cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4697104
title: water isotopic data for the Dumont d'Urville station, Antarctica, 1 minute resolution, summer season 2016-2017

description: Location: Dumont d'Urville (66°39′46″S140°0′07″E) 4 columns for the raw data - Date-time UTC (hour:minute) - mixing ratio (ppmv) - d18O (permil) - dD (permil) 5 columns for the corrected data - Date - time UTC (hour:minute) - mixing ratio (ppmv) - d18O (permil) - dD (permil) - d-excess (permil) Project COMBINISO
DOI: 10.6084/m9.figshare.14779533
title: Upscaling the resilience assessment through comparative analysis

description: Dataset accompanying the paper "Upscaling the resilience assessment through comparative analysis". The data codes features of adaptive capacity for 40 Arctic communities. The analysis uses QCA (qualitative comparative analysis) to identify necessary and sufficient conditions for communities to maintain their livelihoods. The code for the analysis is available at https://github.com/juanrocha/Arctic_QCAThe zip file contains the 40 templates developed to describe cases. The templates are based on literature review and expert elicitation. For more information see the preprint available in SocArxiv.
DOI: 10.5281/zenodo.5105617
title: Physical and deep learning retrieved fine mode fraction (Phy-DL FMF)

description: Aerosol fine-mode fraction (FMF) is a key parameter for discriminating anthropogenic aerosols from natural ones, but it is highly uncertainty from satellite-based retrieval, especially over land. Here we integrated physical and deep learning (Phy-DL) methods to retrieval aerosol FMF in a global land scale based on MODIS data and produced the 20-year (2001-2020) Phy-DL FMF (500 nm) at daily temporal resolution and 1° spatial resolution. The Phy-DL FMF is uploaded as Geotiff format, stretched from -89.5° to 89.5° latitude and from -179.5° to 179.5° longitude. In some certain days Phy-DL FMF might be inavailable, due to the missing MODIS satellite data used for calculating Phy-DL FMF.
DOI: 10.5281/zenodo.5105616
title: Physical and deep learning retrieved fine mode fraction (Phy-DL FMF)

description: Aerosol fine-mode fraction (FMF) is a key parameter for discriminating anthropogenic aerosols from natural ones, but it is highly uncertainty from satellite-based retrieval, especially over land. Here we integrated physical and deep learning (Phy-DL) methods to retrieval aerosol FMF in a global land scale based on MODIS data and produced the 20-year (2001-2020) Phy-DL FMF (500 nm) at daily temporal resolution and 1° spatial resolution. The Phy-DL FMF is uploaded as Geotiff format, stretched from -89.5° to 89.5° latitude and from -179.5° to 179.5° longitude. In some certain days Phy-DL FMF might be inavailable, due to the missing MODIS satellite data used for calculating Phy-DL FMF.
DOI: 10.48370/ofd/2u2mnn/8rbpbg
title: HMW_Carex_panicea_L._H_7309.jpg

description: :unav
DOI: 10.48370/ofd/2u2mnn
title: Turzyca prosowata (Carex panicea L.), 7309

description: Herbarium
DOI: 10.48370/ofd/mzzhtd/moqcde
title: HMW_Carex_panicea_L._H_8512.jpg

description: :unav
DOI: 10.48370/ofd/mzzhtd
title: Turzyca prosowata (Carex panicea L.), 8512

description: Herbarium
DOI: 10.6084/m9.figshare.14749161
title: Metadata record for: A global dataset of inland fisheries expert knowledge

description: This dataset contains key characteristics about the data described in the Data Descriptor A global dataset of inland fisheries expert knowledge. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.14749161.v1
title: Metadata record for: A global dataset of inland fisheries expert knowledge

description: This dataset contains key characteristics about the data described in the Data Descriptor A global dataset of inland fisheries expert knowledge. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.48370/ofd/nlvegn/5ak0ts
title: HMW_Carex_panicea_L._H_9410.jpg

description: :unav
DOI: 10.48370/ofd/nlvegn
title: Turzyca prosowata (Carex panicea L.), 9410

description: Herbarium
DOI: 10.48370/ofd/53wqkt/gp8wqf
title: HMW_Carex_panicea_L._H_8249.jpg

description: :unav
DOI: 10.48370/ofd/53wqkt
title: Turzyca prosowata (Carex panicea L.), 8249

description: Herbarium
DOI: 10.6084/m9.figshare.14761866
title: Metadata record for: GazeBase, a large-scale, multi-stimulus, longitudinal eye movement dataset

description: This dataset contains key characteristics about the data described in the Data Descriptor GazeBase, a large-scale, multi-stimulus, longitudinal eye movement dataset. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.5281/zenodo.5105631
title: Stochastic Mixed-Integer Programming for a Spare Parts Inventory Management Problem

description: The German Armed Forces provide an operation contingent to support the North Atlantic Treaty Organization (NATO) Response Force (NRF). For short deployments (e.g., one month), the NRF troops can bring with them a tightly constrained "warehouse" of spare parts. To ensure optimal use this warehouse, we developed the computer program "The OPtimization of a Spare Parts INventory" (TOPSPIN) to find an optimal mix of spare parts to repair a set of systems. Each system is composed of several parts, and it can only be used again in the mission if all broken parts are replaced. Due to the stochastic nature of the problem, we generate scenarios that simulate the failure of the parts. The backbone of TOPSPIN is a mixed-integer linear program that determines an optimal, scenario-robust mix of spare parts. Using input data provided by the German Logistikzentrum (RealData.xlsx), we analyze how many scenarios need to be generated in order to determine reliable solutions. A further data set (SimData.xlsx) was generated with random data, having a similar structure as the real data set. Using these two data sets, we analyze the composition of the warehouse over a variety of different weight restrictions, and we examine the number of repairable systems for different values of this bound.
description: A preprint of the manuscript can be found at DOI: 10.26127/BTUOpen-5080
description: {"references": ["Johannsmann et al. (2020), DOI: 10.26127/BTUOpen-5080"]}
DOI: 10.5281/zenodo.5105630
title: Stochastic Mixed-Integer Programming for a Spare Parts Inventory Management Problem

description: The German Armed Forces provide an operation contingent to support the North Atlantic Treaty Organization (NATO) Response Force (NRF). For short deployments (e.g., one month), the NRF troops can bring with them a tightly constrained "warehouse" of spare parts. To ensure optimal use this warehouse, we developed the computer program "The OPtimization of a Spare Parts INventory" (TOPSPIN) to find an optimal mix of spare parts to repair a set of systems. Each system is composed of several parts, and it can only be used again in the mission if all broken parts are replaced. Due to the stochastic nature of the problem, we generate scenarios that simulate the failure of the parts. The backbone of TOPSPIN is a mixed-integer linear program that determines an optimal, scenario-robust mix of spare parts. Using input data provided by the German Logistikzentrum (RealData.xlsx), we analyze how many scenarios need to be generated in order to determine reliable solutions. A further data set (SimData.xlsx) was generated with random data, having a similar structure as the real data set. Using these two data sets, we analyze the composition of the warehouse over a variety of different weight restrictions, and we examine the number of repairable systems for different values of this bound.
description: A preprint of the manuscript can be found at DOI: 10.26127/BTUOpen-5080
description: {"references": ["Johannsmann et al. (2020), DOI: 10.26127/BTUOpen-5080"]}
DOI: 10.21227/jdzh-4m97
title: Dataset for An Ensemble Method for Keystroke Dynamics Authentication in Free-Text Using Word Boundaries

description: Dataset used in the article "An Ensemble Method for Keystroke Dynamics Authentication in Free-Text Using Word Boundaries". For each user and free-text sample of the companion dataset LSIA, contains a CSV file with the list of words in the sample that survived the filters described in the article, together with the CSV files with training instances for each word. The source data comes from a dataset used in previous studies by the authors. The language of the free-text samples is Spanish.
DOI: 10.5281/zenodo.5105588
title: planet wind evaporation data

description: Data associated with publication submitted by MacLeod & Oklopcic to ApJ, studying stellar wind impingement on hydrodynamical outflows from close in planets using hydrodynamical simulations.
DOI: 10.48370/ofd/7qz4vn/yqhwor
title: HMW_Carex_panicea_L._H_6406.jpg

description: :unav
DOI: 10.48370/ofd/7qz4vn
title: Turzyca prosowata (Carex panicea L.), 6406

description: Herbarium
DOI: 10.48370/ofd/3y46a5/yjicfx
title: HMW_Carex_panicea_L._H_4268.jpg

description: :unav
DOI: 10.48370/ofd/3y46a5
title: Turzyca prosowata (Carex panicea L.), 4268

description: Herbarium
DOI: 10.6084/m9.figshare.14802774
title: Metadata record for: A DICOM dataset for evaluation of medical image de-identification

description: This dataset contains key characteristics about the data described in the Data Descriptor A DICOM dataset for evaluation of medical image de-identification. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.14802774.v1
title: Metadata record for: A DICOM dataset for evaluation of medical image de-identification

description: This dataset contains key characteristics about the data described in the Data Descriptor A DICOM dataset for evaluation of medical image de-identification. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.48370/ofd/xdvgd9/xiqrif
title: HMW_Carex_panicea_L._H_2937.jpg

description: :unav
DOI: 10.48370/ofd/xdvgd9
title: Turzyca prosowata (Carex panicea L.), 2937

description: Herbarium
DOI: 10.48370/ofd/iyt9ng/tmg8zv
title: HMW_Carex_panicea_L._H_1287.jpg

description: :unav
DOI: 10.48370/ofd/iyt9ng
title: Turzyca prosowata (Carex panicea L.), 1287

description: Herbarium
DOI: 10.48370/ofd/vifmdg/wlinxw
title: HMW_Carex_panicea_L._H_1266.jpg

description: :unav
DOI: 10.48370/ofd/vifmdg
title: Turzyca prosowata (Carex panicea L.), 1266

description: Herbarium
DOI: 10.6084/m9.figshare.14484342
title: Metadata record for: A database of submarine landslides offshore West and Southwest Iberia

description: This dataset contains key characteristics about the data described in the Data Descriptor A database of submarine landslides offshore West and Southwest Iberia. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.6084/m9.figshare.14484342.v1
title: Metadata record for: A database of submarine landslides offshore West and Southwest Iberia

description: This dataset contains key characteristics about the data described in the Data Descriptor A database of submarine landslides offshore West and Southwest Iberia. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format
DOI: 10.48370/ofd/ar2nd7/1xoj4h
title: HMW_Carex_panicea_L._H_1251.jpg

description: :unav
DOI: 10.48370/ofd/ar2nd7
title: Turzyca prosowata (Carex panicea L.), 1251

description: Herbarium
DOI: 10.48370/ofd/iiptyc/k5nofr
title: HMW_Carex_panicea_L._H_8103.jpg

description: :unav
DOI: 10.48370/ofd/iiptyc
title: Turzyca prosowata (Carex panicea L.), 8103

description: Herbarium
DOI: 10.48370/ofd/xeo2p3/rerlzr
title: HMW_Carex_panicea_L._H_6407.jpg

description: :unav
DOI: 10.48370/ofd/xeo2p3
title: Turzyca prosowata (Carex panicea L.), 6407

description: Herbarium
DOI: 10.5281/zenodo.5105570
title: Temperature and humidity observations in Kampala, Uganda, during the boreal summer 2018-2019

description: Both climate change and rapid urbanization accelerate exposure to heat in the city of Kampala, Uganda. To investigate the heterogeneous distribution of temperature and humidity throughout the city, we set up a network of low-cost iButton sensors, operational in the boreal summer months of 2018-2019. This dataset provides the observational data of 45 sensors installed at 15 different locations in the city of Kampala.
DOI: 10.5281/zenodo.5105569
title: Temperature and humidity observations in Kampala, Uganda, during the boreal summer 2018-2019

description: Both climate change and rapid urbanization accelerate exposure to heat in the city of Kampala, Uganda. To investigate the heterogeneous distribution of temperature and humidity throughout the city, we set up a network of low-cost iButton sensors, operational in the boreal summer months of 2018-2019. This dataset provides the observational data of 45 sensors installed at 15 different locations in the city of Kampala.
DOI: 10.48370/ofd/klqxu7/doyz6r
title: HMW_Carex_panicea_L._H_6009.jpg

description: :unav
DOI: 10.48370/ofd/klqxu7
title: Turzyca prosowata (Carex panicea L.), 6009

description: Herbarium
DOI: 10.48370/ofd/h5urxm/lb0mld
title: HMW_Carex_panicea_L._H_4616.jpg

description: :unav
DOI: 10.48370/ofd/h5urxm
title: Turzyca prosowata (Carex panicea L.), 4616

description: Herbarium
DOI: 10.48370/ofd/w2p3r7/smnctv
title: HMW_Carex_panicea_L._H_1353.jpg

description: :unav
DOI: 10.48370/ofd/w2p3r7
title: Turzyca prosowata (Carex panicea L.), 1353

description: Herbarium
DOI: 10.6084/m9.figshare.14986944
title: Supplementary Material for: Modeling Manifest Huntington’s Disease Prevalence Using Diagnosed Incidence and Survival Time

description: <b><i>Introduction:</i></b> Understanding the epidemiology of Huntington’s disease (HD) is key to assessing disease burden and the healthcare resources required to meet patients’ needs. We aimed to develop and validate a model to estimate the diagnosed prevalence of manifest HD by the Shoulson-Fahn stage. <b><i>Methods:</i></b> A literature review identified epidemiological data from Brazil, Canada, France, Germany, Italy, Spain, the UK, and the USA. Data on staging distribution at diagnosis, progression, and mortality were derived from Enroll-HD. Newly diagnosed patients with manifest HD were simulated by applying annual diagnosed incidence rates to the total population in each country, each year from 1950 onwards. The number of diagnosed prevalent patients from the previous year who remained in each stage was estimated in line with the probability of death or progression. Diagnosed prevalence in 2020 was estimated as the sum of simulated patients, from all the incident cohorts, still alive. <b><i>Results:</i></b> The model estimates that in 2020, there were 66,787 individuals diagnosed with HD in the 8 included countries, of whom 62–63% were in Shoulson-Fahn stages 1 and 2 (with less severely limited functional capacity than those in stages 3–5). Diagnosed prevalence is estimated to be 8.2–9.0 per 100,000 in the USA, Canada, and the 5 included European countries and 3.5 per 100,000 in Brazil. <b><i>Conclusion:</i></b> The modeled estimates generally accord with the previously published data. This analysis contributes to better understanding of the epidemiology of HD and highlights areas of uncertainty.
DOI: 10.48370/ofd/aspust/d3180b
title: HMW_Carex_pallescens_L._H_7287.jpg

description: :unav
DOI: 10.48370/ofd/aspust
title: Turzyca blada (Carex pallescens L.), 7287

description: Herbarium
DOI: 10.6084/m9.figshare.14189021
title: Hoya group plastome exons

description: Three sequence datasets, all derived from genome skimming of Hoya, Dischidia, Oreosparte, Papuahoya and related genera (outgroups: Jasminanthes and Marsdenia). a single copy of all exons is included, except accD, ycf1 and ycf2. The datasets are: unaligned sequences, mafft aligned sequences and trimal trimmed alignments.<br>Only exons over 90 bp were used for the published phylogeny, but shorter exons are also included in this dataset.
DOI: 10.48370/ofd/dlelds/2ujvpm
title: HMW_Carex_pallescens_L._H_8980.jpg

description: :unav
DOI: 10.48370/ofd/dlelds
title: Turzyca blada (Carex pallescens L.), 8980

description: Herbarium
DOI: 10.48370/ofd/scjzyp/lpfkxc
title: HMW_Carex_pallescens_L._H_8595.jpg

description: :unav
DOI: 10.48370/ofd/scjzyp
title: Turzyca blada (Carex pallescens L.), 8595

description: Herbarium
DOI: 10.48370/ofd/hzggfx/8drzyo
title: HMW_Carex_pallescens_L._H_4394.jpg

description: :unav
DOI: 10.48370/ofd/hzggfx
title: Turzyca blada (Carex pallescens L.), 4394

description: Herbarium
DOI: 10.48370/ofd/qcktos/lpogqh
title: HMW_Carex_pallescens_L._H_3721.jpg

description: :unav
DOI: 10.48370/ofd/qcktos
title: Turzyca blada (Carex pallescens L.), 3721

description: Herbarium
DOI: 10.48370/ofd/lh9cao/5aqkne
title: HMW_Carex_pallescens_L._H_3061.jpg

description: :unav
DOI: 10.48370/ofd/lh9cao
title: Turzyca blada (Carex pallescens L.), 3061

description: Herbarium
DOI: 10.48370/ofd/3p62il/v8ilbs
title: HMW_Carex_pallescens_L._H_2789.jpg

description: :unav
DOI: 10.48370/ofd/3p62il
title: Turzyca blada (Carex pallescens L.), 2789

description: Herbarium
DOI: 10.48370/ofd/il6lc5/ustrjx
title: HMW_Carex_pallescens_L._H_2788.jpg

description: :unav
DOI: 10.48370/ofd/il6lc5
title: Turzyca blada (Carex pallescens L.), 2788

description: Herbarium
DOI: 10.48370/ofd/yfkxhs/q9qm5y
title: HMW_Carex_pallescens_L._H_2787.jpg

description: :unav
DOI: 10.48370/ofd/yfkxhs
title: Turzyca blada (Carex pallescens L.), 2787

description: Herbarium
DOI: 10.48370/ofd/8n1kza/oje6zk
title: HMW_Carex_pallescens_L._H_1258.jpg

description: :unav
DOI: 10.48370/ofd/8n1kza
title: Turzyca blada (Carex pallescens L.), 1258

description: Herbarium
DOI: 10.48370/ofd/lrpjmy/adxtal
title: HMW_Carex_pallescens_L._H_1259.jpg

description: :unav
DOI: 10.48370/ofd/lrpjmy
title: Turzyca blada (Carex pallescens L.), 1259

description: Herbarium
DOI: 10.48370/ofd/kcxyrc/ohntee
title: HMW_Carex_pallescens_L._H_8716.jpg

description: :unav
DOI: 10.48370/ofd/kcxyrc
title: Turzyca blada (Carex pallescens L.), 8716

description: Hebarium
DOI: 10.48370/ofd/vki8co/essmqh
title: HMW_Carex_pallescens_L._H_1263.jpg

description: :unav
DOI: 10.48370/ofd/vki8co
title: Turzyca blada (Carex pallescens L.), 1263

description: Herbarium
DOI: 10.48370/ofd/u62psb/fzfdav
title: HMW_Carex_pallescens_L._H_1456.jpg

description: :unav
DOI: 10.48370/ofd/u62psb
title: Turzyca blada (Carex pallescens L.), 1456

description: Herbarium
DOI: 10.48370/ofd/h5sefj/2mgwju
title: HMW_Carex_pallescens_L._H_5423.jpg

description: :unav
DOI: 10.48370/ofd/h5sefj
title: Turzyca blada (Carex pallescens L.), 5423

description: Herbarium
DOI: 10.6084/m9.figshare.14842530
title: eksperci 2020 (1).xlsx

description: The methods of collecting data used in the research include the analysis of the literature on the subject and the survey method. The above-described survey was one of the three main stages of research under this project. The remaining two stages (quantitative and qualitative research) concerned farmers’ households in the area of six randomly selected provinces (one from each macroregion in Poland). The sampling frame included all 16 provinces in Poland, and the following provinces were drawn: Dolnośląskie; Zachodniopomorskie; Lubelskie; Warmińsko-mazurskie; Małopolskie and Łódzkie. The spatial scope of the research of farmers and experts was identical. Adoption of the research methodology taking into account the division into macro-regions and random selection in their spatial scope made it possible to consider various socio-economic features of rural areas in Poland. The analyses used the results of the survey conducted between November 2019 and March 2020. The selection of the sample for expert research was deliberate. The research project established that the minimum research sample would be 30 experts, including at least 4 experts with knowledge and experience in the field of energy poverty in the study area. The experts were mainly employees of agricultural advisory centres.
DOI: 10.6084/m9.figshare.14842530.v2
title: eksperci 2020 (1).xlsx

description: The methods of collecting data used in the research include the analysis of the literature on the subject and the survey method. The above-described survey was one of the three main stages of research under this project. The remaining two stages (quantitative and qualitative research) concerned farmers’ households in the area of six randomly selected provinces (one from each macroregion in Poland). The sampling frame included all 16 provinces in Poland, and the following provinces were drawn: Dolnośląskie; Zachodniopomorskie; Lubelskie; Warmińsko-mazurskie; Małopolskie and Łódzkie. The spatial scope of the research of farmers and experts was identical. Adoption of the research methodology taking into account the division into macro-regions and random selection in their spatial scope made it possible to consider various socio-economic features of rural areas in Poland. The analyses used the results of the survey conducted between November 2019 and March 2020. The selection of the sample for expert research was deliberate. The research project established that the minimum research sample would be 30 experts, including at least 4 experts with knowledge and experience in the field of energy poverty in the study area. The experts were mainly employees of agricultural advisory centres.
DOI: 10.6084/m9.figshare.14986938
title: Overwintering of two pupal parasitoids of Drosophila under natural conditions

description: This dataset contains the raw data for the publication with the same title<br>
DOI: 10.6084/m9.figshare.14986938.v1
title: Overwintering of two pupal parasitoids of Drosophila under natural conditions

description: This dataset contains the raw data for the publication with the same title<br>
DOI: 10.48370/ofd/amcgni/wb4hcd
title: HMW_Carex_vulpina_L._H_7279.jpg

description: :unav
DOI: 10.48370/ofd/amcgni
title: Turzyca lisia (Carex vulpina L.), 7279

description: Herbarium
DOI: 10.48370/ofd/6bupwe/dk4u5v
title: HMW_Carex_vulpina_L._H_8158.jpg

description: :unav
DOI: 10.48370/ofd/6bupwe
title: Turzyca lisia (Carex vulpina L.), 8158

description: Herbarium
DOI: 10.48370/ofd/izxmbh/civzlu
title: HMW_Carex_vulpina_L._H_6671.jpg

description: :unav
DOI: 10.48370/ofd/izxmbh
title: Turzyca lisia (Carex vulpina L.), 6671

description: Herbarium
DOI: 10.48370/ofd/vyvbsz/ssmq3g
title: HMW_Carex_vulpina_L._H_4423.jpg

description: :unav
DOI: 10.48370/ofd/vyvbsz
title: Turzyca lisia (Carex vulpina L.), 4423

description: Herbarium
DOI: 10.48370/ofd/yybmm3/xrm665
title: HMW_Carex_vulpina_L._H_4139.jpg

description: :unav
DOI: 10.48370/ofd/yybmm3
title: Turzyca lisia (Carex vulpina L.), 4139

description: Herbarium
DOI: 10.48370/ofd/y28bka/6jwl2j
title: HMW_Carex_vulpina_L._H_3738.jpg

description: :unav
DOI: 10.48370/ofd/y28bka
title: Turzyca lisia (Carex vulpina L.), 3738

description: Herbarium
DOI: 10.48370/ofd/vzavdo/gkraxq
title: HMW_Carex_vulpina_L._H_3115.jpg

description: :unav
DOI: 10.48370/ofd/vzavdo
title: Turzyca lisia (Carex vulpina L.), 3115

description: Herbarium
DOI: 10.48370/ofd/iceme5/kpe5jb
title: HMW_Carex_vulpina_L._H_2971.jpg

description: :unav
DOI: 10.48370/ofd/iceme5
title: Turzyca lisia (Carex vulpina L.), 2971

description: Herbarium
DOI: 10.48370/ofd/geawj1/o055hf
title: HMW_Carex_vulpina_L._H_0657.jpg

description: :unav
DOI: 10.48370/ofd/geawj1
title: Turzyca lisia (Carex vulpina L.), 657

description: Herbarium
DOI: 10.48370/ofd/dd0mqu/y8qddi
title: HMW_Carex_vulpina_L._H_8589.jpg

description: :unav
DOI: 10.48370/ofd/dd0mqu
title: Turzyca lisia (Carex vulpina L.), 8589

description: Herbarium
DOI: 10.48370/ofd/wxyw0s/3hozev
title: HMW_Carex_vulpina_L._H_6643.jpg

description: :unav
DOI: 10.48370/ofd/wxyw0s
title: Turzyca lisia (Carex vulpina L.), 6643

description: Herbarium
DOI: 10.48370/ofd/qs7obv/pg5uyu
title: HMW_Carex_vulpina_L._H_6160.jpg

description: :unav