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: Lake climate change scenarios CH2018

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

envidat

en: EnviDat: the Environmental Data Portal

envi

en: Environment

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 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 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


$oid: OBSOLETE

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

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

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

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

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

format: ZIP

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

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

literature-review

display_name: literature-review

mountain-ecology

display_name: mountain-ecology

treeline-ecosystems

display_name: treeline-ecosystems


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

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

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

media_type: application/zip

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

format: TXT

media_type: text/plain

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

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

envidat

en: EnviDat: the Environmental Data Portal

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’.

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...

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

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed


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: Land use projections and services for Switzerland

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

envi

en: Environment

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

modeling

display_name: modeling

statistical-model

display_name: statistical-model

switzerland

display_name: switzerland

urbanization

display_name: urbanization


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: Above- and below-ground herbivore communities along elevation

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

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:
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: 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: 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: 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 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

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

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: 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: Environmental layers for SDM simulations (GDPlants)

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

envidat

en: EnviDat: the Environmental Data Portal

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

format: TIFF

media_type: image/tiff

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

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

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

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

en:
Resource Title: CHELSA_bio10_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

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

en:
Resource Title: 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

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

en: dispersal ecology reef-fish biodiversity traits

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.

envi

en: Environment

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.

format: CSV

media_type: text/csv

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

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: 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:
    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: 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: 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: 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 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: 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: 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.

biodiversity

display_name: biodiversity

dispersal

display_name: dispersal

ecology

display_name: ecology

reef-fish

display_name: reef-fish

traits

display_name: traits


en:
Surface topography maps (spatial extent: 400 m x 400 m) obtained at approximately 300 m from the top of the Hammarryggen Ice Rise in Dronning Maud Land, East Antarctica, using a Riegl VZ-6000 Terrestrial Laser Scanner (TLS). Scans were obtained on 5 days in the 2018-2019 Austral summer: on December 21 and 27, and January 2, 4 and 11. By using reflectors installed on bamboo poles, scans were registered with respect to the reflectors, such that the difference between two successive scans reveals the spatial patterns of erosion and deposition of snow. On each scan day, we used multiple scan positions to create one combined point cloud. After applying an octree filter on the point cloud, a 3D surface was obtained. For each day, the dataset contains a 1 mm and a 10 cm octree filter resolution file, only including points in a 400 m x 400 m area centered around the scan positions.
Notes:
* All files in the dataset are in the same coordinate system. However, this coordinate system is arbitrary (i.e., not related to any global coordinate system).
* From the installed reflectors, 4 reflectors could be used over the full period. The scan accuracy is generally higher within the area enclosed by the reflectors.
* The scans from January 2 were found to have exhibited small tilt during the scan and are of lesser accuracy.
* By walking along fixed corridors, disturbance of the snow was limited.

en: Terrestrial laser scans on Hammarryggen Ice Rise, Dronning Maud Land, East Antarctica

en: antarctica terrestrial-laser-scans terrestiral-laserscanning gridded-data depth-of-snowfall

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Deprecated: Scan from 11 January 2019, 10 cm resolution, version 1
    Size: 33017091 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/ca01d845-b9c9-4ff4-9721-e52096546a03/download/20190111_combi_2.5d_0.1m.zip
    Description: This resource is deprecated. It contains erroneous data.

en:
Resource Title: Scan from 4 January 2019, 10 cm resolution
    Size: 31421084 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/85476f78-5964-4d09-9b39-bf6b44cf3ea2/download/20190104_combi_2.5d_0.1m.zip
    Description: Scan from 4 January 2019, 10 cm resolution

en:
Resource Title: Scan from 11 January 2019, 1 mm resolution
    Size: 384645137 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/2abd22ce-9aa5-48d3-85d6-16fce30e4dac/download/20190111_combi_2.5d_0.001m.zip
    Description: Scan from 11 January 2019, 1 mm resolution

en:
Resource Title: Scan from 2 January 2019, 1 mm resolution
    Size: 358665175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/cce4e4f2-713a-4ced-8276-994c3c6d1fca/download/20190102_combi_2.5d_0.001m.zip
    Description: Scan from 2 January 2019, 1 mm resolution

en:
Resource Title: Scan from 27 December 2018, 10 cm resolution
    Size: 26161402 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/3493a5ce-398d-482c-942f-2ebd558acd10/download/20181227_combi_2.5d_0.1m.zip
    Description: Scan from 27 December 2018, 10 cm resolution

en:
Resource Title: Scan from 21 December 2018, 10 cm resolution
    Size: 20747718 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/24c7f00b-bffd-4ecd-b1cc-b8595cf9cabc/download/20181221_combi_2.5d_0.1m.zip
    Description: Scan from 21 December 2018, 10 cm resolution

en:
Resource Title: Scan from 11 January 2019, 10 cm resolution, version 2
    Size: 21786633 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/11ab1fc7-2eba-4506-823c-c06120c538e2/download/20190111_combi_2.5d_0.1m.zip
    Description: Scan from 11 January 2019, 10 cm resolution, version 2

en:
Resource Title: Scan from 4 January 2019, 1 mm resolution
    Size: 371000882 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/f6bacba5-c126-496c-aae8-0cea0a7db3c1/download/20190104_combi_2.5d_0.001m.zip
    Description: Scan from 4 January 2019, 1 mm resolution

en:
Resource Title: Scan from 21 December 2018, 1 mm resolution
    Size: 271646425 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/0bf20a3a-f462-4313-9393-dcba4c207bfe/download/20181221_combi_2.5d_0.001m.zip
    Description: Scan from 21 December 2018, 1 mm resolution

en:
Resource Title: Scan from 27 December 2018, 1 mm resolution
    Size: 324407426 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/713d2875-611c-483f-af9c-2756125153d7/download/20181227_combi_2.5d_0.001m.zip
    Description: Scan from 27 December 2018, 1 mm resolution

en:
Resource Title: Scan from 2 January 2019, 10 cm resolution
    Size: 33632491 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/eaf0f187-6a26-4fca-8315-b48bb6a10234/resource/31da45fa-770b-44ee-8121-cdbccffa9f03/download/20190102_combi_2.5d_0.1m.zip
    Description: Scan from 2 January 2019, 10 cm resolution

antarctica

display_name: antarctica

depth-of-snowfall

display_name: depth-of-snowfall

gridded-data

display_name: gridded-data

terrestiral-laserscanning

display_name: terrestiral-laserscanning

terrestrial-laser-scans

display_name: terrestrial-laser-scans


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

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

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.

envi

en: Environment

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:

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:

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 the raw environmental DNA data associated with the publication *Environmental drivers of eukaryotic plankton and fish biodiversity in an Arctic fjord* in the journal Polar Biology (2023).
 Methods

**Sampling**
We sampled the Lilliehöök fjord on the west coast of Spitsbergen (Svalbard, Norway) over 3 days from 3 to 5 of August 2021. Samples were taken from the glacier front up to the fjord mouth of the Krossfjorden system, around 30 km long, after the Lilliehöök fjord merged with the mouth of Möller fjord. The fjord’s maximum depth has been recorded at 373 m (Svendsen et al. 2002) and has no sill at its entrance, thereby facilitating water exchange with the open ocean of the West Spitsbergen Current. We used a research vessel to sample 5 sites for a total of 15 samples, sampling 3 depths per site (3-m, chlorophyll a maximum and 85-m, unless sea floor was shallower). Shallow and intermediate samples between 3-m and 12-m represent ~35-L of water filtered in-situ using long tubing and a peristaltic pump, and all other deeper samples were taken from a total of 3 Niskin bottles (General Oceanics), representing 22-L of water sampled per sample. Water was filtered through a VigiDNA filtration capsule (SPYGEN) with a 0.20-µm pore size using an Athena peristaltic pump (Proactive Environmental Products, Bradenton, Florida) with a flow rate of ~1-L/min. Each sample was handled with single use tubing and gloves.
**Molecular**
To perform the amplification, we used two sets of primers: teleo (forward: ACACCGCCCGTCACTCT, reverse: CTTCCGGTACACTTACCATG; Valentini et al. 2016) and the universal eukaryotic 1389F/1510R primer pair, amplifying the V9-18S rDNA gene (Amaral-Zettler et al. 2009) (forward: TTGTACACACCGCCC, reverse: CCTTCYGCAGGTTCACCTAC).
 Data content:
+ Metabarcoding data: This zip file contains the 2 sequencing libraries filtered to only retain the samples used in the present study.
+ Code, data and figure: This zip file contains all data and code to reproduce the figures and the analysis in the study, with an associated README explaining the content of each folder.
 Additional informations
For more details, please see the Methods in the associated publication: DOI: 10.1007/s00300-023-03187-9.

en: Data: Environmental drivers of eukaryotic plankton and fish biodiversity in an Arctic fjord

en: marine biodiversity environmental-dna fish fjord plankton dna-metabarcoding

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Code, data and figures
    Size: 63570143 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2a7f749a-430f-443b-bbac-073b166c2361/resource/ce6111f5-09b4-4d7a-8a5d-21529c2da40b/download/code_data_figures.zip
    Description: Here there are all the data and code to reproduce the figures and analysis presented in the paper, with a README.md file

en:
Resource Title: Metabarcoding data
    Size: 621901827 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/2a7f749a-430f-443b-bbac-073b166c2361/resource/1e6638c8-fb7e-4049-8fee-effa8d64177b/download/metabarcoding-data.zip
    Description: Raw metabarcoding data for both primers (teleo and 18S) and corresponding file to perform the demultiplexing and primer trimming

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

fish

display_name: fish

fjord

display_name: fjord

marine

display_name: marine

plankton

display_name: plankton


en:
The data set contained in this repository was used in the analysis by Mayer et al. (2023):
Mayer, S. I., Techel, F., Schweizer, J., and van Herwijnen, A.: Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations, EGUsphere, https://doi.org/10.5194/egusphere-2023-646, 2023.

en: Data-set for prediction of natural dry-snow avalanche activity and avalanche size using physics-based snowpack simulations

en: snowpack-model natural-avalanches avalanche machine-learning avalanche-size

en:
Resource Title: dataForAvalancheDayModelDevelopment.csv
    Size: 1584694 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/28660c6d-68ce-484d-a7d7-24d7a612f392/resource/961c07d9-5f7e-4c7b-9073-e2b31b6dab28/download/dataforavalanchedaymodeldevelopment.csv
    Description: Data set AV1 was used for training the avalanche-day classifier (Sections 2.1.1, 2.2, and 3.1 in Mayer et al.).

format: XLS

en:
Resource Title: dataForAvalancheSizeModelDevelopment.csv
    Size: 423741 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/28660c6d-68ce-484d-a7d7-24d7a612f392/resource/49e9e29b-683a-4784-a3ab-0c02d2e0902b/download/dataforavalanchesizemodeldevelopment.csv
    Description: Data set AV2 used for training the avalanche-size estimator (Sections 2.1.2 and 3.2 in Mayer et al.)

en:
Resource Title: dataForValidationWithDangerLevels.csv
    Size: 34614625 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/28660c6d-68ce-484d-a7d7-24d7a612f392/resource/fac61ade-ba4c-40bc-bc90-f47c763e153c/download/dataforvalidationwithdangerlevels.csv
    Description: Data set DL was used for validation of the avalanche-day classifier and the avalanche-size estimator. The data set contains the quality-checked danger levels merged with the respective SNOWPACK simulations (Sections 2.3 and 3.3(2) in Mayer et al.).

en:
Resource Title: dataForValidationDavos.csv
    Size: 74355 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/28660c6d-68ce-484d-a7d7-24d7a612f392/resource/38836706-8b98-47a5-9f94-a3b5e88553e2/download/davos_validation.csv
    Description: Data set AV3 was used for validation of the avalanche-day classifier (Sections 2.1.3 and 3.3(1) in Mayer et al.).

avalanche

display_name: avalanche

avalanche-size

display_name: avalanche-size

machine-learning

display_name: machine-learning

natural-avalanches

display_name: natural-avalanches

snowpack-model

display_name: snowpack-model


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

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

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

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

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

alpine-precipitation

display_name: alpine-precipitation

extreme-values

display_name: extreme-values

low-flow

display_name: low-flow

reservoir-inflow

display_name: reservoir-inflow

return-periods

display_name: return-periods


en:
The files correspond to the data and R-script used for the analyses of the following paper "Feasting on the ordinary or starving for the exceptional: phenological synchrony between spongy moth and budburst of European trees in a warmer climate" published in Ecology and Evolution by Vitasse et al. 2023.
There are three zip files corresponding to the Temperature data, phenology/preference/performance tests and R-Scripts for the analyses.
Input data:
'Synchrony_Cuttings_Pheno.txt':

en: Synchrony between spongy moth hatching and leaf phenology of temperate trees

en: budburst chilling phenology spongy-month hatch

envi

en: Environment

en:
Resource Title:
    Size: 19723 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/31166a90-ab95-46c4-b651-4f7d474e66a7/resource/6680e96d-e720-4e07-b844-ba19e2de693e/download/r-scripts.zip
    Description: 3 R-Scripts used for the analyses of the temperature, phenology and performance/preference tests

en:
Resource Title: Phenology and performance/preference tests Data
    Size: 7058 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/31166a90-ab95-46c4-b651-4f7d474e66a7/resource/464b7325-15da-49ed-8e50-9c1be08a3d20/download/phenology_performance_preference-tests_data.zip
    Description: -"Synchronex_Cuttings_Pheno.txt" provides the budburst date ('Stage 2') of each twig of the six studies species in the four different temperature treatments ("ambient", "a+5"=Ambient +5°C, 'Greenhouse-5'= Greenhouse at temperature >5°C, 'Greenhouse_10' = Greenhouse at temperature >10°C); 'Success' give the percentage of buds within the twig that succeeded to reach at least stage 2 during the experiment.

'Synchronex-Gypsy.txt' provides the number of eggs that have hatched at each monitoring date (Day of the year in columns); "DOY_hatch_1" corresponds to the first DOY when at least one egg has hatched; "Replicate_egg_mass" correspond to the egg mass replicate (1 to 5)

'PerformanceTest_GypsyMoth.txt' provides the biomass in mg of the caterpillars fed with fresh leaves of each tested tree species during one week. "Fresh_alive" is the biomass of only the living caterpillars after 1 week and "Freshpermoth" corresponds the weight per living caterpillar (Fresh alive/Nalive)

'PreferenceTest_All_species.txt' provides the total surface of leaf disc of each tested tree species remaining after exposing 5 caterpillars to these leaves during 24H. "Total_area" is the surface of the disc of each species measured after 24h exposed to the spongy moth first instars. For each species 'control' means the surface of the disc after 24H without any exposure to the larvae. 'EatenPercent correspond to the percentage surface loss compared to the control.

en:
Resource Title: Temperature data Spongy moth experiment
    Size: 84293 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/31166a90-ab95-46c4-b651-4f7d474e66a7/resource/3891fb6e-eb1d-4835-80bf-e8ae0c85164c/download/temperature.zip
    Description: 4 files with hourly temperature recorded at the height of buds in each of the four temperature treatments:
- Winter6: greenhouse where temperature was kept >6°C over winter
- Winter10: greenhouse where temperature was kept >10°C over winter
- OTC_Ambient: Open Top Chamber at Ambient temperature
- OTC_Warm: Open Top Chamber at +3.5°C warmer temperature

budburst

display_name: budburst

chilling

display_name: chilling

hatch

display_name: hatch

phenology

display_name: phenology

spongy-month

display_name: spongy-month


en:
Summary
This data set contains Python programming code and modeled data discussed in a related research article. We developed a simple isotope model to study the drivers of the particularly depleted vapour isotopic composition measured on the ship of the Antarctic Circumnavigation Expedition close to the outlet of the Mertz glacier, East Antarctica, in the 6-day period from 27 January 2017 to 1 February 2017. The model considers the stable water isotopologues H2(16O), H2(18O), and HD(16O). It uses data from the ERA5 reanalysis product with a spatial resolution of 0.25° x 0.25° (Hersbach et al., 2018) and 10-day backward trajectories for the location of the ship, published by Thurnherr et al. (2020a). Our data set includes the model code, Python scripts for visualizing the results, and data produced by the model including the results shown in the figures of the related research article. Here, we summarize the most important model characteristics while further details can be found in the readme.txt file and the related research article including its supporting information.
 Main model characteristics
The modeling approach consists of two steps called *Model Sublimation* and *Model Air Parcel*. The former estimates the isotopic compositions of the snow and sublimation flux across the Antarctic Ice Sheet using an Eulerian frame of reference while the latter models the vapour isotopic composition and specific humidity along air parcel trajectories using a Lagrangian frame of reference. The isotope effects of most phase changes are represented by equilibrium fractionation. Only for ocean evaporation, kinetic fractionation is additionally taken into account (original Craig-Gordon formula). For snow sublimation, two assumptions are tested: *Run E* assumes that sublimation is associated with equilibrium fractionation while *Run N* assumes that sublimation occurs without isotopic fractionation.
 Model Sublimation
Model Sublimation uses a simple one-dimensional mass-balance approach in each grid cell, considering snow accumulation due to snowfall and vapour deposition and snow ablation due to sublimation. The snowpack is represented by 100 layers of equal thickness (e.g., 1 cm) and density (350 kg m-3). The isotopic composition of snowfall is parameterized by generalizing a site-specific, empirical relationship between the daily mean air temperature and snowfall isotopic composition. In the case of vapour deposition, Model Sublimation assumes equilibrium fractionation and estimates the isotopic composition of the atmospheric vapour as the average value for two idealized situations: (i) locally sourced vapour which has the same isotopic composition as the sublimation flux; (ii) non-locally sourced vapour in isotopic equilibrium with snowfall. Model Sublimation is run with a time step of 1 h, independently of Model Air Parcel.
 Model Air Parcel
Every hour, an ensemble of trajectories arrives at different heights in the ABL above the ship. For each of these trajectories, we consider an air parcel with a constant volume of 1 x 1 x 1 m3. The air parcels are initialized at the first suitable time when the trajectories are located in the ABL, either over the ice-free ocean in conditions of evaporation or over snow (Antarctic Ice Sheet or sea ice). Subsequently, the masses of the water isotopologues in the air parcels are simulated with a time step of 3 h, considering vapour uptake or removal due to the moisture flux at the snow or liquid ocean surface (only if the parcel is in the ABL) and cloud/precipitation formation (if the saturation specific humidity is reached). Sea ice is taken into account in a very simplified way. We represent the sea ice by grid cells with a sea-ice cover of more than 90% and assume the isotopic composition of the sublimation flux to be identical to that in the nearest grid cell of the Antarctic Ice Sheet. The isotopic composition of the sublimation flux is taken from Model Sublimation whereas the isotopic composition of the vapour deposition flux (over snow) and condensation flux (over ice-free ocean) is simulated assuming an isotopic equilibrium with the air parcel. Isotope effects of cloud/precipitation formation are represented using the classic Rayleigh distillation model with equilibrium fractionation, where the cloud water is assumed to precipitate immediately after formation.
 References
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horanyi, A., Munoz Sabater, J.,... others (2018). *ERA5 hourly data on single levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS)*. doi: 10.24381/cds.bd0915c6
Thurnherr, I., Wernli, H., & Aemisegger, F. (2020a). *10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017*. Zenodo. doi: 10.5281/zenodo.4031705

en: Modeled Isotopic Composition of Water Vapour Along Air Parcel Trajectories in the Antarctic

en: snow-sublimation lagrangian-analysis antarctica isotopic-distillation backward-trajectories evaporation stable-water-isotopes

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Python scripts for data visualization
    Size: 21542 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/99ad307f-be6f-48d3-ac80-387bcb0aded7/resource/acb8a9ee-2499-4892-a6ea-79d7381019d4/download/python_scripts_plotting.zip
    Description: Scripts for generating the figures of the related research article and generating the data files (csv) from the model output

en:
Resource Title: Readme
    Size: 23594 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/99ad307f-be6f-48d3-ac80-387bcb0aded7/resource/8be31ec0-9d80-4995-be16-c6e1704144fb/download/readme.txt
    Description: Meta data

en:
Resource Title: Model code
    Size: 38463 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/99ad307f-be6f-48d3-ac80-387bcb0aded7/resource/9d6a4ef1-c0fa-46bf-9479-43bbf1d13964/download/python_scripts_model.zip
    Description: Model Sublimation and Model Air Parcel (python scripts)

en:
Resource Title: Data
    Size: 2993639 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/99ad307f-be6f-48d3-ac80-387bcb0aded7/resource/6d387739-0552-425f-90ac-584c2f8330d0/download/data_processed.zip
    Description: Modeled data including the data shown in the figures of the related research article

antarctica

display_name: antarctica

backward-trajectories

display_name: backward-trajectories

evaporation

display_name: evaporation

isotopic-distillation

display_name: isotopic-distillation

lagrangian-analysis

display_name: lagrangian-analysis

snow-sublimation

display_name: snow-sublimation

stable-water-isotopes

display_name: stable-water-isotopes


en:
The fate of plastic in the environment is of global concern, because its production recently has
increased strongly and it accumulates in terrestrial and aquatic ecosystems. Although some knowledge on
its role in aquatic and terrestrial ecosystems was gained in the recent decade, hitherto very little is known
about the impact of micro and nanoplastics in forest ecosystems.
The aim of this pioneering project was to explore if nanoplastics are taken up by forest trees species
through leaves or roots. In greenhouse experiments, we exposed leaves or roots of seedling of two forest
trees species to solutions with highly 13C-labelled polystyrene nanoparticles (13C-nPS, 99 atom%) and
examined if they were incorporated in different above- and belowground tissues.
Treated part of the trees for both species showed significant 13C-enrichment, indicating that trees take up nanoparticles. However, the overall 13C signal strength in tissues that were not exposed to the 13C label remained low (Δδ13C-1‰) and was confined to a few seedlings, leaving it ambiguous whether nanoplastic transport occurs or not.
We acknowledge that the new method developed might be not sensitive enough to unequivocally detect
mechanisms of nanoplastic uptake and transport at environmentally realistic concentrations.

en: Nanoplastics in forests: Exploring the effects of nanoplastics on forest soils and tree physiology (NanoPlast)

en: uptake forest-trees nanoplastic 13c-labelling polystyrene

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.

forest-trees

display_name: forest-trees

nanoplastic

display_name: nanoplastic

polystyrene

display_name: polystyrene

uptake

display_name: uptake


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

en: Seasonal snow data for Switzerland OSHD - FSM2sohd

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

oshd

display_name: oshd

seasonal-snow-data

display_name: seasonal-snow-data

snow-cover-fraction

display_name: snow-cover-fraction

snow-depth-distribution

display_name: snow-depth-distribution

snow-melt

display_name: snow-melt


en:
The R script eemma.R, which implements Ensemble End-Member Mixing Analysis (EEMMA) to estimate source fractions in mixtures, exploiting information contained in time-series correlations among tracer time series.
A brief user's guide, a demonstration script, and a demonstration data set are also provided, to accompany Kirchner, J.W., Mixing models with multiple, overlapping, or incomplete end-members, quantified using time series of a single tracer, Geophysical Research Letters, 2023.
The user's guide is available for public use under Creative Commons CC-BY-SA.  Public use of the scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en: eemma.R, an R script for Ensemble End-Member Mixing Analysis

en: stable-isotopes emma end-member-mixing-analysis tracers eemma mixing-models

envi

en: Environment

en:
Resource Title: eemma.R
    Size: 46043 bytes
    Format: text/x-r
    URL: https://www.envidat.ch/dataset/48dff6cd-bfcb-4c5e-a30d-f909dc8d36d3/resource/af04514c-75bb-4fbb-a5d2-4b25fcadf32f/download/eemma.r
    Description: An R script that performs ensemble end-member mixing analysis

en:
Resource Title: eemma user's guide
    Size: 501164 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/48dff6cd-bfcb-4c5e-a30d-f909dc8d36d3/resource/8df18f5d-c902-4acc-a8ee-b94324a043a1/download/eemma-users-guide.pdf
    Description: A brief user's guide to EEMMA, with illustrations using a simple data set

format: PDF

media_type: application/pdf

en:
Resource Title: vignette data
    Size: 1659 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/48dff6cd-bfcb-4c5e-a30d-f909dc8d36d3/resource/f72873bb-b4f2-4cce-a408-8d53f54bdbec/download/vignette_data.txt
    Description: A simple data set for the vignette script

en:
Resource Title: eemma vignette script
    Size: 4457 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/48dff6cd-bfcb-4c5e-a30d-f909dc8d36d3/resource/a96e9b19-9fee-4b21-b36c-5f7f84a4fb37/download/eemma_vignette_script.r
    Description: An R script for the vignettes (simple data analysis demonstrations) shown in the user's guide

format: OCTET

eemma

display_name: eemma

emma

display_name: emma

end-member-mixing-analysis

display_name: end-member-mixing-analysis

mixing-models

display_name: mixing-models

stable-isotopes

display_name: stable-isotopes

tracers

display_name: tracers


en:
What are the research data files about: Raw data on perfomance (dry weight, development and mortality) of emerald ash borer larvae used in published bioassays. Raw data on ash dieback leasion lenghts. Raw data on untargeted and targeted specialized ash metabolites.
Which methods were used: Bioassays in greenhouses and climate chambers to collect data on emerald ash borer and ash dieback perfomance. Phytochemical analyses on ash phloem for quantifiying specialized metabolites.
When and where was the data created / extracted: Summer 2020-2021

en: Raw data-Publication cross-resistance in ash - New Phytologist

en: cross-resistance defense-chemistry ash-dieback invasive-species intraspecific-variation emerald-ash-borer fraxinus

envidat

en: EnviDat: the Environmental Data Portal

ash-dieback

display_name: ash-dieback

cross-resistance

display_name: cross-resistance

defense-chemistry

display_name: defense-chemistry

emerald-ash-borer

display_name: emerald-ash-borer

fraxinus

display_name: fraxinus

intraspecific-variation

display_name: intraspecific-variation

invasive-species

display_name: invasive-species


en:
This dataset includes the processed data of the glide-snow avalanche activity and dynamics on Dorfberg (Davos, Switzerland) covering seasons 2008/09 to 2021/22. This dataset was described in the research article:
Fees, A., van Herwijnen A., Altenbach, M., Lombardo, M., Schweizer, J.: Glide-snow avalanche characteristics at different time-scales extracted from time-lapse photography, Annals of Glaciology, 91
We extracted the dynamics of opening glide-cracks and the glide-snow avalanche activity from time-lapse photographs. Glide-snow avalanches were separated into surface and interface events using the liquid water content which was simulated with SNOWPACK at 10 virtual stations on Dorfberg.

en: Glide-snow avalanche activity on Dorfberg, Davos, Switzerland

en: avalanche-activity time-lapse-photography snowpack-simulation avalanche glide-snow-avalanche

en:
Resource Title: Glide distances for opening glide-cracks
    Size: 512266 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6c7a578-6317-49f3-8ba5-71f62b5b6610/resource/7ee75315-9399-48fe-b5b1-e3ef1d2f0774/download/metadata.zip
    Description: This folder contains all glide-cracks where glide-distances were extracted from time-lapse photographs. Glide-distances were calculated in x-direction (width) and y-direction (downslope, length) by georeferencing the images.

en:
Resource Title: SNOWPACK simulations
    Size: 719769784 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6c7a578-6317-49f3-8ba5-71f62b5b6610/resource/73dee7b2-a419-4fd2-ac0e-585bc0138d90/download/snowpack.zip
    Description: SNOWPACK simulations (.pro and .smet) covering season 2008/09 to 2021/22 at 10 virtual locations on Dorfberg. The locations correspond to the most common glide-snow avalanche paths.

en:
Resource Title: Glide-snow avalanche activity
    Size: 88583 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6c7a578-6317-49f3-8ba5-71f62b5b6610/resource/0aca99e1-7b3d-492f-a7bb-2756e5b74bbd/download/events.csv
    Description: Table that contains all glide-snow avalanche events that were detected in time-lapse photographs (season 2008/09 to 2021/22). The columns are explained in the README.txt

en:
Resource Title: README
    Size: 1996 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d6c7a578-6317-49f3-8ba5-71f62b5b6610/resource/26a702a9-37e6-4dc9-9ce9-e7a223d73bff/download/readme.txt
    Description: README.txt explaining the dataset and columns of tables in more detail.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snowpack-simulation

display_name: snowpack-simulation

time-lapse-photography

display_name: time-lapse-photography


tree-ring-laser-ablation-data

en:
This dataset contains the values of several chemical elements (Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, Tl, Pb, Bi) measured in the latewood of tree rings of Mongolian oak from Harbin, China, at a 5-year resolution. Due to the lack of a suitable reference material for wood, absolute concentration was not calculated, and the ratio between the chemical element and 13C was taken as proxy for the element signal.
In Harbin, one of the largest cities and most important industrial centers in northeastern China, air quality monitoring systems were built only by the end of 2015 to meet the national requirements. Thus, dendrochemical analyses could be used as a tool to complement for the lack of air quality data over longer periods of time, allowing for the reconstruction of the temporal trend of trace metals. Our main scopes were to: (a) assess the chemical composition of Quercus mongolica Fisch. ex Ledeb. tree rings from Harbin using a recently developed system of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), (b) identify the main chemical elements which
derived from air pollution and may be used as indicators over the period 1965–2020 in Harbin, while excluding those that were controlled by physiological processes in the tree, and (c) reconstruct the history of pollution in Harbin by comparing the tree-ring chemical composition of recent decades with that of previous decades, in trees growing in the highly polluted city of Harbin and in trees growing in a control site 90 km away from major pollution sources.
Briefly, the temporal trend of some elements was influenced by physiological factors, by environmental factors such as pollution, or influenced by both. Mg, K, Zn, Cu, Ni, Pb, As, Sr and Tl showed changes in pollution levels over time.

en: Tree-ring laser ablation data

en: dendrochemistry laser-ablation dendrochronology air-pollution tree-rings

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.

title_for_slug: tree-ring-laser-ablation-data

air-pollution

display_name: air-pollution

dendrochemistry

display_name: dendrochemistry

dendrochronology

display_name: dendrochronology

laser-ablation

display_name: laser-ablation

tree-rings

display_name: tree-rings


en: This data includes (1) Scripts to aggregate landscape resistance layers into squared and hexagonal grids (i.e., different representations and resolutions), (2) Input resistance layers and focal nodes in .txt format to run in Circuitscape (Python implementation v4.0.5). Circuitscape is a software tool for modeling and analyzing landscape connectivity, which simulates movement of organisms across landscapes by estimating resistance to movement across each point of the landscape. (3) Scripts for the ecological network analysis, and (4) environmental predictors for amphibian whole-life cycle habitats used to describe the local environment for BGI design (i.e. topographic, hydrologic, edaphic, vegetation, land-use derived, movement-ecology related).

en: Multi-Scale Prioritization framework for Urban Blue-Green Infrastructure Planning to Support Biodiversity: Data & Codes

en: ecosystem-services circuit-theory biodiversity network-analysis urban-planning ecological-corridors

envi

en: Environment

en:
Resource Title:  Amphibian movement resistance layers and scripts for connectivity modelling - part 2
    Size: 20335272 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/dd7b7d6e-6fe8-455e-9743-adf791914a17/resource/1283e651-6999-46ad-b23d-0e81c593a90e/download/2_network-analysis.zip
    Description: The zipped folder includes the script to create and analyse the networks from Circuitscape outputs. The subfolders “Boundaries”, “Layers”, and “Reference_net” contain files either called by the code or created in the process. The subfolder “Outputs_from_Circuitscape” contains the outputs from Circuitscape including node and branch cumulative currents in a network format.

en:
Resource Title:  Amphibian movement resistance layers and scripts for connectivity modeling - part 1
    Size: 247430561 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/dd7b7d6e-6fe8-455e-9743-adf791914a17/resource/e364cf62-5561-4b4d-8909-0977b3da60f3/download/1_resistance_layers.zip
    Description: The zipped folder includes the script to aggregate the resistance layers into squared and hexagonal grids. The subfolders “Boundaries”, “Layers”, “Reference_grids”, and “Resistance_from_SDMs” contain files either called by the code or created in the process.The subfolder “Inputs_for_Circuitscape” contains the inputs to run Circuitscape, after doing some subsequent processing steps in QGIS (listed in the R script) with the files created with the script.

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

ecosystem-services

display_name: ecosystem-services

network-analysis

display_name: network-analysis

urban-planning

display_name: urban-planning


en:
Topic of Survey
The data at hand on energy cooperatives in Switzerland were collected in 2016 as part of the project "Collective financing of renewable energy projects in Switzerland and Germany" of the National Research Programme 71 "Managing Energy Consumption". The cooperatives were surveyed on their organizational structure, their activities in electricity and heat generation, their finances, the political context and their assessments of the future.
 Survey Method
The survey was targeted at all energy cooperatives in Switzerland (this is the basic population). The Swiss Commercial Register was searched for cooperatives and specific keywords in order to determine this basic population and collect addresses. This search in May 2016 resulted in a total of 304 energy cooperatives, to which a questionnaire was sent in July 2016. A pre-test with 8 persons had been carried out before the questionnaire was sent out. The questionnaire was provided in German and French. It was sent by mail and an attached letter referred to a link for the digital version if preferred. The online version was designed with the software "Sawtooth". After three weeks, a first, and after six weeks a second reminder letter was sent to those cooperatives that had not yet completed the questionnaire. The returned hardcopy questionnaires were manually entered into the database and then combined with the electronic data from the online survey. In the course of the survey, the total population was reduced from 304 to 289: in 4 cases the survey was not deliverable, 4 cooperatives had dissolved, 6 were not actually energy cooperatives, 1 case had recently changed its legal form. With a response rate of 47%, the final data set comprises 136 responses (from 77 digital and 59 hardcopy questionnaires). However, not all 136 of the returned questionnaires were filled out completely. We checked for answers that seemed contradictory or incomprehensible. If an error could be clearly identified and the correct answer derived, the answer was adjusted, otherwise the answer was replaced by "missing data".
 Anonymization
Participating cooperatives have been assured that their information will be kept confidential and will only be made public anonymously. For this reason, the data have been anonymized in in order to prevent any identification of individual cooperatives.
 How to Use the Data
* The data are available in CSV and SPSS (sav.) format.
* A codebook and a modified version of the used questionnaire are provided to illustrate the data and variable structure. In the questionnaire, the variable names are assigned to the corresponding questions. In the codebook, further information on these variables (valid n, answer categories) can be found. This information (of the codebook) is already integrated in the SPSS file.
 Current Embargo on Data
These data are currently under embargo and will only be released when the project is completed (not before 2020).
Additional Information
* The used questionnaire is provided in German and French.
* Descriptive results of the survey were published in a WSL report: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:18943

en: Energy Cooperatives in Switzerland: Survey Results // Energiegenossenschaften in der Schweiz: Befragungsergebnisse

en: renewable-energy energy-cooperatives cooperatives community-energy switzerland

envidat

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Codebook
    Size: 2433879 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/30440e19-9f40-4bd5-a779-af1640db1891/download/energy-cooperatives-switzerland_codebook.pdf
    Description: Description of variable attributes and valid n

en:
Resource Title: Raw date (SPSS)
    Size: 323839 bytes
    Format: application/x-spss-sav
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/1319f978-1d65-498c-8bfd-589f1b89e6a7/download/energy-cooperatives-switzerland_data.sav
    Description: Raw data in sav. format (SPSS). For comprehension of the data and variable structure, please consult the modified questionnaire with variable names.

en:
Resource Title: Questionnaire with variable names
    Size: 3397996 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/806cb4ee-b4b7-4b77-9bbd-c014ae28bc76/download/energy-cooperatives-switzerland_questionnaire-with-variable-names.pdf
    Description: Modified questionnaire with variable names for each item. Should be used together with the data files (.csv or .sav) to reconstruct the data and variable structures.

en:
Resource Title: Raw data (.csv)
    Size: 196544 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/ec4125f8-d549-452f-a134-b53439f3b6e5/resource/7f6c3275-0b87-410f-882e-4496a5705a08/download/energy-cooperatives-switzerland_data.csv
    Description: Raw data in csv. format. For comprehension of the data and variable structure, please consult the codebook and the modified questionnaire with variable names.

community-energy

display_name: community-energy

cooperatives

display_name: cooperatives

energy-cooperatives

display_name: energy-cooperatives

renewable-energy

display_name: renewable-energy

switzerland

display_name: switzerland


bryophytes-of-europe-traits-bet-dataset

en: The Bryophytes of Europe Traits (BET) dataset includes values for 65 biological and ecological traits and 25 bioclimatic variables for all 1816 bryophytes included in the European Red List (Hodgetts et al. 2019). The traits are compiled from several regional trait datasets and manually complemented using Floras, species-specific literature and expert knowledge. The bioclimatic variables are calculated using the European range of each species. Details regarding the trait compilation and extraction of bioclimatic variables can be found in the corresponding data paper (Van Zuijlen et al. 2023).

en: iucn hornworts life-history-traits bioclimatic-variables mosses liverworts red-list indicator-values

title_for_slug: bryophytes-of-europe-traits-bet-dataset

en:
Resource Title: BET_data_explanations
    Size: 981939 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4865a082-169d-40d1-920b-fc20ad0acad2/resource/6367f57f-1894-4f1b-997d-068d4d7511cc/download/betdata.xlsx
    Description: Excel file including the BET dataset and (trait) explanations.

en:
Resource Title: BET_data
    Size: 1072488 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/4865a082-169d-40d1-920b-fc20ad0acad2/resource/d2d2f958-051c-4638-a808-88547cc64d92/download/betdata.txt
    Description: Text file including the BET dataset.

en:
Resource Title: BET_explanations
    Size: 249953 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/4865a082-169d-40d1-920b-fc20ad0acad2/resource/9ac4a865-5bb2-479b-93f4-b3bfd99c7ada/download/bet_explanations.pdf
    Description: PDF including the (trait) explanations.

bioclimatic-variables

display_name: bioclimatic-variables

hornworts

display_name: hornworts

indicator-values

display_name: indicator-values

iucn

display_name: iucn

life-history-traits

display_name: life-history-traits

liverworts

display_name: liverworts

mosses

display_name: mosses

red-list

display_name: red-list


en: We conducted four drone flights in Davos Wolfgang Arelen, in 2020/21 and 2022 to obtain data for the generation of DSMs and orthomosaics at a high resolution. The data was processed with the Agisoft Metashape Professional Software.

en: Photogrammetric Drone Data Wolfgang Arelen

en: uav wingtra dsm photogrammetry drone-data

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.

drone-data

display_name: drone-data

dsm

display_name: dsm

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra


photogrammetric-drone-data-schurlialp

en: The data was collected on 16.04.2021 and on 28.05.2021 with a Wingtra Gen II and a Sony RX1 II RGB sensor to obtain snow depth and distribution data. Following the data collection, the data was processed with Agisoft Metashape. A 10cm DSM, a 10cm snow depth raster, a 3mm orthophoto and the original drone images are available for download.

en: Photogrammetric Drone Data Schürlialp

en: wingtra orthophoto photogrammetry dsm drone-data uav

title_for_slug: photogrammetric-drone-data-schurlialp

envi

en: Environment

orthophoto

display_name: orthophoto