en:
The dataset refers to samples collected across 6 farms in the Bega Valley region of Australia. The farms are located in the grassy woodland ecoregion and are extensively managed with sheep and cattle grazing. Livestock shares the landscape with native mammalian and invertebrate herbivores. On each farm, two nested fenced exclosure systems were established. These included an open area, a fence excluding livestock but allowing access to native mammals and invertebrates and a fence excluding all mammals but allowing access to invertebrates. In each farm, one of these systems was located in a zone dominated by the native Kangaroo grass, and another in a zone co-dominated by the Invasive African lovegrass. The sample and treatment numbering, as well as a summary of the aggregated indicators is provided in the file Indicator_summary.
Leaf swab s(phyllosphere) samples were taken and DNA was extracted and amplified for 16s and ITS markers. The resulting metabarcoding derived tables are presented (Bacteria_swabs and Fungi_swabs respectively), as are the inferred functional profiles for bacteria at the pathway level (PICRUSt2_pathways), as derived by the PICRUSt2 pipeline.
Two 20 by 100 cm strips had their vegetation removed and their living and litter biomass quantified by dry weight (Biomass). Sensors measuring temperature 10 cm above the soil surface were installed in each plot and their output is presented in Climate. Invertebrates were collected with both pitfall traps and sweepnets and the counts for both sampling techniques can be found in Invertebrates. Damage scores across different categories were collected on 5 leaves of the two species in each plot and the average scores can be found in Leaf_damage.

en: Herbivory disrupts invasion_associated phyllosphere and arthropod community shifts in grasslands

en: herbivore-exclusion biological-invasions grassland invertebrates phyllosphere

envidat

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

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Biomass.csv
    Size: 3031 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/ac6aecef-5a8d-4539-b231-3403691fc3f9/download/biomass.csv
    Description: Dry biomass weight of collected plant material

en:
Resource Title: PICRUSt2.csv
    Size: 469821 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/665f8907-396a-4b1e-b564-fa100a2b5968/download/picrust2.csv
    Description: Predicted pathway profiles of sampled phyllosphere bacterial communities

en:
Resource Title: Leaf_damage.csv
    Size: 2007 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/5c2f7e5f-cc22-4ac6-aa16-f3ef13d27ea7/download/leaf_damage.csv
    Description: Aggregated leaf damage scores for African lovegrass and Kangaroo grass

en:
Resource Title: Fungi_swabs.csv
    Size: 1059062 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/02fb3082-a33e-4af4-8ea1-d4c4953eec4e/download/fungi_swabs.csv
    Description: OTU table of fungal phyllosphere communities

en:
Resource Title: Bacteria_swabs.csv
    Size: 1153434 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/f97a1423-4749-45fa-a07e-93697dd72676/download/bacteria_swabs.csv
    Description: OTU table of bacterial phyllosphere communities

en:
Resource Title: Climate.csv
    Size: 5096079 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/787a3947-a316-4ac5-aeda-ffacfd832bed/download/climate.csv
    Description: Sensor collected soil surface temperatures

en:
Resource Title: Indicator_summary.csv
    Size: 19067 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/d68e884c-0153-4d0f-95c6-eb5702972cce/download/indicator_summary.csv
    Description: Sample metadata and aggregate indicators

en:
Resource Title: Invertebrates.csv
    Size: 18842 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/593901f4-0a08-4dc6-98a4-1decf904dbc1/resource/493ae610-9929-4499-8dfb-fdb7c8feafed/download/invertebrates.csv
    Description: Counts of invertebrates collected with pitfall traps and sweepnets

biological-invasions

display_name: biological-invasions

grassland

display_name: grassland

herbivore-exclusion

display_name: herbivore-exclusion

invertebrates

display_name: invertebrates

phyllosphere

display_name: phyllosphere


$oid: OBSOLETE

en:
Description
This dataset contains continuous sap-flow measurements and derived whole-tree transpiration estimates for 45 Pinus sylvestris trees at the Pfynwald experimental platform in southwestern Switzerland during 2024–2025. Trees were distributed across five treatment combinations established within the VPDrought experiment: Control, Irrigation, Irrigation + VPD reduction, Roof, and Roof + VPD reduction. Sap flux density was measured every 10 min using heat-ratio sap-flow sensors (IX-SF30, Implexx, Melbourne, Australia) installed at breast height on the north-facing side of each tree.
Raw temperature signals were converted to sap flux density following the heat ratio method (Marshall 1958; Burgess et al. 2001; Forster 2019). Thermal diffusivity and related wood properties were parameterized using increment cores collected near the site and tree-specific allometric relationships. Probe misalignment was corrected by estimating a zero-flow offset from nighttime measurements during well-watered, low-VPD conditions in February 2024 and subtracting this offset from the full time series.
Sap flux density measurements at 0.5 and 1.5 cm sapwood depth were combined to total sap flow for the depth where the sensors were installed. Whole-tree transpiration can be calculated by integrating sap flux density across concentric sapwood depth of 2 cm.
The dataset includes processed sap flux density values together with metadata on treatment, tree identity, sensor depth, and quality-control corrections. Limitations include possible residual uncertainty due to sensor drift, assumptions in the sapwood depth, and the replacement of two trees that died during summer 2024 and lost parts of their crown in 2025.
 Additional Information
Data processing was performed in an R environment following the heat ratio method workflow described by Forster (2019). Raw heat-pulse measurements were converted to sap flux density and subsequently corrected for thermal diffusivity, and probe misalignment. Outliers and implausible values were identified and removed using the R package datacleanr (Hurley et al. 2022). Sensor needle misalignment was corrected by defining a zero-flow offset during periods of low atmospheric demand and assumed zero sap flow (i.e. rainy periods), and subtracting this offset from the time series. The processing script used to derive the dataset is available from the authors upon request.
Relevant literature:
- Burgess S.S.O., Adams M.A., Turner N.C., Beverly C.R., Ong C.K., Khan A.A.H. & Bleby T.M. (2001) An improved heat pulse method to measure low and reverse rates of sap flow in woody plants†. Tree Physiology 21, 589–598.
- Forster M.A. (2019) The Dual Method Approach (DMA) Resolves Measurement Range Limitations of Heat Pulse Velocity Sap Flow Sensors. Forests 10.
- Hurley A.G., Peters R.L., Pappas C., Steger D.N. & Heinrich I. (2022) Addressing the need for interactive, efficient, and reproducible data processing in ecology with the datacleanr R package. PLOS ONE 17, e0268426-.
- Marshall D.C. (1958) Measurement of Sap Flow in Conifers by Heat Transport. 1. Plant Physiology 33, 385–396.

en: Pfynwald VPDrought  experiment sap flow parameter

en: forest-ecophysiology pfynwald reduction transpiration xylem-flux vpdrought vpd continuous-monitoring rain-exclusion drought-experiment pinus-sylvestris irrigation rhone-valley tree-transpiration sap-flow

envidat

approval_status: approved

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

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

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

de: EnviDat: das Umwelt-Datenportal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2025.zip
    Size: 53424631 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/455662d6-f0b7-4ea8-8cb6-d31eb714952e/download/pfynwald_vpdrought_sapflow_10minutes_2025.zip
    Description:

format: ZIP

media_type: application/zip

en:
Resource Title: pfynwald_vpdrought_sapflow_10Minutes_2024.zip
    Size: 53546175 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9e439e5-827a-40a7-956c-1a05699e6adc/resource/6a0cd3b8-8e29-4b85-9296-86196808fd32/download/pfynwald_vpdrought_sapflow_10minutes_2024.zip
    Description:

continuous-monitoring

display_name: continuous-monitoring

drought-experiment

display_name: drought-experiment

forest-ecophysiology

display_name: forest-ecophysiology

irrigation

display_name: irrigation

pfynwald

display_name: pfynwald

pinus-sylvestris

display_name: pinus-sylvestris

rain-exclusion

display_name: rain-exclusion

reduction

display_name: reduction

rhone-valley

display_name: rhone-valley

sap-flow

display_name: sap-flow

transpiration

display_name: transpiration

tree-transpiration

display_name: tree-transpiration

vpd

display_name: vpd

vpdrought

display_name: vpdrought

xylem-flux

display_name: xylem-flux


en:
Project description:
Forest soils are among the largest terrestrial carbon pools. How soil carbon (C) responds to changing water availability is still poorly understood, particularly in already water-limited systems. This project investigates the composition and persistence of soil organic matter (SOM) and associated microbial communities in a dry inner-Alpine Scots pine forest exposed to long-term changes in precipitation and atmospheric demand. Earlier work showed that 19 years of irrigation redistributed bulk soil C from the organic layer into the mineral soil. Although total soil C stocks remained unchanged, a higher incorporation into mineral soils may increase long-term C storage (Guidi et al., 2022; Minich et al., 2026). We now ask, how persistent this redistributed C is, in which soil C fraction (particulate or mineral-associated) it resides, and which microbial communities are associated with it.
The work is based at Pfynwald, where a long-term irrigation experiment (since 2003) and the recently installed [VPDrought platform](https://vpdrought.wsl.ch/de/) together span three precipitation regimes (≈300, 600, and 1200 mm per year) crossed with manipulation of atmospheric vapour-pressure deficit. This setup allows us to disentangle the effects of soil and atmospheric drought, which typically co-vary in nature but may shape soil carbon dynamics through distinct pathways. SOM is separated by physical fractionation into particulate (POM) and mineral-associated (MAOM) fractions, characterized through elemental and isotopic analyses (C, N, δ¹³C, δ¹⁵N, ¹⁴C) and fraction-specific microbial community profiling. At the bulk soil level, we measure nutrient pools and extracellular enzyme activities, continue year-round soil respiration, and complement them by CH4 fluxes. Together, these data will reveal how soil carbon stocks and microbial processing respond to changing precipitation in a water-limited pine forest.

en: Soil organic matter dynamics under altered precipitation in a dry Scots pine forest

en: som radiocarbon microbial-communities drought pfynwald

drought

display_name: drought

microbial-communities

display_name: microbial-communities

radiocarbon

display_name: radiocarbon

som

display_name: som


historical-vegetation-height-model-nfi

en:
The main datasets available are 4 nationwide **Digital Surface Models (DSMs)** and corresponding **Vegetation Height Models (VHMs)** with a spatial resolution of 1 m.
The Vegetation Height Models are calculated by subtraction of a Digital Terrain Model (swissAlti3d version 2017, swisstopo) from the generated DSMs. DSMs were derived by image matching of **scanned historical images** (panchromatic 8-bit) acquired with a RC10 frame camera, in the context of the swisswide image acquisition campaigns of swisstopo.
Nationwide products could be generated for the **four epochs**
 1979-1985 / 1985-1991 / 1990-1998 / 1998-2006.
Additional information about successful image matching vs. interpolation of pixels and about the year of image acquisition are available in the corresponding files (**matched_area_xxxx_xxxx_binay.tif** and **meta_acquisition_year_xxxx_xxxx.json**, respectively).
To separate vegetation from non-vegetation areas a mask derived from a combination of information of the Topographic landscape model - TLM (swisstopo) and a NDVI layer was used and is supplied as **"TLM_mask.tif"**
Due to the occurrence of unrealistic vegetation height values caused by the failure of the image matching process (mainly overexposed images and clouds or very steep rocky terrain), pixel values - 60 m were set to NoData and - 0 m to 0.
All datasets are available in the Reference System **LV95 (EPSG: 2056) LN02 (EPSG: 5728)** and share the common **extent definition** (xmin ymin xmax ymax): 2480000 1070000 2840000 1300000

en: Historical Vegetation Height Model NFI

en: historical vhm dsm photogrammetry forest nfi

envidat

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

en: EnviDat: the Environmental Data Portal

title_for_slug: historical-vegetation-height-model-nfi

en:
Resource Title: 1985-1991 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1985-1991_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1998-2006 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1998-2006_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: readme.txt
    Size: 2045 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d16d27e5-b239-4909-b914-1b0b5337dab3/resource/f6cabeaa-bf7c-4141-bea9-af99d3224487/download/readme.txt
    Description: Description of available data

format: TXT

media_type: text/plain

en:
Resource Title: 1990-1998 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1990-1998_vegetation_height_model_nfi%2F
    Description:

en:
Resource Title: 1979-1985 Vegetation Height Model
    Size: 219902325555 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.528%2F1979-1985_vegetation_height_model_nfi%2F
    Description:

dsm

display_name: dsm

forest

display_name: forest

historical

display_name: historical

nfi

display_name: nfi

photogrammetry

display_name: photogrammetry

vhm

display_name: vhm


vegetation-height-model-lidar-nfi

en:
Countrywide **vegetation height models (VHM)** were generated for Switzerland based on
LiDAR data acquired in the framework of the **swissSURFACE3D** campaign (swisstopo).
To derive vegetation height, the classified point cloud got normalized by calculating height above ground for all points not belonging to the class ground (2). Vegetation point (class 3,4,5) got then rasterized to a grid size of 0.5 m using an interpolation distance of one grid cell. Raster cells not belonging to a vegetation class got set to 0 m above ground.
These VHM's are produced in the framework of the Swiss National forest Inventory (NFI).
Each year about 1/6 of switzerland surface is updated using swissSURFACE3D data in leaf-off state.

en: Vegetation Height Model LiDAR NFI

en: vegetation vegetation-height point-cloud forest nfi vegetation-classification three-dimensional

title_for_slug: vegetation-height-model-lidar-nfi

en:
Resource Title: 2024 Vegetation Height Model LiDAR NFI
    Size: 149786984448 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2024%2F
    Description: Vegetation Height Model of Switzerland for the year 2024 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

en:
Resource Title: 2025 Vegetation Height Model LiDAR NFI (current)
    Size: 160202280141 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.664%2F2025%2F
    Description: Vegetation Height Model of Switzerland for the year 2025 (cloud optimized geotiff)
and Metadata file with information about acquisition date and point densities of used LiDAR data for tiles of 1 x 1 km (geopackage).

point-cloud

display_name: point-cloud

three-dimensional

display_name: three-dimensional

vegetation

display_name: vegetation

vegetation-classification

display_name: vegetation-classification

vegetation-height

display_name: vegetation-height


en:
The data show locations of the most recent outdoor activity (referred to as restorative location, RL) of Swiss residents, and descriptive characteristics of these places. The data was collected via an online participatory mapping survey targeting residents of urban, peri-urban, and rural areas across Switzerland. Respondents were selected using a stratified random sampling method, considering the greenness and noise exposure of their home locations, and demographic factors such as age, gender, and language region.
The survey was conducted using Maptionnaire software (https://maptionnaire.com). Participants were asked to map the location of their most recent outdoor activity (referred to as restorative location, RL) and provide additional information on their experience in these places. The responses were integrated with the quantitative spatial information (biophysical landscape characteristics, referred to as metrics) on the visited locations, obtained from spatial and remote sensing data.

en: Restorative locations from participatory mapping by Swiss residents

en: quiet-areas soundscape sensory-perception restorative-environments gis-analysis traffic-noise

envi

en: Environment

gis-analysis

display_name: gis-analysis

quiet-areas

display_name: quiet-areas

restorative-environments

display_name: restorative-environments

sensory-perception

display_name: sensory-perception

soundscape

display_name: soundscape

traffic-noise

display_name: traffic-noise


en:
This study examines the siting scenarios for renewable energy infrastructure (REI) in Switzerland, incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed.
MARXAN was run for 2 versions: a) without ground-mounted open space PV infrastructure (excl. OS) and b) with ground-mounted open space PV infrastructure (incl. OS). In each version optimization was done using ecological costs (ECUess) or social costs (ECUsoc) in a regular grid of 4x4km (planning unit).
File:
PU_data.shp: compressed Shapefile (ESRI) from the MARXAN optimization with 2216 rows (objects) and 18 columns (variables) with sf (simple feature) and data frame classes.
Headers are described below:
X01 = Planning_units (PUs)
X02 = incl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X03 = incl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X04 = incl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X05 = incl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X06 = incl.OS. total energy (MWh/a)
X07 = incl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X08 = incl.OS. energy from wind turbines (MWh/a)
X09 = incl.OS. energy from ground-mounted PV infrastructure (MWh/a)

X10 = excl.OS. number of times pu was selected in MARXAN  when optimized for ecological costs
X11 = excl.OS. number of times pu was selected in MARXAN when optimized for social  costs
X12 = excl.OS. ecological costs (ECUess) of pu when realizing the total energy (normalized)
X13 = excl.OS. social costs (ECUsoc) of pu when realizing the total energy (normalized)
X14 = excl.OS. total energy (MWh/a)
X15 = excl.OS. energy from roof-mounted PV infrastructure (MWh/a)
X16 = excl.OS. energy from wind turbines (MWh/a)
X17 = excl.OS. energy from ground-mounted PV infrastructure (MWh/a)
geometry = Simple feature XY geometry (SFC_POINT) each representing the center of a 4x4km planning unit (PU) in EPSG 21781 (CRS CH1903 / LV03).
For MARXAN optimizations (for meaning of standard files in MARXAN see https://scholar.google.ch/scholar_url?url=https://courses.washington.edu/cfr590/software/Marxan1810/marxan_manual_1_8_2.pdf&hl=de&sa=X&ei=NAWHZI6JJ8PFmAGMo47oDQ&scisig=AGlGAw-DBrsV4kUzkR6GkN1jtG66&oi=scholarr), pu_data.shp was used to generate MARXAN files input.dat, pu.dat, puvfeat.dat, spec.dat.
Coordinate Reference System: CH1903 / LV03. EPSG: 21781.

en: Optimizing renewable energy siting in the Swiss landscape

en: social-acceptance wind-power optimization landscape ecosystem-services marxan spatial-planning photovoltaic energy

ecosystem-services

display_name: ecosystem-services

energy

display_name: energy

landscape

display_name: landscape

marxan

display_name: marxan

optimization

display_name: optimization

photovoltaic

display_name: photovoltaic

social-acceptance

display_name: social-acceptance

spatial-planning

display_name: spatial-planning

wind-power

display_name: wind-power


alan-spongy-moth-laboratory-experiment

en:
Data and Code for ALAN Spongy Moth lab experiment
In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file.
Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

en: ALAN Spongy Moth Laboratory Experiment

en: alan spongy-moth insect-development lab-experiment light-pollution

envidat

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

en: EnviDat: the Environmental Data Portal

title_for_slug: alan-spongy-moth-laboratory-experiment

en:
Resource Title: Pupation_analysis.R
    Size: 7606 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/f5ad6fb7-b540-4742-8b77-e5fa86855b1d/download/pupation_analysis.r
    Description: R code for the pupation analysis and producing the graphics.

format: OCTET

en:
Resource Title: SM_R_long_NvK.csv
    Size: 567035 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/401242a6-4430-4725-8c41-263a4f769041/download/sm_r_long_nvk.csv
    Description: Raw data modified and used for the Bodymass Analysis

format: CSV

media_type: text/csv

en:
Resource Title: CoxHazard_KaplanMeier_Mort_Pup.R
    Size: 3933 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0a205353-8812-4f39-af3f-8d67d2d1495c/download/coxhazard_kaplanmeier_mort_pup.r
    Description: R code for the Cox hazard analysis and producing the Kaplan Meier survival curves for both Mortality and Pupation.

en:
Resource Title: BodyMass_analysis.R
    Size: 4254 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/0ff15832-2eb3-4420-9afd-869e36ce92ef/download/bodymass_analysis.r
    Description: R code for the bodymass analysis and producing the graphics.

en:
Resource Title: SM_R_NvK.csv
    Size: 56547 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/7f7beb40-642a-4a45-a99f-e631c90e1042/resource/c93124fd-448c-403b-bc42-70f4b6722636/download/sm_r_nvk.csv
    Description: Raw data used for the Pupation and Cox Hazard/Kaplan Meier Analysis.

alan

display_name: alan

insect-development

display_name: insect-development

lab-experiment

display_name: lab-experiment

light-pollution

display_name: light-pollution

spongy-moth

display_name: spongy-moth


en: Site description of the Seehornwald Davos (CH-DAV) research site. The material provided offers information on the biomass and growth of trees in CH-DAV, including supporting materials such as maps, geolocations and analyses. CH-DAV is part of networks such as ICOS, LWF, TreeNet, ICPForests and is dedicated to forest monitoring and research.

en: Site description Davos Seehornwald CH-DAV

en: carbon-cycle metadata co2 ecosystem-functioning open-data forest-biomass eddy-covariance carbon-storage tree-stem forest-canopy carbon-dioxide icp-forests dbh ilter davos atmospheric-conditions biomass carbon-sequestration forest-monitoring lwf twd automated-monitoring dendrometer subalpine forest-dynamics forest-area forest-characteristics climate-change icos water-relations climate-growth forest picea-abies flux treenet sap-flow ecophysiology seehornwald stem-growth forest-ecosystems forest-function eddy-covariance-measurements

en:
Resource Title: CH-DAV_Site_2024.zip
    Size: 34214528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/73875879-bec0-4e15-a805-e6cd9d4fe596/download/ch-dav_site_2024.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

en:
Resource Title: CH-DAV_Site_2024_V2.zip
    Size: 27267396 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/41e3d87c-7907-4a01-bf5e-36a0d4457c40/download/ch-dav_site_2024_v2.zip
    Description: Collection of files with information about the research site Seehornwald Davos CH-DAV

en:
Resource Title: Readme
    Size: 2476 bytes
    Format: application/rtf
    URL: https://www.envidat.ch/dataset/4d332ffa-d5f5-413c-ba1c-5f73ceebbed6/resource/7f13f634-76b5-4d56-aa5a-61140240f616/download/readme.rtf
    Description:

format: rtf

atmospheric-conditions

display_name: atmospheric-conditions

automated-monitoring

display_name: automated-monitoring

biomass

display_name: biomass

carbon-cycle

display_name: carbon-cycle

carbon-dioxide

display_name: carbon-dioxide

carbon-sequestration

display_name: carbon-sequestration

carbon-storage

display_name: carbon-storage

climate-change

display_name: climate-change

climate-growth

display_name: climate-growth

davos

display_name: davos

dbh

display_name: dbh

dendrometer

display_name: dendrometer

ecophysiology

display_name: ecophysiology

ecosystem-functioning

display_name: ecosystem-functioning

eddy-covariance

display_name: eddy-covariance

eddy-covariance-measurements

display_name: eddy-covariance-measurements

flux

display_name: flux

forest

display_name: forest

forest-area

display_name: forest-area

forest-biomass

display_name: forest-biomass

forest-canopy

display_name: forest-canopy

forest-characteristics

display_name: forest-characteristics

forest-dynamics

display_name: forest-dynamics

forest-ecosystems

display_name: forest-ecosystems

forest-function

display_name: forest-function

forest-monitoring

display_name: forest-monitoring

icos

display_name: icos

icp-forests

display_name: icp-forests

ilter

display_name: ilter

lwf

display_name: lwf

metadata

display_name: metadata

open-data

display_name: open-data

picea-abies

display_name: picea-abies


forest-canopy-layer

en: This dataset provides a LiDAR-based classification of the forest canopy layer for selected Swiss cantons. Combining an area-based and tree-centred approach, forest areas are categorised into four canopy layering classes that differentiate between single-layered and multi-layered canopies.

en: Forest Canopy Layer

en: forest-structure lidar forest-management forest-canopy nfi mountain-forest

title_for_slug: forest-canopy-layer

envi

en: Environment

en:
Resource Title: ForestCanopyLayer.qml
    Size: 8139 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/378dbed2-33a3-4398-8a41-5c341d27557d/download/forestcanopylayer.qml
    Description: QGIS QML file with stored layer style definitions for the ForestCanopyLayer.tif.

en:
Resource Title: IFA_Data.csv
    Size: 3837 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/a15b3bdb-c45e-4a8a-b526-8d43b265862c/download/ifa_data.csv
    Description: Validation data from the Independent Forester Assessment (IFA). x- /y-coordinate (CH1903+ LV03) and layer (1: single-layered; 2: multi-layered; -999: NA).

en:
Resource Title: ForestCanopyLayer.tif
    Size: 558505541 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/01aaf289-b61f-43ab-be61-39d8e4705c30/resource/90bcde13-c71d-4618-a198-362ebccd0516/download/forestcanopylayer.tif
    Description: Forest Canopy Layer (class 1: single-layered; class 2: probably single-layered; class 3: probably multi-layered; class 4: multi-layered).

format: TIFF

media_type: image/tiff

forest-management

display_name: forest-management

forest-structure

display_name: forest-structure

lidar

display_name: lidar

mountain-forest

display_name: mountain-forest

nfi

display_name: nfi


individual-detected-trees

en: This dataset provides individual detected trees for selected Swiss Cantons (Appenzell Outer-Rhodes - AR, Grisons - GR, Nidwald - NW, Obwald - OW and St. Gall - SG), including the derived diameter at breast height and the derived NFI development stage. Data show the Individual detected trees (ITD) with the x- and y-positions of each detected tree based on a spike-free vegetation height model based on nationwide LiDAR data. The shapefile contains the following attributes: tree height [m] (Height), estimated diameter at breast height [cm] (BHD), and the NFI development stage (Ent; 1: young growth/thicket (- 12 cm); 2: pole timber (12-30 cm); 3: young timber (31-40 cm); 4: medium timber (41-50 cm); 5: old timber (- 50 cm).

en: Individual Detected Trees

en: forest-management nfi mountain-forest forest-structure development-stage itd

envidat

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

en: EnviDat: the Environmental Data Portal

title_for_slug: individual-detected-trees

development-stage

display_name: development-stage

itd

display_name: itd


en:
This dataset contains gridded snow depth projections for Switzerland at 1km X 1km resolution. This study was supported by Speed2Zero. The dataset contains the following structure:
- data/data_reference/hs_reference_1991_2020.nc
- data/data_projection_flat/hs_projection_flat.nc
- data/data_projection_aspect/hs_projection_aspect.nc
The data is based on climatological SPASS dataset (Marty et al., 2015) using the reference period 1991-2020. For this reference data, median snow depth evolution, as well as 5th and 95th percentile were computed for each grid point and can be found in this dataset (data/data_reference/*). Future snow depth evolutions for the flat field (data/data_projection_flat/*) were projected for the temperature scenarios +1°C, +2°C, +3°C and +4°C (deviation from 1991-2020 annual mean temperature in Switzerland) following the literature-based approach of Richter and Marty, 2026. Furthermore, this dataset contains gridded projections for north- and south-facing ascpects with a slope anle of 15° (data/data_projection_aspect/*). Detailed can be found in the related publication Richter et al., in preparation.
The files in this data set have a similar structure. Each file is a NetCDF-file containing snow depths (median, 5th, 95th percentile) for each day of the year, coordinate, temperature scenario (data_projection_flat and data_projection_aspect) and aspect (data_projection_aspect).
References:
Marty, C., Michel, A., Jonas, T., Steijn, C., Muelchi, R., and Kotlarski, S.: SPASS – new gridded climatological snow datasets for Switzerland: potential and limitations, The Cryosphere, 19, 4391–4407, https://doi.org/10.5194/tc-19-4391-2025, 2025.
Richter, B. and Marty, C.: Technical note: Literature based approach to estimate future snow, Hydrol. Earth Syst. Sci., 30, 659–670, https://doi.org/10.5194/hess-30-659-2026, 2026.
Richter et al., Gridded snow depth projections, in prepration.

en: Gridded projections of snow depth for Switzerland

en: switzerland climate-change future swiss-alps scenario snow gridded-data climate-projections snow-depth

climate-change

display_name: climate-change

climate-projections

display_name: climate-projections

future

display_name: future

gridded-data

display_name: gridded-data

scenario

display_name: scenario

snow

display_name: snow

snow-depth

display_name: snow-depth

swiss-alps

display_name: swiss-alps

switzerland

display_name: switzerland


iwet-insect-weight-estimation-tool

en:
Because of some corrections, a new version of the whole Dataset will be published soon.
We present a novel tool called IWET (Insect Weight Estimation Tool) for estimating morphometrics of arthropod samples using image analysis. IWET is a Java application built around ImageJ libraries and is designed to estimate length, width, area and body mass of individual arthropods from images of specimens sorted into pre-defined taxonomic groups. Using allometric relationships from Sohlströhm et al. (2018), we developed specific regression models to calculate both the individual body mass and the total biomass of arthropod taxonomic groups. IWET provides several advantages: it is non-destructive, cost-effective, and capable of processing large numbers of samples, making it particularly well-suited for biodiversity monitoring projects investigating changes in abundance and biomass, as well as for automating measurements such as specimen length, width and area.

en: IWET – Insect Weight Estimation Tool

en: image-analysis automatic-detection biomass body-size arthropods temperate allometric

title_for_slug: iwet-insect-weight-estimation-tool

en:
Resource Title: R-Script_and_suppl.zip
    Size: 2243953 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/6ca41ee8-bda9-4e65-b859-1dd9c0184c50/download/r-script_and_suppl.zip
    Description: R Script for Regression models

en:
Resource Title: IWET_EnviDat.zip
    Size: 10255073 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/3d7e7b44-af7f-4824-84b8-fc2abd1f04b3/resource/7f5681bf-cf49-47b0-a8cc-a1e8dde61354/download/iwet_envidat.zip
    Description: IWET-Software with prorpriety and model files (inkl. materials)

allometric

display_name: allometric

arthropods

display_name: arthropods

automatic-detection

display_name: automatic-detection

biomass

display_name: biomass

body-size

display_name: body-size

image-analysis

display_name: image-analysis

temperate

display_name: temperate


en:
This dataset contains all necessary data to reproduce the validation simulations performed in the linked manuscript.
The validation data includes:
- 2 cm DEM of the study site Weissfluhjoch. For the 3 cm DEM of the study site Chant Sura, see [this dataset](https://www.doi.org/10.16904/envidat.174).
- roughness index rasters for both study sites
- rock point clouds of EOTA and Real Equant shapes
- release points used in the validation simulations of both study sites
- a sample XML input file for the rockfall simulator

en: Validation Data for Rockfall Simulations with Geometric Roughness Model

en: surface-roughness numerical-simulation rockfall natural-hazards validation

envi

en: Environment

en:
Resource Title: DEM Weissfluhjoch
    Size: 1005521469 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/9598c524-85b4-4dad-981c-59a126314973/download/dem_weissfluhjoch_2cm.tif
    Description: Digital Elevation Model (DEM) of validation test site Weissfluhjoch with a grid resolution of 2 cm. The DEM for test site Chant Sura can be found in the linked dataset.

en:
Resource Title: Sample Simulation
    Size: 126372 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/230c5218-e7a2-4e4f-8633-0c00695cff71/download/sample_sim.zip
    Description: This dataset contains a small sample simulation to showcase the recommended folder/file structure to run rockfall simulations. The input parameters for the simulation can be changed in the XML file, which is then also used as input for the rockfall simulator.

en:
Resource Title: Roughness Index Rasters
    Size: 36884 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/2c863503-c73d-4b97-a660-d2998b717093/download/roughness.zip
    Description: Roughness index rasters used for the validation simulations. They have a resolution of 3 m.

en:
Resource Title: Rock Pointclouds
    Size: 3779 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/c99baa33-50ba-480a-8e4b-82450130900b/download/rocks.zip
    Description: Rock point clouds of EOTA and Real Equant shapes

en:
Resource Title: Release Points
    Size: 4649 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/b6c60fc1-448d-445b-98bf-57806bbade9e/resource/636d34b5-5031-4bb6-aa28-b3d1cb11b80e/download/release.zip
    Description: Release points used in the validation simulations of both study sites. Use the *.txt files as input for the simulator.

natural-hazards

display_name: natural-hazards

numerical-simulation

display_name: numerical-simulation

rockfall

display_name: rockfall

surface-roughness

display_name: surface-roughness

validation

display_name: validation


sliding-deadwood-geometry-generator

en: This dataset contains a python code to create deadwood log geometries as well as sample data used for simulations of sliding deadwood with RAMMS::Rockfall.

en: Sliding Deadwood Geometry Generator

en: forest-management natural-hazards protection-forest mass-movements deadwood

envidat

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

en: EnviDat: the Environmental Data Portal

title_for_slug: sliding-deadwood-geometry-generator

en:
Resource Title: Sample Data
    Size: 108780 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/5ba5fd5d-1b1e-485f-ab24-422df5a509ac/download/sample_data.zip
    Description: Contains all necessary data to do a sample simulation of sliding deadwood:
- Deadwood log geometries (*.pts)
- Release points of the logs (*.shp)
- Treefiles (*.txt), containing the locations, heights, BHD and energy absorption capacities of the standing trees

The data is from the two case studies Gruobenwald and Rhäzüns presented in the linked publication. The DEM for these case studies can be downloaded from swisstopo (swissALTI3D dataset)

en:
Resource Title: Sliding deadwood geometry generator
    Size: 6062 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/a6325cb3-bdb3-4b7c-90f6-1ca41c159918/resource/6fc08e26-7bbe-45c9-8ea1-ab85c36c1793/download/sliding_deadwood_geometry-main.zip
    Description: Python code to create deadwood logs as input for RAMMS::Rockfall.

This version was used for the linked publication. The most recent version and the full documentation can be found in the [GitHub Repository](https://github.com/joelborner/sliding_deadwood_geometry)

deadwood

display_name: deadwood

forest-management

display_name: forest-management

mass-movements

display_name: mass-movements

protection-forest

display_name: protection-forest


en:
The dataset contains the time series of: overland flow (OF) and topsoil interflow (TIF) measured at two large runoff plots (8 m large by 10 m long), streamflow from two sub-catchments of the Studibach catchment, and streamflow from the outlet of the Studibach and Erlenbach catchments. The time series cover 12 rainfall events in the summer 2022.
OF, TIF and the streamflow of the sub-catchments and the Studibach catchment outlet were measured at a 5-min resolution. The streamflow at the Erlenbach catchment outlet was measured at 10-min resolution.
The precipitation was measured with a tipping bucket at the Erlenhöhe meteorological station and has a 10-min resolution.

en: Time serie of overland flow, topsoil interflow and stream flow in the Studibach Catchment and streamflow in the Erlenbach catchment - summer 2022

en: studibach upscaling alptal overland-flow runoff-plot topsoil-interflow streamflow erlenbach

alptal

display_name: alptal

erlenbach

display_name: erlenbach

overland-flow

display_name: overland-flow

runoff-plot

display_name: runoff-plot

streamflow

display_name: streamflow

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow

upscaling

display_name: upscaling


en:
ERRA is a data-driven, nonparametric, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags, in systems that may be nonlinear, nonstationary, and spatially heterogeneous.
Researchers using ERRA in published work should cite J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, https://doi.org/10.5194/hess-28-4427-2024, 2024 (for ERRA itself) and J.W. Kirchner, "Impulse response functions for nonlinear, nonstationary, and heterogeneous systems, estimated by deconvolution and de-mixing of noisy time series", Sensors, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022 (for the underlying mathematics).
This data set includes two versions of the ERRA script written in the open-source programming language R, a detailed user's guide, and sample scripts and source data for all of the results in Kirchner (2024).
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.  The data and documentation are made available under Creative Commons Attribution Share-Alike CC-BY-SA.
ETH Zurich, WSL, and James Kirchner make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose. Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: ERRA -- an R script for Ensemble Rainfall-Runoff Analysis

en: precipitation nonstationarity time-series streamflow hydrology rainfall-runoff-modelling ecohydrology nonlinear-deconvolution

en:
Resource Title: An introduction to ERRA v1.12.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/927de1da-fef7-4b05-8534-ae8330bbb48c/download/an-introduction-to-erra-v1.12.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

format: PDF

media_type: application/pdf

en:
Resource Title: ERRA_scripts_v1.12.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/11af276e-c779-468c-9504-ef56bd490c7d/download/erra_scripts_v1.12.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.12.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.12_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.06.zip
    Size: 114452 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/64819efe-d661-41c8-8410-f61665564c05/download/erra_scripts_v1.06.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.06.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.06_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} ERRA_scripts_v1.11.zip
    Size: 2621440 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/6e05e468-ccd2-4d42-be7b-b7578a68061e/download/erra_scripts_v1.11.zip
    Description: Zip-compressed folder containing two versions of the ERRA script. ERRA_v1.11.R uses Rcpp to speed up several key calculations, but requires a C++ compiler. ERRA_v1.11_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp. Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.06.pdf
    Size: 3166700 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/0c048816-816a-4c1f-bedf-32be20e4d4c2/download/an-introduction-to-erra-v1.06.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: Demonstration scripts.zip
    Size: 65399685 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/ca1f4818-aff6-4b13-a83d-82376dde2834/download/demonstration-scripts.zip
    Description: Zip-compressed folder containing demonstration scripts, source data, and output files for the ERRA results shown in "Introduction to ERRA" and in J.W. Kirchner, "Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using Ensemble Rainfall-Runoff Analysis (ERRA): proof of concept", Hydrology and Earth System Sciences, 2024.

en:
Resource Title: {{deprecated version}} ERRA_scripts.zip
    Size: 114811 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/9e833898-3a78-4e79-83bd-d23c5ba76765/download/erra_scripts.zip
    Description: Zip-compressed folder containing two versions of the ERRA script.  ERRA_v1.0.R uses Rcpp to speed up several key calculations, but requires a C++ compiler.  ERRA_v1.0_no_Rcpp.R is a bit slower but does not require a C++ compiler or Rcpp.  Public use of these scripts is permitted under GNU General Public License 3 (GPL3); for details see https://www.gnu.org/licenses/

en:
Resource Title: {{deprecated version}} An introduction to ERRA v1.11.pdf
    Size: 3072328 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/eee3eb76-74b7-4d84-bd23-fa2a97544b58/download/an-introduction-to-erra-v1.11.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them. This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

en:
Resource Title: {{deprecated version}} An introduction to ERRA.pdf
    Size: 3156214 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/84277dcd-ccde-4eaf-a65b-d1ecf6a0385c/resource/51f419cd-f933-4cad-88b4-a20ac7dcf545/download/an-introduction-to-erra.pdf
    Description: "An introduction to ERRA" presents a series of vignettes that introduce some of the capabilities of the Ensemble Rainfall-Runoff Analysis (ERRA) script, and that show how to invoke them.  This introduction also includes documentation for ERRA function calls, largely reproducing the documentation embedded in the ERRA script itself.

ecohydrology

display_name: ecohydrology

hydrology

display_name: hydrology

nonlinear-deconvolution

display_name: nonlinear-deconvolution

nonstationarity

display_name: nonstationarity

precipitation

display_name: precipitation

rainfall-runoff-modelling

display_name: rainfall-runoff-modelling

time-series

display_name: time-series


en:
**CH-POA300** is a dataset of hourly solar irradiance maps projected onto tilted surfaces (analogous to monofacial solar panels).
- **Spatial resolution:** 300 m
- **Coverage:** Switzerland
Two temporal extents are available, depending on the number of surface orientations (azimuth–tilt combinations):
 1. Long-term
- **Period:** 2004–2020
- **Orientations:**
  - Azimuth: 180° (South)
  - Tilts: 0°, 35°, 60°, 90°
 2. Typical year
- **Period:** 2016
- **Orientations:**
  - Azimuths: 0° (North), 90° (East), 135°, 180° (South), 225°, 270° (West)
  - Tilts: 0°, 3°, 8°, 15°, 25°, 35°, 45°, 60°, 80°, 90°
 Notes
- Azimuth angles: 0° = North, 90° = East, 180° = South, 270° = West
- Tilt angles: 0° = horizontal, 90° = vertical
 Additional data
- Seasonal and annual statistics derived from the maps are included.
- Methodology and quality assessment are documented in *CH-POA300-v-specs.pdf*.

en: CH-POA300 -- Hourly Plane-of-Array Solar Irradiance at High Resolution for Switzerland

en: sweet-edge rooftop-pv solar-irradiance plane-of-array speed2zero alpine-pv agri-pv

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Data 2004-2020
    Size: 858993459200 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300/&prefix=2004-2020
    Description:

en:
Resource Title: CH-POA300-v2-specs
    Size: 11473219 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/c184fb33-6751-47cd-a936-2f04de24c760/download/ch-poa300-v2-specs.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: Data 2016
    Size: 751619276800 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2FCHPOA300%2F&prefix=2016
    Description:

en:
Resource Title: CH-POA300-v2-statistics
    Size: 1889349528 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ed1238d2-b8c0-42f1-9b65-b837ac2dd259/download/stats.zip
    Description: Contains seasonal and annual statistics (mean and sum) derived from the CH-POA300 dataset.
File naming conventions:
yyyy_agg_period_hourly_stat.nc : statistic <stat> for aggregation period <agg_period> in year <yyyy>
all_agg_period_stat_mean.nc : statistic <stat> for aggregation period <agg_period> computed over the entire dataset (all years)
Definitions:
yyyy = year (2004–2020)
agg_period = winter, summer, annual
stat = mean, sum

en:
Resource Title: CH-POA300_v1_specs
    Size: 11472383 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/7146fc4a-df12-44a8-923f-69476b147a55/download/chpoa300_specs_v1.pdf
    Description: This document provides an in-depth description of the CH-POA300 dataset. It includes methodology and validation details.

en:
Resource Title: CH-POA300_v1_statistics
    Size: 1445061901 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0ec532fd-a319-4569-a181-ab391104b47f/resource/ea36025c-c855-488d-857d-f658bace53e2/download/chpoa300_statistics.zip
    Description: Contains seasonal and annual statistics (mean, sum) of the CH-POA300 dataset.

- "yyyy_agg_period_hourly_stat.nc": statistic <stat> for the period <agg_period> of the year <yyyy>
- "all_agg_period_stat_mean.nc": statistic <stat> for the period <agg_period> reduced on the entire dataset (all years).
\
yyyy: [2004, 2020]
agg_period: [winter, summer, annual]
stat: [mean, sum]

agri-pv

display_name: agri-pv

alpine-pv

display_name: alpine-pv

plane-of-array

display_name: plane-of-array

rooftop-pv

display_name: rooftop-pv

solar-irradiance

display_name: solar-irradiance

sweet-edge

display_name: sweet-edge


en:
Lebensraumkarte der Schweiz v1.2 2025/La carte des milieux naturels de Suisse v1.2 2025
The FOEN funded project ‘The Habitat Map of Switzerland:continual improvement’ conducted at the WSL, has improved on versions 1.0 and 1.1 of a map of Swiss habitats according to the TypoCH classification (Delarze et al. 2015). The datasets is now separated into two data sets:  The Habitat Map of Switzerland v1.2, ground cover layer,  and The Habitat Map of Switzerland v1.2, individual trees and shrubs outside forest v1.0 (above ground) layer.
The Habitat Map of Switzerland maps the TypoCH habitat types wall-to-wall across the whole of Switzerland, to at least the classification’s 2nd level of detail (where possible to the 3rd level of detail).
Habitats are mapped through a variety of approaches that can be grouped as either:
1: Derived from the existing Swiss-wide datasets a) the high quality landcover mapping from Swisstopo’s Topographical Landscape Model (TLM), b) the harmonised mapping of agricultural fields area from the ‘Landwirtschaftliche Nutzfläche’ (LWN) mapping and, in settlements areas, c) the harmonised cadastral data (‘Amitliche Vermessung’ AV).
2: Modelled within the project using Random Forest or Ensemble Modelling techniques to model the spatial distribution of individual habitat types (further detail below),
3: Combining existing species distribution models to determine habitat types, or
4: Classification with relatively simple rule-sets based on auxiliary spatial datasets, i.e. vegetation height models (based on digital aerial photogrammetry and/or SwissSurface3D aerial laser scanning (ALS) data), the digital terrain model, the normalised difference vegetation index (NDVI) derived from aerial imagery and/or time-series of growing season Sentinel-2 or Planet satellite imagery.
Further detail on the methodology can be found within the README document.

en: The Habitat Map of Switzerland v1_2 2025

en: forest shrub-forest dwarf-shrubs remote-sensing typoch lidar grasslands random-forest wetland sentinel-2 ensemble-modelling milieux-naturels lebensraumkarte urban habitat-modelling tof

en:
Resource Title: N2025_HabitatMap_CH_v1_2_20251211.gdb.zip
    Size: 7247757312 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/a90d17bf-221e-4819-a8b1-94b807a33720/download/n2025_habitatmap_ch_v1_2_20251211.gdb.zip
    Description: The Habitat Map of Switzerland version 1.2 2025. Ground cover layer, All of Switzerland. Vector data in file geodatabase format. Is complemented by the trees and shrubs layer.

en:
Resource Title: symbology_v1_2_2025.zip
    Size: 61778 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/47c0e914-986f-4ad3-9bcf-49160023c030/download/symbology_v1_2_2025.zip
    Description: Symbology for the Habitat Map, ground layer and tree and shrub layer, and in ArcGIS and QGIS layer formats. German, French and Italian versions

en:
Resource Title: Data_Description_Lebensraumkarte_v1_2_Dec2025.pdf
    Size: 645376 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/564b16e5-0523-4431-94bc-3e6d1415c5a1/download/data_description_lebensraumkarte_v1_2_dec2025.pdf
    Description: Data description and documentation of methods

en:
Resource Title: TypoCH_NUM_LookupTable_26112025.csv
    Size: 46705 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/28aace15-eb00-4ec2-98ef-b55acc18286f/download/typoch_num_lookuptable_26112025.csv
    Description: Look up table for the data N2025_HabitatMap_CH_v1_2_20251211
giving the full text names for habitat types in German, French and Italian for each habitat type as well as the key for the type of methodology used

en:
Resource Title: LUT_einzelbaum_gebuesch_v_1_0.csv
    Size: 216 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/0035dd77-ea6d-4d3a-89bd-3ad6ee36302e/download/lut_einzelbaum_gebuesch_v_1_0.csv
    Description: Look up table for the data N2025_einzelbaum_gebuesche_v1_0_20251216
giving the full text names for each habitat type in German, French and Italian

en:
Resource Title: N2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Size: 2469606195 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/d6182107-2086-49c0-97dd-f3a77056157c/resource/cd4e36db-926c-4e2b-bb89-27dbe606dac3/download/n2025_einzelbaum_gebuesche_v1_0_20251216.gdb.zip
    Description: The Habitat Map of Switzerland v1.2, non-forest trees and shrubs layer, v1.0. Vector dataset in file geodatabase format. Complements the ground cover layer dataset

dwarf-shrubs

display_name: dwarf-shrubs

ensemble-modelling

display_name: ensemble-modelling

forest

display_name: forest

grasslands

display_name: grasslands

habitat-modelling

display_name: habitat-modelling

lebensraumkarte

display_name: lebensraumkarte

lidar

display_name: lidar

milieux-naturels

display_name: milieux-naturels

random-forest

display_name: random-forest

remote-sensing

display_name: remote-sensing

shrub-forest

display_name: shrub-forest

tof

display_name: tof

typoch

display_name: typoch

urban

display_name: urban

wetland

display_name: wetland


en: This data supplement contains the data associated with the manuscript: "Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions" (Janzing et al., 2025). It contains the data to create the figures in the paper and consists of model output from **PCRaster Global Water Balance Model (PCR-GLOBWB) 2.0** model over the larger Alpine region at 30 arcsec resolution. As the full model output takes up very high memory space, we here mostly provide time series for the different measurement stations used for evaluation and some additional maps needed to recreate the figures in the manuscript.

en: Data supplement to Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions

en: hydrological-simulations discharge hydrology european-alps large-scale

envidat

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

en: EnviDat: the Environmental Data Portal

discharge

display_name: discharge

european-alps

display_name: european-alps

hydrological-simulations

display_name: hydrological-simulations

hydrology

display_name: hydrology

large-scale

display_name: large-scale


chelsacerra-daily

en:
CHELSA is a mechanistic downscaling model that links large-scale atmospheric conditions with local topographic factors to produce very high-resolution climate data. It includes commonly used climate variables for impact modeling, such as air temperature, precipitation, humidity, solar radiation, wind speed, and derived variables.
CHELSAcerra daily is a high resolution climate dataset for air-temperatures generated with the CHELSA downscaling model using the Copernicus regional reanalysis for Europe (CERRA).
Daily summaries are provided for: Daily Mean Near-Surface Air Temperature

en: CHELSAcerra-daily

en: air-temperature minimum-temperature maximum-temperature climate reanalysis europe

title_for_slug: chelsacerra-daily

envi

en: Environment

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1993
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1993%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2004
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2004%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2005
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2005%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2006
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2006%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1985
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1985%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2008
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2008%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1996
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1996%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2001
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2001%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1998
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1998%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2010
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2010%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1989
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1989%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2009
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2009%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1997
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1997%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2012
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2012%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1988
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1988%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1999
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1999%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1991
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1991%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1986
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1986%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1992
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1992%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2011
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2011%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1987
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1987%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2014
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2014%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1994
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1994%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2000
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2000%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2002
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2002%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2007
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2007%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1995
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1995%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2003
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2003%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2015
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2015%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 2013
    Size: 16777216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F2013%2FCERRA%2F
    Description: Daily Mean Near-Surface Air Temperature

en:
Resource Title: Daily Mean Near-Surface Air Temperature 1990
    Size: 1 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Feurope%2Fdaily%2Ftas%2F1990%2FCERRA%2F
    Description:

air-temperature

display_name: air-temperature

climate

display_name: climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

reanalysis

display_name: reanalysis


en:
List of key debris flow variables from the WSL Illgraben monitoring station (2023) such as occurrence date and time, peak flow depth, peak flow velocity, total volume and bulk density.
This table contains values based on our current analysis methods. The list will be updated annually after each debris flow season, and as our methods continue to improve, individual values may change slightly in the future.

en: magnitude monitoring-station illgraben debris-flow force-plate

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Illgraben debris-flow characteristics 2023
    Size: 786 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/8483e966-c20d-4403-93ed-26cc8fbf1d4d/download/df_characteristics_illgraben_2023.csv
    Description: List of key debris flow variables from the WSL Illgraben monitoring station (2023)

en:
Resource Title: Readme.txt
    Size: 1523 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d24373f7-566f-441f-be64-6dbd8d0cc7e4/resource/ea1a8f18-6989-493b-ac4d-72b60966f112/download/readme.txt
    Description:

debris-flow

display_name: debris-flow

force-plate

display_name: force-plate

illgraben

display_name: illgraben

magnitude

display_name: magnitude

monitoring-station

display_name: monitoring-station


climarctic-seasons

en: This dataset includes measurements of potential microbial functions (potential extracellular enzyme activities and microbial functional genes abundance) and soil physico-chemical properties (pH, nutrients, texture, etc) in biocrusts and underlying mineral soils in High-Arctic tundra near Ny-Ålesund (Svalbard) during each season along a toposequence.

en: Climarctic seasons

en: soil greenhouse-gases microbial-functions arctic microbial-biodiversity

title_for_slug: climarctic-seasons

format: XLS

arctic

display_name: arctic

greenhouse-gases

display_name: greenhouse-gases

microbial-biodiversity

display_name: microbial-biodiversity

microbial-functions

display_name: microbial-functions

soil

display_name: soil


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.

en: Data on interaction diversity in urban gardens

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

en:
Resource Title: Raw data nests
    Size: 667409 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/1d6ef3da-b431-4fa9-8463-cad7fc487e6e/download/trapnest_data_bettergardens.csv
    Description: Host-enemy interaction data, used to compute the interaction diversity metrics

en:
Resource Title: Not used: data of the study
    Size: 15319 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/89ab594f-d989-4b77-afce-c6443cc1089d/download/dataset_betgard_predictors.csv
    Description:

en:
Resource Title: Data of the study
    Size: 14672 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/b181b669-3290-4f59-a30d-2933071e1090/download/dataset_betgard_predictors.csv
    Description: 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:
Resource Title: Thesaurus
    Size: 9654 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/5f684f4b-8b68-4565-bed4-d7b7782cb036/download/thesaurus_data.xlsx
    Description: Variable names and their description.

en:
Resource Title: Script for the analyses v2.0
    Size: 54771 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/94ea4ad2-dbb3-45a6-8782-31ba29b788fb/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

en:
Resource Title: Read me file
    Size: 5214 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/188e4fa7-8cdd-43e5-aae4-ae66c5fa73c5/download/readme.txt
    Description:

en:
Resource Title: Not used: readme
    Size: 6373 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/d35b12e9-ac52-44d3-82d3-102da2190c2d/download/readme.txt
    Description:

en:
Resource Title: Not used: raw questionnaires
    Size: 30569 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/13da58d0-ae92-4ed3-8c24-f099c4ce400c/download/raw_questionnaires.csv
    Description:

en:
Resource Title: Questionnaires management intensity anonymised
    Size: 30557 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/0f2466e6-a748-440e-a690-a13992c3e284/download/raw_questionnaires.csv
    Description: Results from the management intensity questionnaires anonymised. IDs are randomized and don't match those in the study data csv

en:
Resource Title: Script for the analyses v1.0
    Size: 53666 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/2c3c9562-aa8a-4b53-8226-0d9336114bf3/resource/6f3ab130-4a41-4f08-ad61-ef692b41c871/download/script_betgards_clean.r
    Description: Cleaned script to reproduce the analyses

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: The dataset contains measured values of soil liquid water content, matric potential, and soil texture of 40 soil samples in Davos, Switzerland. The measurements were used for determining van Genuchten parameter values through fitting of water retention curves, pedotransfer functions, and inverse fitting with Hydrus-1D.

en: Soil measurements of Seewer Berg and Davos

en: measurements soil-texture lwc alpine soil matric-potential soil-classification glide-snow-avalanche

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: coordinates.csv
    Size: 1222 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/7494a93b-068b-4d87-8f33-a16d197d27bf/download/coordinates.csv
    Description: Coordinates of each soil location, location of the snow profiles, and location of the snow liquid water content measurements

en:
Resource Title: swb_px_direct_fitting.csv
    Size: 7529 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d4114528-bd8a-4335-b9ba-3d8eba7bb1fa/download/swb_px_direct_fitting.csv
    Description: Daily averaged values used for the direct fitting

en:
Resource Title: README.txt
    Size: 1599 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/ffffb46c-fc15-49a7-b179-e20ff120fb48/download/readme.txt
    Description: Detailed information of each file in the dataset

en:
Resource Title: texture_data.csv
    Size: 1189 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/c1c4be41-28ff-4d20-97d5-aa6c28e74695/download/texture_data.csv
    Description: Texture data of the soil locations

en:
Resource Title: van_genuchten_parameter_values.csv
    Size: 3098 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/810089c7-a4f8-4e9a-a9b9-5d1a55676b81/download/van_genuchten_parameter_values.csv
    Description: Complete list of the van Genuchten parameter values for each soil and method

en:
Resource Title: swb_hydrus_files.zip
    Size: 2906045 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3227a87b-43f4-46b8-b0ad-76af36528e03/resource/d7ce01fb-cce5-45ea-85ec-44a25ac49a77/download/swb_hydrus_files.zip
    Description: Hydrus files used for the inverse fitting

alpine

display_name: alpine

glide-snow-avalanche

display_name: glide-snow-avalanche

lwc

display_name: lwc

matric-potential

display_name: matric-potential

measurements

display_name: measurements

soil-classification

display_name: soil-classification

soil-texture

display_name: soil-texture


c-n-p-release-treeline

en:
1. Chemical characteristics of litter layer sampled along elevation gradient across treeline ecotones in the Khibiny mountains (birch) and South Urals (spruce)
2. Release of C-N-P during decomposition at 5°C and 15° studied in an incubation experiment with microlysimeters
3. Data on microbial biomass C-N-P, potential activity of C-N-P requiring enzymes in the litter layer
4. Mineralization of 13C labeled glucose-6 phosphate, microbial 13C uptake, and net P immobilization of released P to identify microbial processing of labile organic P

en: C-N-P-Release Treeline

en: climate-change treeline-ecosystems microbial-biomass litter-decomposition biogeochemical-cycling carbon-cycle nutrient-fluxes enzymatic-activities

title_for_slug: c-n-p-release-treeline

biogeochemical-cycling

display_name: biogeochemical-cycling

carbon-cycle

display_name: carbon-cycle

climate-change

display_name: climate-change

enzymatic-activities

display_name: enzymatic-activities

litter-decomposition

display_name: litter-decomposition

microbial-biomass

display_name: microbial-biomass

nutrient-fluxes

display_name: nutrient-fluxes

treeline-ecosystems

display_name: treeline-ecosystems


en: This dataset consists of data related to capillary rise experiments performed with neutron radiography. There are 4 videos of capillary rise experiments as well as the files used to perform the inverse fitting with Hydrus. The videos show the upward flow of water in glass columns filled with sand and snow or sand, gravel, and snow. The videos show the 2D evolution of the unitless optical density with time. The Hydrus files were used to fit the parameter values of the Mualem-van Genuchten model. The experiments were performed at the Paul Scherrer Institute (PSI) in Villigen, Switzerland.

en: Capillary rise rise experiments in snow using neutron radiography

en: water soil measurements transport snow pore-water

en:
Resource Title: README.txt
    Size: 1089 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/5631a26d-f9f0-4548-9e78-e6eecdffcee5/download/readme.txt
    Description: Descriptions of the nomenclature, Hydrus files, and videos.

en:
Resource Title: Hydrus_inverse_fitting_files.zip
    Size: 749844 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/a4e140c9-e73a-402e-9b59-63b6000d5bb6/download/hydrus_inverse_fitting_files.zip
    Description: The Hydrus files used for the inverse fitting of the hydraulic conductivity.

en:
Resource Title: capillary_rise_experiment_videos.zip
    Size: 10552661 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/4d5ee580-c1b4-49d4-868f-971b8383afa7/download/capillary_rise_experiment_videos.zip
    Description: Videos of the capillary rise experiments

en:
Resource Title: depricated.txt
    Size: 496 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/44ba7f26-f741-4b92-a4ff-8e99dd8f689c/resource/74c3db20-eaed-40de-a880-f042010cf6cc/download/readme.txt
    Description: Description of the videos

pore-water

display_name: pore-water

snow

display_name: snow

soil

display_name: soil

transport

display_name: transport

water

display_name: water


en:
This dataset originates from a two-year transplant experiment conducted across a temperature gradient in Europe (mean annual temperatures: 8.4–21.8 °C). It includes physiological measurements of one invasive palm species (Trachycarpus fortunei) and two co-occurring native species (Ilex aquifolium and Tilia cordata). The dataset captures plant acclimation responses to air temperature, focusing on photosynthetic and respiratory traits that influence carbon balance.
Variables that can be extracted:
- Optimal temperature of photosynthesis (Topt)
- Photosynthetic rate at optimal temperature (Aopt)
- Thermal breadth of photosynthesis (T80)
- Respiration rate at 25 °C (R25)
- Temperature sensitivity of respiration (Q10)
Raw data are reported for all species across multiple sites and time points, enabling assessment of their acclimation capacity to warming. The dataset supports comparisons of functional plasticity between an invasive species and native taxa, providing insights into climate responses and invasion ecology.

en: Thermal acclimation fails to confer a carbon budget advantage to invasive species over natives

en: respiration invasive-species acclimation photosynthesis leaf spac-model

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

acclimation

display_name: acclimation

invasive-species

display_name: invasive-species

leaf

display_name: leaf

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

spac-model

display_name: spac-model


en: This dataset contains experimental acoustic and vibration signals recorded by the Phased Microphone Arrays (PMA) system during laboratory impact calibration tests. The PMA system is designed for surrogate monitoring of bedload transport. It consists of a stainless-steel plate mounted on elastomer supports and instrumented with an array of microphone elements and an accelerometer fixed to the internal plate. The microphone sensors (sensitivity = 11.2 mV/Pa, frequency response = 10 Hz - 20 kHz) record air-pressure fluctuations caused by particle impacts, while the accelerometer (sensitivity = 50.0 mV/g, frequency response = 0.5 Hz - ~10 kHz) measures vibrations of the internal plate. All channels were synchronously sampled at 10 kHz using a 16-channel, 24-bit data acquisition system. Additional data and details on experimental setup, signal analysis, and interpretation are available in the associated publication.

en: Acoustic Data from the PMA Bedload Monitoring System

en: particle-size microphone natural-hazards bedload-transport acoustic-signals impact-test accelerometer localization monitoring-techniques surrogate-measurement

accelerometer

display_name: accelerometer

acoustic-signals

display_name: acoustic-signals

bedload-transport

display_name: bedload-transport

impact-test

display_name: impact-test

localization

display_name: localization

microphone

display_name: microphone

monitoring-techniques

display_name: monitoring-techniques

natural-hazards

display_name: natural-hazards

particle-size

display_name: particle-size

surrogate-measurement

display_name: surrogate-measurement


en:
Data and code for the paper published in Ecography: Community structure and range shifts in Arctic marine fish under climate change
Abstract:
Arctic marine ecosystems are rapidly transforming due to climate change. Warming temperatures and shrinking sea ice are enabling boreal fish to expand northward, possibly disturbing cold-adapted Arctic species assemblages. Species range shifts have been documented in the Bering and Barents Seas, raising concerns about ecosystem restructuring. Range shifts are especially difficult to detect in the Arctic due to sparse and inconsistent data. Here, we studied fish composition from eDNA water samples taken in East Greenland, Svalbard, the Barents Sea, and the Kara Sea during the TOPtoTOP and Arctic Century expeditions. We examined the environmental drivers of fish community structure using global dissimilarity models. We calculated the decadal rate of temperature change to identify the fastest-changing areas. We compared fish detections from eDNA with published historical records for the Kara Sea to assess possible range expansions. We found that temperature was the main factor influencing the taxa turnover of fish communities, with Gadidae and Liparis sp. driving the greatest compositional differences. Over the past 30 years, temperatures increased by 0.2 to 0.6°C per decade at our study sites, with the highest increases in western Svalbard and the lowest in the eastern Kara Sea. Despite the apparent dependence on temperature, we identified only one species detected outside its known latitudinal range, and five species in the Kara Sea with recent occurrences or representing an extended distribution. Our study suggests that temperature, the main driver of fish community assembly, is increasing rapidly in the Arctic, and a few species have likely already shifted recently, or at least their detections are new in some areas. While these detections cannot be definitively linked to range shifts, our results highlight the need to improve monitoring of high-latitude fish communities to detect and predict future ecosystem changes.
Article:
Marques, V., Fopp, F., Jaquier, M., Ellingsen, K. E., Yoccoz, N., Jucker, M., ...Pellissier, L. (2025). Community structure and range shifts in Arctic marine fish under climate change. Ecography, e8014. doi: 10.1002/ecog.08014
Data:
The resource contains a zip file with the entire project structure.
Data README:
 Intro
This repo presents data and code associated with the paper "Community structure and range shifts in Arctic marine fish under climate change" published in Ecography
 Usage
Launch the `main.R` script to reproduce the entire analysis.
It executes code blocks to create the data necessary for the analysis and then creates the figures.
💣 attention, total size is expected ~20 Go and the script will query the CMEMS database to fetch environmental data
 Tools
To make the scripts run, you need R, R packages (see session info below), python3, and the copernicusmarine python tool (https://pypi.org/project/copernicusmarine/).
 SessionInfo
```
sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS 15.5
Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Zurich
tzcode source: internal
attached base packages:
[1] stats     graphics  grDevices
[4] utils     datasets  methods
[7] base
other attached packages:
 [1] lwgeom_0.2-14
 [2] metR_0.15.0
 [3] ggtext_0.1.2
 [4] scico_1.5.0
 [5] ggnewscale_0.5.0
 [6] colorspace_2.1-1
 [7] climetrics_1.0-15
 [8] rts_1.1-14
 [9] xts_0.14.0
[10] zoo_1.8-12
[11] ggpubr_0.6.0
[12] adespatial_0.3-23
[13] ggspatial_1.1.9
[14] colorplaner_0.1.4
[15] ape_5.8
[16] factoextra_1.0.7
[17] corrgram_1.14
[18] FactoMineR_2.11
[19] betapart_1.6
[20] gdm_1.5.0-9.1
[21] terra_1.7-78
[22] rnaturalearth_1.0.1
[23] ggrepel_0.9.5
[24] vegan_2.6-6.1
[25] lattice_0.22-6
[26] permute_0.9-7
[27] cowplot_1.1.3
[28] tidyterra_0.6.1
[29] sf_1.0-16
[30] egg_0.4.5
[31] gridExtra_2.3
[32] patchwork_1.2.0
[33] viridis_0.6.5
[34] viridisLite_0.4.2
[35] mgcv_1.9-1
[36] nlme_3.1-165
[37] MBA_0.1-0
[38] reshape2_1.4.4
[39] conflicted_1.2.0
[40] lubridate_1.9.3
[41] forcats_1.0.0
[42] stringr_1.5.1
[43] dplyr_1.1.4
[44] purrr_1.0.2
[45] readr_2.1.5
[46] tidyr_1.3.1
[47] tibble_3.2.1
[48] ggplot2_3.5.1
[49] tidyverse_2.0.0
[50] devtools_2.4.5
[51] usethis_2.2.3
loaded via a namespace (and not attached):
  [1] splines_4.4.0
  [2] later_1.3.2
  [3] bitops_1.0-7
  [4] minpack.lm_1.2-4
  [5] XML_3.99-0.16.1
  [6] lifecycle_1.0.4
  [7] rstatix_0.7.2
  [8] doParallel_1.0.17
  [9] MASS_7.3-60.2
 [10] flashClust_1.01-2
 [11] backports_1.5.0
 [12] magrittr_2.0.3
 [13] rmarkdown_2.27
 [14] yaml_2.3.8
 [15] remotes_2.5.0
 [16] httpuv_1.6.15
 [17] sp_2.1-4
 [18] sessioninfo_1.2.2
 [19] pkgbuild_1.4.4
 [20] mapproj_1.2.11
 [21] pbapply_1.7-2
 [22] DBI_1.2.3
 [23] RColorBrewer_1.1-3
 [24] ade4_1.7-22
 [25] maps_3.4.2
 [26] abind_1.4-5
 [27] pkgload_1.3.4
 [28] RCurl_1.98-1.14
 [29] itertools_0.1-3
 [30] yaImpute_1.0-34
 [31] rcdd_1.6
 [32] units_0.8-5
 [33] adegenet_2.1.10
 [34] codetools_0.2-20
 [35] xml2_1.3.6
 [36] adephylo_1.1-16
 [37] DT_0.33
 [38] tidyselect_1.2.1
 [39] RNeXML_2.4.11
 [40] raster_3.6-26
 [41] farver_2.1.2
 [42] jsonlite_1.8.9
 [43] e1071_1.7-14
 [44] phylobase_0.8.12
 [45] ellipsis_0.3.2
 [46] iterators_1.0.14
 [47] emmeans_1.10.4
 [48] systemfonts_1.1.0
 [49] foreach_1.5.2
 [50] progress_1.2.3
 [51] tools_4.4.0
 [52] ragg_1.3.2
 [53] snow_0.4-4
 [54] Rcpp_1.0.13
 [55] glue_1.8.0
 [56] xfun_0.44
 [57] withr_3.0.0
 [58] fastmap_1.2.0
 [59] boot_1.3-30
 [60] latticeExtra_0.6-30
 [61] fansi_1.0.6
 [62] spData_2.3.1
 [63] digest_0.6.35
 [64] timechange_0.3.0
 [65] R6_2.5.1
 [66] mime_0.12
 [67] estimability_1.5.1
 [68] wk_0.9.1
 [69] textshaping_0.4.0
 [70] jpeg_0.1-10
 [71] utf8_1.2.4
 [72] generics_0.1.3
 [73] data.table_1.15.4
 [74] class_7.3-22
 [75] prettyunits_1.2.0
 [76] httr_1.4.7
 [77] htmlwidgets_1.6.4
 [78] scatterplot3d_0.3-44
 [79] spdep_1.3-5
 [80] pkgconfig_2.0.3
 [81] gtable_0.3.5
 [82] picante_1.8.2
 [83] adegraphics_1.0-21
 [84] htmltools_0.5.8.1
 [85] carData_3.0-5
 [86] profvis_0.3.8
 [87] multcompView_0.1-10
 [88] scales_1.3.0
 [89] leaps_3.2
 [90] png_0.1-8
 [91] doSNOW_1.0.20
 [92] geometry_0.4.7
 [93] rnaturalearthhires_1.0.0.9000
 [94] knitr_1.47
 [95] rstudioapi_0.16.0
 [96] rncl_0.8.7
 [97] uuid_1.2-0
 [98] tzdb_0.4.0
 [99] checkmate_2.3.1
[100] coda_0.19-4.1
[101] magic_1.6-1
[102] proxy_0.4-27
[103] cachem_1.1.0
[104] KernSmooth_2.23-24
[105] parallel_4.4.0
[106] miniUI_0.1.1.1
[107] s2_1.1.6
[108] pillar_1.9.0
[109] grid_4.4.0
[110] vctrs_0.6.5
[111] urlchecker_1.0.1
[112] promises_1.3.0
[113] car_3.1-2
[114] xtable_1.8-4
[115] cluster_2.1.6
[116] evaluate_0.24.0
[117] mvtnorm_1.2-5
[118] cli_3.6.3
[119] compiler_4.4.0
[120] rlang_1.1.4
[121] crayon_1.5.2
[122] ggsignif_0.6.4
[123] labeling_0.4.3
[124] interp_1.1-6
[125] classInt_0.4-10
[126] plyr_1.8.9
[127] fs_1.6.4
[128] stringi_1.8.4
[129] deldir_2.0-4
[130] munsell_0.5.1
[131] Matrix_1.7-0
[132] hms_1.1.3
[133] seqinr_4.2-36
[134] shiny_1.8.1.1
[135] gridtext_0.1.5
[136] igraph_2.0.3
[137] broom_1.0.6
[138] memoise_2.0.1
[139] fastmatch_1.1-4
```
 Data content and reproducibility
Uncleaned raw table out of the bioinformatics pipeline can be found concatenated in `outputs/table_raw_before_cleaning.csv`, yet we caution readers to properly read the cleaning scripts should they wish to reproduce our analysis and this file is presently uncleaned.

en: Data and code for Community structure and range shifts in Arctic marine fish under climate change

en: environmental-dna climate-change community-structure arctic fish

arctic

display_name: arctic

climate-change

display_name: climate-change

community-structure

display_name: community-structure

environmental-dna

display_name: environmental-dna

fish

display_name: fish