cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.16904/envidat.549
title: 21st century projections of dry- and wet-snow avalanche activity

description: This data set includes 21st century projections of dry- and wet-snow avalanche activity for seven sites in the Swiss Alps as well as the downscaled climate scenarios and SNOWPACK configuration files used to produce these projections. The methods used to produce these data are described in the research article: 
Mayer, S., Hendrick, M., Michel, A., Richter, B., Schweizer, J., Wernli, H., and van Herwijnen, A.: Changes in snow avalanche activity in response to climate warming in the Swiss Alps, EGUsphere, 2024, 1-32, https://doi.org/10.5194/egusphere-2024-1026, 2024.
We used downscaled climate projections to drive the snow cover model SNOWPACK and evaluated future dry- and wet-snow avalanche occurrences in the vicinity of seven automatic weather stations from the IMIS network using machine learning models trained with observed records of avalanche activity. Projections are available for three different emission scenarios (Representative Concentration Pathways, RCP2.6, RCP4.5 and RCP8.5) and eight climate model chains from the CH2018 ensemble. The output of the model chain is given by a daily probability for dry- or wet-snow avalanche occurrences. These probabilities can then be used to classify a day as a dry- and wet-snow avalanche day (AvD) or non-avalanche day.
description: Resource Title: Projections of avalanche activity
 Size: 244124715 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/57e53301-e5b5-4366-b1e3-983088b73332/download/avd_projections.zip
 Description: contains one file per IMIS station that indicates the daily probability for the occurrence of dry- or wet-snow avalanches in the vicinity of the respective station for each day during the time period 1.12.1981-31.05.2099 (months December to May) and all climate model chains and RCP scenarios.
description: Resource Title: Climate scenarios .smet 
 Size: 1768931461 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/12ca4022-4445-41aa-8720-a1caf547eb09/download/smet.zip
 Description: contains one .smet file per combination of station, climate model chain and RCP scenario. Each .smet file contains the downscaled meteorological data (time span 1.9.1981-31.8.2099) that was used to drive the SNOWPACK simulations.
description: Resource Title: SNOWPACK settings
 Size: 3070 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/b05a3845-4efc-429b-8a95-6e519b1eaef4/download/snowpack_settings.zip
 Description: contains .ini and .sno file indicating the settings used to drive SNOWPACK with the climate scenarios
description: Resource Title: README.txt
 Size: 4232 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/e777e9f2-5515-43b9-a5cb-b0d8b7d649e4/resource/e100befd-5ef4-495a-b922-ac8316cbdd4b/download/readme.txt
 Description:
DOI: 10.16904/envidat.550
title: Pfynwald Geoelectric Experiment 2022

description: This collection of datasets consists of various measurements taken during the year 2022 in Pfynwald. It combines 2 electrical resistivity transects which were monitored in May and July, before and after the irrigation season. The transects transverse all treatments (irrigation, control, irrigation stop). Each transect was repeated twice during the day for a period of 3 days to a week.
In addition there are raw and post-processed drone images (and resulting PRI maps), which were used to compare the below ground responses (from resistivity) to the above ground (crown) stress. 
Here, the raw data is stored and a link to a git project is provided where python code is stored to reproduce all the results the published manuscript: "Does optimality partitioning theory fail for belowground traits? Insights from geophysical imaging of a drought-release experiment in a dry Scots Pine forest", New Phytologist, Shakas et al., 2024. The in-depth explanations from each processing step are found in the code (git project).
description: Resource Title: 2022_NP.zip
 Size: 511138780 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/1e4afcde-3acf-4b78-ab2f-0376aab525be/resource/167b27d0-27c2-48d3-b16b-83f4eb2bf740/download/2022_np.zip
 Description: This zip file contains all raw and processed data for the electrical resistivity and drone campaigns that took place in Pfynwald, 2022
description: Resource Title: SWPC_data_Pfynwald_NP2024_data.csv
 Size: 153809 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/1e4afcde-3acf-4b78-ab2f-0376aab525be/resource/e0f3f914-7db4-4536-a47f-ee8b878b5ad1/download/swpc_data_pfynwald_np2024_data.csv
 Description: This .csv file contains the soil water potential data for all treatments (irrigation, irrigation-stop and control) and for the whole year of 2022. The data is given as a mean value and with an upper and lower uncertainty bound, given from the manufacturer. The depth of the sensor is given in cm, and the measured values are in units of kPa.
DOI: 10.16904/envidat.552
title: Quantitative Wood Anatomy and Maximum Latewood Density from Yamal peninsula

description: Data (Quantitative Wood Anatomy, Maximum Latewood Density, Volumetric Density, holo-cellulose-to-wood-ratio) used in the manuscript "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy". Wood samples stem from Larix sibirica collected in the Yamal region, northeastern Siberia, Russia. We investigated wood properties of living trees and subfossil wood buried in riverbank sediments, dated to approximately -2760 to -2600 BCE. Our goal was to evaluate the integrity of climate proxies in sub-fossil wood and develop practical methods to detect wood degradation when reconstructing Late Holocene and Common Era climate conditions using tree-ring data.
description: Resource Title: Figure3_dataset.txt
 Size: 8581 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/743a897f-26e7-4871-a014-b0f95238564d/resource/2435516e-8dfc-4347-a35c-893eadcdf569/download/figure3_dataset.txt
 Description: This dataset contains the mean chronologies of MXD and QWA of the relict and living wood material presented in Figure 3. It also contains the JJA temperature record of the Salekhard Meteo station.
description: Resource Title: Figure2_dataset.csv
 Size: 1668 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/743a897f-26e7-4871-a014-b0f95238564d/resource/b0e00f50-78a2-4006-ab8d-7d4d796efc05/download/bulkdensity.csv
 Description: This dataset contains data presented in Figure 2 in the paper "New Prospects for Temperature Reconstructions from Relict Wood Using Tree-Ring Anatomy".
 
Sample ID = Sample ID
group = living or relict wood material
Bulk wood density = volumetric measured density (kg / m^3)
Mean Tree Ring Density = Density derived via X-ray densitometry (kg / m^3)
Cellulose_to_wood ratio = Holo-cellulose-to-wood ratio
Anatomical density = Area of cell wall / (area of cell wall + lumen area)
DOI: 10.16904/envidat.547
title: European Beech tree-ring dataset 1952-2020

description: This dataset contains the raw ring-width and climate data (1952-2020), as well as the R code to run the model and the model output used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".
description: Resource Title: final_cwb_model.R
 Size: 13781 bytes
 Format: application/octet-stream
 URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/5d54048a-25a6-4861-89a3-6586b970177d/download/final_cwb_model.r
 Description: R code to run the model behind the results of the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation".
Requires beech_rawtrw.txt.
description: Resource Title: Model output
 Size: 679105614 bytes
 Format: application/octet-stream
 URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/c0117599-93c9-4ea0-8f12-753c711f003c/download/ebtrnplus_model_newcwbmean2
 Description: Output of the Mixed-effects model
description: Resource Title: beech_rawtrw.txt
 Size: 332605512 bytes
 Format: text/plain
 URL: https://www.envidat.ch/dataset/6b052bdb-9e18-4f00-92b6-e102347245ec/resource/f3bc670c-3474-4987-966e-c9a2e94bebd3/download/beech_rawtrw.txt
 Description: This dataset contains the raw ring-width and climate data (1952-2020) used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation". 

RW= ring width
Year= Calendar year
CN = core number
ID3= plot identifier
longitude = longitude (°)
latitude = latitude (°)
elevation = elevation (m)
age= estimated age in calendar year
radius= estimated radius in calendar year (mm)
MAT= mean annual temperature (°C)
MAP= mean annual precipitation (mm)
MCWB= mean climatic water balance (P-PET; mm)
amplitude= simple continentality measure (July - January mean maximum temperatures)
MATspline1 and 2, MCWBspline1 and 2, radiusspline4 and 5= natural spline transformed values of MAT, MCWB and radius #ns(x,2)
CWD_pMay_Jun= Climatic Water Balance of previous year May to June #!!!#please note CWD here is NOT Climatic Water Deficit, this was a labeling error in the creation of the dataset headers
CWD_May_Jun= Climatic Water Balance of current year May to June
Tmax_pMay_Jun= mean monthly maximum temperature of previous year May to June
Tmax_May_Jun= mean monthly maximum temperature of current year May to June
weight = site replication-based weighting input for model
SOM= membership of regional cluster 1-8 based on Supervised Organized Mapping
DOI: 10.16904/envidat.555
title: Daten Bryolich-Projekt Moose und Flechten in Gärten

description: Im Rahmen des Bryolich-Projekts “Moose und Flechten in Gärten” wurden möglichst vollständige Artenlisten von Moosen und Flechten in 26 bzw. 7 Gärten um Wohnhäuser erstellt. In 5 dieser Gärten wurden beide Artengruppen erfasst. Zusätzlich wurden Informationen über unterschiedliche Lebensräume innerhalb der Gärten (z.B. Fläche mit Gehölzen, Fläche von Blumenbeeten) und weitere Garten-Charakteristika (z.B. Fläche des Gartens, Alter des Gartens, Einsatz von Dünger) erfasst. Details zum Projekt und den erfassten Daten können im zugehörigen Artikel (Bergamini et al. 2024) und auf der Webseite von Bryolich gefunden werden (https://www.bryolich.ch/mfig/mfig_de.html).
description: Resource Title: FleMoGa_Daten4envidat.xlsx
 Size: 59449 bytes
 Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
 URL: https://www.envidat.ch/dataset/3d6d3fff-6677-4707-8a6f-792c1e5b22e3/resource/4a3f1911-ec66-4ea1-a908-0ef52e007971/download/flemoga_daten4envidat.xlsx
 Description:
DOI: 10.17632/b8hpyhvzst
title: Diagnostic Utility of Xpert MTB/RIF Ultra in Abdominal Tuberculosis: A Prospective Observational Dataset

description: This dataset provides diagnostic data collected during a prospective observational study aimed at evaluating the diagnostic accuracy of the Xpert MTB/RIF Ultra assay for abdominal tuberculosis (TB). 
The study was conducted at Sir Ganga Ram Hospital, Delhi, India, between September 2019 and March 2021.
A total of 144 patients with clinico-radiological features of abdominal TB were enrolled. 
Key findings across demographic, clinical, radiological, endoscopic, microbiological, and histopathological domains were systematically recorded. 
Patient specimens (lymph node aspirates, tissues, pus, other aspirates, body fluids) were analysed using Xpert MTB/RIF Ultra, direct fluorescence microscopy, liquid culture (BD MGIT 960 system) with backup solid culture (Löwenstein-Jensen medium), and histopathology, as applicable.
Key variables in the dataset include:
• Patients’ age and gender distribution
• Sites of sample collection 
• Xpert MTB/RIF Ultra results (including rifampicin resistance status)
• Phenotypic and genotypic drug susceptibility testing (DST) results
• Smear and culture results
• Histopathology results
• Results of other diagnostic modalities (i.e., radiological, endoscopic, biochemical)
• Treatment response
This dataset allows for the analysis of Xpert MTB/RIF Ultra's diagnostic performance using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio, negative likelihood ratio, and overall accuracy, in comparison with TB culture and a composite reference standard (CRS). 
CRS was defined as either a positive TB culture, or positive results in at least two of the following modalities: imaging or endoscopy suggestive of TB, elevated ascitic fluid adenosine deaminase (ADA) levels (&gt;39 IU/mL), a positive acid-fast bacilli (AFB) smear, presence of granulomas on histopathology, or clinical with radiological and endoscopic improvement after 3 months of empirical anti-tubercular therapy. 
It is intended to facilitate secondary analysis, comparison with other diagnostic assays, and meta-analytical reviews.
Applications:
• Diagnostic performance assessment
• Comparative studies of TB diagnostics
• Educational resource for medical microbiology or infectious disease training
All patient data were anonymised in compliance with ethical standards and institutional ethics committee.
DOI: 10.17632/b8hpyhvzst.1
title: Diagnostic Utility of Xpert MTB/RIF Ultra in Abdominal Tuberculosis: A Prospective Observational Dataset

description: This dataset provides diagnostic data collected during a prospective observational study aimed at evaluating the diagnostic accuracy of the Xpert MTB/RIF Ultra assay for abdominal tuberculosis (TB). 
The study was conducted at Sir Ganga Ram Hospital, Delhi, India, between September 2019 and March 2021.
A total of 144 patients with clinico-radiological features of abdominal TB were enrolled. 
Key findings across demographic, clinical, radiological, endoscopic, microbiological, and histopathological domains were systematically recorded. 
Patient specimens (lymph node aspirates, tissues, pus, other aspirates, body fluids) were analysed using Xpert MTB/RIF Ultra, direct fluorescence microscopy, liquid culture (BD MGIT 960 system) with backup solid culture (Löwenstein-Jensen medium), and histopathology, as applicable.
Key variables in the dataset include:
• Patients’ age and gender distribution
• Sites of sample collection 
• Xpert MTB/RIF Ultra results (including rifampicin resistance status)
• Phenotypic and genotypic drug susceptibility testing (DST) results
• Smear and culture results
• Histopathology results
• Results of other diagnostic modalities (i.e., radiological, endoscopic, biochemical)
• Treatment response
This dataset allows for the analysis of Xpert MTB/RIF Ultra's diagnostic performance using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio, negative likelihood ratio, and overall accuracy, in comparison with TB culture and a composite reference standard (CRS). 
CRS was defined as either a positive TB culture, or positive results in at least two of the following modalities: imaging or endoscopy suggestive of TB, elevated ascitic fluid adenosine deaminase (ADA) levels (&gt;39 IU/mL), a positive acid-fast bacilli (AFB) smear, presence of granulomas on histopathology, or clinical with radiological and endoscopic improvement after 3 months of empirical anti-tubercular therapy. 
It is intended to facilitate secondary analysis, comparison with other diagnostic assays, and meta-analytical reviews.
Applications:
• Diagnostic performance assessment
• Comparative studies of TB diagnostics
• Educational resource for medical microbiology or infectious disease training
All patient data were anonymised in compliance with ethical standards and institutional ethics committee.
DOI: 10.16904/envidat.569
title: Simulation parameters and outputs for towards a physically and microstructure-based equation for the evolution of the specific surface area in snow

description: In the associated study [1], evolution of randomly generated bi-continuous microstructures that resemble real snow microstructures has been investigated. The control of the ambient conditions (temperature and temperature gradient) and of the physical processes at play on the rate of change of the specific surface area have been evaluated. Based on the evaluation, a new physically-informed governing law for the coarsening of microstructures has been proposed. This law accurately predicts the simulation outputs under various conditions. Furthermore, a potential parametrization of newly introduced material properties has been proposed and evaluated on snow coarsening data.
This dataset contains the parameters used for the mesh generation and the finite-element simulations. The output parameters of simulations, such as the ice fraction, surface of the ice-air interface per total volume, mean curvature and growth rate are provided.
[1]: A.Braun, K. Fourteau, S. Frei, M. Lehning, H. Löwe: Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow, Journal of Glaciology, accepted for publication in 2024
description: Resource Title: parameters_SSA_growth_rate_equation_snow.ods
 Size: 107275 bytes
 Format: application/vnd.oasis.opendocument.spreadsheet
 URL: https://www.envidat.ch/dataset/6751620e-b36e-48e2-8e03-02f00d4324f2/resource/10aa98b3-0731-4ff5-bc1c-ae1ccae498fe/download/parameters_ssa_growth_rate_equation.ods
 Description: Simulation parameters and outputs for "Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow"
DOI: 10.16904/envidat.554
title: Short-term Drainage Density Dynamics Dataset for the Haute-Mentue Catchment

description: The dataset contains time series of water levels, precipitation measured in the two sub-catchments of the Haute-Mentue catchment and its vicinity during summer and autumn 2022, as well as flowing drainage network lengths calculated for these areas using the CEASE method developed by the authors. Detailed description of the dataset is provided in the documentation.
description: Resource Title: short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Size: 519660 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/462d51a9-7cd5-49c2-be0e-3575ac402727/resource/d12556c4-35f6-4e8e-bf94-86293d8bcebb/download/short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Description:
description: Resource Title: dataset_of_flowing_drainage_network_lengths_water_levels_and_precipitation_for_the_haute-mentue_catchment.csv
 Size: 13023792 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/462d51a9-7cd5-49c2-be0e-3575ac402727/resource/eaf3906a-17a8-400b-a922-7c576728526a/download/short-term_drainage_density_dynamics_dataset_for_the_haute-mentue_catchment.csv
 Description: The dataset consists of time series of measured surface and groundwater levels, calculated flowing drainage network lengths, and nearby precipitation data for two sub-catchments of the Haute-Mentue catchment, Switzerland (Summer-Autumn 2022). The details of the dataset are described in the provided documentation (short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf)
description: Resource Title: short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Size: 519660 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/462d51a9-7cd5-49c2-be0e-3575ac402727/resource/ea13b49c-e8a1-4571-817f-d1409df9f119/download/short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Description:
description: Resource Title: short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Size: 519480 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/462d51a9-7cd5-49c2-be0e-3575ac402727/resource/408870d4-1372-4f7e-88ce-5aa0e0e2d357/download/short-term_drainage_density_dynamics_dataset_documentation_for_the_haute-mentue_catchment.pdf
 Description: Documentation for the Short-term Drainage Density Dynamics Dataset for the Haute-Mentue Catchment (dataset_of_flowing_drainage_network_lengths_water_levels_and_precipitation_for_the_haute-mentue_catchment.csv). This document provides a detailed description of the collected data, the locations where it was recorded, the data format, and the curation process applied.
DOI: 10.16904/envidat.570
title: Tectonic and climatic controls on plant biodiversity in the Hengduan Mountains China

description: This dataset includes geomorphic predictors and plant biodiversity patterns in the Hengduan Mountains, published in the Geological Society of London special volume: Asian Geodynamics, Climate and Biodiversity (https://doi.org/10.1144/SP549-2024-17).
The geomorphic predictors include catchment-restricted relief and chi maps, while the climate predictors comprise site water balance, growing degree days, and climate change velocity from the Last Glacial Maximum (LGM) to the present.
The plant biodiversity patterns are represented by a plant richness map for 13,321 species in the Hengduan Mountains. Species-level plant range maps are available in the dataset, previously published under DOI: 10.16904/envidat.424.
description: Resource Title: Opendata.zip
 Size: 496058380 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/dabf596f-dbf6-4a04-84aa-81db2e1ae639/resource/3ea51a5e-7012-44e9-a6ca-08cd9cc73599/download/opendata.zip
 Description:
DOI: 10.17632/9vgv5bfcry
title: Phytase-mediated hydrolysis of different soil phytate species: Kinetics and mineral interfacial mechanisms

description: Phytates adsorption and hydrolysis kinetics; In-situ ATR-FTIR data; P K-edge XANES data; P NMR data; Characterization of minerals and phytase; Linear fit of phytates hydrolysis; CD spectra data