cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0010714.10fu
title: SH0010714.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/5t3-52z-k7g
title: Epilobium palustre L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010715.10fu
title: SH0010715.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/hxl-fff-5g9
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/wj6-xgh-trj
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010716.10fu
title: SH0010716.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/hnp-6gy-6pf
title: Myriophyllum alterniflorum DC.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/pak-fnm-79f
title: Myriophyllum alterniflorum DC.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010717.10fu
title: SH0010717.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/cqw-bhz-c0l
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/mxe-3tj-s7v
title: Hypericum maculatum Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/jkw-vtd-al1
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/slq-f7m-ft5
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010718.10fu
title: SH0010718.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0010719.10fu
title: SH0010719.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/pbw-8ca-18m
title: Hypericum maculatum Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/bvx-mb7-3gd
title: Epilobium palustre L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/tav-h3v-gym
title: Myriophyllum alterniflorum DC.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010720.10fu
title: SH0010720.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/3ny-mvr-hrg
title: Hypericum maculatum Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/65z-dbd-flp
title: Myriophyllum alterniflorum DC.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010721.10fu
title: SH0010721.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.9aawxy
title: Occurrence Download

description: A dataset containing 25391 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "GadmGid is IND.34.15_1",
 "Geometry POLYGON((409.97893 6.66321,484.54562 6.66321,484.54562 36.47712,409.97893 36.47712,409.97893 6.66321))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 25391 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074588-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/ps6-2l3-7c0
title: Tilia cordata Mill.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/y9c-gsd-aat
title: Epilobium palustre L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0010722.10fu
title: SH0010722.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/3pg-4e0-wvf
title: Epilobium palustre L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.5281/zenodo.10471060
title: UFLUX 100m half-yearly carbon, water, and energy fluxes in Europe in 2021

description: UFLUX Ensemble Europe100m6monthly (European 100 6-monthly) in 2021

OverviewThe UFLUX ensemble dataset offers European fluxes at 100 m spatial resolution, generated using Deep Forest machine learning models. It integrates satellite-based Sentinel-2 vegetation proxies NIRv with ERA5 climate reanalysis, and is trained against ICOS eddy covariance observations. The UFLUX project includes five core flux components:





Gross Primary Production (GPP)




Ecosystem Respiration (RECO)




Net Ecosystem Exchange (NEE)




Sensible Heat Flux (H)




Latent Energy Flux (LE)



Background and MethodologyThe Unified FLUXes (UFLUX) initiative is a data-driven, machine learning-based platform designed to upscale eddy covariance (EC) flux measurements from tower sites to the global scale. It aims to answer pressing questions about how effectively terrestrial ecosystems are managed under climate change.

Key innovations of UFLUX include:





Consistent Upscaling Framework: Harmonizes flux upscaling across spatial/temporal scales and multiple flux types (GPP, RECO, etc.) using deep decision tree-based methods, better suited than conventional neural networks for EC flux data.




Hybrid Explainable ML: Combines black-box ML with ecological interpretability through residual learning, offering both predictive power and new scientific insight (UFLUXv2).




Uncertainty Quantification: Employs sampling space completeness to assess model uncertainty in a transparent, robust manner.




Multisource Integration: Leverages complementary strengths of vegetation proxies (e.g., NIRv, SIF) and climate data (e.g., ERA5) to represent carbon dynamics more comprehensively than single-source approaches.




Superior Gap-Filling: Originally developed as a global EC flux gap-filling tool, UFLUX improves accuracy by up to 30% and reduces uncertainty by as much as 70% compared to traditional methods.




High Performance: Achieves strong predictive accuracy, with global-scale R² > 0.8 for RECO and ≈0.9 for GPP, while being computationally efficient enough to run on a standard laptop.




Community Adoption: Already used by other global upscaling projects, highlighting its reliability and impact.



ApplicationsUFLUX is ideal for studying the interactions between land management, climate change, and carbon fluxes, particularly in improving global estimates of GPP and RECO by addressing biases in EC measurements.

Resources



UFLUX Website: https://sites.google.com/view/uflux



Code Repository: https://github.com/soonyenju/uflux




Technical & Descriptive Publication: https://doi.org/10.1080/01431161.2024.2312266
DOI: 10.5281/zenodo.10471061
title: UFLUX 100m half-yearly carbon, water, and energy fluxes in Europe in 2021

description: UFLUX Ensemble Europe100m6monthly (European 100 6-monthly) in 2021

OverviewThe UFLUX ensemble dataset offers European fluxes at 100 m spatial resolution, generated using Deep Forest machine learning models. It integrates satellite-based Sentinel-2 vegetation proxies NIRv with ERA5 climate reanalysis, and is trained against ICOS eddy covariance observations. The UFLUX project includes five core flux components:





Gross Primary Production (GPP)




Ecosystem Respiration (RECO)




Net Ecosystem Exchange (NEE)




Sensible Heat Flux (H)




Latent Energy Flux (LE)



Background and MethodologyThe Unified FLUXes (UFLUX) initiative is a data-driven, machine learning-based platform designed to upscale eddy covariance (EC) flux measurements from tower sites to the global scale. It aims to answer pressing questions about how effectively terrestrial ecosystems are managed under climate change.

Key innovations of UFLUX include:





Consistent Upscaling Framework: Harmonizes flux upscaling across spatial/temporal scales and multiple flux types (GPP, RECO, etc.) using deep decision tree-based methods, better suited than conventional neural networks for EC flux data.




Hybrid Explainable ML: Combines black-box ML with ecological interpretability through residual learning, offering both predictive power and new scientific insight (UFLUXv2).




Uncertainty Quantification: Employs sampling space completeness to assess model uncertainty in a transparent, robust manner.




Multisource Integration: Leverages complementary strengths of vegetation proxies (e.g., NIRv, SIF) and climate data (e.g., ERA5) to represent carbon dynamics more comprehensively than single-source approaches.




Superior Gap-Filling: Originally developed as a global EC flux gap-filling tool, UFLUX improves accuracy by up to 30% and reduces uncertainty by as much as 70% compared to traditional methods.




High Performance: Achieves strong predictive accuracy, with global-scale R² > 0.8 for RECO and ≈0.9 for GPP, while being computationally efficient enough to run on a standard laptop.




Community Adoption: Already used by other global upscaling projects, highlighting its reliability and impact.



ApplicationsUFLUX is ideal for studying the interactions between land management, climate change, and carbon fluxes, particularly in improving global estimates of GPP and RECO by addressing biases in EC measurements.

Resources



UFLUX Website: https://sites.google.com/view/uflux



Code Repository: https://github.com/soonyenju/uflux




Technical & Descriptive Publication: https://doi.org/10.1080/01431161.2024.2312266
DOI: 10.1594/pangaea.969098
title: Effect of waveform on turbulence transition in pulsatile pipe flow

description: Pulsatile flow in a straight pipe is a model system for unsteady internal flows in industrial engineering and physiology. In some parameter regimes, the laminar flow is susceptible to helical perturbations, whose transient energy growth scales exponentially with the Reynolds number (Re). We link the transient growth of these perturbations to the instantaneous linear instability of the laminar flow. We exploit this link to study the effect of the waveform on turbulence transition by performing linear stability and transient growth analyses of flows driven with different waveforms. We find a higher-energy growth in flows driven with longer low-velocity phases as well as with steeper deceleration and acceleration phases. Finally, we perform direct numerical simulations and show that, in pulsatile flows, the linear mechanisms responsible for turbulence transition are distinctly different from the nonlinear mechanisms sustaining turbulence. In this dataset we include all the codes used to perform the analysis: from the codes in Matlab to perform transient growth and stability analyses of pulsatile pipe flow, to the Fortran code we use to perform direct numerical simulations. Additionally we include the codes in Matlab we use to fit our data to a physically inspired formula and to initialize the direct numerical simulations. Our strategy is to first postprocess the results of the codes we use, and save them as '.mat' files. We then generate the figures using these '.mat' files. These '.mat' files can be found in this dataset. They are saved in compressed folders, named following the figures of the paper this dataset is linked to.
DOI: 10.1594/pangaea.969126
title: Turbulent puffs in transitional pulsatile pipe flow at moderate pulsation amplitudes

description: We show that, in the transitional regime of pulsatile pipe flow, at moderate-to-high amplitudes 0.5≲𝐴≲1, the first long-lived turbulent structures are localized and take the form of the puffs and slugs observed in statistically steady pipe flow. We perform direct numerical simulations at many pulsation frequencies (Wo), amplitudes, and Reynolds number (Re) and observe different dynamics of puffs and slugs. At certain flow parameters we find, using a causal analysis, that puffs actively make use of linear instabilities in the laminar Sexl-Womersley (SW) profile to survive the pulsation. Using all these lessons learned, we extend a low-order model by Barkley et al. [Nature (London) 526, 550 (2015)] to reproduce these dynamics. We find a good agreement between the extended model and our numerical results in a broad parametric space of pulsation amplitudes 0.5≲𝐴≲1, frequencies Wo≳5 and 2100≤Re≤3000. With the help of our numerical results, causal analysis and model, we determine that turbulence production has two sources at these flow parameters: the mean shear as in statistically steady pipe flow and the instabilities of the instantaneous pulsatile mean profile.
DOI: 10.1594/pangaea.973048
title: Sediment echosounder processed data (Atlas Parasound P70 echosounder working area dataset) of RV METEOR during cruise M122, offshore Namibia, South Atlantic Ocean

description: The main objectives of the study are to characterize the sedimentary structures observed in the area where internal waves interact with the seafloor and to identify the interaction and breaking mechanisms that result in seafloor erosion and sediment resuspension. We imaged the water column and the sub-seafloor with a ParaSound sub-bottom profiler off Namibia (SE Atlantic Ocean). The data was collected during R/V METEOR cruise M122 in 2016.
DOI: 10.1594/pangaea.969452
title: Natural gamma ray (NGR) data from core GLAD6 BOS04 5B

description: Here we present original Natural Gamma Ray (NGR) data from core GLAD6 BOS04 5B against depth that have been used as basis in the framework of the REFINE project aiming to establish an age-depth model that bases on a combination of cyclostratigraphy and correlation analyses. All core data (GLAD6 BOS04 5B) have been retrieved in a ~4 cm resolution by the Continental Scientific Drilling Facility at the University of Minnesota, USA using a Geotek MSCL-S multisensor core logger equipped with a 3-inch diameter NaI(Tl) detector housed in a 6-inch diameter lead shield. Measurement uncertainties range between 5 and 10%. All data are reported as total counts, integrating all emission counts over the gamma ray energy range between 0 and 3 MeV. For these measurements the archive core half has been used. Note that for correlation analyses the NGR data have been smoothed using a 35 point mean. The smoothed data can be also found at PANGEA. As correlation target, we used the Iberian Margin Sea Surface Temperatures. A suite of tiepoints has been created to bring the depth domain of core GLAD6 BOS04 5B to the age domain considering the age model of the Sea Surface Temperature record from the Iberian Margin. These tiepoints are also provided at doi:10.1594/PANGAEA.969454.