maintainer: Maria Elvira Murazzi

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

en: Nanoplastic in forests experiment

en:
Data embargoed until August 2022, and it will be provided upon request

-  excel file containing: two working sheets (leaf supply and root supply experiment) with a table with the values 13C-nanopolystyrene in the different tissues of the two forest tree species; graph showing the differences between controls and treatments of 13C-nanopolystyrene enrichment for each tissue of each forest tree species; ANOVA table showing significant values after having exposed the tree species to 13C-nanopolystyrene

en:
The fate of plastic in the environment is of global concern, because its production recently has
increased strongly and it accumulates in terrestrial and aquatic ecosystems. Although some knowledge on
its role in aquatic and terrestrial ecosystems was gained in the recent decade, hitherto very little is known
about the impact of micro and nanoplastics in forest ecosystems.

The aim of this pioneering project was to explore if nanoplastics are taken up by forest trees species
through leaves or roots. In greenhouse experiments, we exposed leaves or roots of seedling of two forest
trees species to solutions with highly 13C-labelled polystyrene nanoparticles (13C-nPS, 99 atom%) and
examined if they were incorporated in different above- and belowground tissues.

Treated part of the trees for both species showed significant 13C-enrichment, indicating that trees take up nanoparticles. However, the overall 13C signal strength in tissues that were not exposed to the 13C label remained low (Δδ13C<1‰) and was confined to a few seedlings, leaving it ambiguous whether nanoplastic transport occurs or not.

We acknowledge that the new method developed might be not sensitive enough to unequivocally detect
mechanisms of nanoplastic uptake and transport at environmentally realistic concentrations.

forest-trees

display_name: forest-trees

nanoplastic

display_name: nanoplastic

polystyrene

display_name: polystyrene

uptake

display_name: uptake

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

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


en: sensor-technology eota dissipated-energy windthrow breaking-energy rockfall-experiments forest rockfall lying-deadwood stonenode protective-effect

state: active

type: dataset

media_type: application/zip

en: All soil moisture data measurements acieved by GS1 and MPS6 sensors and logged by a Decagon EM 50 data logger. Additionally, the location of the data logger (.shp file) and the area, which is considered as represented by the measurements (also .shp files) are saved in this .zip file.

format: ZIP

en: This archive contains all recorded runs from RF32, RF33, RF35, RF37 and RF44 in HD quality (roughly 1900x1200 pixels). The file size is, therefore rather big (>40GB). Single videos can be downloaded in the "individual video directory"

en: input data for the ramms simulations including DEM (.asc), the deadwood files (.pts), the treefile, the release line, othophoto, rocks and soil parameters.

en: LiDAR data sets of the experimental area.

en: During RF44 (10.04.2021) we placed several deadwood logs. Their arrangement was recorded by a terrestrial laser scanner. Additionally, the logs diameter were measured every 3 m (within the excel file)

en: A (not further analyzed) attempt to describe the tree deflections after rock impacts summarized in an Excel spreadsheet.

en: The spatial data, such as the deposition points, the orthophotos, the digital surface models (drones), the detected and measured trees, and the shape files of the deadwood-areas, are summarized in this archive.

en: Matlab datasets containing all the available in-situ StoneNode data featureing acceleration (acc) and rotational data (gyr).

en: VideoArchive_HD_Resolution (individual video directory)

format: SERVICE

en: Figures of the rotational and gyroscopic StoneNodeData and where available the impact categories.

en:
Two tables per experimental run: a jump table including all parablic jumps, sliding and rolling. On the other hand also the table of all soil impacts, inbetween two jumps.
These tables are the results from the trajectory reconstruction, which based on the synchronisation of StoneNode data the Videodata and their geolocations. This synchronisation was dane based on the excel spread sheets, which are aditionally saved in this zip folder.

en: We conducted an experimental rockfall campaign on a forested slope with deadwood and on with the windthrown area cleared in Schiers (CH). Two different rock categories were used: natural rocks with masses between 30 and 85 kg and artificial EOTA-concrete rocks with rock masses ranging from 45 kg up to 3200 kg. In contrast to the intended research article publication, also all information about the experimental runs of the smaller rock masses are available. Besides the geometries of those rocks, the data set contains three LiDAR point clouds, orthophotos, the release point (and release line used in RAMMS), the retrieved single tree positions with DBH, and energy absorption threshold, video footage, and all reconstructed trajectories.

breaking-energy

display_name: breaking-energy

dissipated-energy

display_name: dissipated-energy

eota

display_name: eota

forest

display_name: forest

lying-deadwood

display_name: lying-deadwood

protective-effect

display_name: protective-effect

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

sensor-technology

display_name: sensor-technology

stonenode

display_name: stonenode

windthrow

display_name: windthrow

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Shape still matters - experimental quantification of deadwood effects on rockfall dynamics


maintainer: James W. Kirchner

en: irf system-identification deconvolution de-mixing nonlinear-deconvolution transfer-function arma-noise irfnnhsr impulse-response-function greens-function time-series-analysis

en: Impulse Response Function script

en: Benchmark demonstration scripts and results

en: README file for IRFnnhs.R and benchmark demonstration scripts

en:
The R script IRFnnhs.R, which efficiently estimates impulse response functions for environmental systems that are nonlinear, nonstationary, or heterogeneous, based on their input and output time series.

Scripts and results for a series of benchmark tests are also provided, to accompany Kirchner, J.W., Impulse response functions for heterogeneous, nonstationary, and nonlinear systems, estimated by deconvolution and demixing of noisy time series, _Sensors_, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022.

arma-noise

display_name: arma-noise

de-mixing

display_name: de-mixing

deconvolution

display_name: deconvolution

greens-function

display_name: greens-function

impulse-response-function

display_name: impulse-response-function

irf

display_name: irf

irfnnhsr

display_name: irfnnhsr

nonlinear-deconvolution

display_name: nonlinear-deconvolution

system-identification

display_name: system-identification

time-series-analysis

display_name: time-series-analysis

transfer-function

display_name: transfer-function

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Impulse response functions for nonlinear nonstationary and heterogeneous systems


en: occupancy-models biogeographical-region insects infospecies switzerland elevation insect-decline butterflies

en: Mean annual occupancy estimates

media_type: text/csv

en:
This file contains mean annual occupancy for all 390 species, study years (1970/1980-2020) and study regions (9 bioclimatic zones) as estimated from occupancy-detection models (MCMC: 4 chains, 1000 warmup each, 1000 sampling each). Each row corresponds to a unique combination of species, year and zone. The following columns are included:

-  **species**: Species name used in analyses

-  **year**: Year of the observation

-  **biogeo_elevation**: Bioclimatic zone of the observation, which is a combination of 5 biogeographic regions (Jura, Plateau, Nothern Alps, Central Alps, Southern Alps) and 2 elevational classes (high: above 1000 m. asl, low: below 1000 m. asl)

-  **n_squares**: Number of 1 km x 1 km squares of the respective zone, which were included in the analyses

-  **occ_m\_i[....]**: Mean annual occupancy estimates. Each column corresponds to one iteration of the MCMC sampling (4000 columns in total).

format: CSV

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

**Paper Citation**:

Neff, F., Korner-Nievergelt, F., Rey, E., Albrecht, M., Bollmann, K., Cahenzli, F., Chittaro, Y., Gossner, M. M., Martínez-Núñez, C., Meier, E. S., Monnerat, C., Moretti, M., Roth, T., Herzog, F., Knop, E. 2022. Different roles of concurring climate and regional land-use changes in past 40 years' insect trends. Nature Communications, DOI: [10.1038/s41467-022-35223-3](https://doi.org/10.1038/s41467-022-35223-3)

Please cite this paper together with the citation for the datafile. Please also refer to this publication for details on the methods.

 Summary

Mean annual occupancy estimates for 390 insect species (215 butterflies [Papilionoidea, incl. Zygaenidae moths], 103 grasshoppers [Orthoptera], 72 dragonflies [Odonata]) for nine bioclimatic zones in Switzerland. Covers the years 1970-2020 (for butterflies) and 1980-2020 (for grasshoppers and dragonflies). Mean occupancy denotes the average number of 1 km x 1 km squares in a zone occupied by the focal species. Occupancy estimates stem from occupancy-detection models run with species records data hosted and curated by [info fauna](http://www.infofauna.ch). Data on the level of single MCMC iterations of model fitting are included (4000 sampling iterations). The nine bioclimatic zones were defined based on biogeographic regions and two elevation classes (square above or below 1000 m. asl)

biogeographical-region

display_name: biogeographical-region

butterflies

display_name: butterflies

elevation

display_name: elevation

infospecies

display_name: infospecies

insect-decline

display_name: insect-decline

insects

display_name: insects

occupancy-models

display_name: occupancy-models

switzerland

display_name: switzerland

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: Mean insect occupancy 1970–2020


maintainer: Albrecht von Boetticher

en: natural-hazard interfoam hangmuren dberisintermixing shallow-landslide barrier-impact-simulation debris-flow murgang finite-volumes

media_type: application/pdf

en: These are the installation instructions for debrisInterMixing4

format: PDF

mimetype: application/pdf

en: debrisInterMixing for OF-Version 6

mimetype: application/zip

en: Installation Instructions for debrisInterMixing-6

en:
This version of debrisInterMixing is based on OpenFOAM Version 4.x and was tested on Ubuntu 18.04.1 LTS.
Please follow the instructions given in ReadMe_debrisInterMixing4.pdf for installation.

en:
Here the updated versions of debrisInterMixing are provided for download. The first OpenFoam-compatible Version 2.3.x are available as supplement to v. Boetticher, A., Turowski, J. M., McArdell,W. B., Rickenmann, D., Hürlimann, M., Scheidl, C., and Kirchner, J. W.: DebrisInterMixing-2.3: A Finite Volume solver for three dimensional debris flow simulations based on two calibration parameters. Part two: model validation with experiments. Geoscientific Model Development, 10, 11: 3963-3978. doi: 10.5194/gmd-10-3963-2017.
DebrisInterMixing is a Volume-of-Fluid based Finite Volume code that accounts for shear-thinning sensitive shares of fine sediment suspension together with pressure-sensitive components of the gravel grains within debris flow mixtures. All model properties can be derived from a material sample except for a grid-sensitive calibration parameter.
For more information, please contact albrecht.vonboetticher@wasserbau.ch.

barrier-impact-simulation

display_name: barrier-impact-simulation

dberisintermixing

display_name: dberisintermixing

debris-flow

display_name: debris-flow

finite-volumes

display_name: finite-volumes

hangmuren

display_name: hangmuren

interfoam

display_name: interfoam

murgang

display_name: murgang

natural-hazard

display_name: natural-hazard

shallow-landslide

display_name: shallow-landslide

en: Three-dimensional debris flow simulation tool debrisInterMixing


maintainer: EnviDat Support

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

en: Lake water level scenarios CH2018

en: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

format: XLS

en: Lake characteristics

en: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

en: Lake outflow scenarios CH2018

en: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.

The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).

In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes


number-of-forest-plots

title_for_slug: number-of-forest-plots

en:
Number of forest sample plots (Plots).

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

area-of-largest-gap-aerial-photo

display_name: area-of-largest-gap-aerial-photo

avalanches-silvaprotect

display_name: avalanches-silvaprotect

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

diversity-of-woody-species-in-the-stand

display_name: diversity-of-woody-species-in-the-stand

economic-region

display_name: economic-region

forest

display_name: forest

forest-function-recreation

display_name: forest-function-recreation

infrastructure-for-recreation

display_name: infrastructure-for-recreation

inner-edge-of-stand

display_name: inner-edge-of-stand

intensity-of-pasturing

display_name: intensity-of-pasturing

intensity-of-recreational-use

display_name: intensity-of-recreational-use

landslide-mudflow-silvaprotect

display_name: landslide-mudflow-silvaprotect

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

number-of-forest-plots

display_name: number-of-forest-plots

occurence-of-remnants-of-root-plates

display_name: occurence-of-remnants-of-root-plates

occurrence-of-root-plates

display_name: occurrence-of-root-plates

overall-presence-of-dead-wood

display_name: overall-presence-of-dead-wood

overloads-and-disturbances

display_name: overloads-and-disturbances

ownership

display_name: ownership

pile-of-branches-and-logs

display_name: pile-of-branches-and-logs

processes-in-channels-silvaprotect

display_name: processes-in-channels-silvaprotect

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

recreational-use-seasonality

display_name: recreational-use-seasonality

rockfall-silvaprotect

display_name: rockfall-silvaprotect

snag

display_name: snag

soil-type-of-damage

display_name: soil-type-of-damage

stumps-and-lying-dead-wood

display_name: stumps-and-lying-dead-wood

surroundings-of-soil-damage

display_name: surroundings-of-soil-damage

type-of-gaps

display_name: type-of-gaps

type-of-pasturing

display_name: type-of-pasturing

type-of-recreation-camping

display_name: type-of-recreation-camping

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: defoliation sirex decline wood-wasps ips-acuminatus pissodes tomicus pinus bark-beetles phaenops

en: see ReadMe

en: After a major dieback of Scots pines in the Valais, an inner Alpine valley in Switzerland, the colonization of differently vigorous pines by stem and branch insects was investigated to assess their role in tree mortality. At 2 locations, the needle loss (defoliation) of some 500 pine trees was assessed twice a year. Of these trees, 34-36 trees were cut each year between 2001-2005 across all defoliation classes. From each tree, two 75-cm bolts were cut from both the stem and thick branches. They were incubated in photo-eclectors (metal cabinets) set up in a greenhouse where the insects could develop under the bark. The emerged adults were collected in water-filled eclector boxes and identified to species level by specialists. Attack time was estimated from the development time of each insect species emerged. The colonisation densities of the trees were related to the transparency level of each host tree at the time of attack.

bark-beetles

display_name: bark-beetles

decline

display_name: decline

defoliation

display_name: defoliation

ips-acuminatus

display_name: ips-acuminatus

phaenops

display_name: phaenops

pinus

display_name: pinus

pissodes

display_name: pissodes

sirex

display_name: sirex

tomicus

display_name: tomicus

wood-wasps

display_name: wood-wasps

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Infestation of Scots pines with different vitalities by bark and wood boring insects


maintainer: Elisabeth Hafner

en: snow validation avalanche-hazard-mapping avalanche satellite

en: Satellite Avalanche Mapping Validation data and data description

en: 14 shapefiles to be used only together with the data description also provided as a pdf.

en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).

Coordinate system: CH1903+_LV95

The generation of this dataset is described in detail in:

Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

satellite

display_name: satellite

snow

display_name: snow

validation

display_name: validation

en: Satellite avalanche mapping validation data


en: lichen lichen-distribution swisslichens lichen-conservation biodiversity national-data-centre switzerland

en: data extract 20191113

en:
This dataset provides distribution data of lichens in Switzerland of the National Data and Information Centre, called Swiss Lichens. SwissLichens is a partner of InfoSpecies, the network of Swiss data and information centres for fauna, flora and fungi. One of its main objectives is to document the spatial and temporal distribution of species in Switzerland.

The SwissLichens database currently contains more than 120’000 georeferenced lichen observations, distributed throughout Swizerland. The oldest observations date back to 1790. A large portion of the records dtae from the last two decades of the last century to the present day. The database is continuously updated with new findings. The data have been validated and originate from national inventories, from research projects, from floristic observations by volunteers as well as from private and public herbaria and from the literature.

Each record consists of the species name, information of the location (Swiss Coordinates, precision of the coordinates, elevation above sea level, municipality and canton), the date of observation, the ecotype (epiphytic, terricol, lignicol, saxicol), as well as information on the conservation status of the species (red list status, conservation priority status, status in the Nature and Cultural Heritage Act). Information on the ecology (habitat, substrate) is partially available.
They are free of charge for research projects and can be requested from InfoSpecies using a form.

Licence under www.infospecies.ch. Data is free of charge for research projects and available on request.

biodiversity

display_name: biodiversity

lichen

display_name: lichen

lichen-conservation

display_name: lichen-conservation

lichen-distribution

display_name: lichen-distribution

national-data-centre

display_name: national-data-centre

swisslichens

display_name: swisslichens

switzerland

display_name: switzerland

en: SwissLichens - Distribution of lichens in Switzerland


photogrammetric-drone-data-dorfberg

maintainer: Yves Bühler

title_for_slug: photogrammetric-drone-data-dorfberg

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

en: Data Access

en:
- 3cm-resolution Orthophoto
- 10cm-resolution DSM
- 10cm-resolution snow depth raster
- original RGB images
- Agisoft Metashape Report

All products are also available as a cloud optimized geotiff.

en: The data was collected with a Wingtra Gen II drone and a Sony RX1R II sensor. In total, 10 flights were conducted at different dates, both in summer and winter. A DSM, an orthophoto, a snow depth raster and the original drone images from every flight are available at a high resolution (10cm and 3cm, respectively).

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

snow-distribution

display_name: snow-distribution

uav

display_name: uav

en: Photogrammetric Drone Data Dorfberg


carabid-beetles-in-forests

title_for_slug: carabid-beetles-in-forests

en: running-beetles trapping arthropoda carabidae forest coleoptera insects

en: SQL query used to extract the data from fauna database.

media_type: text/plain

en: Tab-delimited data of the according sql query.

format: TXT

en: Data extract in TAB-delimted format. First row is header, first column is counter.

en: Data query used on Fauna Database to retrieve the submitted data.

en:
Carabidae data from all historic up to the recent projects (21.10.2019) of WSL, collected with various methods in forests of different types.

Version 2 ('FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae') contains additional data field PROJ_FALLENBEZEICHNUNG.

Data are provided on request to contact person against bilateral agreement.

arthropoda

display_name: arthropoda

carabidae

display_name: carabidae

coleoptera

display_name: coleoptera

forest

display_name: forest

insects

display_name: insects

running-beetles

display_name: running-beetles

trapping

display_name: trapping

educ

en: Education, culture and sport

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: Carabid beetles in forests


latent-reserves-within-the-swiss-nfi

title_for_slug: latent-reserves-within-the-swiss-nfi

en: national-forest-inventory tree-mortality switzerland forest-reserves near-natural-forest

en: Data figure 7

en:
This file contains the data required to reproduce Figure 7:

- "SPECIES_GROUP" refers to the species groups used in the mortality analyses (spruce, fir, pine, larch, stone pine, beech, maple and ash, oak, chestnut, other broadleaves)
- "VARIABLE" refers to the explanatory variables used in the model and presented in the figure: DBH (diameter at breast height) and relBAI (relative basal area increment).
- "VALUE" refers to the the values of the variables for which predictions were made.
- "PRED_MORTALITY_PROB" refers to the predicted mortality probability for a given species group and value of either DBH or relBAI.

en: Data for mortality analyses

en:
This table contains the tree- and plot-level data necessary to conduct the tree mortality analyses:

* "DEAD" takes the value '0' when the tree was alive at NFI3 and '1' when it was observed dead
* "SPECIES" refers to which species group the tree belongs to
* "relBAL" is the relative basal area of larger trees
* "DBH" is the diameter at breast height
* "relBAI" is the relative basal area increment of the tree
* "BA" is the basal area in squared meters per hectare (stand-level)
* "STAND_DENSITY_LOG" is the logarithm of the stand density in number of stems per hectare
* "BEERS_ASPECT_CORR" is the Beers aspect corrected for slope of the plot
* "SLOPE_SQRT" is the squared root of the slope of the plot in percentage
* "ELEVATION" is the elevation of the plot in meters above sea level
* "AWC" is the available soil water-holding capacity in millimeters
* "VEGYEAR" is the number of vegetation years between the measurements of the plots at NFI2 and NFI3.

en: Data figure 6

en:
This file contains the data required to reproduce Figure 6:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "MORTALITY_RATE" refers to the mean annual mortality rate of each species group calculated according to Sheil and May (1996)
- "LOWER_CI" and "UPPER_CI" refer to the lower and upper confidence intervals on the mortality rates, calculated according to Sheil and May (1996).

Reference
Sheil, D., & May, R. M. (1996). Mortality and recruitment rate evaluations in heterogeneous tropical forests. Journal of Ecology, 84(1), 91–100. doi: 10.2307/2261703

en: Data figure 3

en:
This file contains the data required to reproduce Figure 3:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "VARIABLE" refers to the indicators described in the figure: Ellenberg indicators for light, temperature and moisture, as well as species richness.
- "mean" refers to the mean value of each indicator for each combination of forest type and elevation vegetation zone (corrected for the inclusion probability of each tree).
- "se" corresponds to the standard error.

For these calculations, site index was constrained to the range observed in 'latent reserves' with at least 40 years without intervention.

en: Data figure 2

en:
This file contains the data required to reproduce Figure 2:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "DENSITY" refers to the proportion of trees (corrected for the inclusion probability of each tree) within each combination of forest type, elevation vegetation zone and species group.

Young-growth trees are not included in the density calculation.

en: Data figure 8

en:
This file contains the data required to reproduce Figure 8:

* "SPECIES_GROUP" refers to the species groups used in the mortality analyses (spruce, fir, pine, larch, stone pine, beech, maple and ash, oak, chestnut, other broadleaves)
* "BASAL_AREA" refers to the values of the basal area in squared meters per hectare for which predictions were made
* "STAND_DENSITY" refers to the values of stand density in number of stems per hectare for which predictions were made
* "NORM_PRED_MORTALITY_PROB" refers to the normalised predicted mortality probability corresponding to a given species group and values of basal area and stand density.

en:
This table contains the tree-level information required to reproduce the charaterisation of 'latent reserves' and comparison to managed forests:

* "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
* "SOURCE" differentiate inventoried trees ("W", DBH greater or equal to 12 cm) and young-growth trees measured on subplots ("JW").
* "SPECIES" refers to the species code of the Swiss NFI.
* "SPECIES_GROUP" refers to which species group a tree belongs to (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
* "ALIVE_NFI2" takes the value '1' when the tree was alive at the previous inventory (NFI2). Trees with no value (NA) were not measured at NFI2. This variable should be used to calculate mortality rates, as only trees that were present at NFI2 can be used to calculate the mortality rate between NFI2 and NFI3.
* "DEAD" takes the value '1& when a tree was observed dead at NFI3, and the value '0' when it was observed alive.
* "INCLUSION_PROB" represents the inclusion probability of a tree i.e. the number of trees that a given tree represents per hectare. This number depends on the DBH of the tree and on whether the plot area was reduced by a boundary (e.g. a forest edge). This variable should be used to weight the trees in some calculations.
* "DBH" is the diameter at breast height of a tree in centimeters.
* "LIGHT", "TEMPERATURE", "MOISTURE" refer to the value of the Ellenberg indicators for light, temperature and moisture that are species-specific. 'NA' is attributed when the value of an indicator is not available for a given species.

en: Data figure 4

en:
This file contains the data required to reproduce Figure 4:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
- "SPECIES_GROUP" refers to all the trees of a given species group (spruce, fir, pine, larch, stone pine, other conifers, beech, maple, ash, oak, chestnut, other broadleaves)
- "DBH_CL" refers to the DBH (diameter at breast height) class to which a tree belongs to, in centimetres.
- "DENSITY" refers to the proportion of trees (corrected for the inclusion probability of each tree) within each combination of forest type, elevation vegetation zone, species group and DBH class.

The inclusion probability of each tree was accounted for in the density calculation.

en: Data figure 5

en:
This file contains the data required to reproduce Figure 5:

- "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
- "DOMINANT_SPECIES" refers to the dominant species in a given plot (spruce, fir, other conifers, beech, other broadleaves)
- "VARIABLE" refers to the attributes described in the figure: basal area in squared meters per hectare, median DBH in cm, stand density in number of stems per hectare, deadwood in tons per hectare, site index in tons per hectare per year. Basal area, median DBH and stand density are given both with and without including young-growth trees.
- "mean" refers to the mean value of each attribute for each combination of forest type and dominant species (corrected for the inclusion probability of each tree).
- "se" corresponds to the standard error.

For these calculations, site index was constrained to the range observed in ‘latent reserves’ with at least 40 years without intervention. Additionally, only NFI sample plots from the montane and subalpine zones were used as colline and submontane NFI plots from ‘latent reserves’ and managed forests are located in different geographical regions.

en:
This table contains the plot-level information required to reproduce the charaterisation of 'latent reserves' and comparison to managed forests:

* "FOREST_TYPE" states whether a row corresponds to managed forests or to 'latent reserves' with a given number of years without human intervention (for example, 'LATENT_RESERVE40' are the 'latent reserves' with at least 40 years without human intervention)
* "ELEV_VEG_ZONE" refers to the elevation vegetation zone (colline and submontane, montane or subalpine)
* "DOMINANT_SPECIES" refers to the dominant species in a given plot (spruce, fir, other conifers, beech, other broadleaves)
* "TIME_SINCE_INTERVENTION" refers to the numbers of years since the last human intervention on the plot. This variable should be used to set the threshold of time since last intervention one wants to use to define 'latent reserves'.
* "VEGYEAR" refers to the number of vegetation years between the measurements of a plot for NFI2 and NFI3.
* "BA" provides the basal area in squared meters per hectare of a plot calculated from trees having a DBH of at least 12 cm.
* "BA_WITH_YG" provides the basal area in squared meters per hectare of a plot calculated from trees having a DBH of at least 12 cm as well as young growth trees.
* "STAND_DENSITY" provides the stand density in number of stems per hectare of a plot calculated from trees having a DBH of at least 12 cm.
* "STAND_DENSITY_WITH_YG" provides the stand density in number of stems per hectare of a plot calculated from trees having a DBH of at least 12 cm as well as young growth trees.
* "SITE_INDEX" refers to the site index of a plot, i.e. the total biomass productivity calculated according to Keller (1976).
* "DEADWOOD" refers to the amount of deadwood of a plot in tons per hectare.

******

Reference
Keller, W. (1976). Einfacher ertragskundlicher Bonitätsschlüssel für Waldbestände in der Schweiz. Zurich, Switzerland: ETH Zurich.

en:
The files refer to the data used in Portier et al. "‘Latent reserves’: a hidden treasure in National Forest Inventories" (2020) *Journal of Ecology*.

**'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database:

* Shrub forests were excluded.
* Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested.
* To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994).
* Plots had to originate from natural regeneration.
* Intensive livestock grazing must never have occurred on the plots.

The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php).

****

The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper.

The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement.

forest-reserves

display_name: forest-reserves

national-forest-inventory

display_name: national-forest-inventory

near-natural-forest

display_name: near-natural-forest

tree-mortality

display_name: tree-mortality

envidat

en: EnviDat: the Environmental Data Portal

en: 'Latent reserves' within the Swiss NFI


en: number-of-dead-persons avalanche-fatalities number-of-caught-persons avalanche-accidents avalanche-accident-statistics

en: Fatal avalanche accidents in Switzerland since 1936/37

en:
**When using this data, please consider and adhere to the associated [Terms of Use](https://www.slf.ch/en/services-and-products/data-and-monitoring/slf-data-service.html)**.

This data collection contains information concerning all known accidents by snow avalanches in Switzerland with at least one fatality. The data set commences on 01/10/1936. After the completion of a hydrological year, the new data is added.

The following information is provided:

 * avalanche identifier
 * date of the accident
 * accuracy of the date in range of days before and after
 * hydrological year (always from first of october to end of september)
 * canton
 * municipality
 * start zone point latitude
 * start zone point longitude
 * start zone point accuracy (in meters)
 * start zone point elevation (in meteres above sea level)
 * slope aspect (main orientation of start zone)
 * slope inclination (in degree, steepest point within start zone)
 * forecasted avalanche danger level 1 (first danger)
 * forecasted avalanche danger level 2 (second danger)
 * accident within the core zone (most dangerous aspect and elevation as mentioned in the forecast)
 * number of dead persons
 * number of caught persons
 * number of fully buried persons
 * activity/location of the accident party at the time of the incident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

number-of-caught-persons

display_name: number-of-caught-persons

number-of-dead-persons

display_name: number-of-dead-persons

educ

en: Education, culture and sport

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.


maintainer: Dirk Nikolaus Karger

en: climate-change bioclim climatology climate temperature precipitation climate-layers free-climate-data

en: CHELSA Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA V2.1 (current)

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

format: GeoTIFF

en: CHELSA V1.2 (deprecated)

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.

Paper Citation:
 > _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017) [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

temperature

display_name: temperature


en: diurnal-cycle groundwater snowmelt ecohydrology evapotranspiration streamflow sap-flow diel-cycle

en: 30-minute time series

en: 30-minute hydrometeorological and ecohydrological time series.

mimetype: text/plain

en: MODIS EVI2 script

en: Google Earth Engine script for computing MODIS two-band enhanced vegetation index (EVI2) values and averaging them over subcatchments.

en: Metadata

en: Column descriptions for both data files, and map coordinates for all measurement locations.

en: Daily time series

en: Daily hydrometeorological and ecohydrological time series

en: MODIS NDSI script

en: Google Earth Engine script for computing MODIS normalized difference snow index (NDSI) values and averaging them over subcatchment areas.

en: Subcatchment polygons

en: Subcatchment polygons for use in the Google Earth Engine scripts.

en:
Hydrometerological and ecohydrological time series from Sagehen Creek and Independence Creek, Sierra Nevada, USA, illustrating hydrological responses to daily cycles in snowmelt and evapotranspiration forcing.

Data include 30-minute time series of

- weather variables,

- sap flow fluxes,

- groundwater levels (in two riparian transects of shallow groundwater wells),

- and stream stages (at 12 sites spanning a 500-meter elevation gradient),

and daily time series of

- temperature, precipitation, and snow water equivalent at three nearby snow telemetry stations

- diel cycle index values for groundwater levels and stream stages,

- and MODIS normalized difference snow index (NDSI) and enhanced vegetation index (EVI2) values averaged over selected subcatchments.

Google Earth Engine scripts for extracting the MODIS data are also provided.

diel-cycle

display_name: diel-cycle

diurnal-cycle

display_name: diurnal-cycle

ecohydrology

display_name: ecohydrology

evapotranspiration

display_name: evapotranspiration

groundwater

display_name: groundwater

sap-flow

display_name: sap-flow

snowmelt

display_name: snowmelt

streamflow

display_name: streamflow

en: Daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen and Independence Creeks, Sierra Nevada, USA


en: free-climate-data timeseries climate precipitation air-temperature century climate-layers minimum-temperature maximum-temperature

en: CHELSA Technical Documentation

en: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.

en: Data Access

en:
CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.

CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

century

display_name: century

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

timeseries

display_name: timeseries

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: CHELSAcruts -  High resolution temperature and precipitation timeseries for the 20th century and beyond


maintainer: Frank Techel

en: danger-level european-alps snow avalanche-forecast warning-regions

en: Forecast avalanche danger level

en: contains the highest forecast danger level (dangerLevelMax) for each day and warning region

mimetype: text/csv

en: shape file warning regions Alps

en:
This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci).
For details on the data please refer to this publication.
The dataset contains the following:
- shape files for the warning regions in the Alps
- highest forecast danger level for each warning region and day

avalanche-forecast

display_name: avalanche-forecast

danger-level

display_name: danger-level

european-alps

display_name: european-alps

snow

display_name: snow

warning-regions

display_name: warning-regions

en: Forecast avalanche danger level European Alps 2011 - 2015


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

en: climate realizations

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

climate-change-impact

display_name: climate-change-impact

cryosphere

display_name: cryosphere

natural-climate-variability

display_name: natural-climate-variability

rain-on-snow

display_name: rain-on-snow

snow-water-equivalent

display_name: snow-water-equivalent

uncertainty

display_name: uncertainty

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


maintainer: Virginie Marques

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

en: Code, data and figures

en: Here there are all the data and code to reproduce the figures and analysis presented in the paper, with a README.md file

en: Metabarcoding data

en: Raw metabarcoding data for both primers (teleo and 18S) and corresponding file to perform the demultiplexing and primer trimming

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

 Methods

**Sampling**
We sampled the Lilliehöök fjord on the west coast of Spitsbergen (Svalbard, Norway) over 3 days from 3 to 5 of August 2021. Samples were taken from the glacier front up to the fjord mouth of the Krossfjorden system, around 30 km long, after the Lilliehöök fjord merged with the mouth of Möller fjord. The fjord’s maximum depth has been recorded at 373 m (Svendsen et al. 2002) and has no sill at its entrance, thereby facilitating water exchange with the open ocean of the West Spitsbergen Current. We used a research vessel to sample 5 sites for a total of 15 samples, sampling 3 depths per site (3-m, chlorophyll a maximum and 85-m, unless sea floor was shallower). Shallow and intermediate samples between 3-m and 12-m represent ~35-L of water filtered in-situ using long tubing and a peristaltic pump, and all other deeper samples were taken from a total of 3 Niskin bottles (General Oceanics), representing 22-L of water sampled per sample. Water was filtered through a VigiDNA filtration capsule (SPYGEN) with a 0.20-µm pore size using an Athena peristaltic pump (Proactive Environmental Products, Bradenton, Florida) with a flow rate of ~1-L/min. Each sample was handled with single use tubing and gloves.

**Molecular**
To perform the amplification, we used two sets of primers: teleo (forward: ACACCGCCCGTCACTCT, reverse: CTTCCGGTACACTTACCATG; Valentini et al. 2016) and the universal eukaryotic 1389F/1510R primer pair, amplifying the V9-18S rDNA gene (Amaral-Zettler et al. 2009) (forward: TTGTACACACCGCCC, reverse: CCTTCYGCAGGTTCACCTAC).

 Data content:

+ Metabarcoding data: This zip file contains the 2 sequencing libraries filtered to only retain the samples used in the present study.
+ Code, data and figure: This zip file contains all data and code to reproduce the figures and the analysis in the study, with an associated README explaining the content of each folder.

 Additional informations
For more details, please see the Methods in the associated publication: DOI: 10.1007/s00300-023-03187-9.

biodiversity

display_name: biodiversity

dna-metabarcoding

display_name: dna-metabarcoding

environmental-dna

display_name: environmental-dna

fish

display_name: fish

fjord

display_name: fjord

marine

display_name: marine

plankton

display_name: plankton

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


weather-station-klosters

maintainer: Maxime Hervo

title_for_slug: weather-station-klosters

en: weather temperature wind raclets precipitation klosters

en: Weather Station Klosters

en: All in one weather station measuring temperature (°C), humidity (%), wind (m s‾ ¹) and precipitation type. The time format is: number of days from January 0, 0000, UTC.

en: A weather station (Lufft WS600) measured meteorological parameters at Klosters (LON: 9.880413, LAT: 46.869019). Detailed information on the specifications can be found [here](https://www.lufft.com/products/compact-weather-sensors-293/ws600-umb-smart-weather-sensor-1832/productAction/outputAsPdf/).

klosters

display_name: klosters

precipitation

display_name: precipitation

raclets

display_name: raclets

temperature

display_name: temperature

weather

display_name: weather

wind

display_name: wind

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


en: biodiversity time-series long-term switzerland insect-decline

en: Fused catching data 1987, 1997, 2019

en: Complete dataset of species and abundances per year an trap

en: Body size lookup-table

en: Carabidae

en: SQL query executed on WSL Fauna Database to retrieve the data

en: Heteroptera

en: Species incidence per year

en: Total abundance of species per year

en: Input data - species list and trophic guilds

en: List of found species and associated trophic guild

en: Staphylinidae

en: Species number and abundances per trap

en: Sum of species and abundances listed per trap

en: Sites and traps

en: Lookup table of trap and site locations

en: Climate data

en: Climate data of the respective sampling years

en: Capture data with size and mass

en: Complete capture data including body sizes and biomass values

en: Syrphidae

en: Data extract from WSL Fauna Database containing arthropod species and abundance data from 1987, 1997, 2019

en: Additional climate data on climate trend

en: Neuropteroidae

en: Coleoptera

en: R code

en: R code for data editing

en: Master thesis of Regula Gygax, 1999, at University of Zürich

en: The study is comparing in 1997 the trapping efficiency of a newly developed combination trap with traditional window traps and yellow pan traps. Study locations in the Limpach valley matched with a subset from a larger study, which was conducted in 1987.

en:
Recent publications about declines in arthropod biomass, abundance and species diversity
raise concerns and call for measures. Agricultural intensification is likely one cause for the negative trends. But rare long-term arthropod surveys conceal trends in arthropod communities in agricultural land. Here, we report about a standardized sampling of arthropod fauna in a Swiss agricultural landscape, repeated over 32 years (1987, 1997 and 2019). We sampled 8 sites covering 4 semi-natural and agricultural habitat types. Four trap types were used to capture a wide range of flying and ground dwelling arthropods between May and July. Over the three sampling periods, 58’255 specimens of 1’343 species were analysed. Mean arthropod biomass, abundance and species richness per trap was significantly higher in 2019 than in prior years and gamma diversity of the study area was highest in 2019. Biomass and abundance increased stronger in the flight traps than in the pitfall traps. The implementation of agri-environmental schemes has improved habitat quality since 1993, while landscape composition and pesticide and fertilizer use remained stable over the study period, both contributing to the findings. The results of this study contrast with outcomes of comparable investigations and highlight the importance of further long-term investigations on arthropod dynamics.

Data are provided on request to contact person against bilateral agreement.

en: Arthropod biomass, abundance and species richness trends over 32 years in the agricultural Limpach valley, Switzerland


en:
Sum of stem cross-section areas of all dead trees in a stand at a height of 1.3 m (dbh measurement height) recorded according to the NFI1 method.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

accessible-forest-without-shrub-forest

display_name: accessible-forest-without-shrub-forest

altitudinal-vegetation-zone

display_name: altitudinal-vegetation-zone

biogeographical-region

display_name: biogeographical-region

canton

display_name: canton

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

lower-higher-altitudinal-zones

display_name: lower-higher-altitudinal-zones

main-tree-species

display_name: main-tree-species

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

tree-state-standing-lying

display_name: tree-state-standing-lying

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Basal area of dead wood NFI1


en: structure-from-motion forest-inventory 3d-point-cloud terrestrial-laser-scanning terrestrial-photogrammetry unmanned-aerial-vehicle-laser-scanning mobile-laser-scanning lidar

en:
Close Range Remote Sensing Benchmark for different LiDAR and photogrammetric Sensors in a mixed temperate forest.
Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices.

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

mobile-laser-scanning

display_name: mobile-laser-scanning

structure-from-motion

display_name: structure-from-motion

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

terrestrial-photogrammetry

display_name: terrestrial-photogrammetry

unmanned-aerial-vehicle-laser-scanning

display_name: unmanned-aerial-vehicle-laser-scanning

en: Ramerenwald Close Range Remote Sensing Benchmark


en: icp-forests swiss-forest-lab long-term-forest-ecosystem-research damage-causes crown-condition forest-vitality damaging-agents forest-condition

en: Data Request

en:
Annual Crown Condition Assessment including mortality and removal and Damage Causse Assessment on the Sanasilva-Sites and LWF plots.

 Purpose:

To assess tree and forest health and its changes and to assess occurence and extent of diseases

 Manual Citation:

 * Matthias Dobbertin, Christian Hug, Andreas Schwyzer, Serge Borer, Hanna Schmalz, 2016: Aufnahmeanleitung Kronenansprachen auf den Sanasilva- und den LWF-Flächen (Version 10). Sanasilva Inventur und Langfristige Waldökosystem-Forschung, Birmensdorf, 86 S. [>>>](https://www.wsl.ch/fileadmin/user_upload/WSL/Wald/Waldentwicklung_Monitoring/LWF/Sanasilva/ssi_anleitung_v10_extern.pdf)

 * Eichhorn J, Roskams P, Potocic N, Timmermann V, Ferretti M, Mues V, Szepesi A, Durrant D, Seletkovic  I,  Schröck  H-W,  Nevalainen  S,  Bussotti  F,  Garcia  P,  Wulff  S,  2016:  Part  IV:  Visual  Assessment of Crown Condition and Damaging Agents. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 49 p. + Annex [>>>](https://www.icp-forests.org/pdf/manual/2016/ICP_Manual_2017_02_part04.pdf )

 Paper Citation:

 * BAFU (2017) Jahrbuch Wald und Holz 2017. Umwelt-Zustand, Bundesamt für Umwelt, Bern, Vol. 1718: 110 p. [>>>](http://www.bafu.admin.ch/uz-1718-d)

 * Michel A, Seidling W, Prescher A K (2018) Forest Condition in Europe. 2018 Technical Report of ICP Forests. Report under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). BFW-Dokumentation 25/2018, BFW Austrian Research Centre for Forests, Vienna, 92 p. [Technical Reports](http://icp-forests.net/page/icp-forests-technical-report)

 * Brang P., 1998: Sanasilva-Bericht 1997. Zustand und Gefährdung des Schweizer Waldes – eine Zwischenbilanz nach 15 Jahren Waldschadenforschung. Berichte der Eidg. Forschungsanstalt für Wald, Schnee und Landschaft, Vol. 345. Eidg. Forschungsanstalt WSL, Birmensdorf, 102 S. [>>>](https://www.dora.lib4ri.ch/wsl/islandora/object/wsl:14555)

crown-condition

display_name: crown-condition

damage-causes

display_name: damage-causes

damaging-agents

display_name: damaging-agents

forest-condition

display_name: forest-condition

forest-vitality

display_name: forest-vitality

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

swiss-forest-lab

display_name: swiss-forest-lab

en: Crown Condition Assessment and Damage Cause Assessment Sanasilva


en: drought switzerland dieback forest beech tree-ring fagus-sylvatica

en: Additional information to data

en: Additional information to the data explaining data collection and variables.

en: Tree-ring data of European beech with premature leaf discoloration in 2018 and beech with normal leaf fall (.RWL)

en: Tree-ring data of the selected beech trees in rwl-format.

en: Tree information

en: Table giving tree location, diameter at breast height and mortality status.

en: Tree-ring data of European beech with premature leaf discoloration in 2018 and beech with normal leaf fall (.CSV)

en: Tree-ring data of the selected trees as .csv

en:
Tree-ring data and tree location from 470 European beech trees (Fagus sylvatica L.) located in the northern part of Switzerland. 278 trees showed drought-induced premature leaf discoloration and shedding in summer 2018 and 192 showed normal leaf fall. The trees were selected from the "1000-Beech-Project" published by Frei et al. 2022 and the data was analyzed in Neycken et al 2023 (in preparation). The corresponding crown data are archived in the EnviDat data portal https://doi.org/10.16904/envidat.422 (Frei et al. 2023). All other data generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Publications related to original data set and crown data:

Wohlgemuth, T., Kistler, M., Aymon, C., Hagedorn, F., Gessler, A., Gossner, M.M., Queloz, V., Vögtli, I., Wasem, U., Vitasse, Y., Rigling, A., 2020. Früher Laubfall der Buche während der Sommertrockenheit 2018: Resistenz oder Schwächesymptom? Schweizerische Zeitschrift fur Forstwesen 171, 257–269. https://doi.org/10.3188/szf.2020.0257

Frei, E.R., Gossner, M.M., Vitasse, Y., Queloz, V., Dubach, V., Gessler, A., Ginzler, C., Hagedorn, F., Meusburger, K., Moor, M., Samblás Vives, E., Rigling, A., Uitentuis, I., von Arx, G., Wohlgemuth, T., 2022. European beech dieback after premature leaf senescence during the 2018 drought in northern Switzerland. Plant Biol J 24, 1132–1145. https://doi.org/10.1111/plb.13467

Publication related to tree-ring data and growth analysis:
Neycken et al 2023 (in preparation)

beech

display_name: beech

dieback

display_name: dieback

drought

display_name: drought

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

switzerland

display_name: switzerland

tree-ring

display_name: tree-ring


full-content-of-wsl-fauna-database

title_for_slug: full-content-of-wsl-fauna-database

en: arthropods invertebarates wsl database collections

en: Updated export with semicolon-delimited columns instead of comma delimited

en: Complete dataset of all projects and data collected in WSL Fauna Database

en:
Query executed to retrieve the complete dataset from WSL Fauna Database
FIDO_global_extract 2023-03-08_16-27-28 WSL-AllData-AllTaxa.sql compressed in zip-archive

en: Complete extract of Fauna Database of WSL, containing all projects and all taxa. Meant as exchange and citation platform for sharing the data with the national data centre 'Centre Suisse de la Cartographie de la Fauna (CSCF)', and Info Fauna.

arthropods

display_name: arthropods

collections

display_name: collections

database

display_name: database

invertebarates

display_name: invertebarates

wsl

display_name: wsl

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Full content of WSL Fauna Database


en: forest-accessibility forest economic-efficiency wood-harvesting switzerland wood-extraction forest-roads timber-transport

en: Data Request "Extraction Method"

en: Raster map (10m resolution) of the most suitable extraction method for wood in the Swiss forest

en: Data Request "Forest Accessibility"

en: Raster map (10m resolution) of the overall suitability of the Swiss forest for economic wood extraction and transport

en:
Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport.
A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination.
Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the "helicopter" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based.
Road transport was investigated using network analysis, based on the data set "Forest access roads 2013" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account.
Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the "helicopter" category or transport with trucks under 26 tons).
The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland.
The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php)
Input data used:
- Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016).
- NFI forest mask, 10 m resolution (2015)
- Digital elevation model, 10m resolution (based on swissALTI3D 2016)
- Slope map, 10m resolution (based on swissALTI3D 2016)
- Soil suitability map, 10m resolution (based on soil suitability map BFS 2000)
- Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)

economic-efficiency

display_name: economic-efficiency

forest-accessibility

display_name: forest-accessibility

forest-roads

display_name: forest-roads

timber-transport

display_name: timber-transport

wood-extraction

display_name: wood-extraction

wood-harvesting

display_name: wood-harvesting

en: Accessibility of the Swiss forest for economic wood extraction (2021)


en: 3d digital-surface-model image-matching photogrammety point-cloud

en: Thumbnail (JPG)

en: 2016 Hillshade DSM for Vegetation Heigth Model (current)

en: Hillshade of the digital surface model (DSM), calculated from digital aerial stereo images. The image data was acquired by the Federal Office of Topography swisstopo. The resolution of the DSM is 1 m x 1 m.

digital-surface-model

display_name: digital-surface-model

image-matching

display_name: image-matching

photogrammety

display_name: photogrammety

point-cloud

display_name: point-cloud

en: Hillshade for Vegetation Height Model NFI


en: climada avalanche-hazard-mapping risk avalanche hazard-indication-mapping

en: Avalanche and Climada files

en:
Avalanche release files.
Avalanche domain files.
Avalanche simulation output files (.tiff).
CLIMADA operational files (.gdf, .hdf5 and .xlsx).

en: Potential release files and the artificial RAMMS avalanche simulation output files as well as exposure geodataframe for the case study region of Ortner et al. 2022. Furthermore, all the necessary files to run the risk model Climada Avalnache which code is located at https://github.com/CLIMADA-project/climada_papers.

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

climada

display_name: climada

hazard-indication-mapping

display_name: hazard-indication-mapping

risk

display_name: risk

en: Large-scale risk assessment on snow avalanche hazard in alpine regions


en: tracking soil-degradation fallout-radionuclides sediment-transport soil-erosion

en: Reference Pu samples

en: We have collected 19 Bulk soil samples in and 3 depth incremental soil profiles in undisturbed reference locations.

en: Erosion Pu samples

en: We have measured Pu-239+240 in soil samples at erosional sites in the catchment.

en: Quantifying the rates of soil redistribution worldwide poses a significant challenge, which has been addressed using various methods such as direct sediment measurements, models, and the use of isotopic, geochemical, and radionuclide tracers. Among these tracers, the isotope of Plutonium, specifically 239+240Pu, is a relatively recent addition to the study of soil redistribution. However, there is still a lack of direct validation for 239+240Pu as a tracer for soil redistribution. To address this gap, we conducted a study in Southern Italy using a unique sediment yield dataset that extends back to the initial fallout of 239+240Pu. Soil samples were collected from the catchment area as well as undisturbed reference sites, and 239+240Pu was extracted, measured using ICP-MS, and converted into soil redistribution rates.

fallout-radionuclides

display_name: fallout-radionuclides

sediment-transport

display_name: sediment-transport

soil-degradation

display_name: soil-degradation

soil-erosion

display_name: soil-erosion

tracking

display_name: tracking

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Plutonium-239+240 and sediment yield data for a small catchment in Southern Italy


title_for_slug: yield-of-merchantable-timber

en:
Wood volume of the stem (without bark and stump) and the branches (with bark) at least 7 cm in diameter (limit for coarse wood) from trees and shrubs starting at 12 cm dbh that were living in the pre-inventory and were cut between the two inventories.

Citation:
 > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_

biogeographical-region

display_name: biogeographical-region

conifers-broadleaves

display_name: conifers-broadleaves

economic-region

display_name: economic-region

ownership

display_name: ownership

production-region

display_name: production-region

protection-forest-region

display_name: protection-forest-region

yield-of-merchantable-timber

display_name: yield-of-merchantable-timber

en: Yield of merchantable timber


en: modelling sedcas illgraben debris-flow awe-gen sediment-transport geomorphology

en: SedCas Input/Output Data

en:
The dataset contains the input and output files from the publication by Hirschberg et al. (2022).

The input files are the climate forcing time series generated with the AWE-GEN model. The output files include the hydrological outputs, which is the same for scenarios 1-6 considered in Hirschberg et al. (2022), and the sediment-related outputs, whereas the transport-limited scenario 6 is included in the output of scenario 1.

The input file includes:

- time _D_ (h)
- precipitation _Pr_ (mm/h)
- atmospheric temperature _Ta_ (°C)
- incoming shortwave radiation _Rsw_ (W/m^2)
- cloudiness _N_ (-)

The output files include:

- hydrological outputs (accroding to time in input and normalized by basin area)
  - total discharge _Q_ (mm/h)
  - surface discharge _Qs_ (mm/h)
  - subsurface discharge _Qss_ (mm/h)
  - soil water storage _Vw_ (mm)
  - snow depth _snow_ (mm SWE)
  - snow depth change _snowacc_ (mm/h SWE)
  - potential evapotranspiration _PET_ (mm/h)
  - actual evapotranspiration _AET_ (mm/h)

- sediment outputs (accroding to time in input and normalized by basin area)
  - hillslope landslide magnitude _ls_ (mm/h)
  - channel sediment storage _sc_ (mm)
  - hillslope sediment storage _sh_ (mm)
  - total sediment discharge _so_ (mm/h)
  - transport-limited total sediment discharge _sopot_ (mm/h)
  - sediment discharge by debris flows _dfs_ (mm/h)
  - transport-limited sediment discharge by debris flows _dfspot_

awe-gen

display_name: awe-gen

debris-flow

display_name: debris-flow

geomorphology

display_name: geomorphology

illgraben

display_name: illgraben

modelling

display_name: modelling

sedcas

display_name: sedcas

en: Data for Numerical Investigation of Sediment Yield Underestimation in Supply-Limited Mountain Basins with Short Records


maintainer: Marcia Phillips

en: ritigraben meteo-station permos permafrost borehole

en: DATA ACCESS

en: Meterological station at the [Ritigraben permafrost borehole](http://www.envidat.ch/dataset/rit1) (RIT_0102) in canton Valais, Switzerland. The station is located at 2690 m asl on a flat site.

borehole

display_name: borehole

meteo-station

display_name: meteo-station

permafrost

display_name: permafrost

permos

display_name: permos

ritigraben

display_name: ritigraben

en: RIT2: Meteorological station at Ritigraben borehole site


en: landscape-evolution flora geology endemism madagascar

en: Data v1.o

en: used for paper submission only

en: Escarpment evolution drives the diversification of the Madagascar flora

en: This upload contains the data (species checklist, species range maps, time-calibrated phylogenies, topographic change, etc.) generated, analyzed, and presented in the paper .

en: Although much of the endemic biodiversity of Madagascar can be attributed to its isolation as an island in the Indian Ocean, the high rates of speciation throughout its geologic history suggest an influence of local-scale landscape dynamics. The topographic evolution of Madagascar is dominated by the formation of high-relief continental rift escarpment and we argue that the erosion and landward retreat of this topography creates habitat heterogeneity that has served as a speciation pump for the island. The highest plant richness is found along the escarpment and is characterized by steady diversification rates over the last 45 Ma. Modeled landscape evolution by escarpment retreat demonstrates opportunities for allopatric speciation by transient habitat fragmentation through multiple mechanisms, including catchment expansion, isolation of highland remnants and formation of topographic and river barriers The segregation of floral phylogenetic turnover parallel to the escarpment is consistent with these mechanisms and indicates the importance of erosion-driven landscape dynamics on speciation.

endemism

display_name: endemism

flora

display_name: flora

geology

display_name: geology

landscape-evolution

display_name: landscape-evolution

madagascar

display_name: madagascar


en: reflection mountain photovoltaic albedo snow energy irradiance

en: PV Data

en: Windows users use the 7-zip app to extract the zip-file.

en:
 Overview
The SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication "The bright side of PV production in snow-covered mountains", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.

 Format
All code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format.
This is the case for:

- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM),
- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE),
- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster,
- Electricity production from three of our validation sites (/Validation/WSL),
- Measured irradiance for two validation sites (/Validation/ASRB)
The ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format.

 Structure
The central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the ‘DataProcessing’ and the ‘functions’ folder. Functions are called in the different Mains.

‘InputsFromMatlab’ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.

‘Outputs’ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)

‘Publication_figures’ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.

‘Validation’ contains the data sets used in the model validation:

- Electricity production from three of our validation sites (/WSL),
- Measured irradiance for two validation sites (/ASRB)

Electricity production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available.

Paper Citation:
 > _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_

albedo

display_name: albedo

energy

display_name: energy

irradiance

display_name: irradiance

mountain

display_name: mountain

photovoltaic

display_name: photovoltaic

reflection

display_name: reflection

snow

display_name: snow

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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


wood-mobilization-survey

title_for_slug: wood-mobilization-survey

en: wood-harvest forest-managers trading-preferences forest-owners distribution-channels

en: CE Upper Bavaria

en: CE GER

en: Survey in English

en: CE CH

en: CE Aargau

en: Survey in German

en: CE Lower Franconia

en: CE Grisons

en:
Understanding the market behavior of forest owners and managers is important to identify effective and efficient policy instruments that enhance wood provisioning. We conducted a choice experiment (CE) at two study sites in south-eastern Germany (Upper Bavaria and Lower Franconia) and two in north-eastern Switzerland (Grisons and Aargau) to elicit foresters’ preferences for different supply channels, contract lengths, wood prices and duration of business relations.
CE belong to the stated preference methods to analyze individual decision making. Respondents had to choose among three options based on different attribute levels in 12 consecutive choice sets.
Our study site comparison identified regional differences and particularities, which should be taken into account when promoting wood mobilization. The success of policy instruments, such as the promotion of bundling organizations and long-term contracts, can vary depending on the specific structural and institutional conditions, like existing marketing channels, as well as on behavioral aspects of the particular public and private decision makers.

distribution-channels

display_name: distribution-channels

forest-managers

display_name: forest-managers

forest-owners

display_name: forest-owners

trading-preferences

display_name: trading-preferences

wood-harvest

display_name: wood-harvest

en: Wood Mobilization Survey


en: fish america marine occurrences caribbean

en: Fish observations of Greater Caribbean and Tropical East Pacific

en:
combined and cleaned occurrences of marine fish species of the Greater Caribbean and Tropical East Pacific.

Data were obtain from the following sources in 2019/2020:
https://gbif.org
https://idigbio.org
https://biogeodb.stri.si.edu/sftep/en/pages
https://biogeodb.stri.si.edu/caribbean/en/pages

america

display_name: america

caribbean

display_name: caribbean

fish

display_name: fish

marine

display_name: marine

occurrences

display_name: occurrences

en: marine fish occurrences of Tropical America


swiss-fluxnet-site-lageren

title_for_slug: swiss-fluxnet-site-lageren

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

en: Fluxnet2015 dataset

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

en: Site description

en: Data access

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

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

Measurements

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

Data availability

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

Data policy

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

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

eddy-covariance

display_name: eddy-covariance

flux

display_name: flux

forest

display_name: forest

greenhouse-gas

display_name: greenhouse-gas

meteorological-measurements

display_name: meteorological-measurements

swiss-fluxnet

display_name: swiss-fluxnet

swiss-forest-lab

display_name: swiss-forest-lab

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Swiss FluxNet Site Lägeren


soil-matrix-chemistry-lwf

title_for_slug: soil-matrix-chemistry-lwf

en: swiss-forest-lab long-term-forest-ecosystem-research icp-forests soil-matrix soil-chemistry

en: Data Request

en:
Assessment of several chemical soil parameters at the beginning of the monitoring campaign. Most parameters were determined accordung to the manual of ICP-Integrated-Monitoring. The parameters were analysed for all genetic horizons in soil pits and additionally for fixed layers in the Intensive-Monitoring-Plots. In heterogeneous LWF-plots, several soil pits were analysed in order to assess the soil variability of the plot. The manual (in German) for soil sampling and soil analyses is available in www: http://e-collection.ethbib.ethz.ch/view/eth:25622?q=walthert. The results and data of the first soil survey are available (in German) in www: http://e-collection.ethbib.ethz.ch/view/eth:26275?q=walthert.

 Purpose:

The chemical characterisation of soil matrix down to the paraent material is realised with data from soil pits. The monitoring of the soil matrix in a frequency of roundly 15 years is effected with soil samples from Intensiv-Monitoring-Plots. For soil monitoring, pooled samples with 16 replicats are used down to a depth of 80 cm. The date of the second soil survey is not yet fixed.

 Manual Citation:

 * Walthert L, Lüscher P, Luster J, Peter B (2002) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Aufnahmeanleitung zur ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 269: 56 p. [10.3929/ethz-a-004375470](https://doi.org/10.3929/ethz-a-004375470)

 Paper Citation:

 * Walthert L, Blaser P, Lüscher P, Luster J, Zimmermann S (2003) Langfristige Waldökosystem-Forschung LWF. Kernprojekt Bodenmatrix. Ergebnisse der ersten Erhebung 1994-1999. ETHZ Zürich, e-collection , Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Vol. 276: 340 p.

icp-forests

display_name: icp-forests

long-term-forest-ecosystem-research

display_name: long-term-forest-ecosystem-research

soil-chemistry

display_name: soil-chemistry

soil-matrix

display_name: soil-matrix

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: Soil matrix chemistry LWF


maintainer: Giulia Mazzotti

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

en: Snow depth data open sites

en: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en: Canopy data

en: Includes all canopy structure metrics computed at all surveyed locations

en: Snow depth data forest sites

en: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en: Meteo data to drive FSM2 model

en: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

en: Coordinates data

en: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en: Grid point nomenclature

en: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.  Each point marks the location of snow depth measurements and co-located canopy structure parameters.

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

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling

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


maintainer: Yaquan Chang

en: habitat-heterogeneity hengduan-mountains phytodiversity hypervolume model-residuals

en: Plant range map at Hengduan scale

en: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en: Eurasia SR and heteorgeneity

en: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en: HDM heterogeneity scales

en: The Heterogeneity matrics in the Hengduan mountain scale

en: Hengduan plant family richness map

en: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en: Eurasia plant family richness map

en: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan