maintainer: Marco Moretti

en: community-indices wild-bee hymenoptera functional-diversity resource-availability urbanization elevation-gradient biodiversity predictive-modelling switzerland protected-areas beta-diversity anthophila climate

en: Deprecated-Predictors

en:
The compress file includes the rster files of the predictors used in the analyses, including the climate, resource availability, land-use and beekeeping intensity metrics.

The raster on the climate contains the PCA axes on the CHELSA variables.
The raster on resource availability contains the PCA axes on plant communities
The raster on land-use contains the land-use composition at 2500 m.
The raster on beekeeping intensity contains thedensity of hives within 2500 m

en: Spatial environmental predictors and responses

en:
The .zip file contains the rasters of the environmental predictors and the predicted responses:
-  **Environmental predictors.**:
  -  The raster on the climate contains the PCA axes on the CHELSA variables.
  -  The raster on resource availability contains the PCA axes on plant communities
  -  The raster on land-use contains the land-use composition at 2500 m.
  -  The raster on beekeeping intensity contains thedensity of hives within 2500 m
-  **Responses**:
- The predicted responses (alpha and beta taxonomic and functional metrics and the traits) without masking the waterbodies, used in the analyses (Diversity_stack_revised_Selected_descriptors.tif). It contains a stack of 20 responses in this order: "belowgound", "cleptoparasite","FDis", "feeding_specialization", "FEve", "FRic", "InvSimpson", "ITD","LCBD_fun" ,"LCBD_taxo","phenoduration", "phenostart", "Rao", "Richness", "Shannon", "Simpson","solitary", "TED", "tong_length", "TOP". "FEve", "FRic", "InvSimpson","Rao", "Simpson" were not included in the linked paper.
- The predicted responses (alpha and beta taxonomic and functional metrics and the traits) masking the waterbodies (masked.stack.all.diversity.tiff). It includes a stack of 15 responses (excludes "FEve", "FRic", "InvSimpson","Rao", "Simpson").

en: Wild bee trait data

en: Text file containing the scores of the 8 used traits. The data originates from the European trait database (compiler: Stuart Roberts; pollinator loss module of the EU- FP6 ALARM project).

en: Protected areas

en: Protected areas considered, divided in three groups and rasters: protected areas sensu stricto, protected areas sensu lato and all protected areas

en: Elevation and waterbodies

en: Zip file containing two rasters: the digital elevation model of Switzerland and the waterbodies of Switzerland.

en: Variable importance, model evaluation, partial dependence plots

en: The compress file containes a set of txt files with the variable importance, the model evaluation metrics and the partial dependence plots of each of the responses used (alpha and beta taxonomic and functional diversity metrics; community weighted means of 8 functional traits)

en: Taxonomic and functional metrics in the community plots

en:
Response data used for the modeling.
Lat: latitude community plot
Lon: longitude community plot
Richness: species richness
Shannon: Shannon diversity index
FDis: functional dispersion
TOP: Trait Onion Peeling (functional richness)
TED: Trait Even Distribution (functional evenness)
LCBD_taxo: local community contributions to taxonomic beta diversity
LCBD_fun: local community contributions to functional beta diversity
ITD: community weighted means inter-tegula distance
feeding_specialization: community weighted means feeding specialization
tong_length: community weighted means tongue length
phenostart: community weighted means start of the phenology
phenoduration: community weighted means duration of the phenoloy
cleptoparasite: community weighted means cleptoparasites
belowgound: community weighted means proportion belowground
solitary: community weighted means proportion solitary

en:
Raw data supporting the paper "Countrywide wild bee taxonomic and functional diversity reveal a spatial mismatch between alpha and beta-diversity facets across multiple ecological gradients". It contains taxonomic and functional metrics in 3343 community-plots distributed across Switzerland. The calculated metrics are:
- Alpha taxonomic community metrics: species richness and Shannon diversity
- Alpha functional community metrics: Functional richness (using the Trait Onion Peeling index, TOP), functional eveness (using the Trait Even Distribution index, TED) and the functional dispersion.
- Community weighted means of 8 functional traits
- The local community contributions on the functional and taxonomic beta diversity (LCBD).

The dataset also includes the following:
- The used predictors to model the spatial distribution of the community metrics (climate PCA, vegetation PCA, land-use metrics, beekeeping intensity).
-The three types of protected areas, defined according to the protective measures.
- The model evaluation, variable importance and partial dependece data.

anthophila

display_name: anthophila

beta-diversity

display_name: beta-diversity

biodiversity

display_name: biodiversity

climate

display_name: climate

community-indices

display_name: community-indices

elevation-gradient

display_name: elevation-gradient

functional-diversity

display_name: functional-diversity

hymenoptera

display_name: hymenoptera

predictive-modelling

display_name: predictive-modelling

protected-areas

display_name: protected-areas

resource-availability

display_name: resource-availability

switzerland

display_name: switzerland

urbanization

display_name: urbanization

wild-bee

display_name: wild-bee

en: Data on wild bee taxonomic and functional diversity in Switzerland


maintainer: EnviDat Support

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

state: active

type: dataset

en: Canopy height maps

media_type: application/zip

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

format: ZIP

mimetype: application/zip

en: Readme

media_type: text/plain

format: TXT

mimetype: text/plain

en: Snow depth maps

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

en: Terrain elevation maps

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

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

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

airborne-laser-scanning

display_name: airborne-laser-scanning

canopy-height

display_name: canopy-height

forest-structure

display_name: forest-structure

snow-depth

display_name: snow-depth

snow-distribution

display_name: snow-distribution

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

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

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

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


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

en: Data plot of the forest station (NOB)

media_type: application/pdf

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

format: PDF

mimetype: application/pdf

en: Site photo of the field station (NOF)

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

format: SERVICE

mimetype: image/jpeg

en: Site photo of the forest station (NOB)

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

en: Site aerial photo (Novaggio)

en: Site aerial photo from both Novaggio stations. Source: Google. 2016. Site aerial photo from both Novaggio stations. Retrieved November 15, 2016, from https://www.google.ch/maps

en: Field station data (NOF)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Data plot of the field station (NOF)

en: Forest station data (NOB)

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 Novaggio in Switzerland where one station is located within a natural deciduous forest stand (NOB) with Turkey oak (_Quercus cerris_; 70 yrs), sweet chestnut (_Castanea sativa_; 90 yrs) and silver birch (_Betula pendula_; 70 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, NOF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Novaggio 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

en: Novaggio, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards


en: soil mass-balance sustainability beech nutrient

format: XLS

en: With this study, our aim was to estimate the nutrient fluxes relevant for assessing nutrient sustainability as accurately as possible and to calculate nutrient balances for alternative forest management scenarios. Furthermore, we tested whether mapping units from existing geologic maps can serve as a basis for forest practitioners to estimate nutrient sustainability or whether more detailed data is needed. Positive fluxes include deposition and weathering, while negative fluxes include losses due to leaching and nutrient removal through timber harvesting in the balance. Weathering and leachate losses were modeled with a geochemical model. The SwissStandSim model was used to simulate the biomass growth under different harvesting and silvicultural strategies, allowing sustainability to be assessed for each nutrient at a given intensity of use. This assessment was made per rotation period of 100 years based on two criteria: i) nutrient supply; and ii) total stocking volume.

beech

display_name: beech

mass-balance

display_name: mass-balance

nutrient

display_name: nutrient

soil

display_name: soil

sustainability

display_name: sustainability

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: Nutrient sustainability in beech forests


maintainer: Axel Volkwein

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

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: 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: 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: 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


maintainer: Vanessa Burg

en: manure switzerland review bioenergy biogas

en: Biogas from animal manure in Switzerland: energy potential, technology development and resource mobilization

en: Aim of this white paper is to provide decision-makers, administrations and stakeholders with the most current research findings in order to promote the optimal use of bioenergy from manure in the Swiss energy transition. For this purpose, the results of the Swiss competence center for bioenergy research - SCCER BIOSWEET - are summarized and presented in a broader context. If nothing else is mentioned, the results refer to Switzerland and in case of the feedstock to the domestic biomass potentials.

bioenergy

display_name: bioenergy

biogas

display_name: biogas

manure

display_name: manure

review

display_name: review

switzerland

display_name: switzerland


en: branchwood stemwood growing-stock tree-volume allometry section-wise-diameter

en: manuscript submitted for publication.

en: definitions of data in columns contained in the dataset Stem&Branchchwood_2024-02-29.txt

en: Revised version of the initial submission StemBranchwood_Didionetal_initialsubmission.pdf after review.

en: dataset with section-wise stem diameter and branchwood volume measurements. For column definitions see Column_definitions.pdf.

en: additional background information on this work

en: Updated dataset of outdated_Stem&Branchchwood_2024-02-29.txt, including corrections to the assignment of tree species to NFI main species and location information for two additional sites.

en:
The data presented here were prepared for publication in form of a data paper. The dataset presents an update of the information in Didion M, Herold A, Vulovic Z, Nitzsche J, Stillhard J (2022) Datasets for deriving functions for the stem- and branchwood volume in the Swiss National Forest Inventory. EnviDat. doi:https://www.doi.org/10.16904/envidat.358. The new dataset is based on an alternative, more accurate and comprehensive dataset, that was identified as the source of the dataset in Didion et al. 2022. It includes additional data, including newly digitized information.
The dataset includes section-wise stem measurements on 40’349 felled individual trees and empirically derived coarse (diameter >= 7 cm) and fine branch volume of 27’297 and 18’980, respectively, individual trees. The data were collected between 1888 and 1974 across Switzerland covering a large topographic gradient and a diverse species range. The dataset has undergone quality controls and due to its origin from 768 plots of the Experimental Forest Management project long-term consistency is assured.

allometry

display_name: allometry

branchwood

display_name: branchwood

growing-stock

display_name: growing-stock

section-wise-diameter

display_name: section-wise-diameter

stemwood

display_name: stemwood

tree-volume

display_name: tree-volume

en: A dataset of 40000 trees with section-wise measured stem diameter and length and volume of branches from across Switzerland


digitizing-historical-plague

maintainer: Christian Ginzler

title_for_slug: digitizing-historical-plague

en: black-death historical-plague palaeo-epidemiology plague-mapping plague-outbreaks yersinia-pestis plague-inventory bubonic-plague

en: We present newly digitized data on 6,929 plague outbreaks that occurred between 1347 and 1900 AD across Europe. The data base on an inventory initially published 1976. For georeferencing the information of Tele Atlas 2009 was used. The coordinates are in the reference systems ETRS89 and WGS84.

black-death

display_name: black-death

bubonic-plague

display_name: bubonic-plague

historical-plague

display_name: historical-plague

palaeo-epidemiology

display_name: palaeo-epidemiology

plague-inventory

display_name: plague-inventory

plague-mapping

display_name: plague-mapping

plague-outbreaks

display_name: plague-outbreaks

yersinia-pestis

display_name: yersinia-pestis

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: Digitizing historical plague


envidat-supports-open-science

maintainer: Ionut Iosifescu Enescu

title_for_slug: envidat-supports-open-science

en: wsl open-science research-data-management juypter-notebooks envidat

en: Article as PDF

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.

License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

envidat

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl

en: EnviDat Supports Open Science


en: traits ecology reef-fish biodiversity dispersal

en: Input for spatial congruence test overlap between proportions of low and high dispersal and observed low- and high- dispersal-related traits in assemblages (30-50% threshold). see Table 2.

en: Donati et al. main script

en:
Main script used in : Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages"
accepted in Ecography, August 2019

en: Tropical reef fish trait data

en:
Species trait (i.e. adult body size, home range mobility behaviour, circadian activity and schooling) data gathered from the General Approach to Species Abundance Relationships (GASPAR) database (Kulbicki et al. 2013, Parravicini et al. 2013).

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

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

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

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

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

en: Main text figures

en: R Script used for figures in main text in: Donati et al. 2019: "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019.

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

en:
Grid cells of 5 × 5°, corresponding to circa 555 × 555 km at the Equator (see Parravicini et al. 2013, Leprieur et al. 2016)

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

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

en: Dispersal parameter value d per simulation starting with a minimum dispersal value, where each species is able to colonise each adjacent cell, and ending with the value of d for which all the extant habitats, including the most remote Pacific islands, have been colonised (d ∈ [1.75°: 5.45°]).

en: Functions used in R scripts in: Donati et al. 2019 "A process-based-model supports an association between  # dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019

en: Functions for Figures illustrated in Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted in Ecography, August 2019.

en: Global species distribution of tropical reef fish species

en: Each species corresponds to a "Gaspar_code" gathered from the General Approach to Species Abundance Relationships (GASPAR) database (Kulbicki et al. 2013, Parravicini et al. 2013) and is linked to a specific Fishned ID corresponding to a specific Latitude and Longitude.

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

en: Geographic distribution data (species richness and proportions of high/low dispersal-related traits) on predominantly low dispersing and high dispersing species expected based on the simulations, and those where low- and high- dispersal related traits values are observed for the five investigated traits.

en: Supplementary material Appendix 1 Figures illustrated in Donati et al. 2019 "A process-based-model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages". accepted in Ecography, August 2019

en: Simulated rates of speciation and extinction under a range of dispersal parameters. Net diversification rates are calculated from the difference between speciation and extinction rates. This data allows the creation of Figure A4 in Supporting information, Appendix 1.

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

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

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

en:
This dataset contains all data and R codes (R Development Core Team, https://www.R-project.org) used in the following publication: Donati GFA, Parravicini V, Leprieur F, Hagen O, Gaboriau T, Heine C, Kulbicki M, Rolland J, Salamin N, Albouy C, Pellissier L. "A process-based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages" accepted by Ecography in August 2019. When using this data and R scripts the above publication should be cited.

The interaction of habitat dynamics with species dispersal abilities could generate gradients
in species diversity and prevalence of life-history and ecological traits, when the latter are associated with dispersal potential. In this dataset, we use a spatial mechanistic model of speciation, extinction and dispersal, constrained by a dispersal parameter. This model allows to simulate the interplay between reef habitat dynamics over the past 140 million years and dispersal, shaping lineage diversification history and global assemblage composition of over 6000 tropical reef fish species. Global trait distribution data of tropical reef fish are used to evaluate the congruence between simulations and observations.

biodiversity

display_name: biodiversity

dispersal

display_name: dispersal

ecology

display_name: ecology

reef-fish

display_name: reef-fish

traits

display_name: traits

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


maintainer: Michael Lehning

en: winter-tourism snow-conservation snow-farming terrestrial-laser-scanning snow snowpack

en: HS Martell autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: HS Fluela autumn 2015

en:
Snow depth/ height of snow heap in autumn 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903
Nodata: -9999

en: Fluela .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Flüela heap

en: Martell .sno

en: Input snow profile (.sno file) used for SNOWPACK simulations of the Martell heap

en: HS Fluela spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrrestrial laserscanning
cell size: 10 cm
spatial reference: CH1903

en: Martell .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Hintermartell.

en: HS Martell spring 2015

en:
Snow depth/ height of snow heap in spring 2015 obtained by terrestrial laserscanning
cell size: 10 cm
spatial reference: European Datum 1950 UTM
Nodata: -9999

en: Fluela .smet

en: Meteodata used as input for SNOWAPCK simulations, orginating from Station Windtunnel and DAV.

en:
Two data sets obtained for snow farming projects (Fluela, Davos, CH and Martell, IT) in 2015.

The data set contains for each site:

* 10 cm GIS raster of snow depth calculated from terrestrial laserscanning surveys (TLS) in the end of winter season (April/May)

* 10 cm GIS raster of snow depth calculated from TLS in the end of summer season (October)

Input files for SNOWPACK model:

* .sno: snow profile at the end of winter

* .smet: meteorological data measured by weather stations in the area

For more details see Grünewald, T., Lehning, M., and Wolfsperger, F.: Snow farming: Conserving snow over the summer season, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-93, in review, 2017.

snow

display_name: snow

snow-conservation

display_name: snow-conservation

snow-farming

display_name: snow-farming

snowpack

display_name: snowpack

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

winter-tourism

display_name: winter-tourism

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: Snowfarming data set Davos and Martell 2015


swiss-fluxnet-site-lageren

title_for_slug: swiss-fluxnet-site-lageren

en: swiss-forest-lab flux meteorological-measurements forest eddy-covariance greenhouse-gas swiss-fluxnet

en: Site description

en: Data access

en: The flux and meteo data of the Swiss FluxNet site Lägeren are openly available from the European Fluxes Database Cluster.

en: Fluxnet2015 dataset

en: The flux and meteo data of the Swiss FluxNet site Lägeren are also part of the Fluxnet2015 dataset.

en:
The Swiss FluxNet Site Lägeren is a managed mixed deciduous mountain forest located on the steep Lägeren mountain (NW of Zurich, Swiss Plateau). The forest is highly diverse, dominated by beech, but also including ash, maple, spruce and fir trees. Eddy covariance flux measurements were started in April 2004. The site was part of the international CarboEurope IP network and the National Air Pollution Monitoring Network (NABEL). In addition to Swiss FluxNet, the site is part of the Long-term Forest Ecosystem Research (LWF) of WSL and the biological drought and growth indicator network (TreeNet) of WSL.

Measurements

- Ecosystem flux measurements of CO2, H2O vapour are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.
- Sub-canopy eddy fluxes (CO2, H2O), soil respiration campaigns
- Continuous CO2 profile measurements.
- Auxiliary micrometeorology and soil climate measurements.

Data availability

All data are available from the European Fluxes Database Cluster, but are also part of Fluxnet2015 dataset.

Data policy

ICOS data license:
[https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)

Detailed site info:
[https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae//](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-lae-laegeren/site-info-ch-lae/)

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab

en: Swiss FluxNet Site Lägeren


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

en: Data processing documentation

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

en: Post Processed TLS's

en: Compressed dat files

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

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


en: snow-hydrology snow-depth-distribution dischma davos photogrammetry avalanches

en: Snowdepth maps

format: GeoTIFF

en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.

Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height > 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.html#links). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.

An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.

The work is published in:

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology

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: Snow depth mapping by airplane photogrammetry (2017 -  ongoing)


en: sankt-annafirn findelengletscher alps orthoimage dem glacier griesgletscher orthophoto drone dsm uav gletscher

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of April 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 30th of August 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 19th of April 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 3rd of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 15th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Sankt Annafirn on the 28th of September 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 15th of September 2015.

en: This folder contains all UAV flights paths that we created for the Sankt Annafirn, the Findelengletscher and Griesgletscher. They have been created with the software eMotion2, that was developped for the eBee platform from Sensefly.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 22th of September 2016.

en: This .pdf contains an orthoimage for each dataset as well as a Table which displays the number of flights made, image acquired, number of GCP set and the total area covered.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 13th of September 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 21th of July 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 15th of August 2015.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 09th of April 2015.

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Findelengletscher on the 2nd of July 2016.

en:
This .zip folder contains:

 - An orthoimage (oi) of 0.1m resolution

- A Digital Surface Model (dsm) of 0.1m resolution

- The Agisoft Photoscan automatic processing report

for the UAV field campaign conducted on the Griesgletscher on the 26th of September 2015.

en:
 UAV-derived DSMs and orthoimages

Unmanned Aerial Vehicle (UAV) surveys were conducted between 2015 and 2016 on the Sankt Annafirn, Findelen- and Griesgletscher, situated in the Swiss Alps. Three surveys at the Sankt Annafirn allowed for a full glacier coverage, four surveys at Griesgletscher allowed an almost full glacier coverage and seven surveys at Findelengletscher allowed for a partial coverage of the glacier tongue (see individual datasets for exact extent). For each survey, a high resolution orthoimage and a Digital Surface Model (DSM) was created.

 UAV surveys:

Prior flight, Ground Control Points (GCPs) were deployed on the glacier surface and measured with a differential GPS (Trimble R7 or Leica GPS 1200). They allowed precise georeferencing of the UAV-derived datasets. UAV flight plans were planned with the software *eMotion 2* and a SenseFly eBee was used as surveying platform. The images were then processed with the software Agisoft Photoscan Pro 1.1.6 .

The location and dates of each survey can be found in the table together with the number of flights performed (Nflights), the number of acquired images (Nimages), the number of GCPs set (NGCPs) and the surveyed area.

A folder for each dataset is available (see folder name in table), which contains:

- An orthoimage *glacier_date_photoscan_oi_CH1903+_LV95_0.1m.tif*

- A Digital Surface Model *glacier_date_photoscan_dsm_CH1903+_LV95_0.1m.tif*

- The Agisoft Photoscan automatic processing report  *glacier_date_photoscan_report.pdf*

where:

- *glacier* is the name of the surveyed glacier

- *date* is the date of the UAV image acquisition

- *photoscan* is the name of the photogrammetric software

- *oi* or *dsm* the type of dataset

- *CH1903+_LV95* is the coordinate system and datum of the dataset

- *0.1m* is the resolution of the dataset in meter

- *.tif* is the extention of the dataset

Details about the UAV surveys, the image processing and the accuracy of the UAV-derived products can be found in this publication below.

Paper Citation:
 > _Gindraux et al. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’Imagery on Glaciers, Remote Sensing, 9, 186, 1-15, [doi: 10.3390/rs9020186](https://doi.org/10.3390/rs9020186)._

The folder UAV_flight_paths.zip contains all UAV flights performed on the Sankt Annafirn, Findelengletscher and Griesgletscher. The flights were planned with the software eMotion2 and have the .afp extention.

alps

display_name: alps

dem

display_name: dem

drone

display_name: drone

dsm

display_name: dsm

findelengletscher

display_name: findelengletscher

glacier

display_name: glacier

gletscher

display_name: gletscher

griesgletscher

display_name: griesgletscher

orthoimage

display_name: orthoimage

orthophoto

display_name: orthophoto

sankt-annafirn

display_name: sankt-annafirn

uav

display_name: uav

en: UAV-derived Digital Surface Models and orthoimages for three alpine glaciers


maintainer: Stephan Zimmermann

en: potassium magnesium fagus-orientalis-lipsky biogeochemical-cycling calcium

en: Concentrations of Ca, Mg, K, and Na in throughfall, litterflow and soil solution of a Hyrcanian forst in Northern Iran

en:
Throughfall, litterflow and soil solution were sampled during one whole year under five Oriental beech trees in a mixed Hyrcanian beech forest. The amounts of Ca2+, Mg2+, K+ and Na+ in these fluxes were calculated based on their concentrations and the sampled volumes, and subsequently compared with the respective fluxes in the rainfall and soil solution of an adjacent forest gap.
In addition six soil profiles, one close to every single tree and one in the forest gap, were analyzed for pH, CaCO3, organic matter and texture.

biogeochemical-cycling

display_name: biogeochemical-cycling

calcium

display_name: calcium

fagus-orientalis-lipsky

display_name: fagus-orientalis-lipsky

magnesium

display_name: magnesium

potassium

display_name: potassium

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: Base cation dynamics in an Oriental beech forest


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

en: Fungal amplicon sequencing

en: Fungal ASVs and taxonomic tables

en: Bacterial amplicon sequencing

en: Bacterial ASVs and taxonomic tables

en: Microbial functions and metadata

en: Extracellular enzyme activities, respiration and sites metadata

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

en: Chicken Creek 10 years


en: viscous-deformation snow-mechanics snow-failure fiber-bundle-model snow-avalanche snow sintering acoustic-emissions

en: fiber-bundle-model-for-snow-failure

en: Data underlying Figures in publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted to "Geophysical Research Letters"

en:
This dataset contains modeled and experimental results for laboratory snow failure experiments and the concurrent acoustic emissions signatures for different loading rates. For modelling the snow failure we used a fiber bundle model that includes sintering and viscous deformation.

The data underlay the figures in the publication "Modelling Snow Failure Behavior and Concurrent Acoustic Emissions Signatures with a Fiber Bundle Model" submitted for publication to "Geophysical Research Letters".

acoustic-emissions

display_name: acoustic-emissions

fiber-bundle-model

display_name: fiber-bundle-model

sintering

display_name: sintering

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-mechanics

display_name: snow-mechanics

viscous-deformation

display_name: viscous-deformation

en: Fiber Bundle Model for snow failure and concurrent Acoustic Emissions


maintainer: Giulia Francesca Azzurra Donati

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

en: Amphibian movement resistance layers and scripts for connectivity modelling - part 2

en: The zipped folder includes the script to create and analyse the networks from Circuitscape outputs. The subfolders “Boundaries”, “Layers”, and “Reference_net” contain files either called by the code or created in the process. The subfolder “Outputs_from_Circuitscape” contains the outputs from Circuitscape including node and branch cumulative currents in a network format.

en: Amphibian movement resistance layers and scripts for connectivity modeling - part 1

en: The zipped folder includes the script to aggregate the resistance layers into squared and hexagonal grids. The subfolders “Boundaries”, “Layers”, “Reference_grids”, and “Resistance_from_SDMs” contain files either called by the code or created in the process.The subfolder “Inputs_for_Circuitscape” contains the inputs to run Circuitscape, after doing some subsequent processing steps in QGIS (listed in the R script) with the files created with the script.

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

biodiversity

display_name: biodiversity

circuit-theory

display_name: circuit-theory

ecological-corridors

display_name: ecological-corridors

ecosystem-services

display_name: ecosystem-services

network-analysis

display_name: network-analysis

urban-planning

display_name: urban-planning

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


maintainer: Anita C. Risch

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

en: Correction: Data file native and non-native plant interactions in Australian grasslands

en:
taxa tab:	list and overview of all the recorded species

* family:                 family of the plant

* genus:                genus of the plant

* species:                plant species name

* origin:                indicates whether the plant is native to Australia or not (non-native)

* common name:	        common name of the plant species

* functional group:	        functional group of the plant species: forb, graminoid, fern, tree

* functional group detailed:	gives more detail about the type of graminoid and forb: legume, forb (non-leguminous),
                        grass, sedge, rush, fern, tree

* lifeform:                annual or perennial lifeform (species which can have both of these lifeforms where
                        considered as annuals)

plot tab:	list of species found in each plot and their cover (%)

* sampling.session:        provides information about the sampling time:
                        May2020 = data that was collected in May 2020
                        Nov2020 = data that was collected in November 2020

* farm.name:	            name of the farms where the sampling took place:
                        SF = farm of the Southern group
                        NF = farm of the Northern group
                        numbers 1-3 = randomly allocated to the Southern group of farms
                        numbers 4-6 = randomly allocated to the Northern group of farms

* site.type:	                KG: Kangaroo grass dominated site
                        ALG: ALG+KG site (Kangarooo grass and African lovegrass co-dominated site)

* plot.no:                plot number: 9-12

* scientific.name:	        scientific name of the plant species found in a certain plot

* functional group:	        indicates whether the species found is a tree, forb, graminoid or fern

* functional group detailed:	indicates whether the species found is a tree, legume, forb (non-leguminous),
                        grass, sedge, rush, fern

* lifeform:                specifies the lifeform of the species: annual or perennial lifeform
                        (species which can have both of these lifeforms where considered as annuals)

corrections tab:	Detailed description of corrections made in plot.data tab

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

Paper Citation:

_Schlierenzauer, C., Risch, A.C., Schütz, M., Firn, J. 2021. Non-native Eragrostis curvula reduces plant species diversity in pastures of South-eastern Australia even when native Themeda triandra remains co-dominant. Plants 10, 596._

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

Study area
The study was conducted in the lowland grassy woodlands of the Bega Valley Region, which is located in the south-east corner of New South Wales, Australia. Embedded between the Pacific Ocean and the Australian Alps, the lowland grassy woodlands are mostly located on granitic substrates and reach elevations of roughly 500 m above sea level. Typically, these grassy woodlands receive less precipitation (mean annual precipitation between 700-1100 mm) compared to the more elevated areas that surround them (NSW Government - Office of Environment and Heritage 2017).
The vegetation is dominated by an open tree canopy layer consisting of Eucalyptus tereticornis Sm, Angophora floribunda Sm. (Sweet) and a range of other eucalypt species. Sometimes shrub or small trees are also present, whereas grasses and forbs form the ground-cover. In areas without intensive agricultural history, this layer is dominated by perennial, tussock grasses such as Themeda triandra Forssk, Microlaena stipoides R.Br (Weeping Grass), Eragrostis leptostachya Steud. (Paddock Lovegrass) and Echinopogon ovatus P.Beauv (Forest Hedgehog Grass). The remaining inter-tussock spaces are occupied by a diversity of growth-restricted grasses and herbaceous forbs (NSW - Department of Planing, Industries and Environment 2019; NSW Government - Office of Environment and Heritage 2017).
Clearing, pasture sowing, fertilizer application and livestock grazing resulted in a dramatic decrease in the extent of these natural woodlands, with less than five percent within conservation reserves and overall, with only about 20% of their original extent in New South Wales still existing (Tozer et al. 2010). The remaining areas outside of reserves are threatened by altered fire frequencies, habitat clearing, livestock grazing and especially by non-native plant invasion, particularly Eragrostis curvula (Schrad.) Nees. For this reason, the grassy woodlands are listed as an endangered ecological community in the NSW state legislation. Additionally, they are considered as critically endangered by the Commonwealth of Australia (Threatened Species Scientific Committee (TSSC) 2013).

Experimental design and sampling
The study was conducted on six farms and in each of them two sites were chosen, representing a paired design. One of the sites at each farm is dominated by native Themeda triandra, the other one co-dominated by non-native Eragrostis curvula and Themeda triandra. All farms are within a radius of approximately 10 km from the town Candelo. Three of the farms are located North (36°40’ to 36°42’ S and 149°38’ to 149°42’ E) and three of them are located South (36°51’ to 36°49’ S and 149°38’ to 149°42’ E) of Candelo.
Non-native herbivores (mainly cattle, sheep and rabbits) and native herbivorous marsupials (mainly kangaroos, wallabies and wombats) are present in the area of these sites. On each site, data was collected within four plots (each 1 x 1 m) in May and November 2020. All plant species found within a plot were recorded and their relative abundance was estimated.

References
NSW - Department of Planing, Industries and Environment. 2019. “Lowland Grassy Woodland in the South East Corner Bioregion - Endangered Ecological Community Listing.” https://www.environment.nsw.gov.au/topics/animals-and-plants/threatened-species/nsw-threatened-species-scientific-committee/determinations/final-determinations/2004-2007/lowland-grassy-woodland-south-east-corner-bioregion-endangered-ecological-community-l (February 18, 2021).
NSW Government - Office of Environment and Heritage. 2017. “Lowland Grassy Woodland in the South East Corner Bioregion - Profile.” https://www.environment.nsw.gov.au/threatenedSpeciesApp/profile.aspx?id=20070 (January 31, 2021).
Threatened Species Scientific Committee (TSSC). 2013. Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) Conservation Advice for Lowland Grassy Woodland in the South East Corner Bioregion. http://www.environment.gov.au/biodiversity/threatened/communities/pubs/82-conservation-advice.pdf.
Tozer, Mark et al. 2010. “Native Vegetation of Southeast NSW: A Revised Classification and Map for the Coast and Eastern Tablelands.” Cunninghamia : a journal of plant ecology for eastern Australia 11(3): 359–406.

grassland

display_name: grassland

herbivory

display_name: herbivory

native-plant

display_name: native-plant

non-native-plant

display_name: non-native-plant

weed-management

display_name: weed-management

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


en: photobiont bryophyte lichen climate-change functional-taxonomic-groups endemic-species biodiversity disturbance liverwort endemic elevational-gradient functional-taxonomic-group madeira-island lichen-growth-form climate-change-impact bryophyte-life-strategy lichen-growthform moss

en: MadCrypto – Bryophyte and macrolichen diversity in laurel forests of Madeira

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science.

en:
This dataset includes species lists of bryophytes and macrolichens (presence/absence) sampled on the forest floor and on trees in disturbed and undisturbed plots along elevation gradients in the laurel forests of Madeira island. It also contains species specific information (bryophytes: red list status, endemic status, taxonomic group, life strategy; macrolichens: photobiont type, growth form) as well as plot information (Plot_ID, sampling date, coordinates, elevation a.s.l. (m), disturbance type, sampled host tree species).

The dataset was used for the paper
Boch S, Martins A, Ruas S, Fontinha S, Carvalho P, Reis F, Bergamini A, Sim-Sim M (2019) Bryophyte and macrolichen diversity show contrasting elevation relationships and are negatively affected by disturbances in laurel forests of Madeira island. Journal of Vegetation Science 30: 1122–1133.

The excel file contains 5 sheets:
1) Plot information
2) Bryophyte data with species specific information, separated per substrate
3) Macrolichen data with species specific information, separated per substrate
4) Bryophyte data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 2 and 4 might therefore differ slightly.
5) Macrolichen data with species specific information (plot level data). Species lists of the two substrates were merged; if one substrate in a plot hosted a species identified only to genus level (genus spec.) but the second investigated substrate hosted an identified species of the same genus, we removed the genus spec. entry in the particular plot. The species list of sheet 3 and 5 might therefore differ slightly.

bryophyte

display_name: bryophyte

bryophyte-life-strategy

display_name: bryophyte-life-strategy

climate-change

display_name: climate-change

climate-change-impact

display_name: climate-change-impact

disturbance

display_name: disturbance

elevational-gradient

display_name: elevational-gradient

endemic

display_name: endemic

endemic-species

display_name: endemic-species

functional-taxonomic-group

display_name: functional-taxonomic-group

functional-taxonomic-groups

display_name: functional-taxonomic-groups

lichen

display_name: lichen

lichen-growth-form

display_name: lichen-growth-form

lichen-growthform

display_name: lichen-growthform

liverwort

display_name: liverwort

madeira-island

display_name: madeira-island

moss

display_name: moss

photobiont

display_name: photobiont


maintainer: Leo Gallus Bont

en: qgis geoprocessing forest seilaplan openstreetmap accessible-forest

en: Juypter Notebook for Data Preparation

en: Digitised sample perimeter

en: Power lines vector data (close to the area of the sample forest range)

en: Juypter Notebook for Data Preparation (online)

en: Preview

media_type: image/png

format: PNG

mimetype: image/png

en: DEM (for the area of the sample forest range)

media_type: image/tiff

format: TIFF

mimetype: image/tiff

en: Forest vector data (for sample forest range)

en: Railways vector data (close to the sample forest range)

en:
This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).
The purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.
The vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019.

Additional notes for vector data:
Please note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API - https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any perimeter or area can be digitised freely using the QGIS editing toolbar.

The DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:

- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)
- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif

This methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.

Additional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.

This sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.

accessible-forest

display_name: accessible-forest

forest

display_name: forest

geoprocessing

display_name: geoprocessing

openstreetmap

display_name: openstreetmap

qgis

display_name: qgis

seilaplan

display_name: seilaplan

en: Sample Geodata and Software for Demonstrating Geospatial Preprocessing for Forest Accessibility and Wood Harvesting at FOSS4G2019


en: snow specific-surface-area intercomparison microct icecube

en: TARTES simulations

en: Jupyter notebook with TARTES simulations.

en: The file contains all data for the plot in figure 1 of the co-located density and SSA measurement at Summit, Greenland in May 2015, conducted by Schneebeli, Proksch, Schmid.

en: SMP measurement files for snow types A, B, C and D.

en: Statistics of samples

en: artificial_snow_data set

en: The file contains all micro-CT and IC measurements of the artificial snow data set. The data set was originally produced to investigate the influence of black carbon on SSA measurements.

en: Influence of black carbon on the measurement of the specific surface of snow with the near infrared method - Philipp Baumann

en: These experiments investigate different possible errors by measuring the specific surface area (SSA) of snow with the near infrared method. The influence of black carbon on this measurement was disproved, the theory was therefore validated. It shows that sunlight has no influence on the measurement with the IceCube. Wind drift snow as thin layer on the sample can increase the measured value of the specific surface by a few percent. This could be part of the error, observed in former measurements at SLF. As reference for the measured SSA values with the near infrared method, computer tomography was used to verify the SSA values.

en: IceCube and MicroCT data

en: The file contains all micro-CT and IC measurements for snow types A, B, C, D and E used in our study. All samples were processed (and stored) in a cold laboratory at -15°C.

en: Grain survey of snow particles

en: The file contains all measurements of the artificial particles for snow types A, B, C, D and E, including the artificial particle mass in the Petri dish.

en: The specific surface area (SSA) of different snow types were measured with the IceCube instrument and the Scanco Medical microCT 40. In addition, the snow particles created during the preparation of IceCube samples were counted. The difference in SSA between these instruments is explained by the formation of the surface particles. A numerical simulation using TARTES simulation support the observations.

icecube

display_name: icecube

intercomparison

display_name: intercomparison

microct

display_name: microct

snow

display_name: snow

specific-surface-area

display_name: specific-surface-area

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.


maintainer: Matthias Haeni

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

en: Data plot of the field station (BTF)

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

en: Data plot of the forest station (BTB)

en: Site photo of the forest station (BTB)

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

en: Site photo of the field station (BTF)

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

en: Data file.

en: Site aerial photo (Bettlachstock)

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

en: Field station data (BTF)

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

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

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

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


en: snails arthropods birds diversity spiders urbanization species-abundance-distributions sdms species-richness-models urban-ecology insects

en: contains the raw data to perform species distribution models, only for common species

en: abundance and occurrence data of the 1446 species studied, used to investigate species-abundance distributions and species-occurrence distributions

en: contains the raw data to perform the species richness models of all species

en: contains the raw data to perform the species richness models of the hypercommon species

en: contains the raw data to perform the species richness models of the rare species

en:
Richness, site occurrence and abundance data of bees, beetles, birds, hoverflies, net-wingeds, true bugs, snails, spiders, milipides, wasps collected in the city of Zurich using different sampling techniques, and the environmental variables for each sampling site.
Data are provided on request to contact person against bilateral agreement.

arthropods

display_name: arthropods

birds

display_name: birds

diversity

display_name: diversity

insects

display_name: insects

sdms

display_name: sdms

snails

display_name: snails

species-abundance-distributions

display_name: species-abundance-distributions

species-richness-models

display_name: species-richness-models

spiders

display_name: spiders

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

educ

en: Education, culture and sport

en: Ecological properties of urban ecosystems. Biodiversity dataset of Zurich


en: landuse antarctica cryowrf topography wrf

en: Documentation

en: Documentation about how the provided dataset was produced including details to reproduce the dataset.

en: Scripts

en: Scripts to run the preprocessing to produce WRF binary tiles from REMA and AntarcticaLC2000 for topography and landuse (see Documentation for procedure).

en: WPSinput

en: Input files to run the Weather Research and Forecasting model (WRF) preprocessing system WPS with REMA topography and AntarcticaLC2000 landuse data (see Documentation for details).

en:
Reference Elevation Model of Antarctica (REMA) topography and AntarcticaLC2000 landuse data
are now available as static data input for the Weather Research and Forecasting model (WRF). Topography
and landuse are made available at a spatial resolution of 1 km. This documentation describes the methods
applied to convert REMA and AntarcticaLC2000 to WRF readable format and shows how this improves
the representation of the Antarctic topography and landuse categories over coastal Antarctic regions.

antarctica

display_name: antarctica

cryowrf

display_name: cryowrf

landuse

display_name: landuse

topography

display_name: topography

wrf

display_name: wrf

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: REMA topography and AntarcticaLC2000 for WRF


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

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

en: Environmental DNA Marine France Evhoe 2020


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

en: slow snow compression experiments

en: Compression experiments, X-ray images and with supplemented README file

en: README

en: README file gives an overview of the organization of the data

en:
We conducted consecutive loading-relaxation experiments at low strain rates to study the viscoplastic behavior of the intact ice matrix in snow. The experiments were conducted using a micro-compression stage within the X-ray tomography scanner in the SLF cold laboratory.

Next, to evaluate the experiments, a novel, implicit solution of a transient scalar model was developed to estimate the stress exponent and time scales in the effective creep relation (Glen's law). The result reveals that, for the first time, a transition in the exponent in Glen's law depends on geometrical grain size. A cross-over of stress exponent $n=1.9$ for fine grains to $n=4.4$ for coarse grains is interpreted as a transition from grain boundary sliding to dislocation creep.

The dataset includes compression force data from 11 experiments and corresponding 3D image data from tomography scans.

ice

display_name: ice

microstructure

display_name: microstructure

slow-snow-compression-experiments

display_name: slow-snow-compression-experiments

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography

educ

en: Education, culture and sport

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


en: laperouse fish-composition edna teleo environmental-dna coral-reef marine indian-ocean

en: Please use cyberduck to download for the moment

en:
Fish environmental DNA data set collected in the shallow seamount of La Pérouse located between Madagascar and Réunion Island

In 2019, we sampled the shallow seamount of La Pérouse, located between Madagascar and Réunion Island in the WIO. La Pérouse is an extinct volcano with a summit depth at 60 m below the sea surface. The plateau of the summit has a maximum length of 12 km and a maximum width of 4 km. One side of the seamount might have collapsed in the past, leading to a less common crescent-shaped summit. The abyssal plains that surround this isolated pinnacle are at a depth of 5000 m. Despite its proximity to Réunion Island (160 km northwest), La Pérouse and its surroundings are still poorly studied.
To sample eDNA in this location we used a submersible pump (Subspace, Geneva, Switzerland; nominal flow of ~ 1.0 L/min) to collect samples at various depths during close circuit rebreather dives. The pump has an internal battery and can be activated underwater allowing in situ filtration directly at the targeted habitat and depth. The filtration lasted for 30 min to collect a total water volume of ~ 30 L. During close circuit rebreather dives, water samples from various depths, ranging from 60 to 140 m below the sea surface, were collected using only the Submersible method (eight stations: no replicates). Out of the eight water samples, six were collected during the day, while two were collected at night (IS2_1 at 62 m and IS7_1 at 100–125 m). We applied this filtration protocols to collect and filter water throughout a VigiDNA® 0.2 μM cross-flow filtration capsule (SPYGEN, le Bourget du Lac, France) using disposable sterile tubing for each filtration capsule. After the filtration process, the remaining water in the capsules was emptied. The capsules were then filled with 80 ml of lysis conservation buffer (CL1 buffer SPYGEN, le Bourget du Lac, France) and stored at room temperature in the dark. At La Pérouse, a total of eight water samples were collected during the MONT LA PÉROUSE expedition (https://gombessa-expeditions.com/mont-la-perouse/) on board the ship La Curieuse to the seamount La Pérouse from October 27th to November 5th 2019. We followed a strict contamination control protocol in both field and laboratory stages. Each water sample processing included the use of disposable gloves and single-use filtration equipment to avoid any risk of contamination. Libraries were prepared with ligation using the MetaFast protocol (Fasteris).
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)

coral-reef

display_name: coral-reef

environmental-dna

display_name: environmental-dna

indian-ocean

display_name: indian-ocean

laperouse

display_name: laperouse

marine

display_name: marine

en: Environmental DNA Marine France LaPerouse 2019


en: streamflow stable-water-isotopes groundwater alptal runoff

en: Deuterium rainfall extra event

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
P d.D: Deuterium composition of the rainfall samples (per mil)
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)

en: Precipitation and discharge event B

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
With any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date (year-month-day) and time (hours:minutes:seconds) in UTC
Q: Discharge in mm per hour at catchment outlet (697234,210472)
P: Rainfall in mm per hour averaged for two rain gauges (697494,210675) and (698004, 210680)

en: Deuterium streamwater event B

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

datetime: Date and time of sample collection (UTC; year-month-day, hours:minutes)
Q d.D: Deuterium composition (per mil) of streamwater sampled at the catchment outlet (697234,210472); the first sample is used as pre-event streamflow sample

en: Precipitation and discharge event C

en: Deuterium rainfall event B

en: Deuterium groundwater and baseflow October 2017

en:
This data is collected at the Studibach catchment (Alptal, Switzerland) by Leonie Kiewiet (University of Zürich)
For any questions about the data, please contact leonie.kiewiet@geo.uzh.ch or leoniekiewiet@gmail.com

Date: Date (year-month-day)
Location: Well number or outlet
X: X coordinate (CH1903 LV03)
Y: Y coordinate (CH1903 LV03)
riparian: riparian wells (i.e. from the riparian-like cluster as presented in Kiewiet et al. (2019)) are marked a one, all other wells are marked a zero
d.D (per mil): Deuterium composition (per mil)

en: Deuterium rainfall event A

en: Deuterium groundwater and baseflow October 2016

en: Deuterium streamwater event C

en: Deuterium rainfall event C

en: Deuterium groundwater and baseflow August 2017

en: Precipitation and discharge event A

en: Deuterium streamwater extra event

en: Precipitation and discharge extra event

en: Deuterium streamwater event A

en:
This dataset includes discharge and rainfall measurements and deuterium compositions of streamflow, rainfall and groundwater, for four rainfall events and three baseflow snapshot campaigns in the Studibach (Alptal, Switzerland). More specifically, we present the following data:

- Specific discharge at the catchment outlet at 5-minute resolution (mm per hour);
- Rainfall at 5-minute resolution (mm per hour);
- Rainfall deuterium composition (‰);
- Stormflow deuterium composition (‰);
- Groundwater and baseflow deuterium compositions (‰).

For the files containing rainfall and discharge timeseries (QP), and rainfall and streamwater deuterium compositions ("Deuterium_Rainfall" and "Deuterium_Streamwater"), we added the corresponding event identifier (A, B, C or extra) to the file names. For the files containing the groundwater and baseflow deuterium values ("Deuterium_Snapshot") we added the sample collection date to the file name. We included the X and Y coordinates for each data point (coordinate system: CH1903 LV3) as well as the date and time (UTC).

More information on the data collection and preparation can be found in Kiewiet et al. (in review). A detailed description of the baseflow snapshot campaigns can also be found in Kiewiet et al., 2019.

envidat

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

en: Discharge, rainfall, and deuterium compositions of streamwater, rainwater and groundwater, for four rainfall events in the Studibach, Alptal, Switzerland


en: soil-mapping switzerland ecological-indicator-values soil-moisture landolt ecological-maps soil-ph plants

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en: Description

en: Description of the predictors provided in this dataset

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland

educ

en: Education, culture and sport

en: EnviDat: the Environmental Data Portal


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

en: data_JRL_New particle formation events can reduce cloud droplets in boundary layer clouds at the continental scale.Paper_2023GL106182.zip

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

cloud-droplets

display_name: cloud-droplets

modeling

display_name: modeling

nucleation

display_name: nucleation

pmcamx-uf

display_name: pmcamx-uf

total-number

display_name: total-number

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


en: bees management-intensity zurich host-enemy-interactions urban-ecology urbanization wasps food-webs urban-ecosystems trap-nest hymenoptera cavity-nesting

en: Data of the study

en: The csv. file contains the response variable "interaction diversity" (idiv), and the values of the predictors used in the paper. The "id" column indicates the garden ID, each row in the dataset correspond to a garden and each column to the response (idiv), an explanatory variable or a descriptor (name, Lat, Long). See the thesaurus and the readme file for extended information on the variables.

en: Read me file

en: Not used: readme

en: Script for the analyses v1.0

en: Cleaned script to reproduce the analyses

format: OCTET

en: Script for the analyses v2.0

en: Thesaurus

en: Variable names and their description.

en: Not used: raw questionnaires

en: Not used: data of the study

en: Questionnaires management intensity anonymised

en: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en: Raw data nests

en: Host-enemy interaction data, used to compute the interaction diversity metrics

en:
The data supports the paper "Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens". It provides:
(1) the host-natural enemy interaction networks and network metrics between cavity-nesting bees and wasps and their natural enemies,
 (2) the explanatory variables reflecting urban intensity, temperature, habitat amount and management intensity.
(3) the questionnaires for assessing management intensity.
(4) a thesaurus for the variable names.
(5) a readme file.
(6) the R script used for the analyses.
The data is part of the BetterGardens project. It was sampled in 85 allotment and home gardens in the ctiy of Zurich in 2015 using standardized trapnests.

bees

display_name: bees

cavity-nesting

display_name: cavity-nesting

food-webs

display_name: food-webs

host-enemy-interactions

display_name: host-enemy-interactions

hymenoptera

display_name: hymenoptera

management-intensity

display_name: management-intensity

trap-nest

display_name: trap-nest

urban-ecology

display_name: urban-ecology

urban-ecosystems

display_name: urban-ecosystems

urbanization

display_name: urbanization

wasps

display_name: wasps

zurich

display_name: zurich

en: Data on interaction diversity in urban gardens


en: spongy-month chilling phenology hatch budburst

en: Temperature data Spongy moth experiment

en:
4 files with hourly temperature recorded at the height of buds in each of the four temperature treatments:
- Winter6: greenhouse where temperature was kept >6°C over winter
- Winter10: greenhouse where temperature was kept >10°C over winter
- OTC_Ambient: Open Top Chamber at Ambient temperature
- OTC_Warm: Open Top Chamber at +3.5°C warmer temperature

en: 3 R-Scripts used for the analyses of the temperature, phenology and performance/preference tests

en: Phenology and performance/preference tests Data

en:
-"Synchronex_Cuttings_Pheno.txt" provides the budburst date ('Stage 2') of each twig of the six studies species in the four different temperature treatments ("ambient", "a+5"=Ambient +5°C, 'Greenhouse-5'= Greenhouse at temperature >5°C, 'Greenhouse_10' = Greenhouse at temperature >10°C); 'Success' give the percentage of buds within the twig that succeeded to reach at least stage 2 during the experiment.

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

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

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

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

Input data:
'Synchrony_Cuttings_Pheno.txt':

budburst

display_name: budburst

chilling

display_name: chilling

hatch

display_name: hatch

phenology

display_name: phenology

spongy-month

display_name: spongy-month

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