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

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

envidat

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

en: EnviDat: the Environmental Data Portal

en: Multi-resolution CLM5 simulations across Switzerland

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

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

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

evapotranspiration

display_name: evapotranspiration

forest-productivity

display_name: forest-productivity

high-resolution

display_name: high-resolution

land-cover

display_name: land-cover

land-use

display_name: land-use

oshd

display_name: oshd

snow

display_name: snow

snow-simulation

display_name: snow-simulation


snow-height-classification-dataset

$oid: OBSOLETE

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

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

envidat

approval_status: approved

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

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

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

de: EnviDat: das Umwelt-Datenportal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Snow Height Classification Dataset

title_for_slug: snow-height-classification-dataset

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

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

format: ZIP

media_type: application/zip

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

deep-learning

display_name: deep-learning

imis

display_name: imis

machine-learning

display_name: machine-learning

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height


root-traits

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

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

en: Root-traits

title_for_slug: root-traits

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring


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

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

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

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

format: CSV

media_type: text/csv

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

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

antwerp

display_name: antwerp

cavity-nesting-bees

display_name: cavity-nesting-bees

chelostoma-florisomne

display_name: chelostoma-florisomne

dna-metabarcoding

display_name: dna-metabarcoding

hylaeus-communis

display_name: hylaeus-communis

osmia-bicornis

display_name: osmia-bicornis

osmia-cornuta

display_name: osmia-cornuta

paris

display_name: paris

plant-pollinator-interactions

display_name: plant-pollinator-interactions

poznan

display_name: poznan

tartu

display_name: tartu

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

zurich

display_name: zurich


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

en: avalanche snowpack source-code snowdrift snow-modelling

envidat

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

en: EnviDat: the Environmental Data Portal

en: FSM2trans code

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

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

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

format: TXT

media_type: text/plain

avalanche

display_name: avalanche

snow-modelling

display_name: snow-modelling

snowdrift

display_name: snowdrift

snowpack

display_name: snowpack

source-code

display_name: source-code


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

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

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

envi

en: Environment

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

format: XLS

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

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

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

biodiversity

display_name: biodiversity

colonisation

display_name: colonisation

conservation

display_name: conservation

dead-wood

display_name: dead-wood

forest-management

display_name: forest-management

habitat-availability

display_name: habitat-availability

habitat-heterogeneity

display_name: habitat-heterogeneity

saproxylic-beetles

display_name: saproxylic-beetles

sloss

display_name: sloss


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

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

en: Environmental layers for SDM simulations (GDPlants)

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

format: TIFF

media_type: image/tiff

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

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

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

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

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

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

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

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

aridity

display_name: aridity

frost-change-velocity

display_name: frost-change-velocity

ground-temperature

display_name: ground-temperature

precipitation

display_name: precipitation

sdms

display_name: sdms

soil

display_name: soil


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

en: biodiversity reef-fish traits ecology dispersal

envidat

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

en: EnviDat: the Environmental Data Portal

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

envi

en: Environment

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

dispersal

display_name: dispersal

ecology

display_name: ecology

reef-fish

display_name: reef-fish

traits

display_name: traits


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

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

envidat

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

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

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

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

ice

display_name: ice

microstructure

display_name: microstructure

slow-snow-compression-experiments

display_name: slow-snow-compression-experiments

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography


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

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

envidat

en: EnviDat: the Environmental Data Portal

en: Lake climate change scenarios CH2018

envi

en: Environment

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

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

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

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland


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

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

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

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline


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

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

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

cloud-droplets

display_name: cloud-droplets

modeling

display_name: modeling

nucleation

display_name: nucleation

pmcamx-uf

display_name: pmcamx-uf

total-number

display_name: total-number


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

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

envidat

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

en: Land use projections and services for Switzerland

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

# B_Transition_Analysis.R
Further Analysis of transition numbers

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

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

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

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

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

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

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

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

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

land-use

display_name: land-use

land-use-change

display_name: land-use-change

landscape-services

display_name: landscape-services

statistical-model

display_name: statistical-model

urbanization

display_name: urbanization


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

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

envidat

en: EnviDat: the Environmental Data Portal

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

literature-review

display_name: literature-review

mountain-ecology

display_name: mountain-ecology

treeline-ecosystems

display_name: treeline-ecosystems


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

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

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

envi

en: Environment

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

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

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

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

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

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

alps

display_name: alps

community-indices

display_name: community-indices

elevation

display_name: elevation

environmental-gradients

display_name: environmental-gradients

functional-traits

display_name: functional-traits

herbivores-communities

display_name: herbivores-communities

plant-herbivore-interactions

display_name: plant-herbivore-interactions


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

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

envidat

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

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

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

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

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

air-pressure

display_name: air-pressure

air-temperature

display_name: air-temperature

dew-point-temperature

display_name: dew-point-temperature

precipitation-sum

display_name: precipitation-sum

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

snow-depth

display_name: snow-depth

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

treeline

display_name: treeline

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed


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

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

envidat

en: EnviDat: the Environmental Data Portal

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

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

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

balanced-sampling

display_name: balanced-sampling

habitat

display_name: habitat

multi-stage

display_name: multi-stage

unequal-probability

display_name: unequal-probability

vegetation

display_name: vegetation


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

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

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

envi

en: Environment

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

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

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

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

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

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

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling


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

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

envidat

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

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

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

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

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes


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

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

envidat

en: EnviDat: the Environmental Data Portal

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

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

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

geochemical-solutes

display_name: geochemical-solutes

precipitation

display_name: precipitation

spatially-distributed-sampling

display_name: spatially-distributed-sampling

stream-water

display_name: stream-water


en:
Table of Content: 1. General context of the data set "LUSzoning”; 2. Background and aims of the study using the data set LUSzoning; 3. The data set LUSzoning.
1. General context of the data set "LUSzoning".
The data set "LUSzoning" stands for Land-use simulations integrating zoning regulations in Spanish functional urban areas. The data set has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2021. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, digital zoning plans) into quantitative land-change modelling approaches at the urban regional level.
2.	Background and aims of the study using the data set “LUSzoning”.
As part of the CONCUR project, a specific task was to integrate planning spatial policies in land-change modelling. Planning can be implemented in modelling using either hard or gradual restrictions. Different studies have addressed the inclusion of spatial planning policies in land-use change modelling. However, the integration of zoning constraints is generally established as hard or Boolean-based restrictions (e.g., whether urban development is allowed or not), while not accounting for the spatial heterogeneity or gradual characteristics within planning zones (e.g., whether planning regulations allow low, medium or high urban density), though these could improve real patterns simulations in urban areas. We assume Spanish General Zoning plans were suitable to explore the integration of planning into land-change modelling as soft constrains because they define land-use intensities in the buildable zoning areas. In light of the above considerations, the overall aim of the study was to model urban land-use changes using a multi-scenario approach that integrates digitized zoning plans for the Functional Urban Areas (FUAs) of Madrid, Barcelona, Valencia, and Zaragoza. The following specific objectives were addressed: i) to analyse the role of planning by defining three future scenarios that integrate digitized zoning plans and one scenario that assumes almost no planning intervention; ii) to introduce zoning constraints that reflect different degrees of urban densities; iii) to generate a transferable spatially-explicit modelling framework to integrate planning into land-use change simulations.
Four future land-use demands scenarios were defined for the FUAs. Storylines were created considering probable development scenarios related to zoning plans, current Spanish legislation and sustainability goals defined along two axes: a high market-oriented vs. high planning-intervention axis, and an axis of short-term economic growth vs. long-term sustainable growth. The sustainable development scenario (S1) is characterized by low gross floor area (GFA) growth that is limited to areas that are currently under development according to zoning plans. The business-as-usual scenario (S2) is characterized by medium GFA growth in the range of on-going trends. The strong development scenario (S3) is characterized by high GFA growth rates. Growth is restricted to buildable areas without urbanization project designated in zoning plans. The unrestricted development scenario (S4) prioritizes a high degree of market liberalization characterized by high GFA growth that surpasses population demands. S4 follows a rapid economic growth pattern with almost no planning intervention.
3.	 The data set “LUSzoning”.
The dataset includes 16 .asc raster layers providing the simulated land-uses under four defined scenarios for Barcelona, Madrid, Valencia and Zaragoza Functional Urban Areas (FUAs) for 2030. The simulated raster layers were created using CLUMondo simulation framework and have a spatial resolution of 30m. The .asc layers name include the name of the FUA and scenario number. For example, the output from simulating the urban growth for the city of Zaragoza under Scenario 2 is named “Zaragoza_S2.tif”. Furthermore, a .txt file named “Legend.txt” includes the numeric value of the land-use and the category of land-use that represents to interpret the .asc raster layers. The name of the land-use classes is a reclassification of the Urban Atlas 2012 land-use classes within the four Spanish FUAs analyzed.

en: land-use-transformations digital-zoning-plans land-use-simulations spatial-planning land-use-change

en: LUSzoning: Land-use simulations integrating zoning regulations in Spanish functional urban areas

envi

en: Environment

en:
Resource Title: Madrid_S1
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    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/bc4b8ca6-76a2-43b0-9a5b-4c43394b3fda/download/madrid_s1.asc
    Description:

format: pgp-keys

en:
Resource Title: Barcelona_S1
    Size: 51075742 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/2a6f3cb5-a88e-4abe-865a-12a6fa2bd838/download/barcelona_s1.asc
    Description:

en:
Resource Title: Zaragoza_S1
    Size: 20968481 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/bf187ffd-59a7-4018-b7f8-d843cd03737e/download/zaragoza_s1.asc
    Description:

en:
Resource Title: Zaragoza_S3
    Size: 20961753 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/46cd42ea-2ea9-4881-9056-0c80433cdced/download/zaragoza_s3.asc
    Description:

en:
Resource Title: Valencia_S4
    Size: 6692922 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/ad431d08-3481-4b61-9d4c-a7b75e6c04e9/download/valencia_s4.asc
    Description:

en:
Resource Title: Madrid_S4
    Size: 25185335 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/21a40989-9a12-403a-9dff-15d37a59caf6/download/madrid_s4.asc
    Description:

en:
Resource Title: Zaragoza_S2
    Size: 20964504 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/7b5ad8ca-1f63-4492-89ad-d8e902c4b102/download/zaragoza_s2.asc
    Description:

en:
Resource Title: Madrid_S3
    Size: 25291019 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/dfb0ce17-3c3c-4c40-a406-5fbbd69d7859/download/madrid_s3.asc
    Description:

en:
Resource Title: Valencia_S3
    Size: 6757947 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/94d52c98-ae61-4a1d-8b51-75d8b2994a04/download/valencia_s3.asc
    Description:

en:
Resource Title: Barcelona_S3
    Size: 51044440 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/78f91bc4-cec9-4e30-9db9-a1c2cb4ba546/download/barcelona_s3.asc
    Description:

en:
Resource Title: Madrid_S2
    Size: 25343034 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/5d6fb94e-2557-4428-aae5-30aebd2048a1/download/madrid_s2.asc
    Description:

en:
Resource Title: Zaragoza_S4
    Size: 20914512 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/c5dc051d-16e0-49cc-99cb-3bc105aaa390/download/zaragoza_s4.asc
    Description:

en:
Resource Title: Valencia_S1
    Size: 6769425 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/b0e6fefc-b2ca-48ee-bbaf-a478e4f027ee/download/valencia_s1.asc
    Description:

en:
Resource Title: Valencia_S2
    Size: 6759489 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/af2a0484-7e5e-4cc3-963c-c14ef137131a/download/valencia_s2.asc
    Description:

en:
Resource Title: Barcelona_S2
    Size: 51045666 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/a555ffc0-0266-4987-b70e-e7fddb0abdf2/download/barcelona_s2.asc
    Description:

en:
Resource Title: Barcelona_S4
    Size: 50843588 bytes
    Format: application/pgp-keys
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/0da0d9eb-d2a7-41b0-a050-1a34770fc7e1/download/barcelona_s4.asc
    Description:

en:
Resource Title: Legend simulated maps
    Size: 906 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/572a6da6-b2fd-4635-bba6-dd2756c4632c/resource/927372ee-e8b2-4f36-abc3-7367b112b4fb/download/legend.txt
    Description:

digital-zoning-plans

display_name: digital-zoning-plans

land-use-change

display_name: land-use-change

land-use-simulations

display_name: land-use-simulations

land-use-transformations

display_name: land-use-transformations

spatial-planning

display_name: spatial-planning


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)._

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

envidat

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

en: EnviDat: the Environmental Data Portal

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

envi

en: Environment

en:
Resource Title: Canopy height maps
    Size: 4159760 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/3451cb50-b6af-4df6-8b73-aeda7eb01215/download/canopy-height.zip
    Description: Canopy height maps of each of the three field areas Davos, Engadine and Grand Mesa

en:
Resource Title: Terrain elevation maps
    Size: 2545725 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/9c82946c-09f9-4815-974d-31828e45f439/download/terrain-elevation.zip
    Description: Digital elevation model computed from snow-off flights for each of the field areas Davos, Engadine and Grand Mesa

en:
Resource Title: Readme
    Size: 997 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/a8109354-2581-4863-bcf5-301f3dc361a8/download/readme.txt
    Description:

en:
Resource Title: Snow depth maps
    Size: 3113408 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/98ab851f-7d0e-4c96-9eea-79db59cd83a2/resource/e41d41ca-810c-4ec6-87ef-6daa709f8316/download/snow-depth.zip
    Description: 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)

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


en:
Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds.
All metadata can be found in the attached documents.

en: acclimation drought vpd photosynthesis pinus-sylvestris gas-exchange fluorescence

en: 2013-2020 gas exchange at Pfynwald

en:
Resource Title: Methods ACi curves
    Size: 731 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c7536938-120e-4975-97e4-e40649637634/download/methodsmetadata_acicurves.csv
    Description: Parameters and methods for CO2 response curves of Photosynthesis.

Metatdata format by
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods light response
    Size: 607 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/c5ef8bc5-79ab-4aec-9e02-d031e1e7d976/download/methodsmetadata_lightcurves_darkresp.csv
    Description: Methods and parameters for light response curves

en:
Resource Title: Methods fluorescence
    Size: 534 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/1d2343e4-bdf9-4ff0-9582-0c9ef11e139e/download/methodsmetadata_fluoresence.csv
    Description: Parameters and methodology for Fluorescence measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Methods diurnal measurements
    Size: 593 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/45f2d648-386c-42bb-b766-6f804e7c7de6/download/methodsmetadata_diurnal.csv
    Description: Parameters and methodology for diurnal measurements

Metadata format from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Pfynwald gas exchange
    Size: 4072706 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/3d0f2a0a-c365-4f15-a8e7-312943cbcad6/download/pfynwald_gasexchange_201306_202010.csv
    Description: Full dataset of Pfynwald gas exchange data taken in the period from June 2013 to October 2020.
All metdata can be found in attached documents.
Data uploaded after quality control using guidelines by Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Instrument details
    Size: 1174 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/e7342279-bf44-451b-afa2-78cb77babf5e/download/instrumentdetails_pfynwald.csv
    Description: Instrument details for all LiCor instruments used during collection of dataset.

Metatdata created following guidelines from
Ely et al (2021). A reporting format for leaf-level gas exchange data and metadata. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2021.101232

en:
Resource Title: Variable names and units
    Size: 15839 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/39614a56-a982-4123-a8d6-e9aaa51c838a/download/variable_names_units.xlsx
    Description: Variable names, description and units for the Pfynwald Gas exchange data

en:
Resource Title: Methods survey
    Size: 596 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/bfedd747-6d88-44b4-8aba-3094af8766eb/resource/229fbf92-a0ff-44b5-b799-b55fabe2b99c/download/methodsmetadata_point.csv
    Description: Parameters and methods for point measurements / survey measurements

acclimation

display_name: acclimation

drought

display_name: drought

fluorescence

display_name: fluorescence

gas-exchange

display_name: gas-exchange

photosynthesis

display_name: photosynthesis

pinus-sylvestris

display_name: pinus-sylvestris

vpd

display_name: vpd


name: Gesundheitsdirektion des Kantons Zürich, Kantonales Labor

de: Konzentrationsbereiche zur Trinkwasserqualität für verschiedene Analyten aus den im Auftrag der Wasserversorgungen durchgeführten Selbstkontrolluntersuchungen sowie amtlichen Untersuchungen in den Gemeinden des Kantons Zürich – im regulären Trinkwassernetz (ohne Notversorgung, Laufbrunnen und Ressourcen). Die Daten-Ressource 'Netzproben' enthält u. a. das Datum der Probenahme, die spezifische Bezeichnung des Analyten (z. B. Chlorothalonil "R471811"), die Bezeichnung der Verteilzone(n) der Gemeinde sowie den Konzentrationsbereich (dem der Messwert zugeordnet wurde). Die Daten-Ressource 'Bewertungskategorien' enthält die Kategorien der Konzentrationsbereiche pro Analyt sowie den Zeitraum, zu dem sie für die Qualitätsbewertung Gültigkeit haben. Die Messwerte aus den ergänzenden Selbstkontrolluntersuchungen durchgeführt durch externe Dienstleistungslaboratorien im Auftrag der Wasserversorgungen sind im Datensatz 'Qualität des Trinkwassers im Kanton Zürich ab 2020 (Selbstkontrolle der Wasserversorgungen)' enthalten (siehe Verwandte Datensätze).

de: trinkwasser pestizide wasserversorgung lebensmittel wasser schwellenwert pflanzenschutzmittel gesundheit verunreinigung gemeinden

gesundheitsdirektion-kanton-zuerich

de: Die Gesundheitsdirektion setzt sich ein für eine hochstehende, sichere und wirtschaftlich tragbare Gesundheitsversorgung, für qualitativ einwandfreie medizinische Dienstleistungen, Heilmittel, Lebensmittel und Gebrauchsgegenstände, für finanziell tragbare Krankenversicherungsprämien. Das Veterinärwesen zählt ebenfalls zu ihrem Aufgabenbereich.

de: Gesundheitsdirektion Kanton Zürich

political_level: canton

de: Trinkwasser

en: Trinkwasser

fr: Trinkwasser

it: Trinkwasser

de: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

de: Trinkwasserqualität der Wohngemeinden (Schweizerischer Verein des Gas- und Wasserfaches SVGW)

de: Trinkwasserqualität im Kanton Zürich nach Gemeinden und Verteilzonen

value: ZH-Kt Gesundheitsdirektion - DCAT Harvester

heal

de: Gesundheit

en: Health

fr: Santé

it: Salute

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

de: Kategorien von Konzentrationsbereichen pro Analyt zur Qualitätsbewertung. Variablen: 'analyt' = spezifische Bezeichnung des Indikators (z. B. Chlorothalonil "R471811"); 'kategorie' = Konzentrationsbereich von Messwerten; 'kategorie_sortierung' = Sortierung nach aufsteigender Konzentration; 'farbcode' = hexadezimaler Farbcode, der die Einfärbung der Kategorie in der Visualisierung des Kantonalen Labors bestimmt (siehe 'Trinkwasser' unter "Weitere Informationen"); 'start_datum' = Beginn der Gültigkeit des Konzentrationsbereichs; 'end_datum' = Ende der Gültigkeit des Konzentrationsbereichs; 'bemerkung' = Hinweise zum Grund der Änderung des Konzentrationsbereichs.

de: Netzproben der Trinkwasserqualität

gemeinden

display_name: gemeinden

gesundheit

display_name: gesundheit

lebensmittel

display_name: lebensmittel

pestizide

display_name: pestizide

pflanzenschutzmittel

display_name: pflanzenschutzmittel

schwellenwert

display_name: schwellenwert

trinkwasser

display_name: trinkwasser

verunreinigung

display_name: verunreinigung

wasser

display_name: wasser

wasserversorgung

display_name: wasserversorgung