification forest-persistence planning-outcome basic-services spatial-modelling

en: Master plan Ihabela (zones)

format: SHP

en: Increase in clean water provision service

en: Master plan Ubatuba (zones)

format: SERVICE

en: isolated

en: New built-up pixels classified as isolated

en: Topographic Index Position (TPI)

en:
Basic education in % per census sector (change per
year)

en: Increase in sanitation service

en: Variables description

en: Table of content. Variables description, source, and other important information

en: Increase in waste collection service

en: Permanent housing density increase

en: Descricao dos dados em portiuguês

en: Portugues description

en: slope

en: Slope °

en: infill

en: New built-up pixels classified as infill

en: Increase in Normalized Difference Vegetation Index

en: Population density per pixel (change per year)

en: Human Development Index (HDI) per municipality (change per year)

en: Axial

en: New built-up pixels classified as axial

en: Urban persistence: Built-up 2005 = Built-up 2015

en: Native forest cover persistence from 2005 to 2015

en: Mean income in Reais (R$) per census sector (change per year)

en: Native forest cover gains from 2005 to 2015

en: Ecological-Economic Zoning (EEZ)

en:
The present dataset is part of the published scientific paper entitled “The role of spatial planning in land change: An assessment of urban planning and nature conservation efficiency at the southeastern coast of Brazil” (Pierri Daunt, Inostroza and Hersperger, 2021). In this work, we evaluated the conformance of stated spatial planning goals and the outcomes in terms of urban compactness, basic services and housing provision, and nature conservation for different land-use strategies. We evaluate the 2005 Ecological-Economic Zoning (EEZ) and two municipal master plans from 2006 in a coastal region in São Paulo State, Brazil. We used Partial Least Squares Path Modelling (PLS-PM) to explain the relationship between the plan strategies and land-use change ten years after implementation in terms of urban compactness, basic services and housing increase, and nature conservation.

We acquired the data for the explanatory variables from different sources listed on Table 1. Since the model is spatially explicit, all input data were transformed to a 30 m resolution raster. Regarding the evaluated spatial plans, we acquired the zones limits from the São Paulo State Environmental Planning Division (CPLA-SP), Ilhabela and Ubatuba municipality.

1)	Land use and cover data: Urban persistence, Urban axial, Urban infill, Urban Isolates, Forest cover persistence, Forest cover gain, NDVI increase

We acquired two Landsat Collection 1 Higher-Level Surface Reflectance images distributed by the U.S. Geological Survey (USGS), covering the entire study area (paths 76 and 77, row 220, WRS-2 reference system, https://earthexplorer.usgs.gov/). We classified one image acquired by the Landsat 5 Thematic Mapper (TM) sensor on 2005-05-150, and one image from the Landsat 8 Operational Land Imager (OLI) sensor from 2015-08-15. We collected 100 samples for forest cover, 100 samples for built-up cover and 100 samples for other classes. We then classified these three classes of land cover at each image date using the Support Vector Machine (SVM) supervised algorithm (Hsu et al., 2003), using ENVI 5.0 software.

Land-use and land-cover changes from 2005 to 2015 were quantified using map algebra, by mathematically adding them together in pairs (10*LULC2015 + LULC2005). We reclassified the LULC data into forest gain (conversion of any 2005 LULC to forest cover in 2015); forest persistence (2005 forested pixels that remained forested in 2015); new built-up area (conversion of any 2005 LULC to built-up in 2015); and urban maintenance (2005 built-up pixels that remained built-up in 2015).

To describe the spatial configuration of the urban expansion, we classified the new built-up areas into axial, infill and isolated, following Inostroza et al. (2013) (For details, please refer to Supplementary Material I at the original publication).

The NDVI was obtained from the same source used for the LULC data. With the Google Engine platform, we used an annual average for the best pixels (without clouds) for 2005 and 2015, and we calculated the changes between dates. We used increases of > 0.2 NDVI to represent an improvement in forest quality.

2)	Federal Census data organization: Urban Basic Services and Housing indicator, socioeconomic and population:

The data used to infer the values of basic services provision, socioeconomic and population drivers was derived from the Brazilian National Census data (IBGE, 2000 and 2010). Population density, permanent housing unit density, mean income, basic education, and the percentage of houses receiving waste collection, sanitation and water provision services, called basic services in the context of this study, were calculated per 30 m pixel. The Human Development Index is only available at the municipality level. We attributed the HDI for the vector file with the municipality border, and we rasterized (30 m resolution) this file in QGIS. Annual rates of change were then calculated to allow comparability between LULC periods. To infer the BSH, we used only areas with an increase in permanent housing density and basic services provision (See Supplementary Material I at the original publication).

3)	Topographic drivers

To infer the values of the topographic driver, we used the slope data and the Topographic Index Position (TPI) based on the digital elevation model from SRTM (30 m resolution) produced by ALOS (freely available at eorc.jaxa.jp/ALOS/en/about/about_index.htm), and both variables were considered constant from 2005 to 2015 (See Supplementary Material I at the original publication).

basic-services

display_name: basic-services

built-up-classification

display_name: built-up-classification

forest-gain

display_name: forest-gain

forest-persistence

display_name: forest-persistence

land-use-and-cover-change

display_name: land-use-and-cover-change

nature-conservation

display_name: nature-conservation

planning-outcome

display_name: planning-outcome

spatial-modelling

display_name: spatial-modelling

topography

display_name: topography

urban-compactness

display_name: urban-compactness

urban-morphology

display_name: urban-morphology

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.

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.

en: Spatially explicit data to evaluate spatial planning outcomes in a coastal region in São Paulo State, Brazil