maintainer: Peter Bebi

en: soil-temperature experiment climate-change vegetation stillberg carbon-dioxide

en: Metadata FACE Stillberg Experimental Design

en: Schematic illustration and tabular listing of the FACE experimental design.

en: Project Description FACE Stillberg

media_type: text/html

en: Link to FACE project description on the WSL website.

format: HTML

en: Data FACE Stillberg

en: Folder in .zip format containing the FACE datasets.

mimetype: application/zip

en: Metadata FACE Stillberg Data File Description

en: List of descriptions for each of the .csv FACE data files.

en:
 Background information

High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.

 Experimental design

The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.

 Data description

Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

stillberg

display_name: stillberg

vegetation

display_name: vegetation

envidat

en: EnviDat: the Environmental Data Portal

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

en: FACE: Stillberg CO2 enrichment and soil warming study


aerosol-data-davos-wolfgang

maintainer: EnviDat Support

title_for_slug: aerosol-data-davos-wolfgang

en: drincz aerosol particles ice-nucleation raclets inp

state: active

type: dataset

en: OPC-N3 Dataset Davos Wolfgang

media_type: text/csv

en: Particle concentrations in a size range of 0.35 μm to 40 μm were measured with an OPC-N3 (Alphasense, Inc.) in a resolution of 20 seconds (time in UTC). PM₁, PM₂,₅ and PM₁₀ were directly derived.

format: CSV

mimetype: text/csv

en: APS Dataset Davos Wolfgang

en: The APS file contains aerosol data (total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) for aerodynamic diameters between 0.5 μm and ~20 μm as well as instrument characteristics, in a temporal resolution of 20 seconds, with time in UTC, measured at Davos Wolfgang.

format: SERVICE

mimetype: application/x-netcdf

en: SMPS Dataset Davos Wolfgang

en: The SMPS file contains aerosol data (particle concentration, total number concentration, median, mean, geometric mean, mode and geometric standard deviation of the size distribution) in a size range between 12 and 460 nm (electrical mobility diameter) as well as instrument characteristics (sample temperature, pressure, relative humidity, mean free path and gas viscosity), in a temporal resolution of 2 minutes, with time in UTC, measured at Davos Wolfgang.

en: OPC GT-526S Dataset Davos Wolfgang

en: Particle counts were recorded in six size channels (0.3, 0.5, 0.8, 1.5, 2.5 and 5 μm) in a resolution of 20 seconds (time in UTC) by a particle counter (GT-526S, Met One Instruments, Inc.).

en: DRINCZ Dataset Davos Wolfgang

en: The DRINCZ file contains information on temperature (in °C) dependent frozen fractions, number of Ice Nuleating Particles (INP, per standard liter) and differential INP concentrations (per standard liter and Kelvin).

en:
Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room.

Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0).

Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³).

Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³).

Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles.

aerosol

display_name: aerosol

drincz

display_name: drincz

ice-nucleation

display_name: ice-nucleation

inp

display_name: inp

particles

display_name: particles

raclets

display_name: raclets

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Aerosol Data Davos Wolfgang


en: polar sea-ice-elevation sea-ice terrestrial-laser-scans tls

en: Data processing documentation

en: Post Processed TLS's

media_type: application/zip

en: Compressed dat files

format: ZIP

en: Link to post-processed TLS’s of Antarctic sea ice

en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.

How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls

envidat

en: EnviDat: the Environmental Data Portal

en: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012


root-traits

maintainer: Ivano Brunner

title_for_slug: root-traits

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

en: Root-traits

en:
Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald

Data_Fig.1.xlsx
Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring

Data_Tab1+2_2005.xlsx
Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest

Data_Tab1+2_2016.xlsx
Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest

belowground-biomass

display_name: belowground-biomass

drought

display_name: drought

fine-root-traits

display_name: fine-root-traits

ingrowth-cores

display_name: ingrowth-cores

soil-coring

display_name: soil-coring

en: 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.


global-cryosphere-watch-data-survey

maintainer: Mathias Bavay

title_for_slug: global-cryosphere-watch-data-survey

en: gcw data-portal data-exchange data-usage automatic-publication

en: Data interoperability survey

en: Third party data usage

en: Two surveys on the topic of data usage where conducted for the Global Cryosphere Watch data portal. The first one focused on the data provider point of view while the second one focused on the data user point of view. 37 data providers (ie institutions) worldwide provided their answers for the first survey (from fall 2017 until summer 2018) while 54 users (contacted through various mailing list such as the Cryolist) answered the questions on their third party data usage (fall 2019 until January 2020).

automatic-publication

display_name: automatic-publication

data-exchange

display_name: data-exchange

data-portal

display_name: data-portal

data-usage

display_name: data-usage

gcw

display_name: gcw

en: Global Cryosphere Watch data survey


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

en: Data plot of the forest station (SCB)

media_type: application/pdf

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

format: PDF

en: Site photo of the field station (SCF)

en: Site photo of the field station from above (viewing downwards the slope).

en: Forest station data (SCB)

en: Data file.

en: Site photo of the forest station (SCB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Further details on the data repository

en: Meta data documentation.

en: Field station data (SCF)

en: Data plot of the field station (SCF)

en: Site aerial photo (Schänis)

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

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards


bryophytes-of-europe-traits-bet-dataset

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

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

en: PDF including the (trait) explanations.

en: Excel file including the BET dataset and (trait) explanations.

format: XLS

media_type: text/plain

en: Text file including the BET dataset.

format: TXT

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).

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

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Franziska Gerber

en: cryowrf landuse cosmo-wrf wrf topography static-data

en: Static data for WRF - Landuse

en: Documentation

en: Documentation of the dataset

en: Example namelist.wps to use with the 1s static data

en: Static data for WRF - Topography

en: Static data for WRF - Soiltype top

en:
Example GEOGRID.TBL to use with the 1s static data;
Note about naming:
* 121 -> 1-2-1 topography smoothing applied to dataset
* 1 -> one smoothing cycle applied to the data (needs to be changed depending on the chosen resolution to avoid too steep slope angles)

en: Static data for WRF - Soiltype bottom

en: Static input data (topography, landuse and soiltype) for the WRF preprocessing system WPS is provided for Switzerland and its neighboring countries between 45-49 N and 4-12 E. The data is provided at a resolution of 1 s. Topography is based on the Aster dataset, while landuse is extracted from the Corine landuse dataset. Soil type is set to silty clay loam for the entire domain. This static input data is valid for WRF and CRYOWRF.

cosmo-wrf

display_name: cosmo-wrf

cryowrf

display_name: cryowrf

landuse

display_name: landuse

static-data

display_name: static-data

topography

display_name: topography

wrf

display_name: wrf

en: High resolution static data for WRF over Switzerland


en: beta-diversity microbial-biodiversity soil-respiration ecosystem-functions microbial-respiration

en: Bacterial amplicon sequencing

en: Bacterial ASVs and taxonomic tables

en: Microbial functions and metadata

en: Extracellular enzyme activities, respiration and sites metadata

en: Fungal amplicon sequencing

en: Fungal ASVs and taxonomic tables

en: Structural and functional changes of microbial communities in ephemeral stream sediments and adjacent soils between was assessed in an artificial newly created catchment at 3 and 13 years after catchment construction. Bacterial and fungal communities, respiration and extracellular enzyme activities were assessed.

beta-diversity

display_name: beta-diversity

ecosystem-functions

display_name: ecosystem-functions

microbial-biodiversity

display_name: microbial-biodiversity

microbial-respiration

display_name: microbial-respiration

soil-respiration

display_name: soil-respiration

educ

en: Education, culture and sport

en: Chicken Creek 10 years


maintainer: Chunhong Zhao

en: landscape urban-morphology land-use austin land-dynamics

en: Land use dynamics in Austin since 1992

en: The present dataset is part of the published scientific paper Zhao C, Weng Q, Hersperger A M. Characterizing the 3-D urban morphology transformation to understand urban-form dynamics: a case study of Austin, Texas, USA. Landscape and urban planning, 2020, 203:103881. The overall objective of this paper is to understand urban form dynamics in the Austin metropolitan area for the periods 2006–2011 and 2011–2016. The study also aims to understand to what extent the changes in the built environment (in terms of ‘efficient growth’ versus ‘inefficient growth’) from the 1990s to 2016 in the Austin metropolitan area corresponded with ‘compact and efficient growth’ planning policy documents. The UMT distribution can be found in the paper. The area of transitioning UMT was provided in Table 2 and Table 3 can be found in the Appendix of the paper. A protocol was developed to perform the content analysis of the strategic plans and gather the data. The detailed list of protocol items can be found in Appendix B of the paper. This study demonstrates the advantage of applying Lidar data to characterize 3-D urban morphology type (UMT) transition and understand its dynamics, which helps develop a comprehensive understanding of the urbanization process and provides a tool for planning intentions and policies evaluation on urban development over time. The UMT maps can be found in Appendix A of the paper. The Lidar point datasets and the 30 × 30 m National Land Cover Database (NLCD) are the two main data sources of UMT mapping. Lidar datasets were gathered from different projects that had been conducted and collected by state agencies and other organizations between 2007 and 2017. Table A1 in the appendix in the paper shows the accuracies and acquisition parameters of the Lidar projects from 2007 to 2017. Land use/cover dynamics in Austin metropolitan area dataset provides Land use/cover patterns in the years 1992, 2001, 2004, 2006, 2008, 2011, 2013, 2016 with a spatial resolution of 30 meters. Since NLCD 1992 used a different classification system for the urban land classes, we first reclassified the NLCD 1992 using a customized Arcpy package.

austin

display_name: austin

land-dynamics

display_name: land-dynamics

land-use

display_name: land-use

landscape

display_name: landscape

urban-morphology

display_name: urban-morphology

envidat

en: EnviDat: the Environmental Data Portal

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

en: Land use/cover dynamics in Austin metropolitan area since 1992


maintainer: Rebecca Mott

en: patchy-snow-covers tls riegl-vz6000 terrestrial-laser-scanning snow-ablation-rates

en: Gletschboden test site

mimetype: application/pdf

en: Digital Elevation Modell 2014

en: Snowmask 2014

en: Digital Elevation Modell 2015

en: Snowmask 2015

en: Snowmask 2016

en: Digital Elevation Modell 2016

en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment


en: geoinformation-system open-source raster-processing cable-yarding qgis-plugin swiss-geodata digital-elevation-model digital-planning geodata-processing seilaplan

en: DHM-Kacheln zusammenfügen

en: View video on youtube!

en:
In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!

Link to Seilaplan website: https://seilaplan.wsl.ch

***************************

Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.

Link zur Seilaplan-Website: https://seilaplan.wsl.ch

cable-yarding

display_name: cable-yarding

digital-elevation-model

display_name: digital-elevation-model

digital-planning

display_name: digital-planning

geodata-processing

display_name: geodata-processing

geoinformation-system

display_name: geoinformation-system

open-source

display_name: open-source

qgis-plugin

display_name: qgis-plugin

raster-processing

display_name: raster-processing

seilaplan

display_name: seilaplan

swiss-geodata

display_name: swiss-geodata

educ

en: Education, culture and sport

en: Seilaplan Tutorial: Merge DTM tiles


maintainer: James W. Kirchner

en: streamflow deuterium catchment plynlimon stable-water-isotopes precipitation tracer chloride

en: Weekly stable water isotopes

en: Data set of weekly stable water isotope data collected at Carreg Wen (precipitation) and Lower Hafren and Tanllwyth (streamflow).

mimetype: text/plain

en: Data Set Documentation

en: This file contains a documentation of the data sets, including references to other helpful documentations.

en: 7-hourly stable water istopes

en: Data set of 7-hourly stable water isotope data measured at Carreg Wen (precipitation) and Upper Hafren (streamflow).

en: The data base contains timeseries of stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK. One data set contains weekly stable water isotope data from the Lower Hafren and Tanllwyth catchments, and the other data set contains 7-hourly stable water isotope data from Upper Hafren. Both data sets also include chloride concentrations in precipitation and streamflow.

catchment

display_name: catchment

chloride

display_name: chloride

deuterium

display_name: deuterium

plynlimon

display_name: plynlimon

precipitation

display_name: precipitation

stable-water-isotopes

display_name: stable-water-isotopes

streamflow

display_name: streamflow

tracer

display_name: tracer

envidat

en: EnviDat: the Environmental Data Portal

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

en: Stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK


en: natural-climate-variability rain-on-snow cryosphere snow-water-equivalent uncertainty climate-change-impact

en: climate realizations

en: The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty

en: Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century


maintainer: Lisa Hülsmann

en: empirical-mortality-models inventory-data tree-mortality tree-growth forest-reserves

en: Calibration data

en:
A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory.

 Meta data
Reserve: Name of the forest reserve

Plot: Permanent plot number

 Tree data
Species: Latin species name (or species group, cf. _Quercus_ spp.)

y: Status of the tree with 0 = alive and 1 = dead

dt: Length of the mortality period (years)

DBH: Diameter at breast height (mm) of the second inventory

relBAI: Annual relative basal area increment (-) calculated based on the first and the second DBH measurement as the compound annual growth rate of the trees basal area

 Stand data
_All stand variables were calculated for the second inventory._

mDBH: Mean diameter at breast height (mm)

iqrDBH: Interquartile range of diameter at breast height (mm)

BA: Basal area per hectare (m2 ha-1)

N: Number of trees per hectare (ha-1)

 Climate data
_Both climate variables were calculated for the period between the second and the third inventory._

P: Mean annual precipitation sum (mm)

mT: Mean annual air temperature (°C)

en:
The dataset comprises > 90 000 records from inventories in 54 strict forest reserves in [Switzerland](https://www.wsl.ch/de/wald/biodiversitaet-naturschutz-urwald/naturwaldreservate.html) and [Lower Saxony / Germany](http://naturwaelder.de/) along a considerable environmental gradient. It was used to develop parsimonious, species-specific mortality models for 18 European tree species based on tree size and growth as well as additional covariates on stand structure and climate.

 Inventory data
Measurements had been conducted repeatedly on up to 14 permanent plots per reserve for up to 60 years with re-measurement intervals of 4 - 27 years. The permanent plots vary in size between 0.03 and 3.47 ha. The inventories provide diameter measurements at breast height (DBH) and information on the species and status (alive or dead) of trees with DBH ≥ 4 cm for Switzerland and ≥ 7 cm for Germany.

 Data selection
We excluded three permanent plots where at least 80 % of the trees died during an interval of 10 years, and mortality could be clearly assigned to a disturbance agent. Mortality in the remaining stands was rather low, with a mean annual mortality rate of 1.5 % and strong variation between plots from 0 to 6.5 % (assessed for trees of all species with DBH ≥ 7 cm).
We only used data from permanent plots with at least 20 trees per species to obtain reliable plot-level mortality rates even for species with low mortality rates (about 5 % during 10 years), and selected tree species occurring on at least 10 plots to cover sufficient ecological gradients. This led to a dataset of 197 permanent plots and 18 tree or shrub species: _Abies alba_ Mill., _Acer campestre_ L., _Acer pseudoplatanus_ L., _Alnus incana_ Moench., _Betula pendula_ Roth, _Carpinus betulus_ L., _Cornus mas_ L., _Corylus avellana_ L., _Fagus sylvatica_ L., _Fraxinus excelsior_ L., _Picea abies_ (L.) Karst, _Pinus mugo_ Turra, _Pinus sylvestris_ L., _Quercus pubescens_ Willd., _Quercus_ spp. (_Q. petraea_ Liebl. and _Q. robur_ L.; not properly differentiated in the Swiss inventories), _Sorbus aria_ Crantz, _Tilia cordata_ Mill. and _Ulmus glabra_ Huds..

 Predictors of tree mortality
We considered tree size and growth as key indicators for mortality risk. Radial stem growth between the first and second inventory and DBH at the second inventory were used to predict tree status (alive or dead) at the third inventory. To this end, the annual relative basal area increment (relBAI) was calculated as the compound annual growth rate of the trees basal area. Additional covariates on stand structure and climate comprise mean annual precipitation sum (P), mean annual air temperature (mT), the mean and the interquartile range of DBH (mDBH, iqrDBH), basal area (BA) and the number of trees (N) per hectare.

 Further information
For further information, refer to Hülsmann _et al_. (in press) How to kill a tree – Empirical mortality models for eighteen species and their performance in a dynamic forest model. _Ecological Applications_.

empirical-mortality-models

display_name: empirical-mortality-models

forest-reserves

display_name: forest-reserves

inventory-data

display_name: inventory-data

tree-growth

display_name: tree-growth

tree-mortality

display_name: tree-mortality

educ

en: Education, culture and sport

en: Calibration data for empirical mortality models of 18 European tree species


en: stable-water-isotope 18o metamorphism snow advection

en: Read-me

en: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

en: Data files and read-me

en: raw data and micro-CT data available from contacts

en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

advection

display_name: advection

metamorphism

display_name: metamorphism

snow

display_name: snow

stable-water-isotope

display_name: stable-water-isotope

en: Experiments on stable water isotopes,  snow metamorphism, and advection


maintainer: Esther Frei

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

mimetype: application/x-zip-compressed

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).

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

envidat

en: EnviDat: the Environmental Data Portal

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

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


en: aerosol ice-nucleation clouds backward-trajectories raclets

en: This dataset contains number concentrations of ice-nucleating particles active at -15 °C observed at Weissfluhjoch during February and March 2019, as well as complementary data (measured aerosol number concentrations and modelled total precipitation along air mass trajectories). This data formed the basis of our paper with the title “Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling”.

aerosol

display_name: aerosol

backward-trajectories

display_name: backward-trajectories

clouds

display_name: clouds

ice-nucleation

display_name: ice-nucleation

raclets

display_name: raclets

en: Ice nucleating particle concentrations active at -15 °C at Weissfluhjoch


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

en: Python scripts to reproduces figures in Gerber et al., 2022, revised

en: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

en: Processed CRYOWRF output used for the analysis and the figures in the paper.

en: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

en: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

en: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).

* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.

Note:

* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance

educ

en: Education, culture and sport

en: Reproducibility dataset for CRYOWRF validation


en: edna biodiversity-monitoring crispr-dx african-manatee qpcr threatened-species field-based-protocol crispr-cas environmental-dna

en: File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file in the data folder, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file (also in the data folder). The file includes the GPS coordinates of the sampling location (transect start point).

en:
Folder containing the data files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

en: Description of project and folders and files

en:
Data associated to the publication "Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx"

 Authors:

Flurin Leugger, Martina Lüthi, Michel Schmidlin, Zacharias Kontarakis and Loïc Pellissier

 Contact:

flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch

 Project description:

We collected eDNA samples in the Conkouati-Douli National Park in the Republic of Congo in 2023 in collaboration with Beauval Nature and HELP Congo. We analyzed the samples on site in the national park using CRISPR-Dx assays to detect the African manatee (*Trichechus senegalensis*). Additionally, we transported the remaining samples (buffer) to Switzerland and used a high-sensitivity protocol with CRISPR-Dx assays and a qPCR assay to verify the field-based detections. The qPCR of Hunter et al. (2018) detects the genus manatee (Trichechus). See publication for more details (doi will be added after publication).

 Folders:

 lateral_flow_tests_images\:

Images of the lateral flow tests used to analyze the eDNA extracts in the national park. File names correspond to the site names. At each site, we took two filter replicates. We ran 8 PCRs per filter/extract and pooled two PCRs together, resulting in 4 CRISPR-Dx assays per extract. The EVE number on top of the tests indicates the environmental extract number we use to track the extracts in our data base. It corresponds to the extract_number_field_based in the metadata and data folder. The negative extraction control with the strongest "band" was placed right to the eDNA extract on each image (labelled hand written with NC x.y).

 metadata\:

File containing overview of site names and extract number (field-based or lab-based extraction). The extract_number_field_based corresponds to the identically called column in CRISPR_field_based_classifications.csv file, as the extract_number_lab_based to the column in the file CRISPR_lab_based_classifications.csv file and the qPCR_Cp_2nd_derivative.csv file. The file includes the GPS coordinates of the sampling location (transect start point).

 data\:

Folder containing the files with Cp values (qPCR) and the CRISPR-Dx classifications. CRISPR_field_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection) for the African manatee (Trichechus senegalensis).
CRISPR_lab_based_classifications.csv file contains the classifications per pool per extract (0: no detection, 1: detection).
qPCR_Cp_2nd_derivative.csv file contains the Cp value of the 8 replicates of each extract.

african-manatee

display_name: african-manatee

biodiversity-monitoring

display_name: biodiversity-monitoring

crispr-cas

display_name: crispr-cas

crispr-dx

display_name: crispr-dx

edna

display_name: edna

environmental-dna

display_name: environmental-dna

field-based-protocol

display_name: field-based-protocol

qpcr

display_name: qpcr

threatened-species

display_name: threatened-species

en: Field-based eDNA analysis to detect the threatened and elusive African manatee


photogrammetric-drone-data-schurlialp

maintainer: Yves Bühler

title_for_slug: photogrammetric-drone-data-schurlialp

en: wingtra drone-data uav dsm photogrammetry orthophoto

en: Data Access

en:
- 10 cm DSM
- 10 cm HS
- 3 cm orthophoto
- original RGB images
- Agisoft Metashape Processing Report

All of the products are also available as a cloud optimized geotiff.

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.

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

uav

display_name: uav

wingtra

display_name: wingtra

envidat

en: EnviDat: the Environmental Data Portal

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

en: Photogrammetric Drone Data Schürlialp


maintainer: Sebastian Schlögl

en: atmospheric-turbulence atmosphere snow stable-boundary-layer turbulent-sensible-heat-fluxes

en: Turbulence data WFJ07

en: lower sensor

en: Turbulence data GR00

en: sensor in 1 m height

en: Turbulence data AA00

en: sensor in 0.2 m height

en: Turbulence data WFJ11

en: sensor in 2 m height

en: upper sensor

en: Turbulence data PM07

en: SEE

en: sensor in 25 m height

en: NWW

en:
We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.
The turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations.
Three-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.
The selected datasets and corresponding test sites are briefly introduced below:

Weissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).

Weissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.

Plaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).

Greenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).

Antarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).

atmosphere

display_name: atmosphere

atmospheric-turbulence

display_name: atmospheric-turbulence

snow

display_name: snow

stable-boundary-layer

display_name: stable-boundary-layer

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes

en: How do stability corrections perform in the stable boundary layer over snow?


photogrammetric-drone-data-gruenbodeli

title_for_slug: photogrammetric-drone-data-gruenbodeli

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

en: Data Access

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

All products are also available as a cloud optimized geotiff.

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

snow-depth-mapping

display_name: snow-depth-mapping

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Photogrammetric Drone Data Grüenbödeli


restoring-grassland-multifunctionality

title_for_slug: restoring-grassland-multifunctionality

en: ecosystem-multifunctionality grassland restoration bacteria nematodes mineralization soil-biodiversity plants fungi biodiversity

en: Please note that EMF, MF.below, MF.abio and Soil.hetero have been corrected.

en: Please note that C.sto and Corg have been corrected.

en: Functional diversity above_belowground fauna

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

Resch, M. C., Schütz, M., Buchmann, N., Frey, B., Graf, U., van der Putten, W. H., Zimmermann, S., Risch, A. C. 2021. Evaluating long-term success in grassland restoration – an ecosystem multifunctionality approach. Ecological Applications 31, e02271.

 Study area

The study was conducted in the Canton of Zurich, Switzerland, in and around two nature reserves Eigental and Altläufe der Glatt (47°27’ to 47°29’ N, 8°37’ to 8°32’ E, 417 to 572 m a.s.l.). All studied grasslands were located with a radius of approximately 4 km. Average monthly temperatures range from 0.7 ± 2.0 °C (January) to 19.0 ± 1.5 °C (July), and monthly precipitation range from 60 ± 42 mm (January) to 118 ± 46 mm (July [maxima]; 1989-2017; MeteoSchweiz 2018). In our study, we focused on semi-dry and semi-wet oligo- to mesotrophic grasslands characterized by high plant species richness and groundwater fluctuations throughout the year (Delarze et al. 2015, see also Resch et al. 2019).

 Experimental design and sampling

A large-scale restoration experiment to expand and reconnect isolated remnants of species-rich grasslands was initiated in the nature reserve Eigental in 1990. Twenty hectares of adjacent intensive grasslands were chosen for restoration. In 1995, three restoration methods of increasing intervention intensities were implemented. The goal of all three methods was to lower the availability of soil nutrients and hence, facilitate ecosystem development towards the targeted nutrient-poor grasslands. These methods were: Harvest only (hay harvest twice a year), Topsoil (removal of the nutrient-rich topsoil), and Topsoil+Propagules (topsoil removal combined with the application of hay from target vegetation). Plant biomass harvest (once a year in late summer/early autumn) commenced in Topsoil and Topsoil+Propagules five years after the soils were removed and is still ongoing today. We measured restoration success by comparing the three restoration methods with intensively managed (Initial) and semi-natural grasslands (Target) 22 years after restoration. Initial grassland sites share the same agricultural history as the restored sites: mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes (Resch et al. 2019). Target sites were the sites from which hay for seeding the Topsoil+Propagules sites was collected. Soil conditions (i.e., soil types, soil texture) were comparable to those found in the restored grasslands (Resch et al. 2019). Additionally, Target sites were selected to represent a variety of semi-natural grasslands, including semi-dry to semi-wet conditions. In Target grasslands, biomass is harvested once a year in late summer or early autumn. Eleven 5 m x 5 m (25 m2) plots were randomly established in each of the five treatments (in total 55 plots; for a detailed map see Neff et al. 2020). An additional 2 m x 2 m (4 m2) subplot was randomly established at least 2 m away from each 25 m2 plot for destructive sampling. Data sampling took place between June and September 2017.

Vegetation properties

All plant species were identified within the 25 m2 plots (nomenclature: Lauber and Wagner 1996) in mid-June 2017 (in total 250 species). Vegetation structure and plant biomass were assessed diagonally on a transect of 2 m x 10 cm within the 25 m2 plot in early July 2017. We measured the maximum and mean height of the vegetation at the start, middle and end of the transect and calculated the standard deviation of these measures to describe vegetation structural heterogeneity (Schuldt et al. 2019). Thereafter, biomass was clipped on the entire transect to 1 cm height, sorted into five functional groups (graminoids, forbs, legumes, litter, and woody species), dried at 60 °C for 48 h, and weighed (Meyer et al. 2015).

 Aboveground arthropods

Aboveground arthropods were sampled at two locations in each 25 m2 plot in early July 2017 (see also Neff et al. 2020). Briefly, two cylindrical baskets (50 cm diameter, 67 cm height; woven fabric) were thrown simultaneously from outside the plot into two opposite corners. A closable mosquito mesh sleeve was mounted to the top of the baskets and an integrated metal ring at the bottom was fixed to the ground with metal stakes to assure that insects could not escape. A suction sampler (Vortis, Burkhard Manufacturing Co. Ltd., Hertfordshire, England) was then inserted into one of the baskets through the opening of the sleeve and the plot was “vacuumed" twice for 105 seconds with a 30 seconds break. The collected animals were immediately transferred into 70% ethanol. Arthropods were sorted and assigned to 23 taxonomic groups. Holometabolic larvae were lumped into one category while hemimetabolic larvae were grouped separately from adults in the respective taxonomic rank. We used mean values of individuals per plot for total abundance. Aboveground arthropod richness was defined by the number of different taxa to lowest taxonomic level (in total 23 taxa). All taxa were assigned to one of five trophic levels: 1) primary producers, 2) primary consumers, 3) secondary consumers, 4) tertiary consumers, and 5) quaternary consumers.

 Belowground fauna

Sampling of all belowground fauna took place in mid-July 2017. Earthworms were sampled in two 30 cm x 30 cm x 20 cm soil monoliths at two opposite corners of the 25 m2 plot (opposite to aboveground arthropod sampling). The excavated soil monolith was broken by hand, all earthworms collected and immediately transferred in a 4% formaldehyde solution. Thereafter, earthworm individuals were identified to species level (in total 10 taxa; Christian and Zicsi 1999) and species assigned to three functional groups (Bouché 1977).
To assess soil arthropod communities, we randomly collected one undisturbed soil core (5 cm diameter, 12 cm depth) in each 4 m2 subplot with a slide hammer corer lined with a plastic sleeve (AMS Samplers, American Falls, Idaho, USA). Soil arthropods were extracted using Berlese-Tullgren funnels (3 mm mesh), starting the day of sampling and lasting 14 days. Individuals were stored in 70% ethanol. Soil arthropods were assigned to 41 taxonomic groups and 4 feeding types. Holometabolic and hemimetabolic larvae were treated as previously described for aboveground arthropods. Belowground arthropod richness refers to the 41 taxonomic groups.

For soil nematode sampling, we randomly collected eight soil cores of 2.2 cm diameter (Giddings Machine Company, Windsor, CO, USA) within each 4 m2 subplot to a depth of 12 cm. The eight cores were combined, gently homogenized, placed in coolers, kept at 4 °C and transported to the laboratory at NIOO in Wageningen (NL) within one week after collection. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink 1960) and prepared for morphological identification and quantification as described by Resch et al. (2019). Nematodes were identified to family level (39 taxa) according to Bongers (1988), assigned to 17 functional groups, 5 feeding types and 5 colonizer-persister (C-P) classes (Yeates et al. 1993, Bongers 1990, Resch et al. 2019).

We randomly collected two more soil cores (2.2 cm diameter x 12 cm depth) within each 4 m2 subplot to determine soil microbial communities. Again, the soil cores were combined, homogenized, placed in coolers and transported to the laboratory at WSL in Birmensdorf (Switzerland) where the metagenomic DNA was extracted from 8 g sieved soil (2 mm) using the DNeasy PowerMax Soil Kit (Quiagen, Hilden, NRW, GER) according to the manufacturer`s instructions. PCR amplification of the V3-V4 region of the prokaryotic small-subunit (16S) and the ribosomal internal transcribed spacer region (ITS2) of eukaryotes was performed with 1 ng of template DNA utilizing PCR primers and conditions as previously described (Frey et al., 2016). PCRs were run in triplicates and pooled. The pooled amplicons were sent to the Genome Quebec Innovation Centre (Montreal, QC, Canada) for barcoding using the Fluidigm Access Array technology (Fluidigm) and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA). Quality filtering, clustering into operational taxonomic units (OTUs) and taxonomic assignment were performed as described by Frey et al. (2016) and Adamczyk et al. (2019). We used a customised pipeline largely based on UPARSE (Edgar 2013) implemented in USEARCH v. 9.2 (Edgar 2010). After discarding singletons of dereplicated sequences, clustering into OTUs with 97% sequence similarity was performed (Edgar 2013). Quality-filtered reads were mapped on the filtered set of centroid sequences. Taxonomic classification of prokaryotic and fungal sequences was conducted querying against most recent versions of SILVA (v.132, Quast et al. 2013) and UNITE (v.8, Nilsson et al. 2018). Only taxonomic assignments with confidence rankings equal or higher than 0.8 were accepted (assignments below 0.8 set to unclassified). Prokaryotic OTUs assigned to mitochondria or chloroplasts as well as eukaryotic OTUs assigned other than fungi were removed prior to data analysis. In addition, prokaryotic and fungal datasets were filtered to discard singletons and doubletons. Thereafter, OTU abundance matrices were rarefied to the lowest number of sequences per community, to normalize the total number of reads and achieve parity between samples (Prokaryota: 29,843 reads; Fungi: 26,690 reads). Finally, prokaryotic and fungal observed richness (number of OTUs) were estimated (Prokaryota: 14,010 OTUs; Fungi: 5,813 OTUs). For prokaryotes, we distinguished five and for fungi six functional types based on lowest taxonomic resolution (Nguyen et al. 2016, Tedersoo et al. 2014). Belowground taxon richness was defined by the total number of earthworm, arthropod, nematode, fungi, and prokaryote taxa assigned to lowest taxonomic level. Finally, all belowground taxa were assigned to the same five trophic levels as the aboveground arthropods.

 Soil chemical and physical properties, soil nitrogen mineralization

We randomly collected three 5 cm diameter x 12 cm depth soil samples in each 4 m2 subplot with a slide hammer corer (AMS Samplers, American Falls, Idaho, USA), pooled them and then made two subsamples. One was field-fresh and stored at 3 °C until analysis, the other was dried for 48 h at 60 °C and passed through a 4 mm mesh. From the dried sample, we measured soil pH potentiometrically in 0.01 M CaCl2 (soil:solution ratio=1:2; 30 minutes equilibration time). Total and organic carbon content were measured on fine-ground samples (≤ 0.5 mm) by dry combustion using a CN analyzer NC 2500 (CE Instruments, Wigan, United Kingdom). Inorganic carbon of samples with a pH > 6.5 was removed with acid vapor prior to analysis of organic carbon (Walthert et al. 2010). We calculated total soil carbon (C) storage after correcting its content for soil depth, stone content and density of fine earth (see below). Exchangeable cations were determined on another 5 g dry soil sample with 50 mL unbuffered 1 M NH4Cl solution (soil:solution ratio=1:10, end-over-end shaker for 1.5 hours) and measured by an ICP-OES (Optima 7300 DV, Perkin-Elmer, Waltham, Massachusetts, USA). Thereafter, cation exchange capacity (CEC) was calculated as the sum of exchangeable cations and protons (and expressed as mmolc per 1 kg soil) and used to describe nutrient retention capacity in our plots. Concentrations of exchangeable protons were calculated as the difference between total and Al-induced exchangeable acidity as determined by the KCl-method (Thomas 1982).

Ammonium (NH4+) and nitrate (NO3−) were extracted from a 20 g fresh subsample with 80 mL 1M KCl for 1.5 hours on an end-over-end shaker and filtered through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnemühle FineArt GmbH, Dassel, Germany). NH4+ concentrations were determined colorimetrically by automated flow injection analysis (FIAS 300, Perkin-Elmer, Waltham, Massachusetts, USA). NO3− concentrations were measured colorimetrically according to Norman and Stucki (1981). Potential soil net nitrogen (N) mineralization was assessed during an 8-week incubation period under controlled moisture (60% of field capacity), temperature (20 °C) and light conditions (dark) in the laboratory. We weighed duplicate samples of fresh soil equivalent to 8 g dry soil (24 h at 104 °C) into 50 mL Falcon tubes. Soil samples were extracted for NH4+ and NO3− at the beginning and after eight weeks as described above. Soil net N mineralization was calculated as the difference between the inorganic nitrogen (NH4+ and NO3−) before and after the incubation (Hart et al. 1994), corrected for the total incubation time and represented per day values expressed as mg N kg-1 soil d-1.

To assess soil physical properties, we randomly collected one undisturbed soil core per 4 m2 subplot (5 cm diameter, 12 cm depth) in a steel cylinder that fit into the slide hammer (AMS Samplers, American Falls, Idaho, USA). The cylinder was capped in the field to avoid disturbance. We then measured field capacity in the laboratory. For this purpose, the cylinder and soil therein were saturated in a water bath and drained on a sand/silt-bed with a suction corresponding to 60 cm hydrostatic head. The moist soil was dried at 105 °C to constant weight. Field capacity was calculated by dividing the mass of water by the total mass of wet soil contained at 60 cm hydrostatic head and used to describe water holding capacity. Thereafter, samples were passed through a 4 mm mesh. Fine-earth and skeleton fractions were weighed separately to assess bulk soil density (fine-earth plus skeleton), density of fine earth, and proportion of skeleton. Particle density was determined with the pycnometer method (Blake and Hartge 1986), and total porosity and proportion of fine pores were calculated (Danielson and Sutherland 1986). Clay, silt, and sand contents were quantified with the sediment method (Gee and Bauder 1986).

Surface and soil temperature (12 cm depth, water-resistant digital pocket thermometer; IP65, H-B Instrument, Trappe, Pennsylvania, USA) as well as volumetric soil moisture content (12 cm depth, time domain reflectometry; Field-Scout TDR 300, Spectrum Technologies, Aurora, Illinois, USA) were measured at five random locations within the 4 m2 subplots every month from June to September. We calculated the standard deviation of each temperature and moisture measure over four months to describe seasonal variations. Slope inclination was determined at plot-level via GPS measurements (GPS 1200, Leica Geosystem, Heerbrugg, Switzerland) and categorized into slope gradient classes according to FAO standards (1990). Thickness of the topsoil horizon (equivalent to Ah or Aa horizon) was determined at one soil monolith (30 x 30 x 30 cm3) per 4 m2 subplot in cm and rounded to next integer.

 References

Adamczyk, M., F. Hagedorn, S. Wipf, J. Donhauser, P. Vittoz, C. Rixen, A. Frossard, J. Theurillat, and B. Frey. 2019. The soil microbiome of GLORIA mountain summits in the Swiss Alps. Frontiers in Microbiology 10:1080-1101.

Blake, G.R., and K. H. Hartge. 1986. Particle Density. Pages 377-382 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.

Bongers, T. 1988. De nematoden van Nederland. Stichting Uitgeverij van de Koniklijke Nederlandse Natuurhistorische Verenigung (KNNV), Utrecht.

Bongers, T. 1990. The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia 83:14-19.

Bouché, M. B. 1977. Strategies lombriciennes. Ecological Bulletins 25:122-132.

Christian, E., and A. Zicsi. 1999. Ein synoptischer Bestimmungsschlüssel der Regenwürmer Österreichs (Oligochaeta: Lumbricidae). Die Bodenkultur 50:121-131.

Danielson, R. E., and P. L. Sutherland. 1986. Porosity. Pages 443-461 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.

Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie ‐ Gefährdung ‐ Kennarten, Ott Verlag, Bern.

Edgar, R. C. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461.

Edgar, R. C. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods 10:996–998.

FAO. 1990. Guidelines for soil description, third ed. Land and Water Development Division at the Food and Agriculture Organization of the United Nations (FAO), Rome.

Frey, B., T. Rime, M. Phillips, B. Stierli, I. Hajdas, F. Widmer, and M. Hartmann. 2016. Microbial diversity in European alpine permafrost and active layers. FEMS Microbiology Ecology 92:fiw018.

Gee, G.W., and J. W. Bauder. 1986. Particle-size analysis. Pages 383-411 in A. Klute, editor. Methods of soil analysis: Part 1—Physical and mineralogical methods. Soil Science Society of America (SSSA) Inc., Madison.

Hart, S. C, J. M. Stark, E. A. Davidson, and M. K. Firestone. 1994. Nitrogen mineralization, immobilization, and nitrification. Pages 985-1016 in R. W. Weaver, S. Angle, P. Bottomley, D. Bezdicek, S. Smith, A. Tabatabai, and A. Wollum, editors. Methods of soil analysis: Part 2—Microbiological and biochemical properties. Soil Science Society of America (SSSA) Inc., Madison.

Lauber, K., Wagner, G., 1996. Flora Helvetica. Flora der Schweiz. Haupt Verlag, Bern.

MeteoSchweiz, 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.

Meyer, S. T., C. Koch, and W. W. Weisser. 2015. Towards a standardized rapid ecosystem function assessment (REFA). Trends in Ecology and Evolution 30:390-397.

Neff, F., M. C. Resch, A. Marty, J. Rolley, M. Schütz, A. C. Risch, and M. M. Gossner. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands – a functional approach. Ecological Applications 0:e02133

Nguyen, N.H., Z. W. Song, S. T. Bates, S. Branco, L. Tedersoo, J. Menke, J. S. Schilling, and P. G. Kennedy. 2016. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology 20:241–248.

Nilsson, R. H., K.-H. Larsson, A. F. S. Taylor, J. Bengtsson-Palme, T. S. Jeppesen, D. Schigel, P. G. Kennedy, K. Picard, F. O. Glöckner, L. Tedersoo, I. Saar, U. Kõljalg, and K. Abarenkov. 2018. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research 47:259–264.

Norman, R. J., and J. W. Stucki. 1981. The Determination of Nitrate and Nitrite in Soil Extracts by Ultraviolet Spectrophotometry. Soil Science Society of America Journal 45:347-353.

Oostenbrink, M. 1960. Estimating nematode populations by some selected methods. Pages 81-101 in J. J. Sasser, and W. R. Jenkins, editors. Nematology. Univ. of North Carolina Press, Chapel Hill.

Quast, C., E. Pruesse, P. Yilmaz, J. Gerken, T. Schweer, P. Yarza, J. Peplies, and F. O. Glöckner. 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 41:590-596.

Resch, M. C., M. Schütz, U. Graf, R. Wagenaar, W.H. van der Putten, and A. C. Risch. 2019. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology 56:1782-1793.

Schuldt, A., A. Ebeling, M. Kunz, M. Staab, C. Guimarães-Steinicke, D. Bachmann, N. Buchmann, W. Durka, A. Fichtner, F. Fornoff, W. Härdtle, L. R. Hertzog, A-N. Klein, C. Roscher, J. Schaller, von G. Oheimb, A. Weigelt, W. Weisser, C.Wirth, J. Zhang, H. Bruelheide, and N. Eisenhauer. 2019. Multiple plant diversity components drive consumer communities across ecosystems. Nature Communications 10:1460.

Tedersoo, L., M. Bahram, S. Põlme, U. Kõljalg, N. S. Yorou, R. Wijesundera, L. Villarreal Ruiz, A. M. Vasco-Palacios, P. Q. Thu, A. Suija, M. E. Smith, C. Sharp, E. Saluveer, A. Saitta, M. Rosas, T. Riit, D. Ratkowsky, K. Pritsch, K. Põldmaa, M. Piepenbring, C. Phosri, M. Peterson, K. Parts, K. Pärtel, E. Otsing, E. Nouhra, A. L. Njouonkou, R. H. Nilsson, L. N. Morgado, J. Mayor, T. W. May, L. Majuakim, D. J. Lodge, S. See Lee, K.-H. Larsson, P. Kohout, K. Hosaka, I. Hiiesalu, T. W. Henkel, H. Harend, L.-D. Guo, A. Greslebin, G. Grelet, J. Geml, G. Gates, W. Dunstan, C. Dunk, R. Frenkhan, L. Dearnaley, A. De Kesel, T. Dang, X. Chen, F. Buegger, F. Q. Brearley, G. Bonito, S. Anslan, S. Abell, and K. Abarenkov. 2014. Global diversity and geography of soil fungi. Science 346:1256688.

Thomas, G.W. 1982. Exchangeable cations. Pages 159-165 in A. L. Page, R. H. Miller, and D. R. Keeney, editors. Methods of Soil Analysis: Part 2—Chemical and microbiological properties. Soil Science Society of America (SSSA) Inc., Madison.

Walthert, L., U. Graf, A. Kammer, J. Luster, D. Pezzotta, S. Zimmermann, and F. Hagedorn. 2010. Determination of organic and inorganic carbon, δ13C, and nitrogen in soils containing carbonates after acid fumigation with HCl. Journal of Plant Nutrition and Soil Sciences 173:207-216.

Yeates, G. W., T. Bongers, R. G. M. de Goede, D. W. Freckman, and S. S. Georgieva. 1993. Feeding habits in soil nematode families and genera – an outline for soil ecologists. Journal of Nematology 25:315-331.

bacteria

display_name: bacteria

biodiversity

display_name: biodiversity

ecosystem-multifunctionality

display_name: ecosystem-multifunctionality

fungi

display_name: fungi

grassland

display_name: grassland

mineralization

display_name: mineralization

nematodes

display_name: nematodes

plants

display_name: plants

restoration

display_name: restoration

soil-biodiversity

display_name: soil-biodiversity

en: Restoring grassland multifunctionality


maintainer: Merin Reji Chacko

en: biodiversity-assessment spatial-ecology biomonitoring environmental-dna dna-metabarcoding

en: Genomic data

en: Fastq files, primer descriptions and the final output dataset.

en: Field Metadata

en: Information concerning the locations and times of sampling, as well as the identity of the samplers and relevant comments.

en: Analysis and Figures

en: This zipped file includes R scripts and the datasets required to run the analyses. A README describes the columns in each dataset.

en: This dataset contains the results of a five-day field excursion which the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1 800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. This dataset includes two sets of data. The first (Genomic data) includes all the necessary data for the bioinformatic pipeline, whereas the second (Analysis Figures) contains tidied data and scripts for the reproduction of all figures/analyses in the article describing this study.

biodiversity-assessment

display_name: biodiversity-assessment

biomonitoring

display_name: biomonitoring

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

spatial-ecology

display_name: spatial-ecology

en: Vertebrate and plant taxa recovered from 10 catchments in Vaud using an eDNA-metabarcoding approach


maintainer: Dirk Nikolaus Karger

en: sdm mammals niche-models amphibians iucn reptiles random-forests interannual-climate-variability range-maps generalized-linear-models generalized-additive-models chelsa climate-variablity species-distribution-models

en: Reptiles

en: Species distribution models based on different climate predictor groups

en: File containing the climate predictors as SAGA grid files (.sgrd)

en: File containing the record dimension, genus, and species of the respective netcdf files

en: Mammals

en: Amphibians

en: Readme file containing the file naming convention, file dimensions, and variable names

en: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.

amphibians

display_name: amphibians

chelsa

display_name: chelsa

climate-variablity

display_name: climate-variablity

generalized-additive-models

display_name: generalized-additive-models

generalized-linear-models

display_name: generalized-linear-models

interannual-climate-variability

display_name: interannual-climate-variability

iucn

display_name: iucn

mammals

display_name: mammals

niche-models

display_name: niche-models

random-forests

display_name: random-forests

range-maps

display_name: range-maps

reptiles

display_name: reptiles

sdm

display_name: sdm

species-distribution-models

display_name: species-distribution-models

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Global species distributions for mammals, reptiles, and amphibians


maintainer: EnviDat

en: meteorological-data-format metadata-convention nead csv research-data-management

en: PyNEAD (future reference implementation)

en: MeteoIO (future reference implementation)

mimetype: text/html

en: NEAD syntax v0.1 (EBNF)

en: NEAD on GitHub

en:
Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format.

The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference).

-----------------------

Summary:
The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories.

License: The NEAD specifications are released to the public domain under a Creative Commons CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management

en: Non-Binary Environmental Archive Data (NEAD) format


snow-depth-mapping

maintainer: Mauro Marty

title_for_slug: snow-depth-mapping

en: aerial-imagery image-matching avalanche dsm snow-depth snow-water-equivalent snow-hydrology

en: Snow depth map 20120320

media_type: image/tiff

en: Snow depth map generated from ADS 80 imagery (CIR). GSD of imagery = 0.25 m

format: TIFF

mimetype: image/tiff

en: Snow depth map 20140417

en: Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.18 m

en: Snow depth map 20160126

en:
Snow depth map generated from ADS 100 imagery (CIR). GSD of imagery = 0.16 m
Because of very diffuse light conditions at time of image acquisition the quality of the resulting snow depth values are in some regions quite poor.

en: Snow depth map 20150415

en: Snow depth map 20160309

en: Snow depth map 20130415

en: Snow depth map 20100416

en: Snow depth map 20160420

en:
The available datasets are snow depth maps with a spatial resolution of 2m generated from image matching of ADS 80/100 data. Image acquisition took place at peak of winter (time when the thickest snowpack is expected). The snow depth maps are the difference of a summer DSM from the winter DSM of the corresponding date . The summer DSM used is a product of image matching of ADS 80 data from summer 2013. In the available products buildings, vegetation and outliers were masked (set to NoData).
For the elimination of buildings the TLM layer (swisstopo) was used, because this layer might not represent exactly the
state of infrastructure at time of image acquisition, it is possible that mainly in dense settlement some buildings were not successfully masked. For the relevant area above treeline the masking of buildings showed good results. Vegetation got masked for a height above ground > 1m and was detected in a combination of summer and winter data sets. As Outliers were considered unrealistic snow depths caused by a failure of the image matching algorithm. Snow depths > 15m and smaller than < -15m were classified as outliers. Negative snow depth were kept, because of an uncertainty in image orientation accuracy. It is expected that in regions with negative snow depth also positive snow depth are underestimated by the same amount, which means that an estimation of snow volume should be carried out summing up the absolute values of snow depth (also the negative ones). For volume estimation in small regions the user has to take into account, that orientation accuracy of the images is roughly around 1-2 GSD (30cm), which propagates directly to the snow depth product. Areas which are not covered by snow got assigned a value of 0 as snow depth.

The work is published in:

Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C., (2015). Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9 (1), 229-243. doi: 10.5194/tc-9-229-2015

aerial-imagery

display_name: aerial-imagery

avalanche

display_name: avalanche

dsm

display_name: dsm

image-matching

display_name: image-matching

snow-depth

display_name: snow-depth

snow-hydrology

display_name: snow-hydrology

snow-water-equivalent

display_name: snow-water-equivalent


maintainer: Yohann Chauvier

en: grain-size soil phylogenetic-diversity functional-diversity ecological-indicator-values taxonomic-diversity climate

en: Data access

en:
This dataset comprises a large array of ecological data for the European Alps:

  (1) Current soil and climate predictors at various resolutions.
  (2) GBIF observations of the European Alps Flora (~4,000 species).
  (3) Species habitat suitability maps (1,109 species; based on species observations filtered at 40x40-km)
  at various resolutions used in the study to generate (4); except 'expert'...
  (4) Expert, Taxonomic, phylogenetic and functional diversity of the study region at various resolutions
  (from 100-m to 40-km --> 100-m aggregated & mean to km + non-aggregated/predicted) for CLIM,
  SOIL and CLIM-SOIL models.
  (5) Ecological and altitudinal preferences of the European Alps Flora.
  (6) Data outputs of the related published article.
  (7) All scripts used for analyses.
  (8) Additional files used for analyses.
  (9) Improved set of species habitat suitability maps (~2,600 species; based on species observations
  filtered at 1x1-km) and related taxonomic diversity at 100-m resolution (aggregated to km +
  non-aggregated/predicted) for CLIM, SOIL and CLIM-SOIL models ---> not incorporated in the study.

climate

display_name: climate

ecological-indicator-values

display_name: ecological-indicator-values

functional-diversity

display_name: functional-diversity

grain-size

display_name: grain-size

phylogenetic-diversity

display_name: phylogenetic-diversity

soil

display_name: soil

taxonomic-diversity

display_name: taxonomic-diversity

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity


data-analysis-toolkits

title_for_slug: data-analysis-toolkits

en: error-propagation bayesian-inference uncertainty data-analysis statistics hypothesis-testing

en: toolkit 6: averaging in nonlinear functions

en: The average of a nonlinear function will not equal the function evaluated at its average inputs (the mean of the function will differ from from the function of the mean). This toolkit shows how to estimate that averaging bias.

en: Toolkit 7: hypothesis testing, significance, and power

en: An overview of basic concepts -- and common pitfalls -- in statistical hypothesis testing, statistical significance, and power analysis

en: Toolkit 8: Hodges-Lehmann estimators

en: A quick introduction to Hodges-Lehmann estimators (nonparametric measures of effect size)

en: Toolkit 9: Experimentwise error rates and statistical fishing expeditions

en: Statistical fishing expeditions, and how to avoid being misled by them

en: Toolkit 10: linear regression

en: An overview of the math, logic, and pitfalls of ordinary least-squares linear regression

en: Toolkit 4: confidence intervals

en: Toolkit 11: serial correlation

en: Tools for detecting and correcting for serial correlation in analyses of time series

en: Toolkit 5: uncertainty analysis and error propagation

en: Gaussian error propagation, monte carlo methods, and first-order, second-moment error propagation

en: Toolkit 2: quantifying data distributions using descriptive statistics

en: Toolkit 3: tools for transforming data

en: The ladder of powers and a few other cool transformations

en: Toolkit 1: graphically displaying data distributions

en: Toolkit 12: weighted averages and their uncertainties

en: There are two different ways to calculate the uncertainty of a weighted average. Software packages often don't tell you which one they are reporting, and the resulting errors can be huge.

en:
These are condensed notes covering selected key points in data analysis and statistics. They were developed by James Kirchner for the course "Analysis of Environmental Data" at Berkeley in the 1990's and 2000's. They are not intended to be comprehensive, and thus are not a substitute for a good textbook or a good education!

License: These notes are released by James Kirchner under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.

bayesian-inference

display_name: bayesian-inference

data-analysis

display_name: data-analysis

error-propagation

display_name: error-propagation

hypothesis-testing

display_name: hypothesis-testing

statistics

display_name: statistics

uncertainty

display_name: uncertainty

en: Data analysis toolkits


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

en: Data access

en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2020)

In October 2020 we chose 16 sites from the 2020 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. All sites were located on the continental shelf (26–170 m depth), except one on the upper slope with a depth of 1045 m. To perform eDNA sampling, we collected water samples at 15 sites (Figure 1a). At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http:
//metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).

Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

fish-composition

display_name: fish-composition

teleo

display_name: teleo

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Environmental DNA Marine France Evhoe 2020


maintainer: Axel Volkwein

en: rockfall-experiments experiment field-data impact-testing rockfall natural-hazard mass-movements field-test field-tests experiments

en: Video analysis

en: The zip contains five Excel-files that in turn contain the results of the performed video analyses. The sheet "Daten" contains the pixels of different positions on the blocks that were tracked by the software "Kinovea". The sheet "Auswertung" determines the block kinetics based on the pixel data over time.

en: Acceleration measurements

en: The zip file contains five excel files, one for each test conducted. The first sheet contains the raw data and a data set that went through a low-pass filter. The sheet "Allgemein" contains calibration factors for the sensors and time details of a test. The sheets "DiaDaten" and "DiaDatenGefiltert" show the measurements over time. The block and slab kinetics are determined in the sheets "ZeitintegrationBlock" and "ZeitintegrationPlatte". The sheet "VergleichBeschleunigungen" shows the influence of the low-pass-filter and a running average filter on the block accelerations.

en: Raw data (high speed videos, acceleration measurements, laboratory tests)

en:
This file contains

* the high speed videos showing the concrete blocks impacting the gallery roof.
* the raw data of the acceleration measurements
* the data of Tiefbauamt Graubünden containg the tension tests of gallery reinforcment, ME-testing the cushion layer and the tests on concrete samples.

en: Five full-scale field tests were conducted with concrete blocks weighting between 800 and 3200 kg being dropped onto the roof of a gallery structure made from reinforced concrete. The impacts were recorded using high-speed video and acceleration measurements at the falling blocks. The dataset contains the raw data as well as the analyses of the block trajectories, i.e. kinetics and dynamics. Setup of the measurements and the analyses conducted are published in Volkwein, A. "Durchführung und Auswertung von Steinschlagversuchen auf eine Stahlbetongalerie", WSL-Berichte, Heft 68, 2018.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

impact-testing

display_name: impact-testing

mass-movements

display_name: mass-movements

natural-hazard

display_name: natural-hazard

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

en: Rockfall gallery testing Parde 2016