cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.16904/envidat.343
title: Seilaplan Tutorial: DTM download from swisstopo website

description: In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. As an alternative to using the ‘Swiss Geo Downloader’ plugin, the DTM can be obtained directly from Swisstopo. In this tutorial we explain step by step how to download the necessary DTM from the Swisstopo Website, and how to use it in QGIS for the digital planning of a cable line using the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the elevation model on the swisstopo website: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link to the rope map website: https://seilaplan.wsl.ch
********************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Als Alternative zum Swiss Geo Downloader erklären wir in diesem Tutorial Schritt für Schritt, wie man das nötige Höhenmodell von der Swisstopo Webseite herunterladen und in QGIS zur Seillinienplanung verwenden kann. 
Link zum Höhenmodell auf der swisstopo Webseite: https://www.swisstopo.admin.ch/de/geodata/height/alti3d.htmltechnische_details
Link zur Seilaplan-Website: https://seilaplan.wsl.ch
description: Resource Title: Herunterladen des DHM von swisstopo Website
 Size: 246551051 bytes
 Format: video/mp4
 URL: https://www.envidat.ch/dataset/ed0aaf2e-e5dc-4149-85f2-3bb848a30ffe/resource/6b58a8ae-fb28-42ac-8bec-5db98e69f17e/download/seilaplan_tutorial_2_website.mp4
 Description:
description: Resource Title: View video on youtube!
 Size: 1024 bytes
 Format: No Info
 URL: https://youtu.be/jUuxp_Xk64k
 Description:
DOI: 10.16904/envidat.342
title: Seilaplan Tutorial: DTM download with SwissGeoDownloader

description: In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. The plugin ‘Swiss Geo Downloader’, which is available for the open source geoinformation software QGIS, allows freely available Swiss geodata to be downloaded and displayed directly within QGIS. It was developed in 2021 by Patricia Moll in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. In this tutorial we describe how to download the high accuracy elevation model ‘swissALTI3D’ with the help of the ‘Swiss Geo Downloader’ and how to use it for digital planning of a cable line with the plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to the Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link to Seilaplan website: https://seilaplan.wsl.ch
*********************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. Das Plugin Swiss Geo Downloader, welches für das Open Source Geoinformationssystem QGIS zur Verfügung steht, ermöglicht frei verfügbare Schweizer Geodaten direkt innerhalb von QGIS herunterzuladen und anzuzeigen. Es wurde 2021 von Patricia Moll in Zusammenarbeit mit der eidgenössischen Forschungsanstalt Wald, Schnee und Landschaft WSL entwickelt. In diesem Tutorial beschreiben wir, wie man mit Hilfe des Swiss Geo Downloaders das hochgenaue Höhenmodell swissALTI3D herunterladen und für die Seillinienplanung mit dem Plugin Seilaplan verwenden kann.
Link zum Swiss Geo Downloader: https://pimoll.github.io/swissgeodownloader
Link zur Seilaplan-Webseite: https://seilaplan.wsl.ch
description: Resource Title: Herunterladen des DHM mit SwissGeoDownloader
 Size: 429428137 bytes
 Format: video/mp4
 URL: https://www.envidat.ch/dataset/659dc637-e0ca-4393-9f07-13b04290d6ec/resource/05723528-b1c9-4476-a69b-18327d823588/download/seilaplan_tutorial_1_swissgeodownloader.mp4
 Description:
description: Resource Title: View video on youtube!
 Size: 1024 bytes
 Format: No Info
 URL: https://youtu.be/u7WRrO3GplI
 Description:
DOI: 10.6069/ph9a-pf28
title: LFQ Benchmark Dataset - Generation Beta: Assessing Modern Proteomics Instruments and Acquisition Workflows with High-Throughput LC Gradients

description: Recent advances in liquid chromatography–mass spectrometry (LC-MS) have accelerated the adoption of high-throughput workflows that deliver deep proteome coverage using minimal sample amounts. This trend is largely driven by single-cell proteomics, where sensitivity and reproducibility are essential. Here, we extend our previous benchmark dataset (PXD028735) that was generated using next-generation LC-MS platforms optimized for rapid proteome analysis. With shorter LC gradients and lower sample amounts, we generated an extensive DDA/DIA dataset on a standardized human-yeast-E. coli hybrid proteome. This new dataset includes data acquired by the Orbitrap Astral, which combines an Orbitrap with a time-of-flight (TOF) mass analyzer, and features new scanning quadrupole-based implementations, extending coverage across different instruments and acquisition strategies. Our comprehensive evaluation highlights how technological advances and reduced LC gradients affect proteome depth, quantitative precision, and cross-instrument consistency. The release of this benchmark dataset via ProteomeXchange (PXD070049), allows for the acceleration of cross-platform algorithm development, enhance data mining strategies, and support the continued standardization of short-gradient, high-throughput LC-MS-based proteomics.
DOI: 10.16904/envidat.344
title: Seilaplan Tutorial: Merge DTM tiles

description: In order to use the QGIS plugin ‘Seilaplan’ for digital cable line planning, a digital terrain model (DTM) is required. In this tutorial video, we show how to merge multiple DTM raster tiles into one file, using the QGIS tool ‘Virtual Raster’. This simplifies the digital planning of a cable line using the QGIS plugin ‘Seilaplan’. Please note that the tutorial language is German!
Link to Seilaplan website: https://seilaplan.wsl.ch
***************************
Für die Verwendung des QGIS Plugins Seilaplan zur digitalen Seillinienplanung ist ein digitales Höhenmodell (DHM) nötig. In diesem Tutorialvideo zeigen wir, wie man mit dem QGIS-Plugin Virtuelles Raster mehrere DHM-Kacheln zu einem einzigen Rasterfile zusammenfügen und abspeichern kann. Für die Seillinienplanung mit Seilaplan muss nun nur noch eine Datei, mein neues virtuelles Raster, ausgewählt werden.
Link zur Seilaplan-Website: https://seilaplan.wsl.ch
description: Resource Title: DHM-Kacheln zusammenfügen
 Size: 292363579 bytes
 Format: video/mp4
 URL: https://www.envidat.ch/dataset/15cd0733-843f-4491-9998-f437b4cc1df4/resource/ba9ff01f-f7b8-4b35-957d-ff35889a7979/download/seilaplan_tutorial_3_virtuellesraseter.mp4
 Description:
description: Resource Title: View video on youtube!
 Size: 1024 bytes
 Format: No Info
 URL: https://youtu.be/UcORl_PU3No
 Description:
DOI: 10.16904/envidat.383
title: Ramerenwald Close Range Remote Sensing Benchmark

description: 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.
description: Resource Title: Ramerenwald_Benchmark_FP05
 Size: 25984552141 bytes
 Format: .zip
 URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP05.zip
 Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP05/Ramerenwald_Benchmark_FP05.html
description: Resource Title: Ramerenwald_Benchmark_FP07
 Size: 40050570035 bytes
 Format: .zip
 URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP07.zip
 Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP07/Ramerenwald_Benchmark_FP07.html
description: Resource Title: Ramerenwald_Benchmark_FP08
 Size: 40694815130 bytes
 Format: .zip
 URL: https://s3-zh.os.switch.ch/pointclouds/20230301_Ramerenwald_Benchmark/data/Ramerenwald_Benchmark_FP08.zip
 Description: **preview_url**: https://pointclouds.s3-website-zh.os.switch.ch/20230301_Ramerenwald_Benchmark/vis/Ramerenwald_Benchmark_FP08/Ramerenwald_Benchmark_FP08.html
DOI: 10.16904/envidat.354
title: Global species distributions for mammals, reptiles, and amphibians

description: We modelled the global distribution of 730 amphibian, 1276 reptile, and 1961 mammal species globally as a function of current climate at a 0.5° spatial resolution using four different predictor groups composed of different combinations of input variables: mean climatic conditions, spatial climatic variability, and temporal (interannual) climatic variability.
description: Resource Title: Amphibians
 Size: 1181116006 bytes
 Format: .zip
 URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/amphibians.zip
 Description: Species distribution models based on different climate predictor groups
description: Resource Title: Mammals
 Size: 3650722202 bytes
 Format: .zip
 URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/mammals.zip
 Description: Species distribution models based on different climate predictor groups
description: Resource Title: Reptiles
 Size: 2147483648 bytes
 Format: .zip
 URL: https://envicloud.os.zhdk.cloud.switch.ch/doi/envidat.354/reptiles.zip
 Description: Species distribution models based on different climate predictor groups
description: Resource Title: mammals_metadata
 Size: 54466 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/4589c081-818c-4873-8b15-8f399464b434/download/mammals_metadata.txt
 Description: File containing the record dimension, genus, and species of the respective netcdf files
description: Resource Title: amphibials_metadata
 Size: 18938 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/9bff87c6-e1ce-4553-accb-43af8eaca72e/download/amphibians_metadata.txt
 Description: File containing the record dimension, genus, and species of the respective netcdf files
description: Resource Title: reptiles_metadata
 Size: 32524 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/fa2b6ee3-5067-4eb4-b8a0-fc1cb256a637/download/reptiles_metadata.txt
 Description: File containing the record dimension, genus, and species of the respective netcdf files
description: Resource Title: 
 Size: 4848 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/09bc5a49-e1ef-4491-928e-6c4440fad9d1/download/readme.txt
 Description: Readme file containing the file naming convention, file dimensions, and variable names
description: Resource Title: 
 Size: 1548568 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/5a534bed-71fa-4a48-8fe5-66ca9a4c820f/resource/b01e0b24-8806-4cfc-b9eb-550fe29e4a40/download/climate_predictors.zip
 Description: File containing the climate predictors as SAGA grid files (.sgrd)
DOI: 10.16904/envidat.135
title: Compressive stick slip and snow-micro-quakes

description: When snow is compressed with a certain speed, micro-snowquakes are triggered in the porous structure of bonded crystals. The present dataset covers uniaxial compression experiments of snow at different strain rates and concurrent X-ray tomography imaging documenting this feature. 
The experiments were conducted in a micro-compression stage operated in the X-ray tomography scanner in the SLF cold laboratory. The dataset comprises the compression force data of 17 compression experiments, the 3D image data from 4 X-ray tomography scans and the results of numerical simulations.
description: Resource Title: Snowmicroquakes Data
 Size: 6442450944 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.135/2020_snowmicroquakes_paper_envidat
 Description: Compression experiments, X-ray images and simulation data with supplemented README file
DOI: 10.16904/envidat.83
title: Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples

description: For the investigation of microstructural and mechanical properties of snow unconfined compression experiments and 3D computed tomography (CT) imaging were performed on sintered rounded grain snow and spherical model snow. The spherical model snow was generated to create geometrically simplified, well-defined microstructures for calibration of numerical models, such as discrete element models (DEM) in which the microstructure is represented by spherical particles. 
In the experiments, microstructural variation was created by varying the sintering time (contact size) and the density of the ice sphere samples (number of contacts). The 3D CT images allow for a complete reconstruction of the entire experimental sample (cylindrical sample dimension: diameter = 33.6 mm; height = 14 mm).
description: Resource Title: README.txt
 Size: 1925 bytes
 Format: .txt
 URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/readme.txt
 Description:
description: Resource Title: Data Access
 Size: 161061273600 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.83/3dct/Data/
 Description:
description: Resource Title: Data Structure (Python Notebook)
 Size: 335872 bytes
 Format: .ipynb
 URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.83/3dct/Data_Structure.ipynb
 Description:
DOI: 10.16904/envidat.680
title: Meteorological Time Series Aligned with Projected Temperature Changes

description: This dataset provides 50 years of seasonal synthetic hourly time series for five meteorological variables: incoming shortwave radiation, total precipitation, relative humidity, 2-meter air temperature and wind speed.
The data are generated from observational records (1990–present) from nine MeteoSwiss stations (ABO, BAS, BER, LUG, PUY, SCU, SIO, STG, WFJ). We use a sampling approach that preserves both the temporal structure and inter-variable dependencies. Specifically, the time series are constructed by drawing 7-day blocks from historical observations, ensuring realistic short-term variability and maintaining the physical coherence between variables.
The synthetic sequences are constrained to follow daily temperature change trajectories corresponding to three future climate scenarios for the period 2040–2070: RCP2.6, RCP8.5 and RCP0: a counterfactual scenario with no long-term warming trend, but with temperature variability consistent with the RCP2.6 one.
The temperature constraints are derived from projections downscaled at the staiton level, available at: https://www.envidat.ch//metadata/climate-change-scenarios-at-hourly-resolution
description: Resource Title: Data link
 Size: 377487360 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.680%2F
 Description:
DOI: 10.16904/envidat.225
title: Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7–9 June 2021, Birmensdorf, Switzerland

description: Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings.
FORECOMON 2021 - the 9th forest ecosystem monitoring conference.
7-9 June 2021, WSL, Birmensdorf, Switzerland
The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed.
Copyright © 2021 by WSL, Birmensdorf
The authors are responsible for the content of their contribution.
description: Resource Title: FORECOMON – Proceedings
 Size: 2920688 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/ab0b32ad-43fa-41c3-93bd-68b6d6b7e4e7/download/abstractband_a4_forecomon_vrs14.pdf
 Description: Latest version
description: Resource Title: Link to Proceedings in DORA WSL
 Size: 1 bytes
 Format: No Info
 URL: https://www.dora.lib4ri.ch/wsl/islandora/object/wsl%3A27202
 Description:
description: Resource Title: Deprecated version 1.0
 Size: 2699168 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/6c2c3d5b-8b2f-4c7b-b996-46df4ccf2b20/resource/1928196d-5fee-48c1-9b30-66362abf2045/download/icp_abstractband_web.pdf
 Description: First version of the proceedings containing errors. This early version it is kept, for traceability purposes, in conformance with DOI rules.
DOI: 10.16904/envidat.683
title: Greater observer expertise leads to higher liverwort species richness in bryophyte surveys

description: This dataset contains bryophyte species count data and information about the observers bryophyte expertise for 2950 relevés conducted from 2011 to 2023 on 10-m2 plots in a long-term monitoring program in Switzerland. Plots were situated in raised bogs and fens of national importance, which were distributed across the whole country. The majority of the plots is represented by two relevés as sites are revisited every six years. The dataset was used in the paper mentioned below to test if species richness estimates differed among categories of observer expertise.
Moser T, Boch S, Bedolla A, Ecker KT, Graf UH, Holderegger R, Küchler H, Pichon
NA, Bergamini A (2025) Greater observer expertise leads to higher liverwort species richness in bryophyte surveys. _Journal of Vegetation Science_.
description: Resource Title: Releve data
 Size: 578576 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/2086bbc9-dd8d-4f14-8bf7-12f1fd2d4a38/resource/361a0c29-1a01-4314-b9f5-be866fb01108/download/pub-data.csv
 Description: The CSV file contains all releves considered in the mentioned study. The columns include plot identification, survey period, survey year, habitat category of the surveyed object, vegetation type of the plot, anonymized identification of the observer, observer expertise category, the observers survey experience, scaled mean indicator values (i.e., light, nutrients, reaction, temperature and wetness), counts for the four groups (all species, liverworts, mosses exkl. Sphagnum spp. and Sphagnum spp.), the size categories (small, medium, large) and the modified cover classes (NA, r, +, 1, 2, 3-5).
DOI: 10.15468/dl.cutq5q
title: Occurrence Download

description: A dataset containing 1399 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "TaxonKey is Oreamnos americanus"
 ]
}

 The dataset includes 1399 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010385-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x57wpg
title: Occurrence Download

description: A dataset containing 14852 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is VERTEBRADOS DE VALOR ESPECIAL EN ÁREAS PROTEGIDAS DE LA ARGENTINA"
 ]
}

 The dataset includes 14852 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010386-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10883432
title: Assessing the fate and behaviour of plant nutrients in aquaponic systems by chemical equilibrium modelling: A meta-analytical approach

description: Abstract



Aquaponic systems differ from hydroponics by a higher pH and higher concentrations of dissolved organic matter (DOM). This study assessed whether plant nutrient deficiencies in aquaponics are caused by lacking input of the deficient nutrients or their chemical saturation. Nine scenarios with nutrient concentrations based on Hoagland's solution and different pH (5.5, 6.5, 7.5) and DOM concentrations (0 mg L−1, 20 mg L−1) were constructed, representing theoretical hydroponic and aquaponic systems. Eventually, nutrient concentrations at equilibrium were calculated. In addition, a meta-analysis was conducted to assess whether nutrient concentrations reported in aquaponic studies could be predicted by equilibrium calculations. Theoretical results indicate that solubility thresholds cause deficiencies of P, Ca, Fe, and Cu at equilibrium due to the higher pH in aquaponics compared with hydroponics. Deficiencies in K and other plant nutrients are, meanwhile, likely caused by lacking supply through nutrient inputs at equilibrium. The presence of DOM can increase Fe and Cu solubility. However, equilibrium calculations could not predict nutrient concentrations found in literature. P was present at higher concentrations (max. 0.3 mmol L−1) than predicted (10−3–10−6 mmol L−1), indicating chemical equilibrium was not reached in the assessed systems (average hydraulic retention time = 17 d). Future studies should consider reaction rates. Furthermore, considering the low concentrations of dissolved P in all studies, a system scaling based on P instead of N might be considered.

 

This repository contains the cleaned dataset and Visual MINTEQ input files (without and without assumed presence of dissolved organic matter) for each record in the dataset. Visual MINTEQ is a free software for speciation calculations, among other features.